empirical research project

The University of Chicago The Law School

Civil rights & police accountability clinic—significant achievements for 2023-24.

Our Clinic students continue to make a difference in the community, while learning all that it means to be a lawyer.

The Federal Civil Rights Consent Decree Governing the Chicago Police Department

Years of advocacy by Clinic students and our clients resulted in the 2019 federal civil rights Consent Decree that seeks to remedy the Chicago Police Department’s (CPD’s) pattern and practice of excessive and discriminatory violence targeted disproportionately against Black people. Highlights from our Consent Decree work during the 2023-24 academic year include: (1) our success in remedying CPD’s practice of violent, dehumanizing, and discriminatory home raids that have targeted and traumatized Black and Brown children and families in Chicago; (2) the relief that we won in emergency proceedings that we initiated to prevent unlawful mass arrests and First Amendment violations during the Democratic National Convention in Chicago; (3) our progress toward remedying racially discriminatory practices of targeting Black people for unlawful stop-and-frisks and pretextual traffic stops; and (4) advocacy for critical modifications to strengthen and improve the Decree.

Ending Illegal and Discriminatory Home Raids

Clinic students and our community-based clients won a complete overhaul of the policies that govern residential search warrants in Chicago in months-long court supervised multi-party negotiations, briefs, and court proceedings. CPD’s new policies will seek to restrict home raids to circumstances in which they are necessary and forbid raids whenever the potential harms outweigh the expected benefits. CPD will be required to develop a written plan for the execution of every residential warrant to minimize the harm, trauma, and intrusion to families and their homes. Officers will be evaluated for their success in mitigating harm when executing search warrants. The new policies will protect children and vulnerable people from unnecessary harm, including requiring police to schedule raids at times when they are least likely to be home. They ban high-risk nighttime raids and limit no-knock warrants to circumstances in which people’s lives and physical safety are in jeopardy. They prohibit police from leaving families with broken doors and locks vulnerable to crime. And they will require police to thoroughly document and publicly report on each raid to enhance transparency and accountability. In addition, we won measures that will prevent wrong raids, including requiring CPD to independently investigate and corroborate tips, maintain records of any instance in which the informant provided false or inaccurate information, and provide the prosecutor and court with any information that may undermine the credibility of the informant and tip before seeking a warrant. The proposed new policies will soon be subject to public review and comment in anticipation of full implementation. The public and judicial scrutiny that we brought to bear during our enforcement proceedings has already resulted in a tenfold reduction of home raids and prevented the traumatization of thousands of children.

Protecting First Amendment Rights to Protest and the DNC

In spring 2023, we learned that the CPD intended to implement a new policy to facilitate mass arrests during protests and other First Amendment activities in anticipation of the Democratic National Convention. The proposed new policy would have eviscerated relief that we had won in 2021 that fundamentally transformed Chicago police policies governing the policing of First Amendment activities—relief that requires CPD to protect the rights of people to engage in public protest and dissent rather than to stamp out protests. The Clinic filed an emergency enforcement action to enjoin the proposed mass arrest policy. In the proceedings that followed, we succeeded in preventing the parts of the policy that threatened people’s First Amendment rights from taking effect. The First Amendment policy that we had won in 2021 continues to govern during the DNC and all public demonstrations now and in the future. For example, the revised policy on mass arrests will now prohibit police from arresting people engaged in First Amendment conduct for minor offenses unless they pose an immediate threat to the physical safety or property of others. It also explicitly bans retaliation against people for exercising their First Amendment rights.

Strengthening the Consent Decree and Advancing Racial Justice

Having won our community-based clients’ historic power to enforce the Decree, Clinic students continue to fight to strengthen the Decree to make our clients—people who have been most impacted by CPD’s civil rights violations—full and equal partners in the process. As a result of our advocacy, throughout the 2023-24 academic year, the federal court ordered the City to engage with community representatives when developing policies, procedures, and training—including the recent mass arrests policy that the CPD had initially sought to impose without any meaningful community engagement. Clinic students participated in five full-day public hearings in federal court focusing on potential modifications to the Decree and issues of racial justice. Students presented powerful testimony and legal memoranda that advocated for Consent Decree revisions that (a) require de-escalation and reductions in CPD violence; (b) divert people from the criminal legal system through alternatives to arrest and the elimination of unnecessary negative interactions with police; (c) develop non-criminal responses to people experiencing mental health crises (we won implementation of an historic pilot program on this); (d) prohibit police from pointing guns at people unless they present an immediate threat to serious injury or death to another person; (e) require officers to file a written report each time they point a gun at a community member; (f) provide services to survivors of CPD violence and their family members; and (g) address barriers to police accountability that were erected in the new collective bargaining agreements with the unions representing Chicago police officers. We also succeeded in subjecting CPD’s racially discriminatory stop-and-frisk practices to federal court supervision.

The court is currently deciding whether to also subject CPD traffic stops to federal court oversight under the Consent Decree, as traffic stops have become a flashpoint for unnecessary police violence in Chicago as they have skyrocketed in Black and Brown communities. Eighty-five percent of the instances in which Chicago police used force in traffic stops have been directed at Black people. We presented testimony and briefs that seek to outlaw CPD’s practice of using pretextual stops to harass Black and Brown people, disband police tactical units that have been responsible for unnecessary and disproportionate violence directed toward Black and Brown people, and limit CPD traffic stops to violations that pose genuine threats to public safety.

Ending Incommunicado Detention—A Second Consent Decree

The Clinic continues to advance its historic work in making real the fifty-eight-year-old promise of Miranda v. Arizona in Chicago. Tyler Lawson, ’24 , and Katherine Stanton, ’25, led a team of Clinic students that did outstanding advocacy work with our community-based clients and the Office of the Cook County Public Defender after having won a second consent decree that went into effect in February 2023 in Cook County Circuit Court—a decree that is designed to end the decades-long practice of incommunicado detention in CPD stations that has facilitated torture, coerced confessions, and wrongful convictions. Clinic students produced an empirical report with Professor Kyle Rozema that analyzed data from every arrest in Chicago that took place during the first year of the Decree. The Report found ninety-nine percent of people in CPD custody did not access an attorney and more than half of the people most vulnerable to interrogation did not get prompt access to a phone. Inspections by Clinic students inside Chicago police stations revealed that legible signs required by the Consent Decree that inform people in custody of their rights under the Decree and the Public Defender’s free 24-hour hotline number for legal assistance were routinely missing in the places where CPD detains people who may be subject to interrogation. Clinic students also documented that contrary to the Decree, many of the visiting rooms that CPD is required to maintain in every police station did not allow for private and confidential meetings between people in custody and their attorneys. The Clinic presented the Report and our findings to the court. In response, the Honorable Judge Neil H. Cohen directed CPD to work with the Clinic to ensure the installation of appropriate signs and remedy the documented deficiencies with respect to privacy. We are administering a survey to people at their first court appearance to provide the court with additional information about the reasons why people in CPD custody have not promptly accessed phones and counsel. Our preliminary findings indicate that CPD has failed to offer phones or provided the Public Defender’s 24-hour number to people subject to police interrogation. A quarter of the people surveyed report that CPD interrogated them without access to counsel. In addition, Clinic students have engaged in targeted outreach to people at risk of arrest and criminal defense attorneys in Chicago, created fantastic flyers, social media, and written material to educate people about their rights under the Decree, and developed a long-form interview tool to gain additional insight about barriers to access to counsel and phones.

Individual Cases

While we fight for systemic change, the Clinic has continued its tradition of excellence in serving individuals and families in need.

Clinic students won a stage three post-conviction hearing with our client Christopher Ellis before the Honorable Carol Howard in Cook County Circuit Court that can result in vacating Mr. Ellis’s conviction. Two Chicago police officers pulled Mr. Ellis out of his car, beat and tased him, and then falsely accused Mr. Ellis of aggravated battery against the police officers to cover up their abuse. Mr. Ellis was convicted and sentenced to six years in prison. Based on a phenomenal set of briefs written by Clinic students Hannah V.L. George, ’24, and Becky Marvin, ’24, and Professor Herschella Conyers ’ students Amara Shaikh, ’24 , and Liam Grah, ’25, in the Criminal and Juvenile Justice Clinic and Becky Marvin ’s outstanding oral argument, Judge Howard found that the Clinic has made a substantial showing of Mr. Ellis’s innocence and the ineffective assistance of his trial counsel. Judge Howard offered the highest praise to the students’ work. We expect Mr. Ellis’s case to go to trial in the fall.

 Erin Yonchak,’24, presented Clifton Young’s case before the Illinois Torture and Inquiry Relief Commission. Erin’s presentation and supporting written memorandum were nothing short of superb. As a result of Erin’s scrupulous investigation, factual and legal determinations, and recommendations, the Torture Commission found credible evidence that Mr. Young was tortured by Chicago police and ordered a full evidentiary hearing in Cook County Circuit Court that may result in his freedom after having served more than twenty years in prison.

Amrita Krishnan, ’25, is investigating a novel claim of police torture before the Illinois Torture Commission that is based on Chicago police detectives’ exploitation of a person’s withdrawal symptoms from heroin and denial of medical treatment to obtain a confession. This is the first of a series of claims of torture before the Commission based on deliberate indifference to a person in custody’s severe physical and psychological pain associated with drug withdrawal to leverage an incriminating statement. Amrita’s legal and medical research into whether and under what circumstances drug withdrawal can form a basis for a torture claim is precedential. It has the power to establish the governing legal standards in Illinois for assessing torture claims involving withdrawal.

Gabbie Zook, ’24 , Hannah V.L. George, ’24 , and Becky Marvin, ’24, led an investigation with a client who was repeatedly sexually assaulted by a Chicago police officer in public housing when she was a mere teenager. The Clinic helped to connect our client with the Chicago Torture Justice Center to provide her with critical support as she continues to work through her trauma from the repeated assaults. We face a myriad of legal challenges because of the years that have passed since the assaults and Illinois law that protects municipalities from liability when police officers abuse their state power to sexually assault people, but we remain committed to supporting our client in her fight for a measure of justice and healing. Our students’ work has shined a light on a path forward.

Policy Projects

Chicago police transparency.

Natalie Cohn-Aronoff, ’24 , and Amber Hunter, ’25, have led a critical project to prevent the return to a state of police impunity in Chicago. The Clinic is responding to the Fraternal Order of Police’s (FOP’s) efforts to shroud in secrecy the adjudication of cases in which Chicago police officers have been found to have committed the most serious forms of misconduct to warrant firing or suspension of more than a year. After the FOP won an arbitration award that sought to end a sixty-year history of public hearings before a neutral body to be replaced by secret hearings behind closed doors by a handful of handpicked arbitrators who have a long track record of protecting Chicago police officers from accountability, the Clinic began work with a coalition of community, civil rights, and good government groups organized to stop the FOP from turning back the clock on our progress. We drafted press releases and an op-ed that lifted the threat of Chicago police impunity to visibility. We drafted policy and legal material for City Council to provide the basis for challenging the arbitrator’s award. We provided testimony in public hearings that was widely cited in the media. Our work supporting the organization of community members persuaded the Mayor and City Council to reject the Arbitrator’s award by a 3/5 vote in City Council and challenge the award in court. The Cook County Circuit Court then ruled that the Arbitrator’s award violated fundamental state policy in Chicago police transparency and accountability and ordered that the Chicago police disciplinary cases must remain open to the public. The FOP has filed a notice of appeal. A team of Clinic students led by Ben Postone, ’24, is drafting an amicus brief before the Illinois Court of Appeals on behalf of the broad community-based coalition that will explain the nature and strength of the public interest at stake.

At the same time, Clinic students have conducted extensive research and consulted experts in labor law to draft proposed state legislation that requires the public adjudication of Chicago police misconduct cases. The Clinic is collaborating with stakeholders to devise a path to establish law that will guarantee public transparency on CPD misconduct now and in the future. The Clinic has also drafted potential municipal legislation that would enhance Chicago’s Civilian Office of Police Accountability’s (COPA’s) efforts to promote greater transparency and accountability by enabling COPA to promptly publicly release summaries of completed misconduct investigations, prosecute disciplinary proceedings that result from COPA investigations, and restrict the Police Department’s power to overturn misconduct findings only for clear error and disciplinary recommendations only for abuse of discretion.

Sam Hallam, ’25, and Katherine Stanton, ’25, are leading efforts to remedy other aspects of FOP’s new collective bargaining contract that thwart police accountability and transparency in Chicago, including a provision that prohibits the videotaping of conversations between officers and supervisors after a police officer shoots a community member. The recording and use of such conversations are critical tools to remedy the longstanding code of silence in the CPD—a code that has encouraged officers to manufacture a common narrative when an officer shoots or kills a person or is otherwise accused of misconduct.

Medical-Legal Partnership with University of Chicago Trauma Center

Rosie Gruen, ’25 , and Sam Hallam, ’25, have led a medical-legal project that we launched last year with the Trauma Center at the University of Chicago Medical Center (UCMC) and pro bono attorneys from the Akerman law firm to prevent police from to violating patient civil rights and medical privacy and interfering with critical medical care. We formed this partnership to address reports from the doctors and staff at the Medical Center of police abuse of patients who have suffered gunshot injuries; coercive interrogations of people who are being treated for serious injuries; interference with medical care and patient autonomy over medical decisions; searches and seizures of patients’ personal property; invasions of patient privacy and personal health information; shackling and physical abuse of patients; and forcing medical personal to perform invasive tests on patients. The Clinic team has been conducting and working to publish empirical research on interactions between police and professionals and staff at the Medical Center and patients and their family members. In addition to the conducting approximately fifty long-form interviews, the Clinic has researched the intersection of property law, criminal law and procedure, privacy law, constitutional law, and administrative regulations and practices in medical settings around the United States. Students have also consulted with national medical and legal experts. Based upon our research, the Clinic developed a first draft of recommended UCMC policies for internal feedback to prevent ongoing civil rights violations and interference with patient care. Our research has also taught us that despite similar civil rights violations in hospital settings and interference by law enforcement with medical treatment, there is a lack of model policies or established best practices on the subject. We are hopeful that the publication of our research and the policies that we develop at UCMC will serve as a model for hospitals throughout the country and prevent civil and human rights violations and improve health outcomes in the Trauma Center and beyond.

Partnership with the Cook County Public Defender and Zealous

We also built on our partnership with the Cook County Public Defender’s Office and Zealous, a national non-profit dedicated to supporting public defender offices, to identify and address systemic issues in the criminal legal system that deprive clients of the Public Defender and Clinic access to justice. Darius Diamond, ’24 , Gabbie Zook, ’24 , and Katherine Stanton, ’25, have led our efforts on this project. This year, our focus has been to support the Public Defender’s work to create two holistic community defender offices in Chicago—the first is scheduled to open this fall in the Roseland community on Chicago’s South Side. The second will be in the Austin community on the West Side. Clinic students have been on the ground floor in designing the offices and services with community members, public defenders, and people in jail. We are developing plans for Clinic students to maintain a regular presence in the Community Defender Offices to work with public defenders and their clients in addressing police accountability and other systemic barriers to justice.

In addition, students are working with public defenders in Cook County to achieve greater independence from county prosecutors and judges when advocating with their clients to change and enjoin laws, policies and practices that impair the ability of public defenders to represent their clients and to improve the criminal legal system. For example, Clinic students are currently working with the Public Defender to explore ways to change the law to give the Public Defender the power to retain counsel to bring affirmative civil rights litigation.

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• Published: 02 September 2024

Ecological impacts and supply demand evolution of the Yangtze to Huaihe water transfer project in Anhui section

• Wenqing Ding 1 , 2 ,
• Guangzhi Shi 1 ,
• Hui Zha 1 ,
• Haojie Miao 1 ,
• Mengmin Lu 1 &
• Jing Jin 1  

Scientific Reports volume  14 , Article number:  20311 ( 2024 ) Cite this article

Metrics details

• Ecosystem services
• Sustainability

Human activities have profound impacts on land use and the supply–demand balance of ecosystem services (ESs). Various activities, such as urban construction, urban and rural planning, and inter-basin water transfer projects, continuously reshape land use patterns. This is a case study of the Anhui section of the Yangtze-Huaihe Water Diversion Project. Data from 2000, 2010, and 2020 is analyzed. Additionally, the patch-generating land use simulation (PLUS) model is utilized to quantify the specific impacts of the water diversion project construction on the supply and demand of ESs. The results indicate that the comprehensive dynamic attitude of land use during the project construction period significantly increased, rising from 0.16 to 13.79%, and mainly affected forest, water areas, construction land, and unused land. Specifically, the construction of the project led to significant changes in water purification, biodiversity, and, especially, hydrological regulation services. Additionally, the migration of residents significantly impacted the demand for ESs. The study also found a significant correlation between land use changes and the balance of ES supply and demand: the proportion of cultivated land and construction land is positively correlated with the balance, while the proportion of forest, grassland, and water areas is negatively correlated. This study provides empirical data for understanding the environmental and socio-economic impacts of large-scale water diversion projects and offers a scientific basis for local mitigation and control of adverse impacts. Through quantitative analysis and model prediction, this research effectively bridges the gap between theory and practice, providing important references for sustainable regional development.

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Introduction.

Human activities, as the primary drivers of land use change, have had profound impacts on the supply–demand balance of ecosystem services (ESs) globally. These activities include a wide range of human endeavors such as inter-basin water transfer projects, urban construction, and urban and rural planning 1 . These activities not only alter land use types and patterns but also significantly affect the structure and function of ecosystems. Among the diverse human activities 2 , inter-basin water transfer projects are one of the key factors influencing land use and the supply–demand balance of ESs. Projects such as the Central Valley Project in the United States, the Indus Basin Project in Pakistan, and China’s South-to-North Water Transfer Project have played important roles in national development and regional policy-making 3 . Taking China’s Yangtze-to-Huaihe Water Diversion Project as an example 4 , this project has the potential to bring significant benefits in navigation, irrigation, freshwater supply, hydropower development, and tourism, and it also holds national strategic significance 5 . However, under the backdrop of accelerating urbanization and continuously adjusting urban and rural planning 6 , 7 , the impacts of urban construction and planning on land use cannot be ignored 8 . The Yangtze-to-Huaihe Water Diversion Project, as a link between the Yangtze River Delta urban agglomeration and the Central Plains urban agglomeration, plays a special role in alleviating drought and water shortages in the Huaihe River, constructing a major north–south water transportation artery, and improving the aquatic environment of Chaohu Lake and the Huaihe River 9 , 10 . Nevertheless, the project itself is not the sole factor influencing changes in land use types 11 , 12 . Urban construction, urban and rural planning, and climate change also play important roles 13 . This study aims to consider the water transfer project as one of the factors influencing land use changes, while also incorporating the impacts of other human activities such as urban construction and planning, to deeply analyze how these factors collectively affect the supply–demand balance of ESs. Against this backdrop, this paper takes the Anhui section of the Yangtze-to-Huaihe Water Diversion Project as an example to explore the specific impacts of human activities, particularly water transfer projects, on land use and the supply–demand balance of ESs 14 , as well as the potential implications of these changes for regional sustainable development 15 , 16 , 17 . Through comprehensive analysis, this study aims to provide scientific evidence for understanding and mitigating conflicts between project construction and ecological protection, and to offer important references for regional sustainable development.

In recent years, some scholars have attempted to study the supply and demand of ESs from the perspective of cross-basin water diversion projects 18 . For example, Li et al. analyzed the impact of cross-basin water diversion projects on basin ESs based on the soil and water assessment tool model and the total ES index 19 . Moreover, Souza et al. developed a spatial decision support system with a hydro-economic optimization model and used it to identify and analyze the optimal economic allocation of water resources to improve water resource management efficiency 20 . Furthermore, Peng et al. constructed a payment mechanism for inter-basin water transfer ESs, applying the contingent valuation method to examine the willingness of water-receiving areas to pay and their willingness to accept water sourced from eastern route areas of the South-to-North Water Diversion Project 21 . Additionally, Peng et al. created a method for calculating the ecological compensation standards for water-receiving areas in China's cross-basin water transfers 22 . For example, this method was applied to the main water-receiving areas of the South-to-North Water Diversion Project. Based on the characteristics of the selected ES evaluation indicators for the water-receiving areas, the energy theory was used to calculate the increment in ESs 23 . These studies focus on the economic optimization of water resource allocation and ecological compensation 24 . In contrast, this research introduces the patch-generating land use simulation (PLUS) model, deeply analyzes the relationship between land use changes and the balance between ES supply and demand, innovatively reveals the specific impact of cross-basin water diversion projects on ESs, and provides a new management perspective for sustainable regional development 25 .

Although the aforementioned studies have made certain progress in water resource management and ecological compensation, methodological challenges in the evaluation of ES supply remain 26 . The evaluation methods for ES supply are mainly based on the equivalent factor method (EFM) and ecological modeling 26 . Although ecological modeling can be used to effectively evaluate the integrity of ecosystems, it involves many parameters, is time-consuming and laborious, and includes various complex calculation equations 13 . The complex evaluation process leads to significant uncertainty in the evaluation results. In contrast, EFM can be tailored to local conditions by modifying equivalent values and corresponding calculated area 27 , thereby flexibly and effectively assessing ESs at different scales and effectively avoiding problems with complex multiple calculations of parameters. EFM is based on the evaluation principles, methods, and basic steps created by Costanza. Xie localized Constanza's method, defining the equivalent value per unit area of China's ESs, becoming an important research basis for Chinese scholars to revise ES evaluations 28 . As a universal and reliable method for quantifying ESs, EFM is suitable for large-scale calculations and can provide a solid foundation for ES supply evaluations. The calculation of ES demand is relatively immature, with few quantitative models and methods. Existing studies mostly use expert scoring and socio-economic statistical calculations 29 . Among them, the use of socio-economic statistical indices is widely recognized, reflecting regional ES demand levels through land development intensity, population density, and economic indicators, which is a practical and objective approach 30 . An analysis of the balance between supply and demand is crucial for understanding the impact of water diversion projects on ESs, helping to reveal the dynamic changes in ES supply and demand during project construction and operation 31 . In terms of land use simulation and prediction, compared to other models, PLUS provides high-precision land use simulation 32 . When considering influencing factors, we emphasize the important role of climate factors in service changes or balance changes, especially in large water diversion projects where climate factors are often key factor in ES changes 33 . The management of cross-basin water diversion projects should focus on future trends of ESs, which is crucial for formulating adaptive strategies aimed at protecting the ecological impacts of construction projects 34 . As the construction of the Three Gorges Dam was ongoing, an environmental monitoring network for the dam was established. This network monitored the ecological background and changes in the reservoir area and compiled project environmental impact reports that were adjusted in real-time based on local dynamics, facilitating correct decisions and ensuring the normal operation of the project while preventing harm to the health of the basin's ecological environment.

Generally, the inter-basin water transfer project has brought great social and economic benefits. However, the permanent land cover, water storage inundation, and resettlement resulting from the water transfer project during the construction process have caused significant changes in the land use structure in the basin. These changes have led to spatial differences or imbalances in the supply–demand of ESs in the basin 35 , causing severe environmental impacts on the basin 36 . However, presently, most studies only focus on the economic benefits resulting from the project and do not consider the impact of ecological supply–demand changes 37 . Therefore, this paper selected the Yangtze-to-Huaihe water diversion (YHWD) project in the Anhui section as a research area. The selection of land use data from the years 2000, 2010, and 2020 corresponds to key development phases in China over the past two decades, aligning with existing research findings 38 , 39 , 40 . The land use and ecosystem services (ES) changes in Anhui Province between 2000 and 2020 have shown significant patterns, and this period coincided with the construction of the YHWD project. This choice aims to reveal the long-term trends in land use and ES supply and demand, as well as to understand the long-term changes in the study area. The modified equivalent factor methods 41 , the GeoDa model 42 , and correlation heat maps were used to explore the influence of land use change on the supply–demand of ESs under the inter-basin water transfer project. Moreover, the PLUS model was used to simulate and forecast the land use situation in 2030. Notably, the PLUS model can be used to explore the spatial distribution of ES supply and demand in 2030. The findings of this study provide a basis for the formulation of regional ecological compensation and land improvement policies affected by inter-basin water transfer projects. Therefore, this study focuses on investigating the impact of the construction process of the Anhui section of the YHWD Project on the supply and demand of ESs.

The research data from 2000, 2010, and 2020 were analyzed using the modified EFM, GeoDa model, and related heat maps. To predict future land use changes, the PLUS model was used to simulate and forecast land use scenarios for 2030 (Fig.  1 ). Additionally, 2030 is a critical time point for YHWD program operations. On this basis, the spatial pattern of ES supply and demand for 2030 was further assessed. This study advances the theory of ES supply and demand, especially in the research field of the impact of land use changes on the balance between ES supply and demand. Through a specific case analysis of the Anhui section of the YHWD project, we not only identify the impact of land use changes on the balance between ES supply and demand but also further clarify the specific relationship between different land use types and the dynamics of ES supply and demand, providing theoretical and methodological guidance for future research.

Graphical abstracts.

Material and methodology

The middle and lower reaches of the Yangtze-Huaihe River Basin suffer from severe water pollution. The water bodies have lost their original resource value. Soil erosion is severe in the Yangtze-Huaihe River Basin. The water conservation capacity has decreased, and riverbeds are silted with sediment, affecting navigation, the efficiency of water conservancy projects, and flood control safety. The YHWD Project is a large-scale inter-basin water transfer project in China, with a total water conveyance length of 723 km, of which the Anhui section is 587 km long, accounting for 81.3% of the entire project. The project consists of three segments: the Yangtze-to-Chaohu, the Jianghuai Canal, and the Northward Water Transfer. It closely connects the Yangtze River Delta urban agglomeration with the Central Plains urban agglomeration, playing a crucial role in alleviating drought and water shortages in the Huaihe River, constructing a major north–south water transportation artery, and improving the aquatic environment of Chaohu Lake and the Huaihe River. This study focuses on nine cities within Anhui Province, covering a watershed area of approximately 73,700 km 2 (Fig.  2 ). The impact area of the project is defined as the regions directly affected by the project, including areas along the water diversion route and the surrounding benefiting regions. Specifically, the project's impact area includes: (1) the Yangtze-to-Chaohu segment, which diverts water from the Yangtze River to Chaohu Lake, with a total length of about 170 km; (2) the first segment of the Northward Water Transfer, from Chaohu Lake to the Huaihe River, with a total length of about 224 km; and (3) the second segment of the Northward Water Transfer, from the Huaihe River to the Yangtze River Delta urban agglomeration, with a total length of about 193 km. The project's impact area not only covers the Jianghuai basin but is also closely linked to the Yangtze River Delta and Central Plains urban agglomerations. With the implementation of the water diversion project and the advancement of economic and social development, the supply–demand balance of ecosystem services (ESs) has undergone significant changes.

Study the geographical location of the area.

The provision of ESs encompass several datasets, namely land use status, food production, and food price data. The land use information primarily originated from the Resource and Environment Science and Data Center ( http://www.resdc.cn ). Including 30 m accuracy data in 2000, 2010 and 2020. Although we were unable to obtain land use data for consecutive years between 2000 and 2020, the data for these three time points has been meticulously calibrated to ensure its reliability. ArcGIS 10.2 was employed to reclassify the land utilization data. Grain output and grain price are derived from Anhui Provincial Statistical Yearbook.

ESs’ demand data primarily encompass the ratio of land designated for construction, population density, and Gross Domestic Product (GDP). The building land ratio is determined by dividing the total building land are by the total land area. It can be obtained from the Resources and Environmental Science and Data Center's website, that information on population density and GDP for the period from 2000 to 2020 ( http://www.resdc.cn ).

Drawing on existing research 43 , 44 , 45 findings and considering the actual operational conditions and data availability of the Yangtze River to Huaihe River Project (Anhui section), this paper identifies eight influencing factors (Table 1 ). These factors include rainfall, temperature, altitude, slope, GDP, population density, distance from roads, and distance from rivers, covering aspects of nature, socio-economic conditions, and accessibility.

Methods for quantifying the ESs’ supply–demand

A quantitative approach to ess’ supply.

Initially, we computed the per-unit area factor of ESs, followed by the determination of the per-unit area equivalent of ESs for various land use categories between 2000, 2010, and 2020. To accomplish this, we referenced the per-unit area equivalent of ESs in China, as suggested by Xie Gaodi 46 , 47 . Additionally, the equivalent factors for different time periods were adjusted based on the grain output data derived from the Anhui Statistical Yearbook. Ultimately, the estimation model for ESs valuation was employed to assess the provision of ESs by the YHWD Project within the Anhui section.

ESs equivalent per unit area

Due to the disparity in land use data classification and ecosystem categorization criteria employed by the Xie team 9 , it is necessary to make adjustments according to the research needs. Specifically, it is necessary to merge the dry land and paddy field categories into arable land, combine the mixed conifer, needle width, broadleaf, and shrub categories into woodland, reclassify the shrub category as grassland, and designate the water system and wetland categories as water. Additionally, the urban land and rural residential areas should be considered as building land, while the bare land and marshland should be regarded as unused land. To evaluate the ESs function value, the research findings should be averaged and then compared to a standard equivalent 48 , allowing for the determination of the basic equivalent value for various ESs functions in the study area.

Modified equivalent factor

Taking into account the spatiotemporal dynamics of ESs, we have revised the equivalent variables for the research area spanning from 2000, 2010, and 2020. To accomplish this, the following step-by-step process was executed: Initially, the yield of grain per unit area on average within the research area over a 20-year period was computed as 4884 kg/hm 2 using data from the Anhui Statistical Yearbook 49 .

where D is an equivalent factor, that is, ESs value per unit area, 1/7 is the ratio of consideration of grain income to cost, P is grain output per unit area, which is obtained by dividing grain output by grain arable land area, and Q is grain price.

ES value estimation model

The value denoting the equivalent factor of the research area between 2000, 2010, and 2020 equates to 1779.17 yuan/hm 2 . Based on this, we have calculated the ES value per unit area of the adjusted research area (Table 2 ) 50 .

where, ESV is total value of ESs; Bk is area of the k species; VCk is ecological value coefficient.

A quantitative approach to ESs’ demand

The demand for ESs reflects the need for human utilization. This study chooses three indicators that exhibit a positive correlation with the demand for ESs, specifically the percentage of developed land, density of inhabitants, and economic intensity. A comprehensive model encompassing multiple indicators is employed to calculate the demand index 51 , 52 .

where: N represents the demand index; Di, Pi, and Ei represent the percentage of developed land, developed land, and economic intensity.

Methodologies for determining ESs’ supply–demand

Ess’ supply–demand matching.

The Z-score standardized method was adopted to eliminate the unit influence. Supply and demand are represented on the x and y axes 53 . The relationship is depicted through four quadrants: high supply-high demand (HS-HD), low supply-high demand (LS-HD), low supply-low demand (LS-LD), and high supply-low demand (HS-LD) 54 .

ESs’ Supply–demand balance

The balance represents the degree of coordination between the ecosystem and human well-being 55 .

where: Cv is the equilibrium index; P is the supply index; N is the demand index. The higher the equilibrium index is, the better the coordination. 0 means complete dissonance and 1 means good coordination. With reference to relevant literature, this paper divides the equilibrium degree into the following 5 sections (Table 3 ):

The PLUS model combines two modules: the LESA model and the CA model 56 . This integration enables the accurate simulation of nonlinear relationships associated with land utilization changes and allows for the examination of the effects of land utilization on potential ES functions in different policy scenarios in the future 57 .

Confirm model accuracy Firstly, land utilization data spanning from 2000 to 2010 was used as input for the model, extracting the land use expansion map over this timeframe. Next, the expansion map, along with the driving factors, was loaded into the LEAS module. Generate various types of land development potential maps. Finally, the 2010 land use data and the development potential map for each type of land were input into the CA module, along with the simulation parameters. The simulated data was subsequently juxtaposed with the real data to evaluate the simulation's accuracy. The results show a Kappa coefficient of 0.939. The Kappa coefficient is a statistical indicator used to assess the consistency between model prediction results and actual observed data. The outcome indicates substantial consistency between the simulated data and the real data.

The specific research parameter settings are as follows In the LESA module, the sampling frequency is set to 0.01, and the number of regression trees is set to 20. The sampling frequency refers to the frequency at which samples are extracted from the original dataset during data processing or model training. Setting the number of regression trees to 20 indicates that the model will use 20 independent regression trees to construct a random forest model. With the sampling frequency set at 0.01 and the number of regression trees at 20, the computational efficiency and performance of the model are optimized. In the CARS module, the domain weight can be determined by evaluating the expansion mode of different land categories during the process of change 58 . This evaluation provides a quantitative measure of the intensity with which various land use types expand, and the resulting value ranges from 0 to 1. This study calculates the area covered by different land use categories using a transfer matrix approach. By applying the formula below, the domain weight for each land use category is derived. The formula is as follows 59 :

It means that Wi is the weight of Class i land domain, Ti is the expansion area of Class i land use, T min is the minimum expansion area of each type of land, and T max is the maximum expansion area of each type of land. The calculation results showed that the factors of arable land, forest land, grassland, water area, building land, and unused neighborhood were set as 0, 0.48, 0.49, 0.52, 1, and 0.51. The setting of the neighborhood factor depends on the conversion probabilities and trends between different land use types, aiming to reflect the interactions and conversion potential among various land use types 60 . Based on the conversion probabilities of various land use types from 2010 to 2020, the neighborhood factors for cultivated land, forest land, grassland, water areas, construction land, and unused land are set to 0, 0.48, 0.49, 0.52, 1, and 0.51, respectively.

Evolution of land use pattern

A comparative analysis was conducted on the land use status of the YHWD project in the Anhui section for the years 2000, 2010, and 2020 (Fig.  3 ). Across the entire region (Fig.  3 ), farmland accounts for the largest proportion, followed by build-up land. Over the past two decades, there has been a noticeable decrease in the areas of farmland and forest. Conversely, the coverage of water and build-up land has significantly increased. From 2000 to 2010, the comprehensive dynamic outlook before the project construction was 0.16%. From 2010 to 2020, under the influence of project construction, the comprehensive dynamic attitude rose to 13.79%. In conjunction with Fig.  4 , the reduction rates of farmland and grassland show almost no change. However, from 2010 to 2020, the reduction rate of forest land increased sharply. In contrast, the growth rates of water and unused land from 2010 to 2020 show a significant increase compared to the period from 2000 to 2020. Similarly, the growth rate of build-up land also shows an upward trend. It is noteworthy that the changes in land use types are not only influenced by the water diversion project but also by other factors such as urban construction, urban and rural planning, and climate change. In terms of urban construction, the acceleration of urbanization has led to an increase in build-up land area and a decrease in farmland and forest areas. Adjustments in urban and rural planning have also affected changes in land use types; for instance, some farmland may be reclassified as build-up land to meet urban development needs. The impact of climate change on land use types cannot be ignored either. For example, warming climates could lead to an increase in water area in certain regions, while drought could result in a decrease in farmland area (Table 4 ).

Land use status map in 2000, 2010 and 2020.

Pattern of ESs’ supply in 2000, 2010 and 2020.

Changes in ES supply, demand, and equilibrium degree

Temporal and spatial changes of es supply and demand, temporal and spatial evolution of es supply.

From a regional perspective, the supply level of ESs was relatively low between 2000 and 2020 (Fig.  4 ). The southern region exhibited a higher supply capacity than the northern region. Over the past two decades, the total value of ESs experienced a decline followed by a subsequent increase, with a continuous decrease observed from 2000 to 2010. From 2010 to 2020, the total value of ESs gradually increased. Moreover, the rate of decline was faster than the rate of increase, and the final reduction was 978 million yuan. In Table 5 , it is evident that the rate of change in the two time periods is consistent for most ESs. These services exhibited a gradual decrease over time, following a linear trend. Conversely, water supply service increased linearly. The decline rate of water purification services and biodiversity services from 2000 to 2010 was significantly higher than it was from 2010 to 2020. Furthermore, hydrological regulation services decreased continuously from 2000 to 2010 and gradually increased from 2010 to 2020, with a higher rate of increase than the rate of decline.

Although the construction of the project does not significantly affect most services, it has a considerable impact on services such as water purification, biodiversity, and hydrology regulation. Among these services, hydrological regulation is most significantly affected. Additionally, in terms of supply capacity, section I > section III > section II. The ES value of section III has increased by 138 million yuan, while that of section I has decreased by 327 million yuan.

Spatial and temporal evolution of ES demand

From an overall perspective, the demand for ESs increased by 95.44% from 2000 to 2020 (Fig.  5 ), and the intensity of demand increased in the northern region and diminished in the southern region, contrary to the spatial pattern of supply capacity. The growth rate from 2000 to 2010 was 40.47%, while that from 2010 to 2020 was 31.8%. The growth rate of demand is declining, and the relocation activities caused by construction projects may be one of the underlying reasons. In terms of demand intensity, section III > section II > section I. Moreover, the demand intensity is consistent with population density and built-up land distribution. Sections III, II, and I increased by 22,243.5, 16,025.4, and 10,472, respectively. Due to the rapid development of Hefei, built-up land has expanded rapidly and the population has increased, resulting in the most prominent growth in demand in section II. Among them, Hefei, Bengbu, Fuyang, Bozhou, Huainan, Wuhu, and other cities have high demand intensity, which gradually decreases from the city center to the periphery. Overall, the supply and demand in the Anhui section of the YHWD Project show great differences in spatial position.

Demand pattern of ESs in 2000, 2010 and 2020.

Changes in the supply and demand relationship of ESs

As can be seen from Table 6 , the general balance between supply and demand for the YHWD Project in the Anhui section from 2000 to 2020 is considerable. Moreover, there is a noticeable variation in spatial distribution, with high levels in the northern region and low levels in the southern region. The overall distribution of the quality coordination area surpasses that of the completely disordered area. From 2000 to 2010, the size of completely disordered areas decreased continuously, but from 2010 to 2020, the area affected by engineering construction increased. Similarly, despite the increasing extent of areas with minor disorders, its increase from 2010 to 2020 has demonstrated a substantially higher rate compared to the pace in the preceding period. The preceding period exhibited a higher growth rate in the relative coordination area compared to the rate in the succeeding period. In contrast, the area of quality coordination experienced a continuous decrease. Interestingly, the decline rate in the latter period was relatively slower than that observed in the earlier period. Conversely, the construction of the project has a certain effect, and the most affected disordered area in section I increased significantly compared to the corresponding size of the area before the construction of the project. Research conducted revealed that low supply-high demand (LS-HD) and low supply-low demand (LS-LD) significantly dominate the research area, constituting approximately 34.5% and 40.9% of the area, respectively.

From a regional perspective, the alteration of supply and demand equilibrium is consistent with the trend of change in the demand index (Fig.  6 ). The regions with high-quality coordination and relative coordination are concentrated in sections III and II, while the regions with complete disorder and relative coordination are mainly concentrated in section I. The proportion of LS-HD and LS-LD in section III is relatively high, being 55% and 38.5%, respectively, and the distribution of supply index and demand index is relatively coordinated. Among them, the section of Yangtze River to Huaihe communication is dominated by LS-HD, accounting for approximately 41% of communication. Due to the low supply index and population agglomeration, the demand intensity has increased, and the demand is greater than the supply. Section II has superior natural conditions in the research area, and HS-LD dominate there, accounting for approximately 52% of land use, and the overall supply surpasses demand. With the rapid development of surrounding towns and cities, the built land is gradually intensifying, and the demand for ESs continues to improve, resulting in the constant improvement of the supply and demand equilibrium.

Area changes in the balance between supply and demand for ESs between 2000, 2010 and 2020.

Correlation between land use change and the balance between ES supply and demand

The Moran's I index test indicates a significant correlation between the current state of land use and the balance of ecosystem services (ES) supply and demand across different study periods (Fig.  6 ). The findings indicate that alterations in the supply–demand balance exhibited a linear association, with changes observed in various land categories. Variations in the extent of different land use types will consequently induce modifications in the equilibrium of ES supply and demand.

Further examination of the heat map depicting correlation (Fig.  7 ) shows that the degree of correlation between various land use types and the supply–demand balance corresponds to the following sequence: arable land holds the highest proportion, followed by forest land, water area, built-up land, grassland, and unused land. There is a positive association between the balance of supply and demand and the proportion of farmland and built-up land. Conversely, a negative correlation is observed between the proportion of forest land, grassland, and water area. In 2000, the correlation coefficients of forest, farmland, built-up land, water area, grassland, the proportion of unused land, and supply and demand equilibrium were 0.32, 0.31, 0.22, 0.14, 0.12, and 0.004, respectively. In 2010, the correlation coefficients were 0.52 for farmland, 0.46 for forest, 0.34 for water, 0.32 for built-up land, 0.25 for grassland, and 0.007 for unused land. In 2020, the correlation coefficients were 0.53 for farmland, 0.45 for forest, 0.33 for water area, 0.24 for grassland, 0.22 for built-up land, and 0.002 for unused land.

The correlation between land use proportions and the supply–demand equilibrium from 2000, 2010 and 2020.

The quality coordination of the research area is mainly in sections III and II and mostly consists of farmland and built-up land, dominated by LS-HD areas. The coordination and LS-HD suggest that the difference between supply and demand in this region is minimal: most of the seriously disordered areas are located in section I. Hence, while ensuring an equilibrium between supply and demand, it is essential to uphold harmony between cultivated and built-up land to curtail the surge in demand. Section III has a large difference between supply and demand and, owing to its substantial supply of natural materials, can be properly developed to increase demand.

Forecast of supply and demand of ESs in 2030

Based on the above research, the PLUS model was implemented to estimate future supply and demand modes by predicting land use. The prediction results show that in 2030, farmland and built-up land will dominate the research area, with farmland accounting for the largest proportion (65.99%). Compared with 2020, the area of farmland and forest in the research area in 2030 will decrease by 935.65 km 2 and 23.58 km 2 , respectively, with farmland area showing the most significant decrease.

In terms of supply (Table 7 ), the ES value of the YHWD Project in the Anhui section will be 162,989 billion yuan in 2030, with the water area accounting for the highest proportion. Farmland will be second, accounting for 24.54% of the ES value. Compared with 2020 figures, the ES value of the research area will decrease by 1.52% in 2030. Moreover, in 2030, the ES of farmland, forest, and grassland will experience a decline, whereas the ES of water and unused land will witness an increase. The continuous transformations in land use, caused by engineering construction, have led to significant ecological changes, particularly regarding farmland and water.

The demand index of the research area in 2030 evaluates the population and economic densities for that year, taking into account the population and GDP growth rates in 2000, 2010 and 2020. Additionally, the index determines the percentage of built-up land by analyzing the projected land use data for 2030. As a consequence of the ongoing progress in urban infrastructure, there has been a noticeable rise in the allocation of land for construction purposes. Furthermore, the growth in GDP resulting from economic advancement will fuel the escalating demand for ESs relative to 2020. Specifically, the maximum demand areas will still be primarily located in urban areas, and the overall ES demand will be low in section I due to increased forest and water area (Fig.  8 ). Section III has many small and medium-sized cities, the construction land density is largely dense, and the overall ES demand is high. With Hefei city as a core, the demand for ESs in section II is highest, and the demand gradually decreases from the core to the outside.

Map of ESs’ projections for 2030.

According to scientific research, land use has a substantial impact on supply and demand. A comparison between the ES balance in 2020 and projections for 2030 reveals significant improvements in the overall ES balance and a noticeable shift in equilibrium. LS-HD and LS-LD still dominate supply and demand.

Impact and forecast of water and heating engineering on ES supply and demand

Due to extensive resettlement and population migration, the implementation of the YHWD Project has not only resulted in a substantial rise in water area and built-up land but also has a notable impact on land use transformation 61 . Between 2000 and 2010, land use change was characterized by a decrease in farmland and forest and an increase in built-up land. This situation occurred before the project was constructed, and urban development may have been the primary driving factor 62 . From 2010 to 2020, the predominant land use change involved the transition from other land use types to water and built-up land. This period witnessed a swift expansion of water, with unconventional interference projects being the likely primary driving factor 63 . Compared with other relevant studies, there are similar research results on the impact of engineering construction on land use change 64 .

The construction of the Anhui section of the YHWD project has both positive and negative impacts on ES supply. The project has increased water production and improved hydrological regulation 65 , but services such as environmental purification and biodiversity continue to decline (Fig. 9 ). The influence of engineering projects on water production and hydrological regulation is greater than the influence of other factors, consistent with research findings on the Three Gorges reservoir area and other related studies. According to the research findings, an alteration of land use patterns resulting from engineering construction leads to spatio-temporal variations in supply and demand. The influence of the engineering project on demand primarily stems from a rise in built-up land proportion and changes in demand due to population migration. At the initial construction phase, the area of serious imbalance increased and the area of quality coordination decreased. Furthermore, the intricate nature and diverse composition of human and environmental systems typically result in the transmission of supply–demand of ESs 66 . Consequently, conducting dynamic temporal evolution studies becomes imperative to effectively comprehend the magnitude of supply–demand within the designated research vicinity.

Changes in the supply value of individual ESs in the study area.

Factors influencing the supply and demand of ESs in the YHWD project

When examining factors influencing the supply and demand of ESs and land use changes beyond the construction of the YHWD project (Anhui section), it is crucial to recognize that the dynamics of land use are the result of the interaction of multiple factors. Analyzing the sensitivity of various land uses to eight driving factors not only unveils the intrinsic mechanisms of land use change but also validates the effectiveness of the PLUS model in predicting and simulating land use dynamics. The sensitivity of different land uses to these driving factors varies: farmland is most sensitive to population density and GDP, forests to temperature and population density, grasslands to temperature and elevation, water to population density and distance from rivers, built-up land to population density and distance from major roads, and unused land to temperature and GDP 67 . The construction of the YHWD Project (Anhui section) has had significant impacts on forest, water, build-up land, and unused land, while its effects on farmland and grassland are relatively weaker. This can be attributed to factors such as land acquisition during the construction process, resettlement of residents, and related policy directives. For instance, from 2010 to 2020, the area of water bodies increased by 0.86%, partially due to the implementation of the water diversion project. However, it is important to note that this impact is not caused by a single factor, but is the result of the combined effects of other human activities and natural factors. With the acceleration of urbanization, the types of land use in urban fringe areas have undergone significant changes. We observed that the area of build-up land increased by 10.02% from 2010 to 2020, which is significantly higher than the growth rate from 2000 to 2010 (Fig. 10 ). This change is mainly due to urban expansion, where farmland and forest have been converted to build-up land to meet the demand for residential and commercial facilities. For example, Hefei, the capital of Anhui Province, experienced rapid urbanization during this decade, resulting in a large amount of farmland being converted into build-up land. Adjustments in urban and rural planning policies also significantly influenced changes in land use types. To promote balanced regional development, some areas may have implemented new land use plans, such as establishing industrial parks or new urban districts, leading to large-scale land use transformations. For instance, the urban master plan implemented in Chuzhou during this period likely led to the conversion of suburban farmland into build-up land.

In addition to the aforementioned human activities, other factors also influence land use changes. Economic growth and industrial structure adjustments are significant factors affecting land use changes. Farmland and unused land are most sensitive to GDP changes. With the rapid economic development in Anhui Province, the expansion of the secondary and tertiary industries may have led to more land being utilized for industrial and service sectors. Changes in population density significantly impact various types of land use, especially farmland, forest, and build-up land. Population growth and urbanization have accelerated the expansion of build-up land while also increasing pressure on farmland. Climate factors, particularly temperature changes, have a significant impact on forest and grassland. Climate warming may lead to changes in vegetation cover in certain areas, thereby affecting land use types. Changes in agricultural policies, such as land transfer policies and agricultural subsidy policies, may also lead to changes in farmland types and intensified land use. For example, the agricultural modernization policies implemented in Anhui Province may have promoted the formation of large-scale agricultural land, altering the traditional small-scale farming model. The land use changes observed in 2000, 2010, and 2020 are the result of the combined effects of multiple factors. While the implementation of the YHWD Project has indeed impacted land use in the study area, it is only one of many influencing factors. Urban construction, urban and rural planning, economic development, population changes, and climate change all shape the land use patterns in the study area. This complex interaction has ultimately led to the observed trends in land use changes and has profoundly impacted the supply–demand balance of ESs. Future research should aim to further quantify the relative contributions of these factors to better understand the driving mechanisms of land use changes, providing more precise scientific evidence for regional sustainable development and ecosystem service management.

Sensitivity of various land uses to drivers.

Changes in the supply and demand of ESs are also influenced by multiple factors. As an illustration, ES supply first decreased and then increased from 2000 to 2020, which may be associated with factors such as agricultural policy adjustments, climate change, and biodiversity reduction 68 . Moreover, adjustments in agricultural policies may lead to a decrease in food and raw material production, while climate change may affect the supply of climate regulation services. For example, global warming can impact the distribution of water resources, thereby affecting the supply of hydrological regulation services. Furthermore, the decline rates of water purification services and biodiversity services were significantly higher from 2000 to 2010 compared to their levels from 2010 to 2020, which may be related to the implementation of pollution control measures and the strengthening of ecological protection policies.

ES demand is higher in the north and lower in the south—opposite to the spatial pattern of supply capacity. This phenomenon may be associated with factors such as population growth, urban expansion, and economic development. For example, the rapid development of cities such as Hefei has led to a rapid expansion of construction land and a concentrated increase in population, significantly raising ES demand. Moreover, the migration activities of residents due to construction projects may be one of the reasons behind the decrease in demand growth rates. The changes in the equilibrium of supply and demand align with the trends in demand index changes, with high-quality and high coordination areas concentrated in sections where water is sent north and the section where the Yangtze and Huaihe rivers are connected, while areas of complete disorder and low coordination are mainly concentrated in sections where water is diverted to Lake Chaohu. This outcome may be related to factors such as regional economic development levels, population density, and distribution of construction land. For example, sections where water is sent north and where the Yangtze and Huaihe rivers are connected have high economic development levels and large population densities, leading to high ES demand and relatively low supply capacity, resulting in patterns of high demand with low supply and low demand with low supply. In contrast, in the section where water is diverted to Lake Chaohu, there are more favorable natural conditions and stronger ES supply capacity but relatively lower demand, resulting in a pattern of high-supply with low demand.

The changes in ES supply and demand in the middle and lower reaches of the Yangtze and Huaihe rivers are the result of the combined effects of multiple factors. In assessing these changes, we need to comprehensively consider factors beyond the construction of the Anhui section in the YHWD Project, such as urban development, agricultural policies, natural disasters, and socioeconomic changes as well as their interactions to gain a comprehensive understanding of the dynamic changes in ES supply and demand and provide a scientific basis for sustainable regional development.

Coping strategies for ES supply and demand in the YHWD Project

Although the construction of water diversion projects cannot compensate for the damage caused by natural ecosystems, it can reduce the damage 69 . When a decision is made to build a water diversion project, policy measures should be attempted to minimize threats. During the establishment of the region covered in this research, the conversion of arable land and forest land into built-up land and water areas led to a notable decrease in the availability of ESs. Consequently, there was a substantial increase in demand, resulting in a significant misalignment . When a decision is made to build a water diversion project, policy measures should be attempted to minimize threats. During the establishment of the region covered in this research, the conversion of arable land and forest land into built-up land and water areas led to a notable decrease in the availability of ESs. Consequently, there was a substantial increase in demand, resulting in a significant misalignment between supply and demand. The ecological and environmental monitoring system established during the construction of the Three Gorges Project can serve as a reference, and the monitoring report can be used as a comprehensive evaluation basis for policy regulation. To build a sound monitoring and evaluation system for ES supply and demand, local governments must cover the entire project basin, including areas with HS-HD, HS-LD, LS-LD, and LS-HD for ecological supply and demand monitoring and specific assessment 69 . Firstly, this comprehensive approach aims to capture the impact and changing trends of the project on ES supply and demand. Moreover, the quality and stability of ES supply should be improved 70 . The local government should continue to promote the protection and restoration of the ecosystem. They should refer to Hu's research and use the matching degree of supply and demand to classify the priority level of ecological restoration, formulate restoration zones and optimization strategies 71 , and prioritize the protection of areas severely impacted by major engineering construction 18 .

Supply and demand should serve as the basis for the supervision and evaluation of the planning and implementation of ecological restoration in engineered river basins 55 . Additionally, the alterations in hydrology resulting from the project's construction may affect the spawning grounds and migration routes of fish in the Yangtze River Basin, resulting in a decline of biodiversity in the basin. Consequently, local governments need to formulate strategic plans and action plans for biodiversity protection in water diversion projects and improve the policy and institutional framework for biodiversity protection 54 . Furthermore, focus should be placed on high-supply areas, and the construction of the biodiversity conservation network system should be accelerated 53 , incorporating biodiversity indicators into the monitoring and evaluation system of water diversion projects between basins.

Contribution and limitation of the study

This study effectively bridges the gap between theory and reality through specific case analyses. At the theoretical level, this research deepens an understanding of the supply and demand dynamics of ESs, particularly in the context of land use changes under cross-basin water diversion projects. By examining the Anhui section of the YHWD project, we have unveiled the concrete relationships between different land use types (e.g., farmland, forest, and water areas) and the dynamics of ES supply and demand. These findings not only enrich existing theories but also provide new perspectives on understanding the impact of land use management strategies on ESs.

Compared to previous studies 51 , 52 , our research places greater emphasis on the quantitative relationship between land use changes and the balance of ES supply and demand, providing empirical support for theoretical models. The use of the PLUS model to predict future land use changes, with a high kappa coefficient of 0.939 for simulation validation, further confirms the scientific validity of our results. The integrated application of EFM and the GeoDa model to analyze the relationship between ES supply and demand enhances the accuracy and reliability of the study. Compared to single models or methods 72 , our research is more comprehensive in methodology.

Considering the complex interactions of multiple factors such as climate change and human activities, our research provides a scientific basis for the development of adaptive management strategies. Unlike studies that focus solely on theoretical analysis 50 , our research emphasizes practical applications, providing direct guidance for sustainable regional development. By revealing the impact of water diversion projects on the balance between ES supply and demand, this study provides a scientific basis for public participation in environmental protection and decision-making, thereby positively impacting society and human well-being. Unlike studies that focus solely on academic contributions 49 , our research emphasizes social impact, contributing to the advancement of society and environmental protection.

Although this study has made a preliminary contribution to an analysis of the balance between ES supply and demand in the YHWD Project (Anhui section) and provided a scientific basis and decision support for sustainable regional development, we are acutely aware of the limitations in our research. For instance, due to data source constraints, we were unable to obtain continuous land use data from 2000 to 2020 and instead used discrete data points from the years 2000, 2010, and 2020. This discontinuity in data may affect a comprehensive understanding of land use change trends. Moreover, in the selection of driving factors for the PLUS model, our consideration of climatic factors was not sufficiently comprehensive. The impact of climate change on ESs is complex, and future research should place great emphasis on the role of climatic factors to enhance the predictive accuracy and explanatory power of the model. We look forward to overcoming these limitations in future research and providing an in-depth analysis.

This study focuses on the YHWD Project as an empirical research area. Moreover, this research utilizes EFM and the GeoDa model to analyze the influence of the supply and demand relationship in the Anhui section of the YHWD Project. Additionally, this study predicts the future matching pattern of supply and demand by incorporating the PLUS model to provide theoretical support for the sustainable and healthy development of the basin ecosystem. The results are as follows: (1) The comprehensive dynamic attitude before construction was 0.16% from 2000 to 2010. During construction, from 2010 to 2020, the comprehensive dynamic attitude increased to 13.79%. Project construction had a significant impact on the change in land use patterns. The influence of engineering construction on farmland and grassland is weak but on forest, water area, build-up land, and unused land, it is strong. (2) Engineering construction has a great impact on water purification, biodiversity, and hydrological regulation; notably, the impact on hydrological regulation services is greatest. The migration of residents and economic development resulting from construction may be one of the reasons for the change in demand. (3) The significance test results of ES supply–demand balance and land use reveal a correlation between the matching degree of supply and demand and land use. The proportion of arable land and building land consistently shows a positive correlation with the balance between supply and demand. Conversely, the proportion of forest, grassland, and water area exhibits a negative correlation. Nevertheless, the land use factor merely constitutes a single component that impacts the equilibrium. Hence, it is crucial to integrate this research with the prevailing circumstances for a comprehensive analysis. The construction of the river diversion project is primarily responsible for causing environmental change in the Jianghuai River Basin. Additionally, other practices related to land use and management are part of the driving forces behind environmental change. Therefore, the ecological environment impact caused by the project is intricate and uncertain.

As global climate patterns continue to evolve, it is anticipated that significant changes will occur in rainfall patterns, temperatures, and extreme weather events. These changes will further impact the ecosystem services within the YHWD Project area. Therefore, future research should consider incorporating additional climate factors into models to accurately predict and assess the impacts of these factors on the supply and demand dynamics of ESs. This incorporation will not only help to foster an understanding of the potential effects of climate change on the ESs in the YHWD Project area but also provide a scientific basis for developing adaptive management strategies to mitigate the negative impacts of climate change and promote the sustainable and healthy development of ecosystems.

Data availability

Some data for this study are not published due to [non-publication of data], but may be obtained from the corresponding authors upon reasonable request. Publicly available data is presented in Table 1 . For access to other data, please contact the corresponding author via email at [email protected].

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This work was supported by General project of Humanities and Social Sciences Research, Ministry of Education in China (No. 22YJC630047) and Anhui Province of China social science innovation development research subject (No. 2021CX194, No. 2020cx110).

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Wenqing Ding, Guangzhi Shi, Hui Zha, Haojie Miao, Mengmin Lu & Jing Jin

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Ding, W., Shi, G., Zha, H. et al. Ecological impacts and supply demand evolution of the Yangtze to Huaihe water transfer project in Anhui section. Sci Rep 14 , 20311 (2024). https://doi.org/10.1038/s41598-024-71127-6

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Home Market Research

Empirical Research: Definition, Methods, Types and Examples

Content Index

Empirical research: Definition

Empirical research: origin, quantitative research methods, qualitative research methods, steps for conducting empirical research, empirical research methodology cycle, advantages of empirical research, disadvantages of empirical research, why is there a need for empirical research.

Empirical research is defined as any research where conclusions of the study is strictly drawn from concretely empirical evidence, and therefore “verifiable” evidence.

This empirical evidence can be gathered using quantitative market research and  qualitative market research  methods.

For example: A research is being conducted to find out if listening to happy music in the workplace while working may promote creativity? An experiment is conducted by using a music website survey on a set of audience who are exposed to happy music and another set who are not listening to music at all, and the subjects are then observed. The results derived from such a research will give empirical evidence if it does promote creativity or not.

LEARN ABOUT: Behavioral Research

You must have heard the quote” I will not believe it unless I see it”. This came from the ancient empiricists, a fundamental understanding that powered the emergence of medieval science during the renaissance period and laid the foundation of modern science, as we know it today. The word itself has its roots in greek. It is derived from the greek word empeirikos which means “experienced”.

In today’s world, the word empirical refers to collection of data using evidence that is collected through observation or experience or by using calibrated scientific instruments. All of the above origins have one thing in common which is dependence of observation and experiments to collect data and test them to come up with conclusions.

LEARN ABOUT: Causal Research

Types and methodologies of empirical research

Empirical research can be conducted and analysed using qualitative or quantitative methods.

• Quantitative research : Quantitative research methods are used to gather information through numerical data. It is used to quantify opinions, behaviors or other defined variables . These are predetermined and are in a more structured format. Some of the commonly used methods are survey, longitudinal studies, polls, etc
• Qualitative research:   Qualitative research methods are used to gather non numerical data.  It is used to find meanings, opinions, or the underlying reasons from its subjects. These methods are unstructured or semi structured. The sample size for such a research is usually small and it is a conversational type of method to provide more insight or in-depth information about the problem Some of the most popular forms of methods are focus groups, experiments, interviews, etc.

Data collected from these will need to be analysed. Empirical evidence can also be analysed either quantitatively and qualitatively. Using this, the researcher can answer empirical questions which have to be clearly defined and answerable with the findings he has got. The type of research design used will vary depending on the field in which it is going to be used. Many of them might choose to do a collective research involving quantitative and qualitative method to better answer questions which cannot be studied in a laboratory setting.

LEARN ABOUT: Qualitative Research Questions and Questionnaires

Quantitative research methods aid in analyzing the empirical evidence gathered. By using these a researcher can find out if his hypothesis is supported or not.

• Survey research: Survey research generally involves a large audience to collect a large amount of data. This is a quantitative method having a predetermined set of closed questions which are pretty easy to answer. Because of the simplicity of such a method, high responses are achieved. It is one of the most commonly used methods for all kinds of research in today’s world.

Previously, surveys were taken face to face only with maybe a recorder. However, with advancement in technology and for ease, new mediums such as emails , or social media have emerged.

For example: Depletion of energy resources is a growing concern and hence there is a need for awareness about renewable energy. According to recent studies, fossil fuels still account for around 80% of energy consumption in the United States. Even though there is a rise in the use of green energy every year, there are certain parameters because of which the general population is still not opting for green energy. In order to understand why, a survey can be conducted to gather opinions of the general population about green energy and the factors that influence their choice of switching to renewable energy. Such a survey can help institutions or governing bodies to promote appropriate awareness and incentive schemes to push the use of greener energy.

Learn more: Renewable Energy Survey Template Descriptive Research vs Correlational Research

• Experimental research: In experimental research , an experiment is set up and a hypothesis is tested by creating a situation in which one of the variable is manipulated. This is also used to check cause and effect. It is tested to see what happens to the independent variable if the other one is removed or altered. The process for such a method is usually proposing a hypothesis, experimenting on it, analyzing the findings and reporting the findings to understand if it supports the theory or not.

For example: A particular product company is trying to find what is the reason for them to not be able to capture the market. So the organisation makes changes in each one of the processes like manufacturing, marketing, sales and operations. Through the experiment they understand that sales training directly impacts the market coverage for their product. If the person is trained well, then the product will have better coverage.

• Correlational research: Correlational research is used to find relation between two set of variables . Regression analysis is generally used to predict outcomes of such a method. It can be positive, negative or neutral correlation.

LEARN ABOUT: Level of Analysis

For example: Higher educated individuals will get higher paying jobs. This means higher education enables the individual to high paying job and less education will lead to lower paying jobs.

• Longitudinal study: Longitudinal study is used to understand the traits or behavior of a subject under observation after repeatedly testing the subject over a period of time. Data collected from such a method can be qualitative or quantitative in nature.

For example: A research to find out benefits of exercise. The target is asked to exercise everyday for a particular period of time and the results show higher endurance, stamina, and muscle growth. This supports the fact that exercise benefits an individual body.

• Cross sectional: Cross sectional study is an observational type of method, in which a set of audience is observed at a given point in time. In this type, the set of people are chosen in a fashion which depicts similarity in all the variables except the one which is being researched. This type does not enable the researcher to establish a cause and effect relationship as it is not observed for a continuous time period. It is majorly used by healthcare sector or the retail industry.

For example: A medical study to find the prevalence of under-nutrition disorders in kids of a given population. This will involve looking at a wide range of parameters like age, ethnicity, location, incomes  and social backgrounds. If a significant number of kids coming from poor families show under-nutrition disorders, the researcher can further investigate into it. Usually a cross sectional study is followed by a longitudinal study to find out the exact reason.

• Causal-Comparative research : This method is based on comparison. It is mainly used to find out cause-effect relationship between two variables or even multiple variables.

For example: A researcher measured the productivity of employees in a company which gave breaks to the employees during work and compared that to the employees of the company which did not give breaks at all.

LEARN ABOUT: Action Research

Some research questions need to be analysed qualitatively, as quantitative methods are not applicable there. In many cases, in-depth information is needed or a researcher may need to observe a target audience behavior, hence the results needed are in a descriptive analysis form. Qualitative research results will be descriptive rather than predictive. It enables the researcher to build or support theories for future potential quantitative research. In such a situation qualitative research methods are used to derive a conclusion to support the theory or hypothesis being studied.

LEARN ABOUT: Qualitative Interview

• Case study: Case study method is used to find more information through carefully analyzing existing cases. It is very often used for business research or to gather empirical evidence for investigation purpose. It is a method to investigate a problem within its real life context through existing cases. The researcher has to carefully analyse making sure the parameter and variables in the existing case are the same as to the case that is being investigated. Using the findings from the case study, conclusions can be drawn regarding the topic that is being studied.

For example: A report mentioning the solution provided by a company to its client. The challenges they faced during initiation and deployment, the findings of the case and solutions they offered for the problems. Such case studies are used by most companies as it forms an empirical evidence for the company to promote in order to get more business.

• Observational method:   Observational method is a process to observe and gather data from its target. Since it is a qualitative method it is time consuming and very personal. It can be said that observational research method is a part of ethnographic research which is also used to gather empirical evidence. This is usually a qualitative form of research, however in some cases it can be quantitative as well depending on what is being studied.

For example: setting up a research to observe a particular animal in the rain-forests of amazon. Such a research usually take a lot of time as observation has to be done for a set amount of time to study patterns or behavior of the subject. Another example used widely nowadays is to observe people shopping in a mall to figure out buying behavior of consumers.

• One-on-one interview: Such a method is purely qualitative and one of the most widely used. The reason being it enables a researcher get precise meaningful data if the right questions are asked. It is a conversational method where in-depth data can be gathered depending on where the conversation leads.

For example: A one-on-one interview with the finance minister to gather data on financial policies of the country and its implications on the public.

• Focus groups: Focus groups are used when a researcher wants to find answers to why, what and how questions. A small group is generally chosen for such a method and it is not necessary to interact with the group in person. A moderator is generally needed in case the group is being addressed in person. This is widely used by product companies to collect data about their brands and the product.

For example: A mobile phone manufacturer wanting to have a feedback on the dimensions of one of their models which is yet to be launched. Such studies help the company meet the demand of the customer and position their model appropriately in the market.

• Text analysis: Text analysis method is a little new compared to the other types. Such a method is used to analyse social life by going through images or words used by the individual. In today’s world, with social media playing a major part of everyone’s life, such a method enables the research to follow the pattern that relates to his study.

For example: A lot of companies ask for feedback from the customer in detail mentioning how satisfied are they with their customer support team. Such data enables the researcher to take appropriate decisions to make their support team better.

Sometimes a combination of the methods is also needed for some questions that cannot be answered using only one type of method especially when a researcher needs to gain a complete understanding of complex subject matter.

We recently published a blog that talks about examples of qualitative data in education ; why don’t you check it out for more ideas?

Learn More: Data Collection Methods: Types & Examples

Since empirical research is based on observation and capturing experiences, it is important to plan the steps to conduct the experiment and how to analyse it. This will enable the researcher to resolve problems or obstacles which can occur during the experiment.

Step #1: Define the purpose of the research

This is the step where the researcher has to answer questions like what exactly do I want to find out? What is the problem statement? Are there any issues in terms of the availability of knowledge, data, time or resources. Will this research be more beneficial than what it will cost.

Before going ahead, a researcher has to clearly define his purpose for the research and set up a plan to carry out further tasks.

Step #2 : Supporting theories and relevant literature

The researcher needs to find out if there are theories which can be linked to his research problem . He has to figure out if any theory can help him support his findings. All kind of relevant literature will help the researcher to find if there are others who have researched this before, or what are the problems faced during this research. The researcher will also have to set up assumptions and also find out if there is any history regarding his research problem

Step #3: Creation of Hypothesis and measurement

Before beginning the actual research he needs to provide himself a working hypothesis or guess what will be the probable result. Researcher has to set up variables, decide the environment for the research and find out how can he relate between the variables.

Researcher will also need to define the units of measurements, tolerable degree for errors, and find out if the measurement chosen will be acceptable by others.

Step #4: Methodology, research design and data collection

In this step, the researcher has to define a strategy for conducting his research. He has to set up experiments to collect data which will enable him to propose the hypothesis. The researcher will decide whether he will need experimental or non experimental method for conducting the research. The type of research design will vary depending on the field in which the research is being conducted. Last but not the least, the researcher will have to find out parameters that will affect the validity of the research design. Data collection will need to be done by choosing appropriate samples depending on the research question. To carry out the research, he can use one of the many sampling techniques. Once data collection is complete, researcher will have empirical data which needs to be analysed.

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Step #5: Data Analysis and result

Data analysis can be done in two ways, qualitatively and quantitatively. Researcher will need to find out what qualitative method or quantitative method will be needed or will he need a combination of both. Depending on the unit of analysis of his data, he will know if his hypothesis is supported or rejected. Analyzing this data is the most important part to support his hypothesis.

Step #6: Conclusion

A report will need to be made with the findings of the research. The researcher can give the theories and literature that support his research. He can make suggestions or recommendations for further research on his topic.

A.D. de Groot, a famous dutch psychologist and a chess expert conducted some of the most notable experiments using chess in the 1940’s. During his study, he came up with a cycle which is consistent and now widely used to conduct empirical research. It consists of 5 phases with each phase being as important as the next one. The empirical cycle captures the process of coming up with hypothesis about how certain subjects work or behave and then testing these hypothesis against empirical data in a systematic and rigorous approach. It can be said that it characterizes the deductive approach to science. Following is the empirical cycle.

• Observation: At this phase an idea is sparked for proposing a hypothesis. During this phase empirical data is gathered using observation. For example: a particular species of flower bloom in a different color only during a specific season.
• Induction: Inductive reasoning is then carried out to form a general conclusion from the data gathered through observation. For example: As stated above it is observed that the species of flower blooms in a different color during a specific season. A researcher may ask a question “does the temperature in the season cause the color change in the flower?” He can assume that is the case, however it is a mere conjecture and hence an experiment needs to be set up to support this hypothesis. So he tags a few set of flowers kept at a different temperature and observes if they still change the color?
• Deduction: This phase helps the researcher to deduce a conclusion out of his experiment. This has to be based on logic and rationality to come up with specific unbiased results.For example: In the experiment, if the tagged flowers in a different temperature environment do not change the color then it can be concluded that temperature plays a role in changing the color of the bloom.
• Testing: This phase involves the researcher to return to empirical methods to put his hypothesis to the test. The researcher now needs to make sense of his data and hence needs to use statistical analysis plans to determine the temperature and bloom color relationship. If the researcher finds out that most flowers bloom a different color when exposed to the certain temperature and the others do not when the temperature is different, he has found support to his hypothesis. Please note this not proof but just a support to his hypothesis.
• Evaluation: This phase is generally forgotten by most but is an important one to keep gaining knowledge. During this phase the researcher puts forth the data he has collected, the support argument and his conclusion. The researcher also states the limitations for the experiment and his hypothesis and suggests tips for others to pick it up and continue a more in-depth research for others in the future. LEARN MORE: Population vs Sample

LEARN MORE: Population vs Sample

There is a reason why empirical research is one of the most widely used method. There are a few advantages associated with it. Following are a few of them.

• It is used to authenticate traditional research through various experiments and observations.
• This research methodology makes the research being conducted more competent and authentic.
• It enables a researcher understand the dynamic changes that can happen and change his strategy accordingly.
• The level of control in such a research is high so the researcher can control multiple variables.
• It plays a vital role in increasing internal validity .

Even though empirical research makes the research more competent and authentic, it does have a few disadvantages. Following are a few of them.

• Such a research needs patience as it can be very time consuming. The researcher has to collect data from multiple sources and the parameters involved are quite a few, which will lead to a time consuming research.
• Most of the time, a researcher will need to conduct research at different locations or in different environments, this can lead to an expensive affair.
• There are a few rules in which experiments can be performed and hence permissions are needed. Many a times, it is very difficult to get certain permissions to carry out different methods of this research.
• Collection of data can be a problem sometimes, as it has to be collected from a variety of sources through different methods.

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Empirical research is important in today’s world because most people believe in something only that they can see, hear or experience. It is used to validate multiple hypothesis and increase human knowledge and continue doing it to keep advancing in various fields.

For example: Pharmaceutical companies use empirical research to try out a specific drug on controlled groups or random groups to study the effect and cause. This way, they prove certain theories they had proposed for the specific drug. Such research is very important as sometimes it can lead to finding a cure for a disease that has existed for many years. It is useful in science and many other fields like history, social sciences, business, etc.

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With the advancement in today’s world, empirical research has become critical and a norm in many fields to support their hypothesis and gain more knowledge. The methods mentioned above are very useful for carrying out such research. However, a number of new methods will keep coming up as the nature of new investigative questions keeps getting unique or changing.

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Empirical research in the social sciences and education.

• What is Empirical Research and How to Read It
• Finding Empirical Research in Library Databases
• Designing Empirical Research
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Introduction: What is Empirical Research?

Empirical research is based on observed and measured phenomena and derives knowledge from actual experience rather than from theory or belief. 

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

Key characteristics to look for:

• Specific research questions to be answered
• Definition of the population, behavior, or phenomena being studied
• Description of the process used to study this population or phenomena, including selection criteria, controls, and testing instruments (such as surveys)

Another hint: some scholarly journals use a specific layout, called the "IMRaD" format, to communicate empirical research findings. Such articles typically have 4 components:

• Introduction: sometimes called "literature review" -- what is currently known about the topic -- usually includes a theoretical framework and/or discussion of previous studies
• Methodology: sometimes called "research design" -- how to recreate the study -- usually describes the population, research process, and analytical tools used in the present study
• Results: sometimes called "findings" -- what was learned through the study -- usually appears as statistical data or as substantial quotations from research participants
• Discussion: sometimes called "conclusion" or "implications" -- why the study is important -- usually describes how the research results influence professional practices or future studies

Reading and Evaluating Scholarly Materials

Reading research can be a challenge. However, the tutorials and videos below can help. They explain what scholarly articles look like, how to read them, and how to evaluate them:

• CRAAP Checklist A frequently-used checklist that helps you examine the currency, relevance, authority, accuracy, and purpose of an information source.
• IF I APPLY A newer model of evaluating sources which encourages you to think about your own biases as a reader, as well as concerns about the item you are reading.
• Credo Video: How to Read Scholarly Materials (4 min.)
• Credo Tutorial: How to Read Scholarly Materials
• Credo Tutorial: Evaluating Information
• Credo Video: Evaluating Statistics (4 min.)
• Credo Tutorial: Evaluating for Diverse Points of View
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• Last Updated: Aug 13, 2024 3:16 PM
• URL: https://guides.libraries.psu.edu/emp

How to... Conduct empirical research

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Empirical research is research that is based on observation and measurement of phenomena, as directly experienced by the researcher. The data thus gathered may be compared against a theory or hypothesis, but the results are still based on real life experience. The data gathered is all primary data, although secondary data from a literature review may form the theoretical background.

On this page

What is empirical research, the research question, the theoretical framework, sampling techniques, design of the research.

• Methods of empirical research
• Techniques of data collection & analysis
• Reporting the findings of empirical research
• Further information

Typically, empirical research embodies the following elements:

• A  research question , which will determine research objectives.
• A particular and planned  design  for the research, which will depend on the question and which will find ways of answering it with appropriate use of resources.
• The gathering of  primary data , which is then analysed.
• A particular  methodology  for collecting and analysing the data, such as an experiment or survey.
• The limitation of the data to a particular group, area or time scale, known as a sample: for example, a specific number of employees of a particular company type, or all users of a library over a given time scale. The sample should be somehow representative of a wider population.
• The ability to  recreate  the study and test the results. This is known as  reliability .
• The ability to  generalise  from the findings to a larger sample and to other situations.

The starting point for your research should be your research question. This should be a formulation of the issue which is at the heart of the area which you are researching, which has the right degree of breadth and depth to make the research feasible within your resources. The following points are useful to remember when coming up with your research question, or RQ:

• your doctoral thesis;
• reading the relevant literature in journals, especially literature reviews which are good at giving an overview, and spotting interesting conceptual developments;
• looking at research priorities of funding bodies, professional institutes etc.;
• going to conferences;
• looking out for calls for papers;
• developing a dialogue with other researchers in your area.
• To narrow down your research topic, brainstorm ideas around it, possibly with your colleagues if you have decided to collaborate, noting all the questions down.
• Come up with a "general focus" question; then develop some other more specific ones.
• they are not too broad;
• they are not so narrow as to yield uninteresting results;
• will the research entailed be covered by your resources, i.e. will you have sufficient time and money;
• there is sufficient background literature on the topic;
• you can carry out appropriate field research;
• you have stated your question in the simplest possible way.

Let's look at some examples:

Bisking et al. examine whether or not gender has an influence on disciplinary action in their article  Does the sex of the leader and subordinate influence a leader's disciplinary decisions?  ( Management Decision , Volume 41 Number 10) and come up with the following series of inter-related questions:

• Given the same infraction, would a male leader impose the same disciplinary action on male and female subordinates?
• Given the same infraction, would a female leader impose the same disciplinary action on male and female subordinates?
• Given the same infraction, would a female leader impose the same disciplinary action on female subordinates as a male leader would on male subordinates?
• Given the same infraction, would a female leader impose the same disciplinary action on male subordinates as a male leader would on female subordinates?
• Given the same infraction, would a male and female leader impose the same disciplinary action on male subordinates?
• Given the same infraction, would a male and female leader impose the same disciplinary action on female subordinates?
• Do female and male leaders impose the same discipline on subordinates regardless of the type of infraction?
• Is it possible to predict how female and male leaders will impose disciplinary actions based on their respective BSRI femininity and masculinity scores?

Motion et al. examined co-branding in  Equity in Corporate Co-branding  ( European Journal of Marketing , Volume 37 Number 7/8) and came up with the following RQs:

RQ1:  What objectives underpinned the corporate brand?

RQ2:  How were brand values deployed to establish the corporate co-brand within particular discourse contexts?

RQ3:  How was the desired rearticulation promoted to shareholders?

RQ4:  What are the sources of corporate co-brand equity?

Note, the above two examples state the RQs very explicitly; sometimes the RQ is implicit:

Qun G. Jiao, Anthony J. Onwuegbuzie are library researchers who examined the question:  "What is the relationship between library anxiety and social interdependence?"  in a number of articles, see  Dimensions of library anxiety and social interdependence: implications for library services   ( Library Review , Volume 51 Number 2).

Or sometimes the RQ is stated as a general objective:

Ying Fan describes outsourcing in British companies in  Strategic outsourcing: evidence from British companies  ( Marketing Intelligence & Planning , Volume 18 Number 4) and states his research question as an objective:

The main objective of the research was to explore the two key areas in the outsourcing process, namely:

• pre-outsourcing decision process; and
• post-outsourcing supplier management.

or as a proposition:

Karin Klenke explores issues of gender in management decisions in  Gender influences in decision-making processes in top management teams   ( Management Decision , Volume 41 Number 10).

Given the exploratory nature of this research, no specific hypotheses were formulated. Instead, the following general propositions are postulated:

P1.  Female and male members of TMTs exercise different types of power in the strategic decision making process.

P2.  Female and male members of TMTs differ in the extent in which they employ political savvy in the strategic decision making process.

P3.  Male and female members of TMTs manage conflict in strategic decision making situations differently.

P4.  Female and male members of TMTs utilise different types of trust in the decision making process.

Sometimes, the theoretical underpinning (see next section) of the research leads you to formulate a hypothesis rather than a question:

Martin et al. explored the effect of fast-forwarding of ads (called zipping) in  Remote control marketing: how ad fast-forwarding and ad repetition affect consumers  ( Marketing Intelligence & Planning , Volume 20 Number 1) and his research explores the following hypotheses:

The influence of zipping H1. Individuals viewing advertisements played at normal speed will exhibit higher ad recall and recognition than those who view zipped advertisements.

Ad repetition effects H2. Individuals viewing a repeated advertisement will exhibit higher ad recall and recognition than those who see an advertisement once.

Zipping and ad repetition H3. Individuals viewing zipped, repeated advertisements will exhibit higher ad recall and recognition than those who see a normal speed advertisement that is played once.

Empirical research is not divorced from theoretical considerations; and a consideration of theory should form one of the starting points of your research. This applies particularly in the case of management research which by its very nature is practical and applied to the real world. The link between research and theory is symbiotic: theory should inform research, and the findings of research should inform theory.

There are a number of different theoretical perspectives; if you are unfamiliar with them, we suggest that you look at any good research methods textbook for a full account (see Further information), but this page will contain notes on the following:

This is the approach of the natural sciences, emphasising total objectivity and independence on the part of the researcher, a highly scientific methodology, with data being collected in a value-free manner and using quantitative techniques with some statistical measures of analysis. Assumes that there are 'independent facts' in the social world as in the natural world. The object is to generalise from what has been observed and hence add to the body of theory.

Very similar to positivism in that it has a strong reliance on objectivity and quantitative methods of data collection, but with less of a reliance on theory. There is emphasis on data and facts in their own right; they do not need to be linked to theory.

Interpretivism

This view criticises positivism as being inappropriate for the social world of business and management which is dominated by people rather than the laws of nature and hence has an inevitable subjective element as people will have different interpretations of situations and events. The business world can only be understood through people's interpretation. This view is more likely to emphasise qualitative methods such as participant observation, focus groups and semi-structured interviewing.

While reality exists independently of human experience, people are not like objects in the natural world but are subject to social influences and processes. Like  empiricism  and  positivism , this emphasises the importance of explanation, but is also concerned with the social world and with its underlying structures.

Inductive and deductive approaches

At what point in your research you bring in a theoretical perspective will depend on whether you choose an:

• Inductive approach  – collect the data, then develop the theory.
• Deductive approach  – assume a theoretical position then test it against the data.

It should be emphasised that none of the above approaches are mutually exclusive and can be used in combination.

Sampling may be done either:

• On a  random  basis – a given number is selected completely at random.
• On a  systematic  basis – every  n th element  of the population is selected.
• On a  stratified random  basis – the population is divided into segments, for example, in a University, you could divide the population into academic, administrators, and academic related. A random number of each group is then selected.
• On a  cluster  basis – a particular subgroup is chosen at random.
• Convenience  – being present at a particular time e.g. at lunch in the canteen.
• Purposive  – people can be selected deliberately because their views are relevant to the issue concerned.
• Quota  – the assumption is made that there are subgroups in the population, and a quota of respondents is chosen to reflect this diversity.

Useful articles

Richard Laughlin in  Empirical research in accounting: alternative approaches and a case for "middle-range" thinking  provides an interesting general overview of the different perspectives on theory and methodology as applied to accounting. ( Accounting, Auditing & Accountability Journal,  Volume 8 Number 1).

D. Tranfield and K. Starkey in  The Nature, Social Organization and Promotion of Management Research: Towards Policy  look at the relationship between theory and practice in management research, and develop a number of analytical frameworks, including looking at Becher's conceptual schema for disciplines and Gibbons et al.'s taxonomy of knowledge production systems. ( British Journal of Management , vol. 9, no. 4 – abstract only).

Research design is about how you go about answering your question: what strategy you adopt, and what methods do you use to achieve your results. In particular you should ask yourself... 

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Introduction to Empirical Research

Databases for finding empirical research, guided search, google scholar, examples of empirical research, sources and further reading.

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• Introductory Video This video covers what empirical research is, what kinds of questions and methods empirical researchers use, and some tips for finding empirical research articles in your discipline.

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Empirical Research: Defining, Identifying, & Finding

Defining empirical research, what is empirical research, quantitative or qualitative.

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Calfee & Chambliss (2005)  (UofM login required) describe empirical research as a "systematic approach for answering certain types of questions."  Those questions are answered "[t]hrough the collection of evidence under carefully defined and replicable conditions" (p. 43). 

The evidence collected during empirical research is often referred to as "data." 

Characteristics of Empirical Research

Emerald Publishing's guide to conducting empirical research identifies a number of common elements to empirical research: 

• A  research question , which will determine research objectives.
• A particular and planned  design  for the research, which will depend on the question and which will find ways of answering it with appropriate use of resources.
• The gathering of  primary data , which is then analysed.
• A particular  methodology  for collecting and analysing the data, such as an experiment or survey.
• The limitation of the data to a particular group, area or time scale, known as a sample [emphasis added]: for example, a specific number of employees of a particular company type, or all users of a library over a given time scale. The sample should be somehow representative of a wider population.
• The ability to  recreate  the study and test the results. This is known as  reliability .
• The ability to  generalize  from the findings to a larger sample and to other situations.

If you see these elements in a research article, you can feel confident that you have found empirical research. Emerald's guide goes into more detail on each element. 

Empirical research methodologies can be described as quantitative, qualitative, or a mix of both (usually called mixed-methods).

Ruane (2016)  (UofM login required) gets at the basic differences in approach between quantitative and qualitative research:

• Quantitative research  -- an approach to documenting reality that relies heavily on numbers both for the measurement of variables and for data analysis (p. 33).
• Qualitative research  -- an approach to documenting reality that relies on words and images as the primary data source (p. 33).

Both quantitative and qualitative methods are empirical . If you can recognize that a research study is quantitative or qualitative study, then you have also recognized that it is empirical study. 

Below are information on the characteristics of quantitative and qualitative research. This video from Scribbr also offers a good overall introduction to the two approaches to research methodology: 

Characteristics of Quantitative Research 

Researchers test hypotheses, or theories, based in assumptions about causality, i.e. we expect variable X to cause variable Y. Variables have to be controlled as much as possible to ensure validity. The results explain the relationship between the variables. Measures are based in pre-defined instruments.

Examples: experimental or quasi-experimental design, pretest & post-test, survey or questionnaire with closed-ended questions. Studies that identify factors that influence an outcomes, the utility of an intervention, or understanding predictors of outcomes. 

Characteristics of Qualitative Research

Researchers explore “meaning individuals or groups ascribe to social or human problems (Creswell & Creswell, 2018, p3).” Questions and procedures emerge rather than being prescribed. Complexity, nuance, and individual meaning are valued. Research is both inductive and deductive. Data sources are multiple and varied, i.e. interviews, observations, documents, photographs, etc. The researcher is a key instrument and must be reflective of their background, culture, and experiences as influential of the research.

Examples: open question interviews and surveys, focus groups, case studies, grounded theory, ethnography, discourse analysis, narrative, phenomenology, participatory action research.

Calfee, R. C. & Chambliss, M. (2005). The design of empirical research. In J. Flood, D. Lapp, J. R. Squire, & J. Jensen (Eds.),  Methods of research on teaching the English language arts: The methodology chapters from the handbook of research on teaching the English language arts (pp. 43-78). Routledge.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=125955&site=eds-live&scope=site .

Creswell, J. W., & Creswell, J. D. (2018).  Research design: Qualitative, quantitative, and mixed methods approaches  (5th ed.). Thousand Oaks: Sage.

How to... conduct empirical research . (n.d.). Emerald Publishing.  https://www.emeraldgrouppublishing.com/how-to/research-methods/conduct-empirical-research .

Scribbr. (2019). Quantitative vs. qualitative: The differences explained  [video]. YouTube.  https://www.youtube.com/watch?v=a-XtVF7Bofg .

Ruane, J. M. (2016).  Introducing social research methods : Essentials for getting the edge . Wiley-Blackwell.  http://ezproxy.memphis.edu/login?url=http://search.ebscohost.com/login.aspx?direct=true&db=nlebk&AN=1107215&site=eds-live&scope=site .  

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What is Empirical Research? Definition, Methods, Examples

Appinio Research · 09.02.2024 · 36min read

Ever wondered how we gather the facts, unveil hidden truths, and make informed decisions in a world filled with questions? Empirical research holds the key.

In this guide, we'll delve deep into the art and science of empirical research, unraveling its methods, mysteries, and manifold applications. From defining the core principles to mastering data analysis and reporting findings, we're here to equip you with the knowledge and tools to navigate the empirical landscape.

What is Empirical Research?

Empirical research is the cornerstone of scientific inquiry, providing a systematic and structured approach to investigating the world around us. It is the process of gathering and analyzing empirical or observable data to test hypotheses, answer research questions, or gain insights into various phenomena. This form of research relies on evidence derived from direct observation or experimentation, allowing researchers to draw conclusions based on real-world data rather than purely theoretical or speculative reasoning.

Characteristics of Empirical Research

Empirical research is characterized by several key features:

• Observation and Measurement : It involves the systematic observation or measurement of variables, events, or behaviors.
• Data Collection : Researchers collect data through various methods, such as surveys, experiments, observations, or interviews.
• Testable Hypotheses : Empirical research often starts with testable hypotheses that are evaluated using collected data.
• Quantitative or Qualitative Data : Data can be quantitative (numerical) or qualitative (non-numerical), depending on the research design.
• Statistical Analysis : Quantitative data often undergo statistical analysis to determine patterns , relationships, or significance.
• Objectivity and Replicability : Empirical research strives for objectivity, minimizing researcher bias . It should be replicable, allowing other researchers to conduct the same study to verify results.
• Conclusions and Generalizations : Empirical research generates findings based on data and aims to make generalizations about larger populations or phenomena.

Importance of Empirical Research

Empirical research plays a pivotal role in advancing knowledge across various disciplines. Its importance extends to academia, industry, and society as a whole. Here are several reasons why empirical research is essential:

• Evidence-Based Knowledge : Empirical research provides a solid foundation of evidence-based knowledge. It enables us to test hypotheses, confirm or refute theories, and build a robust understanding of the world.
• Scientific Progress : In the scientific community, empirical research fuels progress by expanding the boundaries of existing knowledge. It contributes to the development of theories and the formulation of new research questions.
• Problem Solving : Empirical research is instrumental in addressing real-world problems and challenges. It offers insights and data-driven solutions to complex issues in fields like healthcare, economics, and environmental science.
• Informed Decision-Making : In policymaking, business, and healthcare, empirical research informs decision-makers by providing data-driven insights. It guides strategies, investments, and policies for optimal outcomes.
• Quality Assurance : Empirical research is essential for quality assurance and validation in various industries, including pharmaceuticals, manufacturing, and technology. It ensures that products and processes meet established standards.
• Continuous Improvement : Businesses and organizations use empirical research to evaluate performance, customer satisfaction , and product effectiveness. This data-driven approach fosters continuous improvement and innovation.
• Human Advancement : Empirical research in fields like medicine and psychology contributes to the betterment of human health and well-being. It leads to medical breakthroughs, improved therapies, and enhanced psychological interventions.
• Critical Thinking and Problem Solving : Engaging in empirical research fosters critical thinking skills, problem-solving abilities, and a deep appreciation for evidence-based decision-making.

Empirical research empowers us to explore, understand, and improve the world around us. It forms the bedrock of scientific inquiry and drives progress in countless domains, shaping our understanding of both the natural and social sciences.

How to Conduct Empirical Research?

So, you've decided to dive into the world of empirical research. Let's begin by exploring the crucial steps involved in getting started with your research project.

1. Select a Research Topic

Selecting the right research topic is the cornerstone of a successful empirical study. It's essential to choose a topic that not only piques your interest but also aligns with your research goals and objectives. Here's how to go about it:

• Identify Your Interests : Start by reflecting on your passions and interests. What topics fascinate you the most? Your enthusiasm will be your driving force throughout the research process.
• Brainstorm Ideas : Engage in brainstorming sessions to generate potential research topics. Consider the questions you've always wanted to answer or the issues that intrigue you.
• Relevance and Significance : Assess the relevance and significance of your chosen topic. Does it contribute to existing knowledge? Is it a pressing issue in your field of study or the broader community?
• Feasibility : Evaluate the feasibility of your research topic. Do you have access to the necessary resources, data, and participants (if applicable)?

2. Formulate Research Questions

Once you've narrowed down your research topic, the next step is to formulate clear and precise research questions . These questions will guide your entire research process and shape your study's direction. To create effective research questions:

• Specificity : Ensure that your research questions are specific and focused. Vague or overly broad questions can lead to inconclusive results.
• Relevance : Your research questions should directly relate to your chosen topic. They should address gaps in knowledge or contribute to solving a particular problem.
• Testability : Ensure that your questions are testable through empirical methods. You should be able to gather data and analyze it to answer these questions.
• Avoid Bias : Craft your questions in a way that avoids leading or biased language. Maintain neutrality to uphold the integrity of your research.

3. Review Existing Literature

Before you embark on your empirical research journey, it's essential to immerse yourself in the existing body of literature related to your chosen topic. This step, often referred to as a literature review, serves several purposes:

• Contextualization : Understand the historical context and current state of research in your field. What have previous studies found, and what questions remain unanswered?
• Identifying Gaps : Identify gaps or areas where existing research falls short. These gaps will help you formulate meaningful research questions and hypotheses.
• Theory Development : If your study is theoretical, consider how existing theories apply to your topic. If it's empirical, understand how previous studies have approached data collection and analysis.
• Methodological Insights : Learn from the methodologies employed in previous research. What methods were successful, and what challenges did researchers face?

4. Define Variables

Variables are fundamental components of empirical research. They are the factors or characteristics that can change or be manipulated during your study. Properly defining and categorizing variables is crucial for the clarity and validity of your research. Here's what you need to know:

• Independent Variables : These are the variables that you, as the researcher, manipulate or control. They are the "cause" in cause-and-effect relationships.
• Dependent Variables : Dependent variables are the outcomes or responses that you measure or observe. They are the "effect" influenced by changes in independent variables.
• Operational Definitions : To ensure consistency and clarity, provide operational definitions for your variables. Specify how you will measure or manipulate each variable.
• Control Variables : In some studies, controlling for other variables that may influence your dependent variable is essential. These are known as control variables.

Understanding these foundational aspects of empirical research will set a solid foundation for the rest of your journey. Now that you've grasped the essentials of getting started, let's delve deeper into the intricacies of research design.

Empirical Research Design

Now that you've selected your research topic, formulated research questions, and defined your variables, it's time to delve into the heart of your empirical research journey – research design . This pivotal step determines how you will collect data and what methods you'll employ to answer your research questions. Let's explore the various facets of research design in detail.

Types of Empirical Research

Empirical research can take on several forms, each with its own unique approach and methodologies. Understanding the different types of empirical research will help you choose the most suitable design for your study. Here are some common types:

• Experimental Research : In this type, researchers manipulate one or more independent variables to observe their impact on dependent variables. It's highly controlled and often conducted in a laboratory setting.
• Observational Research : Observational research involves the systematic observation of subjects or phenomena without intervention. Researchers are passive observers, documenting behaviors, events, or patterns.
• Survey Research : Surveys are used to collect data through structured questionnaires or interviews. This method is efficient for gathering information from a large number of participants.
• Case Study Research : Case studies focus on in-depth exploration of one or a few cases. Researchers gather detailed information through various sources such as interviews, documents, and observations.
• Qualitative Research : Qualitative research aims to understand behaviors, experiences, and opinions in depth. It often involves open-ended questions, interviews, and thematic analysis.
• Quantitative Research : Quantitative research collects numerical data and relies on statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys.

Your choice of research type should align with your research questions and objectives. Experimental research, for example, is ideal for testing cause-and-effect relationships, while qualitative research is more suitable for exploring complex phenomena.

Experimental Design

Experimental research is a systematic approach to studying causal relationships. It's characterized by the manipulation of one or more independent variables while controlling for other factors. Here are some key aspects of experimental design:

• Control and Experimental Groups : Participants are randomly assigned to either a control group or an experimental group. The independent variable is manipulated for the experimental group but not for the control group.
• Randomization : Randomization is crucial to eliminate bias in group assignment. It ensures that each participant has an equal chance of being in either group.
• Hypothesis Testing : Experimental research often involves hypothesis testing. Researchers formulate hypotheses about the expected effects of the independent variable and use statistical analysis to test these hypotheses.

Observational Design

Observational research entails careful and systematic observation of subjects or phenomena. It's advantageous when you want to understand natural behaviors or events. Key aspects of observational design include:

• Participant Observation : Researchers immerse themselves in the environment they are studying. They become part of the group being observed, allowing for a deep understanding of behaviors.
• Non-Participant Observation : In non-participant observation, researchers remain separate from the subjects. They observe and document behaviors without direct involvement.
• Data Collection Methods : Observational research can involve various data collection methods, such as field notes, video recordings, photographs, or coding of observed behaviors.

Survey Design

Surveys are a popular choice for collecting data from a large number of participants. Effective survey design is essential to ensure the validity and reliability of your data. Consider the following:

• Questionnaire Design : Create clear and concise questions that are easy for participants to understand. Avoid leading or biased questions.
• Sampling Methods : Decide on the appropriate sampling method for your study, whether it's random, stratified, or convenience sampling.
• Data Collection Tools : Choose the right tools for data collection, whether it's paper surveys, online questionnaires, or face-to-face interviews.

Case Study Design

Case studies are an in-depth exploration of one or a few cases to gain a deep understanding of a particular phenomenon. Key aspects of case study design include:

• Single Case vs. Multiple Case Studies : Decide whether you'll focus on a single case or multiple cases. Single case studies are intensive and allow for detailed examination, while multiple case studies provide comparative insights.
• Data Collection Methods : Gather data through interviews, observations, document analysis, or a combination of these methods.

Qualitative vs. Quantitative Research

In empirical research, you'll often encounter the distinction between qualitative and quantitative research . Here's a closer look at these two approaches:

• Qualitative Research : Qualitative research seeks an in-depth understanding of human behavior, experiences, and perspectives. It involves open-ended questions, interviews, and the analysis of textual or narrative data. Qualitative research is exploratory and often used when the research question is complex and requires a nuanced understanding.
• Quantitative Research : Quantitative research collects numerical data and employs statistical analysis to draw conclusions. It involves structured questionnaires, experiments, and surveys. Quantitative research is ideal for testing hypotheses and establishing cause-and-effect relationships.

Understanding the various research design options is crucial in determining the most appropriate approach for your study. Your choice should align with your research questions, objectives, and the nature of the phenomenon you're investigating.

Data Collection for Empirical Research

Now that you've established your research design, it's time to roll up your sleeves and collect the data that will fuel your empirical research. Effective data collection is essential for obtaining accurate and reliable results.

Sampling Methods

Sampling methods are critical in empirical research, as they determine the subset of individuals or elements from your target population that you will study. Here are some standard sampling methods:

• Random Sampling : Random sampling ensures that every member of the population has an equal chance of being selected. It minimizes bias and is often used in quantitative research.
• Stratified Sampling : Stratified sampling involves dividing the population into subgroups or strata based on specific characteristics (e.g., age, gender, location). Samples are then randomly selected from each stratum, ensuring representation of all subgroups.
• Convenience Sampling : Convenience sampling involves selecting participants who are readily available or easily accessible. While it's convenient, it may introduce bias and limit the generalizability of results.
• Snowball Sampling : Snowball sampling is instrumental when studying hard-to-reach or hidden populations. One participant leads you to another, creating a "snowball" effect. This method is common in qualitative research.
• Purposive Sampling : In purposive sampling, researchers deliberately select participants who meet specific criteria relevant to their research questions. It's often used in qualitative studies to gather in-depth information.

The choice of sampling method depends on the nature of your research, available resources, and the degree of precision required. It's crucial to carefully consider your sampling strategy to ensure that your sample accurately represents your target population.

Data Collection Instruments

Data collection instruments are the tools you use to gather information from your participants or sources. These instruments should be designed to capture the data you need accurately. Here are some popular data collection instruments:

• Questionnaires : Questionnaires consist of structured questions with predefined response options. When designing questionnaires, consider the clarity of questions, the order of questions, and the response format (e.g., Likert scale , multiple-choice).
• Interviews : Interviews involve direct communication between the researcher and participants. They can be structured (with predetermined questions) or unstructured (open-ended). Effective interviews require active listening and probing for deeper insights.
• Observations : Observations entail systematically and objectively recording behaviors, events, or phenomena. Researchers must establish clear criteria for what to observe, how to record observations, and when to observe.
• Surveys : Surveys are a common data collection instrument for quantitative research. They can be administered through various means, including online surveys, paper surveys, and telephone surveys.
• Documents and Archives : In some cases, data may be collected from existing documents, records, or archives. Ensure that the sources are reliable, relevant, and properly documented.

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Data Collection Procedures

Data collection procedures outline the step-by-step process for gathering data. These procedures should be meticulously planned and executed to maintain the integrity of your research.

• Training : If you have a research team, ensure that they are trained in data collection methods and protocols. Consistency in data collection is crucial.
• Pilot Testing : Before launching your data collection, conduct a pilot test with a small group to identify any potential problems with your instruments or procedures. Make necessary adjustments based on feedback.
• Data Recording : Establish a systematic method for recording data. This may include timestamps, codes, or identifiers for each data point.
• Data Security : Safeguard the confidentiality and security of collected data. Ensure that only authorized individuals have access to the data.
• Data Storage : Properly organize and store your data in a secure location, whether in physical or digital form. Back up data to prevent loss.

Ethical Considerations

Ethical considerations are paramount in empirical research, as they ensure the well-being and rights of participants are protected.

• Informed Consent : Obtain informed consent from participants, providing clear information about the research purpose, procedures, risks, and their right to withdraw at any time.
• Privacy and Confidentiality : Protect the privacy and confidentiality of participants. Ensure that data is anonymized and sensitive information is kept confidential.
• Beneficence : Ensure that your research benefits participants and society while minimizing harm. Consider the potential risks and benefits of your study.
• Honesty and Integrity : Conduct research with honesty and integrity. Report findings accurately and transparently, even if they are not what you expected.
• Respect for Participants : Treat participants with respect, dignity, and sensitivity to cultural differences. Avoid any form of coercion or manipulation.
• Institutional Review Board (IRB) : If required, seek approval from an IRB or ethics committee before conducting your research, particularly when working with human participants.

Adhering to ethical guidelines is not only essential for the ethical conduct of research but also crucial for the credibility and validity of your study. Ethical research practices build trust between researchers and participants and contribute to the advancement of knowledge with integrity.

With a solid understanding of data collection, including sampling methods, instruments, procedures, and ethical considerations, you are now well-equipped to gather the data needed to answer your research questions.

Empirical Research Data Analysis

Now comes the exciting phase of data analysis, where the raw data you've diligently collected starts to yield insights and answers to your research questions. We will explore the various aspects of data analysis, from preparing your data to drawing meaningful conclusions through statistics and visualization.

Data Preparation

Data preparation is the crucial first step in data analysis. It involves cleaning, organizing, and transforming your raw data into a format that is ready for analysis. Effective data preparation ensures the accuracy and reliability of your results.

• Data Cleaning : Identify and rectify errors, missing values, and inconsistencies in your dataset. This may involve correcting typos, removing outliers, and imputing missing data.
• Data Coding : Assign numerical values or codes to categorical variables to make them suitable for statistical analysis. For example, converting "Yes" and "No" to 1 and 0.
• Data Transformation : Transform variables as needed to meet the assumptions of the statistical tests you plan to use. Common transformations include logarithmic or square root transformations.
• Data Integration : If your data comes from multiple sources, integrate it into a unified dataset, ensuring that variables match and align.
• Data Documentation : Maintain clear documentation of all data preparation steps, as well as the rationale behind each decision. This transparency is essential for replicability.

Effective data preparation lays the foundation for accurate and meaningful analysis. It allows you to trust the results that will follow in the subsequent stages.

Descriptive Statistics

Descriptive statistics help you summarize and make sense of your data by providing a clear overview of its key characteristics. These statistics are essential for understanding the central tendencies, variability, and distribution of your variables. Descriptive statistics include:

• Measures of Central Tendency : These include the mean (average), median (middle value), and mode (most frequent value). They help you understand the typical or central value of your data.
• Measures of Dispersion : Measures like the range, variance, and standard deviation provide insights into the spread or variability of your data points.
• Frequency Distributions : Creating frequency distributions or histograms allows you to visualize the distribution of your data across different values or categories.

Descriptive statistics provide the initial insights needed to understand your data's basic characteristics, which can inform further analysis.

Inferential Statistics

Inferential statistics take your analysis to the next level by allowing you to make inferences or predictions about a larger population based on your sample data. These methods help you test hypotheses and draw meaningful conclusions. Key concepts in inferential statistics include:

• Hypothesis Testing : Hypothesis tests (e.g., t-tests , chi-squared tests ) help you determine whether observed differences or associations in your data are statistically significant or occurred by chance.
• Confidence Intervals : Confidence intervals provide a range within which population parameters (e.g., population mean) are likely to fall based on your sample data.
• Regression Analysis : Regression models (linear, logistic, etc.) help you explore relationships between variables and make predictions.
• Analysis of Variance (ANOVA) : ANOVA tests are used to compare means between multiple groups, allowing you to assess whether differences are statistically significant.

Chi-Square Calculator :

t-Test Calculator :

One-way ANOVA Calculator :

Inferential statistics are powerful tools for drawing conclusions from your data and assessing the generalizability of your findings to the broader population.

Qualitative Data Analysis

Qualitative data analysis is employed when working with non-numerical data, such as text, interviews, or open-ended survey responses. It focuses on understanding the underlying themes, patterns, and meanings within qualitative data. Qualitative analysis techniques include:

• Thematic Analysis : Identifying and analyzing recurring themes or patterns within textual data.
• Content Analysis : Categorizing and coding qualitative data to extract meaningful insights.
• Grounded Theory : Developing theories or frameworks based on emergent themes from the data.
• Narrative Analysis : Examining the structure and content of narratives to uncover meaning.

Qualitative data analysis provides a rich and nuanced understanding of complex phenomena and human experiences.

Data Visualization

Data visualization is the art of representing data graphically to make complex information more understandable and accessible. Effective data visualization can reveal patterns, trends, and outliers in your data. Common types of data visualization include:

• Bar Charts and Histograms : Used to display the distribution of categorical data or discrete data .
• Line Charts : Ideal for showing trends and changes in data over time.
• Scatter Plots : Visualize relationships and correlations between two variables.
• Pie Charts : Display the composition of a whole in terms of its parts.
• Heatmaps : Depict patterns and relationships in multidimensional data through color-coding.
• Box Plots : Provide a summary of the data distribution, including outliers.
• Interactive Dashboards : Create dynamic visualizations that allow users to explore data interactively.

Data visualization not only enhances your understanding of the data but also serves as a powerful communication tool to convey your findings to others.

As you embark on the data analysis phase of your empirical research, remember that the specific methods and techniques you choose will depend on your research questions, data type, and objectives. Effective data analysis transforms raw data into valuable insights, bringing you closer to the answers you seek.

How to Report Empirical Research Results?

At this stage, you get to share your empirical research findings with the world. Effective reporting and presentation of your results are crucial for communicating your research's impact and insights.

1. Write the Research Paper

Writing a research paper is the culmination of your empirical research journey. It's where you synthesize your findings, provide context, and contribute to the body of knowledge in your field.

• Title and Abstract : Craft a clear and concise title that reflects your research's essence. The abstract should provide a brief summary of your research objectives, methods, findings, and implications.
• Introduction : In the introduction, introduce your research topic, state your research questions or hypotheses, and explain the significance of your study. Provide context by discussing relevant literature.
• Methods : Describe your research design, data collection methods, and sampling procedures. Be precise and transparent, allowing readers to understand how you conducted your study.
• Results : Present your findings in a clear and organized manner. Use tables, graphs, and statistical analyses to support your results. Avoid interpreting your findings in this section; focus on the presentation of raw data.
• Discussion : Interpret your findings and discuss their implications. Relate your results to your research questions and the existing literature. Address any limitations of your study and suggest avenues for future research.
• Conclusion : Summarize the key points of your research and its significance. Restate your main findings and their implications.
• References : Cite all sources used in your research following a specific citation style (e.g., APA, MLA, Chicago). Ensure accuracy and consistency in your citations.
• Appendices : Include any supplementary material, such as questionnaires, data coding sheets, or additional analyses, in the appendices.

Writing a research paper is a skill that improves with practice. Ensure clarity, coherence, and conciseness in your writing to make your research accessible to a broader audience.

2. Create Visuals and Tables

Visuals and tables are powerful tools for presenting complex data in an accessible and understandable manner.

• Clarity : Ensure that your visuals and tables are clear and easy to interpret. Use descriptive titles and labels.
• Consistency : Maintain consistency in formatting, such as font size and style, across all visuals and tables.
• Appropriateness : Choose the most suitable visual representation for your data. Bar charts, line graphs, and scatter plots work well for different types of data.
• Simplicity : Avoid clutter and unnecessary details. Focus on conveying the main points.
• Accessibility : Make sure your visuals and tables are accessible to a broad audience, including those with visual impairments.
• Captions : Include informative captions that explain the significance of each visual or table.

Compelling visuals and tables enhance the reader's understanding of your research and can be the key to conveying complex information efficiently.

3. Interpret Findings

Interpreting your findings is where you bridge the gap between data and meaning. It's your opportunity to provide context, discuss implications, and offer insights. When interpreting your findings:

• Relate to Research Questions : Discuss how your findings directly address your research questions or hypotheses.
• Compare with Literature : Analyze how your results align with or deviate from previous research in your field. What insights can you draw from these comparisons?
• Discuss Limitations : Be transparent about the limitations of your study. Address any constraints, biases, or potential sources of error.
• Practical Implications : Explore the real-world implications of your findings. How can they be applied or inform decision-making?
• Future Research Directions : Suggest areas for future research based on the gaps or unanswered questions that emerged from your study.

Interpreting findings goes beyond simply presenting data; it's about weaving a narrative that helps readers grasp the significance of your research in the broader context.

With your research paper written, structured, and enriched with visuals, and your findings expertly interpreted, you are now prepared to communicate your research effectively. Sharing your insights and contributing to the body of knowledge in your field is a significant accomplishment in empirical research.

Examples of Empirical Research

To solidify your understanding of empirical research, let's delve into some real-world examples across different fields. These examples will illustrate how empirical research is applied to gather data, analyze findings, and draw conclusions.

Social Sciences

In the realm of social sciences, consider a sociological study exploring the impact of socioeconomic status on educational attainment. Researchers gather data from a diverse group of individuals, including their family backgrounds, income levels, and academic achievements.

Through statistical analysis, they can identify correlations and trends, revealing whether individuals from lower socioeconomic backgrounds are less likely to attain higher levels of education. This empirical research helps shed light on societal inequalities and informs policymakers on potential interventions to address disparities in educational access.

Environmental Science

Environmental scientists often employ empirical research to assess the effects of environmental changes. For instance, researchers studying the impact of climate change on wildlife might collect data on animal populations, weather patterns, and habitat conditions over an extended period.

By analyzing this empirical data, they can identify correlations between climate fluctuations and changes in wildlife behavior, migration patterns, or population sizes. This empirical research is crucial for understanding the ecological consequences of climate change and informing conservation efforts.

Business and Economics

In the business world, empirical research is essential for making data-driven decisions. Consider a market research study conducted by a business seeking to launch a new product. They collect data through surveys , focus groups , and consumer behavior analysis.

By examining this empirical data, the company can gauge consumer preferences, demand, and potential market size. Empirical research in business helps guide product development, pricing strategies, and marketing campaigns, increasing the likelihood of a successful product launch.

Psychological studies frequently rely on empirical research to understand human behavior and cognition. For instance, a psychologist interested in examining the impact of stress on memory might design an experiment. Participants are exposed to stress-inducing situations, and their memory performance is assessed through various tasks.

By analyzing the data collected, the psychologist can determine whether stress has a significant effect on memory recall. This empirical research contributes to our understanding of the complex interplay between psychological factors and cognitive processes.

These examples highlight the versatility and applicability of empirical research across diverse fields. Whether in medicine, social sciences, environmental science, business, or psychology, empirical research serves as a fundamental tool for gaining insights, testing hypotheses, and driving advancements in knowledge and practice.

Conclusion for Empirical Research

Empirical research is a powerful tool for gaining insights, testing hypotheses, and making informed decisions. By following the steps outlined in this guide, you've learned how to select research topics, collect data, analyze findings, and effectively communicate your research to the world. Remember, empirical research is a journey of discovery, and each step you take brings you closer to a deeper understanding of the world around you. Whether you're a scientist, a student, or someone curious about the process, the principles of empirical research empower you to explore, learn, and contribute to the ever-expanding realm of knowledge.

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• 10 Research Question Examples to Guide Your Research Project

10 Research Question Examples to Guide your Research Project

Published on October 30, 2022 by Shona McCombes . Revised on October 19, 2023.

The research question is one of the most important parts of your research paper , thesis or dissertation . It’s important to spend some time assessing and refining your question before you get started.

The exact form of your question will depend on a few things, such as the length of your project, the type of research you’re conducting, the topic , and the research problem . However, all research questions should be focused, specific, and relevant to a timely social or scholarly issue.

Once you’ve read our guide on how to write a research question , you can use these examples to craft your own.

Note that the design of your research question can depend on what method you are pursuing. Here are a few options for qualitative, quantitative, and statistical research questions.

Other interesting articles

If you want to know more about the research process , methodology , research bias , or statistics , make sure to check out some of our other articles with explanations and examples.

Methodology

• Sampling methods
• Simple random sampling
• Stratified sampling
• Cluster sampling
• Likert scales
• Reproducibility

 Statistics

• Null hypothesis
• Statistical power
• Probability distribution
• Effect size
• Poisson distribution

Research bias

• Optimism bias
• Cognitive bias
• Implicit bias
• Hawthorne effect
• Anchoring bias
• Explicit bias

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• What is Empirical Research Study? [Examples & Method]

The bulk of human decisions relies on evidence, that is, what can be measured or proven as valid. In choosing between plausible alternatives, individuals are more likely to tilt towards the option that is proven to work, and this is the same approach adopted in empirical research. 

In empirical research, the researcher arrives at outcomes by testing his or her empirical evidence using qualitative or quantitative methods of observation, as determined by the nature of the research. An empirical research study is set apart from other research approaches by its methodology and features hence; it is important for every researcher to know what constitutes this investigation method. 

What is Empirical Research? 

Empirical research is a type of research methodology that makes use of verifiable evidence in order to arrive at research outcomes. In other words, this  type of research relies solely on evidence obtained through observation or scientific data collection methods. 

Empirical research can be carried out using qualitative or quantitative observation methods , depending on the data sample, that is, quantifiable data or non-numerical data . Unlike theoretical research that depends on preconceived notions about the research variables, empirical research carries a scientific investigation to measure the experimental probability of the research variables 

Characteristics of Empirical Research

• Research Questions

An empirical research begins with a set of research questions that guide the investigation. In many cases, these research questions constitute the research hypothesis which is tested using qualitative and quantitative methods as dictated by the nature of the research.

In an empirical research study, the research questions are built around the core of the research, that is, the central issue which the research seeks to resolve. They also determine the course of the research by highlighting the specific objectives and aims of the systematic investigation. 

• Definition of the Research Variables

The research variables are clearly defined in terms of their population, types, characteristics, and behaviors. In other words, the data sample is clearly delimited and placed within the context of the research. 

• Description of the Research Methodology

 An empirical research also clearly outlines the methods adopted in the systematic investigation. Here, the research process is described in detail including the selection criteria for the data sample, qualitative or quantitative research methods plus testing instruments. 

An empirical research is usually divided into 4 parts which are the introduction, methodology, findings, and discussions. The introduction provides a background of the empirical study while the methodology describes the research design, processes, and tools for the systematic investigation. 

The findings refer to the research outcomes and they can be outlined as statistical data or in the form of information obtained through the qualitative observation of research variables. The discussions highlight the significance of the study and its contributions to knowledge. 

Uses of Empirical Research

Without any doubt, empirical research is one of the most useful methods of systematic investigation. It can be used for validating multiple research hypotheses in different fields including Law, Medicine, and Anthropology. 

• Empirical Research in Law : In Law, empirical research is used to study institutions, rules, procedures, and personnel of the law, with a view to understanding how they operate and what effects they have. It makes use of direct methods rather than secondary sources, and this helps you to arrive at more valid conclusions.
• Empirical Research in Medicine : In medicine, empirical research is used to test and validate multiple hypotheses and increase human knowledge.
• Empirical Research in Anthropology : In anthropology, empirical research is used as an evidence-based systematic method of inquiry into patterns of human behaviors and cultures. This helps to validate and advance human knowledge.

Discover how Extrapolation Powers statistical research: Definition, examples, types, and applications explained.

The Empirical Research Cycle

The empirical research cycle is a 5-phase cycle that outlines the systematic processes for conducting and empirical research. It was developed by Dutch psychologist, A.D. de Groot in the 1940s and it aligns 5 important stages that can be viewed as deductive approaches to empirical research. 

In the empirical research methodological cycle, all processes are interconnected and none of the processes is more important than the other. This cycle clearly outlines the different phases involved in generating the research hypotheses and testing these hypotheses systematically using the empirical data. 

• Observation: This is the process of gathering empirical data for the research. At this stage, the researcher gathers relevant empirical data using qualitative or quantitative observation methods, and this goes ahead to inform the research hypotheses.
• Induction: At this stage, the researcher makes use of inductive reasoning in order to arrive at a general probable research conclusion based on his or her observation. The researcher generates a general assumption that attempts to explain the empirical data and s/he goes on to observe the empirical data in line with this assumption.
• Deduction: This is the deductive reasoning stage. This is where the researcher generates hypotheses by applying logic and rationality to his or her observation.
• Testing: Here, the researcher puts the hypotheses to test using qualitative or quantitative research methods. In the testing stage, the researcher combines relevant instruments of systematic investigation with empirical methods in order to arrive at objective results that support or negate the research hypotheses.
• Evaluation: The evaluation research is the final stage in an empirical research study. Here, the research outlines the empirical data, the research findings and the supporting arguments plus any challenges encountered during the research process.

This information is useful for further research. 

Learn about qualitative data: uncover its types and examples here.

Examples of Empirical Research 

• An empirical research study can be carried out to determine if listening to happy music improves the mood of individuals. The researcher may need to conduct an experiment that involves exposing individuals to happy music to see if this improves their moods.

The findings from such an experiment will provide empirical evidence that confirms or refutes the hypotheses. 

• An empirical research study can also be carried out to determine the effects of a new drug on specific groups of people. The researcher may expose the research subjects to controlled quantities of the drug and observe research subjects to controlled quantities of the drug and observe the effects over a specific period of time to gather empirical data.
• Another example of empirical research is measuring the levels of noise pollution found in an urban area to determine the average levels of sound exposure experienced by its inhabitants. Here, the researcher may have to administer questionnaires or carry out a survey in order to gather relevant data based on the experiences of the research subjects.
• Empirical research can also be carried out to determine the relationship between seasonal migration and the body mass of flying birds. A researcher may need to observe the birds and carry out necessary observation and experimentation in order to arrive at objective outcomes that answer the research question.

Empirical Research Data Collection Methods

Empirical data can be gathered using qualitative and quantitative data collection methods. Quantitative data collection methods are used for numerical data gathering while qualitative data collection processes are used to gather empirical data that cannot be quantified, that is, non-numerical data. 

The following are common methods of gathering data in empirical research

• Survey/ Questionnaire

A survey is a method of data gathering that is typically employed by researchers to gather large sets of data from a specific number of respondents with regards to a research subject. This method of data gathering is often used for quantitative data collection , although it can also be deployed during quantitative research.

A survey contains a set of questions that can range from close-ended to open-ended questions together with other question types that revolve around the research subject. A survey can be administered physically or with the use of online data-gathering platforms like Formplus. 

Empirical data can also be collected by carrying out an experiment. An experiment is a controlled simulation in which one or more of the research variables is manipulated using a set of interconnected processes in order to confirm or refute the research hypotheses.

An experiment is a useful method of measuring causality; that is cause and effect between dependent and independent variables in a research environment. It is an integral data gathering method in an empirical research study because it involves testing calculated assumptions in order to arrive at the most valid data and research outcomes. 

T he case study method is another common data gathering method in an empirical research study. It involves sifting through and analyzing relevant cases and real-life experiences about the research subject or research variables in order to discover in-depth information that can serve as empirical data.

• Observation

The observational method is a method of qualitative data gathering that requires the researcher to study the behaviors of research variables in their natural environments in order to gather relevant information that can serve as empirical data.

How to collect Empirical Research Data with Questionnaire

With Formplus, you can create a survey or questionnaire for collecting empirical data from your research subjects. Formplus also offers multiple form sharing options so that you can share your empirical research survey to research subjects via a variety of methods.

Here is a step-by-step guide of how to collect empirical data using Formplus:

Sign in to Formplus

In the Formplus builder, you can easily create your empirical research survey by dragging and dropping preferred fields into your form. To access the Formplus builder, you will need to create an account on Formplus. 

Once you do this, sign in to your account and click on “Create Form ” to begin. 

Unlock the secrets of Quantitative Data: Click here to explore the types and examples.

Edit Form Title

Click on the field provided to input your form title, for example, “Empirical Research Survey”.

Edit Form  

• Click on the edit button to edit the form.
• Add Fields: Drag and drop preferred form fields into your form in the Formplus builder inputs column. There are several field input options for survey forms in the Formplus builder.
• Edit fields
• Click on “Save”
• Preview form.

Customize Form

Formplus allows you to add unique features to your empirical research survey form. You can personalize your survey using various customization options. Here, you can add background images, your organization’s logo, and use other styling options. You can also change the display theme of your form. 

• Share your Form Link with Respondents

Formplus offers multiple form sharing options which enables you to easily share your empirical research survey form with respondents. You can use the direct social media sharing buttons to share your form link to your organization’s social media pages. 

You can send out your survey form as email invitations to your research subjects too. If you wish, you can share your form’s QR code or embed it on your organization’s website for easy access. 

Empirical vs Non-Empirical Research

Empirical and non-empirical research are common methods of systematic investigation employed by researchers. Unlike empirical research that tests hypotheses in order to arrive at valid research outcomes, non-empirical research theorizes the logical assumptions of research variables. 

Definition: Empirical research is a research approach that makes use of evidence-based data while non-empirical research is a research approach that makes use of theoretical data. 

Method: In empirical research, the researcher arrives at valid outcomes by mainly observing research variables, creating a hypothesis and experimenting on research variables to confirm or refute the hypothesis. In non-empirical research, the researcher relies on inductive and deductive reasoning to theorize logical assumptions about the research subjects.

The major difference between the research methodology of empirical and non-empirical research is while the assumptions are tested in empirical research, they are entirely theorized in non-empirical research. 

Data Sample: Empirical research makes use of empirical data while non-empirical research does not make use of empirical data. Empirical data refers to information that is gathered through experience or observation. 

Unlike empirical research, theoretical or non-empirical research does not rely on data gathered through evidence. Rather, it works with logical assumptions and beliefs about the research subject. 

Data Collection Methods : Empirical research makes use of quantitative and qualitative data gathering methods which may include surveys, experiments, and methods of observation. This helps the researcher to gather empirical data, that is, data backed by evidence.  

Non-empirical research, on the other hand, does not make use of qualitative or quantitative methods of data collection . Instead, the researcher gathers relevant data through critical studies, systematic review and meta-analysis. 

Advantages of Empirical Research 

• Empirical research is flexible. In this type of systematic investigation, the researcher can adjust the research methodology including the data sample size, data gathering methods plus the data analysis methods as necessitated by the research process.
• It helps the research to understand how the research outcomes can be influenced by different research environments.
• Empirical research study helps the researcher to develop relevant analytical and observation skills that can be useful in dynamic research contexts.
• This type of research approach allows the researcher to control multiple research variables in order to arrive at the most relevant research outcomes.
• Empirical research is widely considered as one of the most authentic and competent research designs.
• It improves the internal validity of traditional research using a variety of experiments and research observation methods.

Disadvantages of Empirical Research 

• An empirical research study is time-consuming because the researcher needs to gather the empirical data from multiple resources which typically takes a lot of time.
• It is not a cost-effective research approach. Usually, this method of research incurs a lot of cost because of the monetary demands of the field research.
• It may be difficult to gather the needed empirical data sample because of the multiple data gathering methods employed in an empirical research study.
• It may be difficult to gain access to some communities and firms during the data gathering process and this can affect the validity of the research.
• The report from an empirical research study is intensive and can be very lengthy in nature.

Conclusion 

Empirical research is an important method of systematic investigation because it gives the researcher the opportunity to test the validity of different assumptions, in the form of hypotheses, before arriving at any findings. Hence, it is a more research approach. 

There are different quantitative and qualitative methods of data gathering employed during an empirical research study based on the purpose of the research which include surveys, experiments, and various observatory methods. Surveys are one of the most common methods or empirical data collection and they can be administered online or physically. 

You can use Formplus to create and administer your online empirical research survey. Formplus allows you to create survey forms that you can share with target respondents in order to obtain valuable feedback about your research context, question or subject. 

In the form builder, you can add different fields to your survey form and you can also modify these form fields to suit your research process. Sign up to Formplus to access the form builder and start creating powerful online empirical research survey forms. 

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• uses of empirical research
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• What is empirical research: Methods, types & examples

Defne Çobanoğlu

Having opinions on matters based on observation is okay sometimes. Same as having theories on the subject you want to solve. However, some theories need to be tested. Just like Robert Oppenheimer says, “Theory will take you only so far .” 

In that case, when you have your research question ready and you want to make sure it is correct, the next step would be experimentation. Because only then you can test your ideas and collect tangible information. Now, let us start with the empirical research definition:

• What is empirical research?

Empirical research is a research type where the aim of the study is based on finding concrete and provable evidence . The researcher using this method to draw conclusions can use both quantitative and qualitative methods. Different than theoretical research, empirical research uses scientific experimentation and investigation. 

Using experimentation makes sense when you need to have tangible evidence to act on whatever you are planning to do. As the researcher, you can be a marketer who is planning on creating a new ad for the target audience, or you can be an educator who wants the best for the students. No matter how big or small, data gathered from the real world using this research helps break down the question at hand. 

• When to use empirical research?

Empirical research methods are used when the researcher needs to gather data analysis on direct, observable, and measurable data. Research findings are a great way to make grounded ideas. Here are some situations when one may need to do empirical research:

1. When quantitative or qualitative data is needed

There are times when a researcher, marketer, or producer needs to gather data on specific research questions to make an informed decision. And the concrete data gathered in the research process gives a good starting point.

2. When you need to test a hypothesis

When you have a hypothesis on a subject, you can test the hypothesis through observation or experiment. Making a planned study is a great way to collect information and test whether or not your hypothesis is correct.

3. When you want to establish causality

Experimental research is a good way to explore whether or not there is any correlation between two variables. Researchers usually establish causality by changing a variable and observing if the independent variable changes accordingly.

• Types of empirical research

The aim of empirical research is to collect information about a subject from the people by doing experimentation and other data collection methods. However, the methods and data collected are divided into two groups: one collects numerical data, and the other one collects opinion-like data. Let us see the difference between these two types:

Quantitative research

Quantitative research methods are used to collect data in a numerical way. Therefore, the results gathered by these methods will be numbers, statistics, charts, etc. The results can be used to quantify behaviors, opinions, and other variables. Quantitative research methods are surveys, questionnaires, and experimental research.

Qualitiative research

Qualitative research methods are not used to collect numerical answers, instead, they are used to collect the participants’ reasons, opinions, and other meaningful aspects. Qualitative research methods include case studies, observations, interviews, focus groups, and text analysis.

• 5 steps to conduct empirical research

Necessary steps for empirical research

When you want to collect direct and concrete data on a subject, empirical research is a great way to go. And, just like every other project and research, it is best to have a clear structure in mind. This is even more important in studies that may take a long time, such as experiments that take years. Let us look at a clear plan on how to do empirical research:

1. Define the research question

The very first step of every study is to have the question you will explore ready. Because you do not want to change your mind in the middle of the study after investing and spending time on the experimentation.

2. Go through relevant literature

This is the step where you sit down and do a desk research where you gather relevant data and see if other researchers have tried to explore similar research questions. If so, you can see how well they were able to answer the question or what kind of difficulties they faced during the research process.

3. Decide on the methodology

Once you are done going through the relevant literature, you can decide on which method or methods you can use. The appropriate methods are observation, experimentation, surveys, interviews, focus groups, etc.

4. Do data analysis

When you get to this step, it means you have successfully gathered enough data to make a data analysis. Now, all you need to do is look at the data you collected and make an informed analysis.

5. Conclusion

This is the last step, where you are finished with the experimentation and data analysis process. Now, it is time to decide what to do with this information. You can publish a paper and make informed decisions about whatever your goal is.

• Empirical research methodologies

Some essential methodologies to conduct empirical research

The aim of this type of research is to explore brand-new evidence and facts. Therefore, the methods should be primary and gathered in real life, directly from the people. There is more than one method for this goal, and it is up to the researcher to use which one(s). Let us see the methods of empirical research: 

• Observation

The method of observation is a great way to collect information on people without the effect of interference. The researcher can choose the appropriate area, time, or situation and observe the people and their interactions with one another. The researcher can be just an outside observer or can be a participant as an observer or a full participant.

• Experimentation

The experimentation process can be done in the real world by intervening in some elements to unify the environment for all participants. This method can also be done in a laboratory environment. The experimentation process is good for being able to change the variables according to the aim of the study.

The case study method is done by making an in-depth analysis of already existing cases. When the parameters and variables are similar to the research question at hand, it is wise to go through what was researched before.

• Focus groups

The case study method is done by using a group of individuals or multiple groups and using their opinions, characteristics, and responses. The scientists gather the data from this group and generalize it to the whole population.

Surveys are an effective way to gather data directly from people. It is a systematic approach to collecting information. If it is done in an online setting as an online survey , it would be even easier to reach out to people and ask their opinions in open-ended or close-ended questions.

Interviews are similar to surveys as you are using questions to collect information and opinions of the people. Unlike a survey, this process is done face-to-face, as a phone call, or as a video call.

• Advantages of empirical research

Empirical research is effective for many reasons, and helps researchers from numerous fields. Here are some advantages of empirical research to have in mind for your next research:

• Empirical research improves the internal validity of the study.
• Empirical evidence gathered from the study is used to authenticate the research question.
• Collecting provable evidence is important for the success of the study.
• The researcher is able to make informed decisions based on the data collected using empirical research.
• Disadvantages of empirical research

After learning about the positive aspects of empirical research, it is time to mention the negative aspects. Because this type may not be suitable for everyone and the researcher should be mindful of the disadvantages of empirical research. Here are the disadvantages of empirical research:

• As it is similar to other research types, a case study where experimentation is included will be time-consuming no matter what. It has more steps and variables than concluding a secondary research.
• There are a lot of variables that need to be controlled and considered. Therefore, it may be a challenging task to be mindful of all the details.
• Doing evidence-based research can be expensive if you need to complete it on a large scale.
• When you are conducting an experiment, you may need some waivers and permissions.
• Frequently asked questions about empirical research

Empirical research is one of the many research types, and there may be some questions in mind about its similarities and differences to other research types.

Is empirical research qualitative or quantitative?

The data collected by empirical research can be qualitative, quantitative, or a mix of both. It is up to the aim of researcher to what kind of data is needed and searched for.

Is empirical research the same as quantitative research?

As quantitative research heavily relies on data collection methods of observation and experimentation, it is, in nature, an empirical study. Some professors may even use the terms interchangeably. However, that does not mean that empirical research is only a quantitative one.

What is the difference between theoretical and empirical research?

Empirical studies are based on data collection to prove theories or answer questions, and it is done by using methods such as observation and experimentation. Therefore, empirical research relies on finding evidence that backs up theories. On the other hand, theoretical research relies on theorizing on empirical research data and trying to make connections and correlations.

What is the difference between conceptual and empirical research?

Conceptual research is about thoughts and ideas and does not involve any kind of experimentation. Empirical research, on the other hand, works with provable data and hard evidence.

What is the difference between empirical vs applied research?

Some scientists may use these two terms interchangeably however, there is a difference between them. Applied research involves applying theories to solve real-life problems. On the other hand, empirical research involves the obtaining and analysis of data to test hypotheses and theories.

• Final words

Empirical research is a good means when the goal of your study is to find concrete data to go with. You may need to do empirical research when you need to test a theory, establish causality, or need qualitative/quantitative data. For example, you are a scientist and want to know if certain colors have an effect on people’s moods, or you are a marketer and want to test your theory on ad places on websites. 

In both scenarios, you can collect information by using empirical research methods and make informed decisions afterward. These are just the two of empirical research examples. This research type can be applied to many areas of work life and social sciences. Lastly, for all your research needs, you can visit forms.app to use its many useful features and over 1000 form and survey templates!

Defne is a content writer at forms.app. She is also a translator specializing in literary translation. Defne loves reading, writing, and translating professionally and as a hobby. Her expertise lies in survey research, research methodologies, content writing, and translation.

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5 Research design

Research design is a comprehensive plan for data collection in an empirical research project. It is a ‘blueprint’ for empirical research aimed at answering specific research questions or testing specific hypotheses, and must specify at least three processes: the data collection process, the instrument development process, and the sampling process. The instrument development and sampling processes are described in the next two chapters, and the data collection process—which is often loosely called ‘research design’—is introduced in this chapter and is described in further detail in Chapters 9–12.

Broadly speaking, data collection methods can be grouped into two categories: positivist and interpretive. Positivist methods , such as laboratory experiments and survey research, are aimed at theory (or hypotheses) testing, while interpretive methods, such as action research and ethnography, are aimed at theory building. Positivist methods employ a deductive approach to research, starting with a theory and testing theoretical postulates using empirical data. In contrast, interpretive methods employ an inductive approach that starts with data and tries to derive a theory about the phenomenon of interest from the observed data. Often times, these methods are incorrectly equated with quantitative and qualitative research. Quantitative and qualitative methods refers to the type of data being collected—quantitative data involve numeric scores, metrics, and so on, while qualitative data includes interviews, observations, and so forth—and analysed (i.e., using quantitative techniques such as regression or qualitative techniques such as coding). Positivist research uses predominantly quantitative data, but can also use qualitative data. Interpretive research relies heavily on qualitative data, but can sometimes benefit from including quantitative data as well. Sometimes, joint use of qualitative and quantitative data may help generate unique insight into a complex social phenomenon that is not available from either type of data alone, and hence, mixed-mode designs that combine qualitative and quantitative data are often highly desirable.

Key attributes of a research design

The quality of research designs can be defined in terms of four key design attributes: internal validity, external validity, construct validity, and statistical conclusion validity.

Internal validity , also called causality, examines whether the observed change in a dependent variable is indeed caused by a corresponding change in a hypothesised independent variable, and not by variables extraneous to the research context. Causality requires three conditions: covariation of cause and effect (i.e., if cause happens, then effect also happens; if cause does not happen, effect does not happen), temporal precedence (cause must precede effect in time), and spurious correlation, or there is no plausible alternative explanation for the change. Certain research designs, such as laboratory experiments, are strong in internal validity by virtue of their ability to manipulate the independent variable (cause) via a treatment and observe the effect (dependent variable) of that treatment after a certain point in time, while controlling for the effects of extraneous variables. Other designs, such as field surveys, are poor in internal validity because of their inability to manipulate the independent variable (cause), and because cause and effect are measured at the same point in time which defeats temporal precedence making it equally likely that the expected effect might have influenced the expected cause rather than the reverse. Although higher in internal validity compared to other methods, laboratory experiments are by no means immune to threats of internal validity, and are susceptible to history, testing, instrumentation, regression, and other threats that are discussed later in the chapter on experimental designs. Nonetheless, different research designs vary considerably in their respective level of internal validity.

External validity or generalisability refers to whether the observed associations can be generalised from the sample to the population (population validity), or to other people, organisations, contexts, or time (ecological validity). For instance, can results drawn from a sample of financial firms in the United States be generalised to the population of financial firms (population validity) or to other firms within the United States (ecological validity)? Survey research, where data is sourced from a wide variety of individuals, firms, or other units of analysis, tends to have broader generalisability than laboratory experiments where treatments and extraneous variables are more controlled. The variation in internal and external validity for a wide range of research designs is shown in Figure 5.1.

Some researchers claim that there is a trade-off between internal and external validity—higher external validity can come only at the cost of internal validity and vice versa. But this is not always the case. Research designs such as field experiments, longitudinal field surveys, and multiple case studies have higher degrees of both internal and external validities. Personally, I prefer research designs that have reasonable degrees of both internal and external validities, i.e., those that fall within the cone of validity shown in Figure 5.1. But this should not suggest that designs outside this cone are any less useful or valuable. Researchers’ choice of designs are ultimately a matter of their personal preference and competence, and the level of internal and external validity they desire.

Construct validity examines how well a given measurement scale is measuring the theoretical construct that it is expected to measure. Many constructs used in social science research such as empathy, resistance to change, and organisational learning are difficult to define, much less measure. For instance, construct validity must ensure that a measure of empathy is indeed measuring empathy and not compassion, which may be difficult since these constructs are somewhat similar in meaning. Construct validity is assessed in positivist research based on correlational or factor analysis of pilot test data, as described in the next chapter.

Statistical conclusion validity examines the extent to which conclusions derived using a statistical procedure are valid. For example, it examines whether the right statistical method was used for hypotheses testing, whether the variables used meet the assumptions of that statistical test (such as sample size or distributional requirements), and so forth. Because interpretive research designs do not employ statistical tests, statistical conclusion validity is not applicable for such analysis. The different kinds of validity and where they exist at the theoretical/empirical levels are illustrated in Figure 5.2.

Improving internal and external validity

The best research designs are those that can ensure high levels of internal and external validity. Such designs would guard against spurious correlations, inspire greater faith in the hypotheses testing, and ensure that the results drawn from a small sample are generalisable to the population at large. Controls are required to ensure internal validity (causality) of research designs, and can be accomplished in five ways: manipulation, elimination, inclusion, and statistical control, and randomisation.

In manipulation , the researcher manipulates the independent variables in one or more levels (called ‘treatments’), and compares the effects of the treatments against a control group where subjects do not receive the treatment. Treatments may include a new drug or different dosage of drug (for treating a medical condition), a teaching style (for students), and so forth. This type of control is achieved in experimental or quasi-experimental designs, but not in non-experimental designs such as surveys. Note that if subjects cannot distinguish adequately between different levels of treatment manipulations, their responses across treatments may not be different, and manipulation would fail.

The elimination technique relies on eliminating extraneous variables by holding them constant across treatments, such as by restricting the study to a single gender or a single socioeconomic status. In the inclusion technique, the role of extraneous variables is considered by including them in the research design and separately estimating their effects on the dependent variable, such as via factorial designs where one factor is gender (male versus female). Such technique allows for greater generalisability, but also requires substantially larger samples. In statistical control , extraneous variables are measured and used as covariates during the statistical testing process.

Finally, the randomisation technique is aimed at cancelling out the effects of extraneous variables through a process of random sampling, if it can be assured that these effects are of a random (non-systematic) nature. Two types of randomisation are: random selection , where a sample is selected randomly from a population, and random assignment , where subjects selected in a non-random manner are randomly assigned to treatment groups.

Randomisation also ensures external validity, allowing inferences drawn from the sample to be generalised to the population from which the sample is drawn. Note that random assignment is mandatory when random selection is not possible because of resource or access constraints. However, generalisability across populations is harder to ascertain since populations may differ on multiple dimensions and you can only control for a few of those dimensions.

Popular research designs

As noted earlier, research designs can be classified into two categories—positivist and interpretive—depending on the goal of the research. Positivist designs are meant for theory testing, while interpretive designs are meant for theory building. Positivist designs seek generalised patterns based on an objective view of reality, while interpretive designs seek subjective interpretations of social phenomena from the perspectives of the subjects involved. Some popular examples of positivist designs include laboratory experiments, field experiments, field surveys, secondary data analysis, and case research, while examples of interpretive designs include case research, phenomenology, and ethnography. Note that case research can be used for theory building or theory testing, though not at the same time. Not all techniques are suited for all kinds of scientific research. Some techniques such as focus groups are best suited for exploratory research, others such as ethnography are best for descriptive research, and still others such as laboratory experiments are ideal for explanatory research. Following are brief descriptions of some of these designs. Additional details are provided in Chapters 9–12.

Experimental studies are those that are intended to test cause-effect relationships (hypotheses) in a tightly controlled setting by separating the cause from the effect in time, administering the cause to one group of subjects (the ‘treatment group’) but not to another group (‘control group’), and observing how the mean effects vary between subjects in these two groups. For instance, if we design a laboratory experiment to test the efficacy of a new drug in treating a certain ailment, we can get a random sample of people afflicted with that ailment, randomly assign them to one of two groups (treatment and control groups), administer the drug to subjects in the treatment group, but only give a placebo (e.g., a sugar pill with no medicinal value) to subjects in the control group. More complex designs may include multiple treatment groups, such as low versus high dosage of the drug or combining drug administration with dietary interventions. In a true experimental design , subjects must be randomly assigned to each group. If random assignment is not followed, then the design becomes quasi-experimental . Experiments can be conducted in an artificial or laboratory setting such as at a university (laboratory experiments) or in field settings such as in an organisation where the phenomenon of interest is actually occurring (field experiments). Laboratory experiments allow the researcher to isolate the variables of interest and control for extraneous variables, which may not be possible in field experiments. Hence, inferences drawn from laboratory experiments tend to be stronger in internal validity, but those from field experiments tend to be stronger in external validity. Experimental data is analysed using quantitative statistical techniques. The primary strength of the experimental design is its strong internal validity due to its ability to isolate, control, and intensively examine a small number of variables, while its primary weakness is limited external generalisability since real life is often more complex (i.e., involving more extraneous variables) than contrived lab settings. Furthermore, if the research does not identify ex ante relevant extraneous variables and control for such variables, such lack of controls may hurt internal validity and may lead to spurious correlations.

Field surveys are non-experimental designs that do not control for or manipulate independent variables or treatments, but measure these variables and test their effects using statistical methods. Field surveys capture snapshots of practices, beliefs, or situations from a random sample of subjects in field settings through a survey questionnaire or less frequently, through a structured interview. In cross-sectional field surveys , independent and dependent variables are measured at the same point in time (e.g., using a single questionnaire), while in longitudinal field surveys , dependent variables are measured at a later point in time than the independent variables. The strengths of field surveys are their external validity (since data is collected in field settings), their ability to capture and control for a large number of variables, and their ability to study a problem from multiple perspectives or using multiple theories. However, because of their non-temporal nature, internal validity (cause-effect relationships) are difficult to infer, and surveys may be subject to respondent biases (e.g., subjects may provide a ‘socially desirable’ response rather than their true response) which further hurts internal validity.

Secondary data analysis is an analysis of data that has previously been collected and tabulated by other sources. Such data may include data from government agencies such as employment statistics from the U.S. Bureau of Labor Services or development statistics by countries from the United Nations Development Program, data collected by other researchers (often used in meta-analytic studies), or publicly available third-party data, such as financial data from stock markets or real-time auction data from eBay. This is in contrast to most other research designs where collecting primary data for research is part of the researcher’s job. Secondary data analysis may be an effective means of research where primary data collection is too costly or infeasible, and secondary data is available at a level of analysis suitable for answering the researcher’s questions. The limitations of this design are that the data might not have been collected in a systematic or scientific manner and hence unsuitable for scientific research, since the data was collected for a presumably different purpose, they may not adequately address the research questions of interest to the researcher, and interval validity is problematic if the temporal precedence between cause and effect is unclear.

Case research is an in-depth investigation of a problem in one or more real-life settings (case sites) over an extended period of time. Data may be collected using a combination of interviews, personal observations, and internal or external documents. Case studies can be positivist in nature (for hypotheses testing) or interpretive (for theory building). The strength of this research method is its ability to discover a wide variety of social, cultural, and political factors potentially related to the phenomenon of interest that may not be known in advance. Analysis tends to be qualitative in nature, but heavily contextualised and nuanced. However, interpretation of findings may depend on the observational and integrative ability of the researcher, lack of control may make it difficult to establish causality, and findings from a single case site may not be readily generalised to other case sites. Generalisability can be improved by replicating and comparing the analysis in other case sites in a multiple case design .

Focus group research is a type of research that involves bringing in a small group of subjects (typically six to ten people) at one location, and having them discuss a phenomenon of interest for a period of one and a half to two hours. The discussion is moderated and led by a trained facilitator, who sets the agenda and poses an initial set of questions for participants, makes sure that the ideas and experiences of all participants are represented, and attempts to build a holistic understanding of the problem situation based on participants’ comments and experiences. Internal validity cannot be established due to lack of controls and the findings may not be generalised to other settings because of the small sample size. Hence, focus groups are not generally used for explanatory or descriptive research, but are more suited for exploratory research.

Action research assumes that complex social phenomena are best understood by introducing interventions or ‘actions’ into those phenomena and observing the effects of those actions. In this method, the researcher is embedded within a social context such as an organisation and initiates an action—such as new organisational procedures or new technologies—in response to a real problem such as declining profitability or operational bottlenecks. The researcher’s choice of actions must be based on theory, which should explain why and how such actions may cause the desired change. The researcher then observes the results of that action, modifying it as necessary, while simultaneously learning from the action and generating theoretical insights about the target problem and interventions. The initial theory is validated by the extent to which the chosen action successfully solves the target problem. Simultaneous problem solving and insight generation is the central feature that distinguishes action research from all other research methods, and hence, action research is an excellent method for bridging research and practice. This method is also suited for studying unique social problems that cannot be replicated outside that context, but it is also subject to researcher bias and subjectivity, and the generalisability of findings is often restricted to the context where the study was conducted.

Ethnography is an interpretive research design inspired by anthropology that emphasises that research phenomenon must be studied within the context of its culture. The researcher is deeply immersed in a certain culture over an extended period of time—eight months to two years—and during that period, engages, observes, and records the daily life of the studied culture, and theorises about the evolution and behaviours in that culture. Data is collected primarily via observational techniques, formal and informal interaction with participants in that culture, and personal field notes, while data analysis involves ‘sense-making’. The researcher must narrate her experience in great detail so that readers may experience that same culture without necessarily being there. The advantages of this approach are its sensitiveness to the context, the rich and nuanced understanding it generates, and minimal respondent bias. However, this is also an extremely time and resource-intensive approach, and findings are specific to a given culture and less generalisable to other cultures.

Selecting research designs

Given the above multitude of research designs, which design should researchers choose for their research? Generally speaking, researchers tend to select those research designs that they are most comfortable with and feel most competent to handle, but ideally, the choice should depend on the nature of the research phenomenon being studied. In the preliminary phases of research, when the research problem is unclear and the researcher wants to scope out the nature and extent of a certain research problem, a focus group (for an individual unit of analysis) or a case study (for an organisational unit of analysis) is an ideal strategy for exploratory research. As one delves further into the research domain, but finds that there are no good theories to explain the phenomenon of interest and wants to build a theory to fill in the unmet gap in that area, interpretive designs such as case research or ethnography may be useful designs. If competing theories exist and the researcher wishes to test these different theories or integrate them into a larger theory, positivist designs such as experimental design, survey research, or secondary data analysis are more appropriate.

Regardless of the specific research design chosen, the researcher should strive to collect quantitative and qualitative data using a combination of techniques such as questionnaires, interviews, observations, documents, or secondary data. For instance, even in a highly structured survey questionnaire, intended to collect quantitative data, the researcher may leave some room for a few open-ended questions to collect qualitative data that may generate unexpected insights not otherwise available from structured quantitative data alone. Likewise, while case research employ mostly face-to-face interviews to collect most qualitative data, the potential and value of collecting quantitative data should not be ignored. As an example, in a study of organisational decision-making processes, the case interviewer can record numeric quantities such as how many months it took to make certain organisational decisions, how many people were involved in that decision process, and how many decision alternatives were considered, which can provide valuable insights not otherwise available from interviewees’ narrative responses. Irrespective of the specific research design employed, the goal of the researcher should be to collect as much and as diverse data as possible that can help generate the best possible insights about the phenomenon of interest.

Social Science Research: Principles, Methods and Practices (Revised edition) Copyright © 2019 by Anol Bhattacherjee is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License , except where otherwise noted.

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• Meriam Library

SWRK 330 - Social Work Research Methods

• Literature Reviews and Empirical Research
• Databases and Search Tips
• Article Citations
• Scholarly Journal Evaulation
• Statistical Sources
• Books and eBooks

What is a Literature Review?

Empirical research.

• Annotated Bibliographies

A literature review  summarizes and discusses previous publications  on a topic.

It should also:

explore past research and its strengths and weaknesses.

be used to validate the target and methods you have chosen for your proposed research.

consist of books and scholarly journals that provide research examples of populations or settings similar to your own, as well as community resources to document the need for your proposed research.

The literature review does not present new  primary  scholarship. 

be completed in the correct citation format requested by your professor  (see the  C itations Tab)

Access Purdue  OWL's Social Work Literature Review Guidelines here .  

Empirical Research  is  research  that is based on experimentation or observation, i.e. Evidence. Such  research  is often conducted to answer a specific question or to test a hypothesis (educated guess).

How do you know if a study is empirical? Read the subheadings within the article, book, or report and look for a description of the research "methodology."  Ask yourself: Could I recreate this study and test these results?

These are some key features to look for when identifying empirical research.

NOTE:  Not all of these features will be in every empirical research article, some may be excluded, use this only as a guide.

• Statement of methodology
• Research questions are clear and measurable
• Individuals, group, subjects which are being studied are identified/defined
• Data is presented regarding the findings
• Controls or instruments such as surveys or tests were conducted
• There is a literature review
• There is discussion of the results included
• Citations/references are included

See also Empirical Research Guide

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• Last Updated: Feb 6, 2024 8:38 AM
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6th Edition

Proposing Empirical Research A Guide to the Fundamentals

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Description

Proposing Empirical Research: A Guide to the Fundamentals provides step-by-step instructions for students who will be writing their first research proposal in the social and behavioral sciences and using both quantitative and qualitative methods. The structure of the book enables students to work independently with confidence while writing the first drafts of their proposals. Each major section is divided into short topics and for each topic, students are asked to complete an exercise that leads them toward the goal of preparing a proposal. Numerous illustrative examples throughout the book make the recommendations for proposal writing come alive. In addition, the 10 model proposals provided at the end of the book illustrate proposal writing and provide material for classroom discussions. New to the Sixth Edition: Updates throughout to reflect research and learning in the digital/online environment, e.g., online surveys, digital organization tools, digital recruitment methods for research, and digital databases, records, and archives. Discussion of qualitative methods. Updated references, model proposals, end of chapter exercises etc. Proposing Empirical Research is ideal for use in research methods classes where students write a proposal as a term project, thesis/dissertation preparation classes, senior research seminars where proposing and conducting research is a culminating undergraduate activity, and any graduate-level seminar in which the instructor wants to incorporate a project that will engage students in critical thinking about the content area.

Table of Contents

Melisa C. Galvan is Assistant Professor at California State University, Northridge.

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Identifying Empirical Research Articles

• Identifying Empirical Articles
• Searching for Empirical Research Articles

Where to find empirical research articles

Finding empirical research.

When searching for empirical research, it can be helpful to use terms that relate to the method used in empirical research in addition to keywords that describe your topic. For example: 

• (generalized anxiety  AND  treatment*)  AND  (randomized clinical trial*  OR  clinical trial*)

You might also try using terms related to the type of instrument used:

• (generalized anxiety  AND  intervention*)  AND  (survey  OR  questionnaire)

You can also narrow your results to peer-review . Usually databases have a peer-review check box that you can select. To learn more about peer review, see our related guide:

• Understand Peer Review

Searching by Methodology

Some databases give you the option to do an advanced search by  methodology, where you can choose "empirical study" as a type. Here's an example from PsycInfo: 

Other filters includes things like document type, age group, population, language, and target audience. You can use these to narrow your search and get more relevant results.

Databasics: How to Filter by Methodology in ProQuest's PsycInfo + PsycArticles

Part of our Databasics YouTube series, this short video shows you how to limit by methodology in ProQuest's PsycInfo + PsycArticles database.

Attribution

Information in this guide adapted from Boston College Libraries' guide to " Finding Empirical Research "; Brandeis Library's " Finding Empirical Studies "; and CSUSM's " How do I know if a research article is empirical? "

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• Last Updated: Nov 16, 2023 8:24 AM

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Project Chapter Two: Literature Review and Steps to Writing Empirical Review

Kindly share this story:

• Conceptual review
• Theoretical review,
• Empirical review or review of empirical works of literature/studies, and lastly
• Conclusion or Summary of the literature reviewed.
• Decide on a topic
• Highlight the studies/literature that you will review in the empirical review
• Analyze the works of literature separately.
• Summarize the literature in table or concept map format.
• Synthesize the literature and then proceed to write your empirical review.

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Empirical Research Project

Course Lecturer Name(s):  Wendy Crawford-Daniel

Course Director Name: Wendy Crawford-Daniel

Course Lecturer(s) Contact Information:  [email protected]; ext.3152 Cell:457-4856

Course Director Contact Information:  Same 

Course Lecturer(s) Office Hours:  Mondays 10:11:20 A.M. and  By Appointment

Course Director Office Hours:  Same

Course Lecturer(s) Office Location:  Ballsier Building - Upstairs

Course Director Office Location:        N/A

Course Support:   Nicole  Philip; [email protected];  

Course Management tool: To learn to use Sakai, the Course management tool, access the link https://apps.sgu.edu/members.nsf/mycoursesintro.pdf

Course Description: 

This course is for students in their final year. Students will carry out a field research project using the proposal designed at the Introduction to Empirical Research course.  The course will allow students to revise and improve upon their proposal, carry out an extensive literature review, select the sampled population; improve their data-collection instrument and  conduct data collection. They will be required to conduct data analysis and write up a complete research report. Students will also be required to conduct the IRB training and undertake the online training in Ethic in research to atain the ethical certificate. Students will  use SPSS or other online analysis tools for the analysis of their data.  

Course Objectives:  

• Complete a comprehensive research proposal
• Update/Conduct an extensive Literature Review on topic of interest
• Collect data and analyse data 
• Write up research report
• Present research findings

Student Learning Outcomes:

At the end of the course students must be able to:

• Prepare a research proposal and submit for IRB approval
• Complete the ethical training and certification 
• Conduct a comprehensive literature review
• Collect data in the field
• Enter and analyse data collected
• Write up a research report

Program Outcomes Met By This Course:

PO.1. Apply research methodologies to investigate social problems/issues

PO.2. Demonstrate their critical thinking skills to sociological analysis of social problem/issues. PO.3. Employ sociological research methods to investigate and explain social issues

SAS Grading Scale: Grades will be assigned as follows:

A  = 89.5% or better

B+ = 84.5 - 89.4%

B  = 79.5 - 84.4%

C+ = 74.5 - 79.4%

C = 69.5 - 74.4%

D = 64.5 - 69.4%

F = 64.4% or less

Course Materials:

Text: • Neuman, Lawrence W.  (2006). Social Research Methods Qualitative and Quantitative Approaches,

6th Edition. Pearson Education, Inc. USA d

Course Grading Requirement:

• Revised Project Proposal:                         10%
• Enhanced Literature Review:                    20 %
• Review and Piloting of Instrument:          20 %
• Completed Final Project:                           50 % 

Course Requirements:

• Students must have completed Introduction to Empirical Research
• Students must have an approved research proposal
• Students must have access to analytic tool (SPSS) for Quantitative Method

Course Schedule : 

Monday, Wednesday, Fridays : 

Course Description

• General Ethical Issues in Empirical  Research Project: 
• Discussion of individual Research Proposals  
• Review of Research Proposals
• Ethical Issues in Research/IRB Requirements 
• Assignment due - Research Proposal 
• Expand Review of Literature/ Using Literature in Qualitative Research  Ethical Issues in using Literature/  
• Key Issues in Research Designs – Quantitative:
• Individual design consultations
• Key Issues in Research Designs – Qualitative
• Ethical Issues in Design 
• Individual Design consultations           
• Pilot and finalize Research Instrument 
• (Survey and Interviews)                 
• Data Collection/ Field Work
• (Individual consultations)
• Analyzing Data 
• SPSS – quantitative analysis
• Thematic – qualitative analysis 
• (Individual Consultations) 
• Writing up Results
• (Project Consultation)           

Week 16: Project Due

School of Arts and Sciences Master Syllabi — Info for All Sections

Academic Integrity

The St. George’s University Student Manual (2019/2020)  states as follows:

“ Plagiarism is regarded as a cardinal offense in academia because it constitutes theft of the work of someone else, which is then purported as the original work of the plagiarist. Plagiarism draws into disrepute the credibility of the Institution, its faculty, and students; therefore, it is not tolerated ” (p. 48).

Plagiarism also includes the unintentional copying or false accreditation of work, so double check your assignments  BEFORE  you hand them in.

Be sure to do good, honest work, credit your sources and reference accordingly and adhere to the University’s Honor Code. Plagiarism and cheating will be dealt with very seriously following the university’s policies on Plagiarism as outlined in the Student Manual.

Your work may be subject to submission to plagiarism detection software, submission to this system means that your work automatically becomes part of that database and can be compared with the work of your classmates.

“ Students are expected to attend all classes and or clinical rotations for which they have registered. Although attendance may not be recorded at every academic activity, attendance may be taken randomly. Students’ absence may adversely affect their academic status as specified in the grading policy. If absence from individual classes, examinations, and activities, or from the University itself is anticipated, or occurs spontaneously due to illness or other extenuating circumstances, proper notification procedures must be followed. A particular course may define additional policies regarding specific attendance or participation ” (p. 9).

“ All matriculated students are expected to attend all assigned academic activities for each course currently registered. Medical excuses will be based on self-reporting by students. Students who feel they are too sick to take an examination or other required activity on a specific day must submit the online SAS medical excuse, which is available on Carenage. Students are only allowed two such excuses a year. Upon consultation with the Director of University Health Service, the third excuse will result in a mandatory medical leave of absence. The policies regarding make-up examinations are at the option of the Course Director ” (p.46).

For additional specific examination policies and procedures, refer to the St. George’s University Student Manual (2019/2020), pages 31 through 37.

“ A student with a disability or disabling condition that affects one or more major life activities, who would like to request an accommodation, must submit a completed application form and supporting documentation to the Student Accessibility and Accommodation Services (SAAS) located in the Dean of Students Office. It is highly recommended that students applying for accommodations do so at least one month before classes begin to allow for a more efficient and timely consideration of the request. If a fully completed application is not submitted in a timely fashion, an eligibility determination may not be made, and accommodations, where applicable, may not be granted prior to the commencement of classes and/or examinations ” (p. 8).

It is the responsibility of the student to read and understand the policies, laws, rules and procedures that while they could affect your grade for a course, have not been specifically outlined in the course syllabus. These are contained in the  St. George’s University Student Manual .

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Table of Contents

Related Concepts: Positivism ; Research Methods ; Research Methodologies

What are Empirical Research Methods?

Empirical research refers to methods that investigators use to test knowledge claims and develop new new knowledge through direct or indirect observation and experimentation. Empirical methods emphasize collecting data systematically and rigorously to ensure reliability and validity. Investigators observe phenomena, conduct experiments, and gather measurable evidence to support or refute hypotheses, allowing for the objective analysis and interpretation of results.

There are three major types of empirical research :

• e.g., numbers, mathematical equations).
• Mixed Methods (a mixture of Quantitative Methods and Qualitative Methods .

Investigators use empirical research methods

• to create new knowledge (e.g., Basic Research )
• to solve a problem at work, school, or personal life (e.g., Applied Research ).
• to conduct replication studies–i.e., repeat a study with the same methods (or with slight variations, such as changes in subjects and experimenters).

Empirical research aims to be as objective as possible by being RAD —

• (sufficient details about the research protocol is provided so the study can be repeated)
• (the results and implications of the study can be extended in future research)
• ( quantitative evidence and/or Qualitative evidence are provided to substantiate claims, results, interpretations, implications).

Informally, as humans, we engage routinely in the intellectual strategies that inform empirical research:

• we talk with others and listen to their stories to better understand their perceptions and experiences,
• we make observations,
• we survey friends, peers, coworkers
• we cross cultures and learn about difference, and
• we make predictions about future events based on our experiences and observations.

These same intellectual strategies we use to reason from our observations and experiences also undergird empirical research methods. For example,

• a psychologist might develop a case study based on interviews
• an anthropologist or sociologist might engage in participant observation to write an ethnographic study
• a political science researcher might survey voter trends
• a stock trader may project a stock bounce based on a 30-day moving average.

The main difference between informal and formal empirical research is intentionality : Formal empirical research presupposes a Research Plan , which is sometimes referred to as as Research Protocol . When investigators want their results to be taken seriously they have to employ the research methods a methodological community has for vetting knowledge claims .

Different academic communities (e.g., Natural Sciences, Social Science, Humanities, Arts) have unique ideas about how to conduct empirical research. Professionals in the workplace — e.g., geologists, anthropologists, biologists — use entirely different tools to gather and interpret data. Being credentialed in a particular discipline or profession is tied to mastery of unique methodological practices.

Across disciplines, however, empiricists share a number of operating assumptions: Empiricists

• develop a research plan prior to engaging in research.
• seek approval from Ethics Committees when human subjects or animal testing is involved
• explain how subjects/research participants are chosen and given opportunities to opt in or opt out of studies.

Empiricists are meticulous about how they collect data because their research must be verifiable if they want other empiricists to take their work seriously. In other words, their research plan needs to be so explicit that subsequent researchers can conduct the same study.

Empirical Research is a Rhetorical Practice

Empiricists develop their research question and their research methods by considering their audience and purpose . Prior to initiating a study, researchers conduct secondary research–especially Searching as Strategic Exploration –to identify the current knowledge about a topic. As a consequence of their deep understanding of pertinent scholarly conversations on the topic, empiricists identify gaps in knowledge.

What is the role of textual research in empirical work?

Investigators conduct empirical research when the answers to research questions are not readily available from informal research or textual research , when the occasion is kairotic , when personal or financial gains are on the table. That said, most empirical research is informed by textual research: investigators review the conclusions and implications of previously published research past studies—they analyze scholarly conversations and research methods—prior to engaging in empirical studies.

T extual research plays an important role in empirical research . Empiricists engage in some textual research in order to understand scholarly conversations around the topics that interest them. Empiricists consult archives to learn methods for conducting empirical studies. However, there are important distinctions between how scholars weight claims in textual research and how scientists weigh claims in empirical studies.

Unlike investigators who use primarily textual methods , empiricists do not consider “claims of authority, intuition, imaginative conjecture, and abstract, theoretical, or systematic reasoning as sources of reliable belief” (Duignan, Fumerton, Quinton, Quinton 2020).

What epistemologies inform empirical work?

Empirical research is informed by two key philosophical foundations:

• Empiricism: This philosophy assumes that knowledge is grounded in sensory experiences—what can be seen, heard, or otherwise experienced. Empiricism emphasizes the importance of evidence derived from observation and experimentation.
• Positivism: This philosophy assumes that the universe is an orderly place where events have causes and occur in regular patterns. Positivism holds that these patterns can be discovered through systematic observation and that scientific inquiry can reveal objective truths about the natural world.

Duignan, B., Fumerton, R.,  Quinton, A. M., & Quinton, B. (2020). Empiricism. Encyclopedia Britannica.  https://www.britannica.com/topic/empiricism

Haswell, R. (2005). NCTE/CCCC’s recent war on scholarship. Written Communication, 22 (2), 198-223.

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