research paper on human behavior in organization

•  Sign into My Research
•  Create My Research Account
• Company Website
• Our Products
• About Dissertations
• Español (España)
• Support Center

Select language

• Bahasa Indonesia
• Português (Brasil)
• Português (Portugal)

Welcome to My Research!

You may have access to the free features available through My Research. You can save searches, save documents, create alerts and more. Please log in through your library or institution to check if you have access.

Translate this article into 20 different languages!

If you log in through your library or institution you might have access to this article in multiple languages.

Get access to 20+ different citations styles

Styles include MLA, APA, Chicago and many more. This feature may be available for free if you log in through your library or institution.

Looking for a PDF of this document?

You may have access to it for free by logging in through your library or institution.

Want to save this document?

You may have access to different export options including Google Drive and Microsoft OneDrive and citation management tools like RefWorks and EasyBib. Try logging in through your library or institution to get access to these tools.

• Document 1 of 1
• More like this
• Scholarly Journal

Trends in Organizational Behavior: A Systematic Review and Research Directions

No items selected.

Please select one or more items.

Select results items first to use the cite, email, save, and export options

Purpose - The purpose of this paper is to present a step-by-step guide to facilitate understanding of emerging trends in the discipline of Organizational Behavior using the technique of Systematic Literature Review.

Method - Literature review is done by systematically collecting the existing literature over the period of 1990-2019. The literature is categorized according to the Journal Name and Ranking, Database, and Geographical Distribution (country wise). Literature is also categorized on the basis of type of study (empirical/conceptual), variables used, scales used, sample studies and sub area of study (Leadership/Motivation etc). This classification can serve as a base for researchers who wish to conduct meta-analysis on emerging trends in Organizational Behavior.

Findings - A disciplined screening process resulted in 81 relevant research papers appropriate for the study. These papers explain the emerging trends in the discipline since 1990.

Limitations - Due to the vast areas and sub-areas covered under Organizational Behavior, it is not possible to study the entire discipline since 1990 in a single study. Hence the study only focuses on relevant and emerging trends in Organizational Behavior.

Implications - The study aims to fill the gap of unavailability of a structured systematic literature review in the discipline of Organizational Behaviour. This may serve as an important source of information for Academicians, Practitioners. The study postulates new avenues for future research.

Originality - The study contributes to the methodology for conducting Systematic Literature Reviews in the field of management, specifically in Organizational Behaviour. It highlights an effective method for mapping out thematically, and viewing holistically, emerging research trends.

Keywords: Future Workplaces, Systematic Literature Review, Organizational Behavior

Introduction

Organization Behavior is the study of human behavior in an organizational setting (Baron and Greenberg, 1990). It is a multidisciplinary subject devoted to understanding of individual and group behavior, interpersonal processes, and organizational dynamics. It has emerged from the disciplines of psychology, sociology, political science, and economics (Schneider 1985). The study of Organizational Behavior as a discipline can be categorized into three simple levels: micro level (individual); meso level (group) and macro level (organization) (Barbour, 2017)

The period before 1890 is known as the Pre-Scientific Management era. In the period after 1890, Management Theories started gaining importance. Scientific Management was developed during this period. Scientific Management is also a theory of management, which focuses on improving economic efficiency, especially labor productivity. The period between 1920 and 1930 characterizes the growth of literature on human relations (Warner, 1994). This inter-war period paved way for work groups emerging as an important component of human relations. In 1920's, Hawthorne Effect studied the socio-psychological impact of human behavior in organizations. This study focused on relationship between productivity and variables such as lighting in the workplace, clean workstation, allowing employees to build and work in teams, and having regular breaks. (Mayo et al., 1939). The growing importance of people factor as the core of human relations became a concern for many active organizations in that inter-war period (Follet 1941; Child 1969). During the Word War I, considerable efforts were made to boost up worker's motivation due to war crisis. Similar practices were observed after 1918 in the peace time after World War II. Organizational behavior started to establish post World War II, specifically after 1945, as an academic discipline.

Due to the traditional and obsolete practices adopted by Human Relations, Organizational Behavior as a discipline started gaining importance. It emerged as the study of the structure and functioning of the organizations, its culture, its sub-elements and behavior of the groups and individuals within them. It emerged as an interdisciplinary science interlinking disciplines of sociology, psychology, economics, political science, social anthropology and production engineering. (Pugh et al., 1975).There has been significant literary work done post 1945 after establishment of Organizational Behavior as a discipline.

However, there is a dearth of a well-defined, relevant and structured study that explains the development of the discipline over the years. The need to understand how the discipline will work towards academic and practical implication for future research under the light of multi-disciplinarily gives rise to the need of framing this research paper. Thus, the purpose of this paper is to depict a clear picture of sub-elements in complexities and explore innovative areas of research that would help researchers and scholars in postulating new research avenues for research and development in the domain of Organizational Behavior. These new developments in the discipline will help practitioners take sound decisions backed by a systematic literature base.

In the forthcoming sections, the paper explains the various dimensions and sub-elements of Organizational Behavior. The evolution and establishment of the domain is defined in detail with the help of the technique of Systematic Literature Review. A step-by-step objective approach and the literature can serve as a basis for future research by scholars, as well as for implementation by practitioners.

Review Methodology and Structure

Identification of relevant literature

The first step in the review was identifying the relevant literature on organizational behavior. A total of 81 research papers spread across the time-period of 1990-2019 were considered for the study. The growing significance of understanding Organizational Behavior as a discipline and Systematic Literature Review as a review technique is the primary reason behind selection of the period of 1990-2019 for the study.

Scholarly databases such as EBSCO, Emerald, Springer, Elsevier, Wiley, ProQuest, J Stor and Taylor and Francis were searched using the key phrase 'literature review' 'systematic literature review' and 'organizational behavior'. A total of 93 papers were identified for the study.

Inclusion and Exclusion Criteria

* Keyword: Using the database of ISI Web of Knowledge and the keyword "Organizational Behaviour" 26,418 papers were identified.

* Discipline: Using the inclusion criteria of "Management" as a discipline, the number of papers was reduced to 10,535.

* Language: Selection of "English" as a language reduced the number to 10,454

* Review Papers: Using "Review Papers" as the inclusion criteria, the number reduced down to 774 papers

* Research Areas: Using "Management Science", "Psychology", "Behavior Science", "Social Science", "Education Research", "Operation and Management Science", "Communication", "Sociology" as the inclusion category for allied research areas, 416 research papers were retrieved. Out of which 81 relevant research papers concerning performing Systematic Literature Review on emerging trends in Organizational Behavior were studied.

Analysis of Results

Inference: The country wise segregation shows that there has been manifold increase in the literature availability concerning Organizational Behavior after 1990 (see Table 1). And hence the period of 1990- 2019 has been chosen for the study. The table also shows the growth and prominence of Organizational Behavior as a discipline in developed countries like USA & UK. Hawthorne Studies which was a major development in the discipline was carried out in Western Electric, USA. Due to the majority of developments in the discipline being associated with USA, availability of literary studies is maximum for USA here. In the Indian context, the availability of prominent literature is scarce, and is mainly observed after the period of 2011. Hence there is a dearth of research literature in Organizational Behavior in Indian Context.

Organizational Behavior by definition is concerned with the study of what people do in an organization (social system), and how that behavior affects the performance of the organization at Individual, Group & Organization Level (Robbins and Judge, 1993). Hence we have classified the papers and sub-areas on the basis of three unit of analysis: Individual, Group and Organization.

Inference: Table 2 displays the patterns in literary studies in various sub-areas of Organizational Behavior over the past decade. Some of the sub-areas indicating significant shift in patterns are discussed in the following statements. Emerging subject area like 'Emotions at Workplace' has seen a literary growth in studies from 16.66% in 2001-2005 to 66.66% in 2011-2019. Also with changing patterns of Leadership, a tremendous growth in the sub-domain can be observed. Literary studies in 'Leadership' have moved from 8.33% in 1996-2000 to 83.33% in 2011-2019.

Inference: Table 3 represents study of top journals for the review. 30.76% Journals considered for the analysis have A· ranking in ABDC. And 26.92% of Journals considered here for analysis have A ranking in ABDC (ABDC here is a Journal Quality Ranking given by Australian Business Deans Council). Apart from top journals in Organizational Behavior, A· Journals such as Psychological Bulletin, European Journal of Marketing, Journal of Applied Psychology and others from different disciplines have been considered to provide an interdisciplinary approach to the study.

Trends and Future Directions of Research

Organizational behavior is an interdisciplinary field of study, drawing from the psychological and sociological sciences. One of the main reasons for this interdisciplinary approach is because the field of organizational behavior involves multiple levels of analysis. These levels of analysis are necessary to understand behavior within organizations and also with context to the surrounding environment, because people do not act in isolation. Employees influence their environment and are also influenced by their environment. Hence we have studies the emerging trends in the light of Individual, Group and Organizational level of analysis.

Individual Level

Personality Traits

The aim of organizational behavior and work psychology has been to understand and uncover reasons behind why individuals vary in their motivation to work. A personality trait provides a person with an inclination to behave in a certain way (Eysenck, 1985). The relationship between motivation and individual personality traits as well as situational factors is of prime importance to understand sub-elements of organizational behavior (Furnham 2009). The study of personality traits in the formative years was marked by factor-analytic approach developed by Cattell and Eysenck. The Sixteen Personality Factor Questionnaire (16PF) is a self-report personality test developed by Raymond B. Cattell, Maurice Tatsuoka and Herbert Eber Cattell in 1949. Cattell developed the 16 personality factor (16PF) questionnaire with empirical justifications and identified 16 key personality dimensions. He explained that these 16 personality types accounted for the variance in individual differences between people. Eysenck's approach towards the study of personality types was at more basic level. He identified initially two (extraversion and neuroticism) and later three or four underlying personality factors. Chronologically the next big development was the "big five" model by J.M Digman in 1990. It identified five major factors underlying human individual differences in personality. The big five factors are described as conscientiousness, neuroticism, extraversion, agreeableness, and openness. There are also some competing frameworks such as the "big three" (neuroticism, extraversion, and psychoticism) and the more pragmatic "big nine" (Hough, 1992). Trait factor-analytic theory clearly implies that personality characteristics lead towards a particular behavior across a variety of different situations. Behavior is a summation of consistent individual differences in one's personality and function of the situations. A more recent development is the concept of reciprocal determinism developed by Bandura (1986). The concept focuses on the three key sets of variables, behavior, personal qualities, and situations, which interact in a mutually reciprocating way. It provides clarity on the context regarding the understanding of personality variables. To understand individual behavior as a part of work psychology and organizational behavior, study of personality trait is an important exercise. Future research on the various possible combinations of personality traits with respect to the work environment can work wonders for practitioners ahead. Such study will help the organization understand employee behavior holistically.

Out of all the subject themes in the disciplines of Organizational Behavior and Industrial Organizational Psychology, motivation has consistently been one of the most confusing (Locke and Henne 1986, Shamir 1991). There have been a lot of motivational theories that have developed over years. Need theories (Maslow 1954, Mc. 1985), equity or social comparison theory (Adams 1965), expectancy theory (Vroom 1964), reinforcement theory (Hamner 1975), goal setting theory (Locke and Latham 1990), intrinsic motivation theory (Hackman and Oldham 1990).The problem is not with the development or addition of new theories but with universal applicability of the same. (Shamir 1991). So the need is not to add more motivational theories but to reconceptualise the existing ones. It is difficult to say what may motivate an employee as it may differ on the basis of individual characteristics. The overall aim should be to have employees identify their own welfare and wellbeing with that of the organization. (Bruce and Pepitone 1999, Milne 2007).

The basis of employee motivation has always been to hoard knowledge because of the competitive advantage that this would give to an organization. The new organizational culture shaping up however defies the older norms. It believes in sharing of knowledge and hence is progressing towards Knowledge Management. The restructuring of motivational theories in the light of knowledge management will help understand employee motivation and help organizations match individual goals with organizational goals (Milne, 2007). Future direction of research in this area can help the researchers and practitioners understand the dynamics of factors that keep employees motivated at work. This may then help organizations solve the issue of attrition rate to some extent.

Attachment Theory and Emotions at Workplace

The concept of Emotional Intelligence and management of emotions at workplace has emerged as a powerful concept in work psychology in the last decade (Zeidner, Roberts, and Matthews, 2004, Hjerto 2017). The growing importance of managing emotions at working has led to evolution of concepts like "Attachment Theory". The theory states that how attachment dynamics are directly related to positive organizational outcomes such as follower proactivity (Wu & Parker 2017, Yip 2015), ethical decision making (Chugh, Kern et al.,2014, Yip 2015), effective negotiation behavior (Lee & Thompson2011, Yip 2015), and creative problem solving (Mikulincer, Shaver et al.,2011, Yip 2015).

Whereas it also states the negative aspect that when attachment needs are not fulfilled, consequences follow. There is increased stress (Schirmer and Lopez, 2001, Yip 2015), higher reports of burnout (Littman-Ovadia, Lavy et al., 2013, Yip 2015), and increased turnover (Tziner, Oren et al., Yip 2015) among other undesired outcomes. The influence of attachment theory on organizational behavior has grown manifold.

The number of literature available for the last 5 years is much more than the preceding 25 years combined. The implementation of learnings from the theory can serve as an important tool for managing emotions at workplace and promoting healthy work relationships (Yip 2015).

Managing emotions at workplace is an emerging and challenging issue for most of the organizations. Further research on understanding the dynamics of work relationships, and its impact on employee morale and productivity, can help organizations boost employee engagement to considerable extent.

Group Level

Communication Relationship Satisfaction (CRS)

There has been a significant amount of research in the past decade trying to understand the factors affecting commitment of the employees to their organization. Research has also stated the importance of individual as well as organizational influence on organizational commitment (Angle & Perry, 1983). One of the most important reasons for lack of commitment is the disengagement of employee in important organizational decisions. The importance of communication and member7s satisfaction with communication relationships cannot be overlooked (Putti1990).

Communication Relationship Satisfaction (CRS) is the extent to which and individual seeks information regarding their job role and is informed about the organizational activities. Communication Relationship Satisfaction may be defined as the "personal satisfaction inherent in successfully communicating to someone or successfully being communicated with" (Thayer 1967). Communication Relationship Satisfaction can either be defined as an attitudinal or behavioral concept (Salancik 1977). The study of the impact of individual as well as group attitude and behavior on the concept can help us understand and resolve the issue of organizational commitment to some extent. Further research in this area can help us understand the dynamics of human communications at workplaces with respect to the job role and line of authority involved.

Leadership and Change

Scholars have had contrary views on the established leadership theories. Some of them argue that these theories fail to capture some of the construct space around how leadership is conceptualized (Dickson, Castano, Magomaeva and Den Hartog 2012; Dorfman et al 1997; Liden 2012; Psui 2007; Hiller,Sin, et al., 2019). There has been a considerable and parallel shift in the scholarly view of leadership dimensions. Earlier the simplistic one-dimension approach to leadership wherein "concern withpeople" versus "concern with production" were seen as mutually exclusive leader options (Vecchio 2002). Fieldler's (1967) construct of the Least Preferred Co-worker went through a lot of criticism for being one of its kind bi-polar views. It was said that there is an ideal combination displayed in these constructs. (Vecchio2002).Later, the leadership style defined by Kurt Lewin gained popularity. His classification of leadership includes Autocratic, Democratic, and Laissez Faire leadership (Kurt Lewis, 1974). Post 1974, there have evolved multiple takes on leadership from Charismatic Leadership, Contingency Theory of Leadership, Participative Leadership, Leader- Member Exchange Theory, to Situational Leadership.

Moving past the traditional backdrop, the emergence of value-driven leadership seems to be a growing theoretical stream of thought and research well suited for the complexity of organizational behavior in the 21st century. The shift in the style of leadership is due to the strategic restructuring witnessed by organizations. The recent emerging trend in leadership has been the Paternalistic Leadership (PL). Paternalistic Leadership is defined by genuine concern, kindness by leader for follower's holistic wellbeing. It is based on the expected or typical relationship between a parent (father) and a child. (Aycan 2006; Chen and Farh 2010;Farh and Cheng 2000; Hiller, Sin et al., 2019). Further research on these new theories of leadership, that are value driven as well as focus on the overall wellbeing of the followers, can pave the way for future workplaces. A thorough understanding and study of these emerging leadership styles will solve a lot of organization issues and grievances.

Organization Level

Organizational Identification and Corporate Social Responsibility

Organization identification is yet another emerging trend in the discipline of Organizational Behavior. It is defined as a perceived unity with the feeling of belonging to an organization (Ashton and Mael 1989; Shen 2014). The concept stems from social identity theory which suggests that people categorize themselves and others into social groups in order to develop a positive self-esteem (Shen 2014). An organization's conformity to social norms may help the employees relate and belong to the organization as well as build a positive self-esteem. (Ashforth and Mael, 1989; Dutton et al., 1994; Mathieu and Zajac, 1990; Shen 2014). Under various components of the institutional theory, the regulative and normative structures and activities forces organizations to adhere to social norms (Scott 1995, Shen 2014). Adhering to social norms and taking up Corporate Social Responsibility (CSR) helps employees identify with the organization and is considered a positive influence on various employee behaviors (Rupp et al., 2006, Shen 2014). Practitioners as well as researchers can study the correlation between Organizational Identification, Corporate Social Responsibility and employee engagement. The positive correlation can be enhanced if the factors involved in the equation are studied carefully.

Organizational Citizenship Behavior (OCB)

The term Organizational Citizenship Behavior was coined by Bateman and Oregan (1983). Though there were studies prior to coining of the term that observed employee's willingness to cooperate in the workplace (Katz and Kahn 1966, Lanndon, Venus et al., 2018). Organizational Citizenship Behavior is the work-related cooperation offered by an employee beyond his work obligations. Organizational Citizenship Behavior has been explored in various disciplines and contexts lately. Research in the domain has shown a strong relationship between individual level outcomes (e.g. managerial ratings of employee performance, reward allocation decisions, and a variety of withdrawal-related criteria) as well as organizational-level outcomes (e.g. productivity, efficiency, reduced costs, customer satisfaction, and unit-level turnover) with Organizational Citizenship Behavior (Podsakoffet al. 2009; Lanndon,Venus et al., 2018).

Further research in this area can help researchers, practitioners and policy makers understand the individual as well as group level outcomes associated with the concept. Thus understanding of Organizational Citizenship Behavior in its entirety can help resolve important issues of workplace deviance and employee commitment.

Discussion and Conclusion

There seems to be no doubt that the future of workplaces will uphold major challenges pertaining behavior at individual, group and organizational level. The study delves into research of such patterns at workplaces. The period from 1990- 2019 has been selected for study because of the significant growth rate associated with the discipline during this time. The period has observed major growth in research literature and emerging concepts such as Communication Relationship Satisfaction (CRS), Organization Citizenship Behavior (OCB), Attachment Theory and others. The vast array of topics covered under Organizational Behavior does not make it possible to study the entire discipline since 1990 in a single study. Hence the study limits to understanding and analyzing trends in Organizational Behavior since 1990. This Systematic Literature Review did not place any limitation on the publication year of journal articles; however, evolution of some significant trends (Such as Organizational Citizenship Behavior and Organizational Identification, Attachment Theory etc) in Organizational Behavior took place post 1990. There are a large number of research papers and materials available for study under the well-establish discipline of Organizational Behavior. Due to the inclusion and exclusion criteria used for the screening of the papers, there is a possibility of missing out on some important research work or papers.

This acts as one of the major limitations of the study. Researchers or practitioners can identify the papers that have not been covered under the study to further conduct a research on them. The sub-area wise (motivation, leadership etc) segregation of literature is on the basis of availability of papers used for the study. This makes it difficult to observe trends such as growth in a particular sub-area over the last decade. The limitations mentioned above can serve as a base for future research.

Despite these limitations, our review contributes to practice by focusing exclusively on individual, group and organizational behavior pertaining future of workplaces. This helps practitioners understand how recent trends in Organizational Behavior can form a basis of future challenges at workplaces. This will not only help develop competent and strategically flexible workplaces but also to develop an efficient policy framing guidelines. We hope this contribution inspires more research on developing trends in Organizational Behavior that will define future of workplaces.

Reference to this paper should be made as follows: Kalwani, S., Mahesh, J. (2020). Trends in organizational behavior: A systematic review and research directions. Journal of Business and Management, 26(1), March, 40-78. DOI: 10.6347/JBM.202003_26(1).0003.

Acknowledgment

I would like to express my gratitude towards the esteemed faculty members of Department of Management, BITS Pilani for their constant guidance and support. Also my sincere thanks to my colleagues for their support.

About the Author

Shilpi Kalwani·

Department of Management,

Birla Institute of Technology and Science,

Pilani, Rajasthan (India)

Country: India

Tel.: +91-8085681072

E-mail: [email protected]

Jayashree Mahesh

Tel.: +91-8949709082

*Corresponding author

Shilpi Kalwani is currently a Research Scholar in the Department of Management of Birla Institute of Tech. & Science. (BITS), Pilani. She has completed her MBA from ICFAI Business School, Hyderabad Campus. A full-time PhD research scholar at BITS Pilani with prior corporate experience of working as a Business Analyst with a Fortune 500 Company. A TEDx Speaker, Author, and a Life Coach due to the right blend of required skills and opportunities. Her research areas are Human Resources and Organizational Behavior.

Dr. Jayashree Mahesh is currently an Assistant Professor in the Department of Management of Birla Institute of Tech. & Science. (BITS), Pilani. She has completed her PhD from BITS-Pilani, Pilani Campus. The title of her thesis is 'Indian' Management Practices in the I.T. Sector - An Empirical Investigation. She has more than 10 years of teaching experience in BITS. She has a wide experience in teaching HR and Communication related courses. Her research interests are in the area of Management Practices, Cross Cultural Management, Indian Management and Culture. She is a member of Academy of Management and INDAM (an affiliate of AOM)

Aguinis, H., Simonsen, M. M., & Pierce, C. A. (1998). Effects of nonverbal behavior on perceptions of power bases. The Journal of Social Psychology, 138(4), 455-469.

Ashforth, B. E., Harrison, S. H., & Corley, K. G. (2008). Identification in Organizations: An examination of four fundamental questions. Journal of Management, 34(3), 325-374.

Ashkanasy, N. M., Härtel, C. E. J., & Daus, C. S. (2002). Diversity and emotion: The new frontiers in Organizational Behavior research. Journal of Management; 28(3), 307-338.

Ashkanasy, N. M., Humphrey, R. H., & Huy, Q. N. (2017). Integrating emotions and affect in theories of management. Academy of Management Review, 42(2), 175-189.

Banks, G. C., Gooty, J., Ross, R. L., Williams, C. E., & Harrington, N. T. (2018). Construct redundancy in leader behaviors: A review and agenda for the future. The Leadership Quarterly, 29(1), 236-251.

Bolino, M. C., Kacmar, K. M., Turnley, W. H., & Gilstrap, J. B. (2008). A multi-level review of impression management motives and behaviors. Journal of Management, 34(6), 1080-1109.

Bonaccio, S., O'Reilly, J., O'Sullivan, S. L., and Chiocchio, F. (2016). Nonverbal behavior and communication in the workplace. Journal of Management, 42(5), 1044-1074.

Brown, A. D., & Starkey, K. (1994). The effect of organizational culture on communication and information. Journal of Management Studies, 31(6), 807-828.

Bruce J. Avolio; William L. Gardner (2005). Authentic leadership development: Getting to the root of positive forms of leadership. The Leadership Quarterly, 16 (3), 315-338

Carnes, C. M., Xu, K., Sirmon, D. G., & Karadag, R. (2019). How competitive action mediates the resource slack-performance relationship: A meta-analytic approach. Journal of Management Studies, 56(1), 57-90.

Carnes, C. M., Xu, K., Sirmon, D. G., & Karadag, R. (2018). How competitive action mediates the resource slack-performance relationship: A meta-analytic approach. Journal of Management Studies, 56(1), 57-90.

Cascio, W. F., and Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3(1), 349-375.

Chiaburu, D. S., & Harrison, D. A. (2008). Do peers make the place? Conceptual synthesis and meta-analysis of coworker effects on perceptions, attitudes, OCBs, and performance. Journal of Applied Psychology, 93(5), 1082-1103.

Clark, M. A., Robertson, M. M., & Young, S. (2018). "I feel your pain": A critical review of organizational research on empathy. Journal of Organizational Behavior, 40(2), 166-192

Cooper, H. M. (2003). Editorial. Psychological Bulletin, 129(1), 3-9.

Donia, M. B. L., Johns, G., Raja, U., & Khalil Ben Ayed, A. (2017). Getting credit for OCBs: potential costs of being a good actor vs. a good soldier. European Journal of Work and Organizational Psychology, 27(2), 188-203.

Eldor, L. (2016). Work engagement. Human Resource Development Review, 15(3), 317-339.

Ferris, G. R., Ellen, B. P., McAllister, C. P., & Maher, L. P. (2019). Reorganizing Organizational Politics research: A review of the literature and identification of future research directions. Annual Review of Organizational Psychology and Organizational Behavior, 6(1), 299-323.

Furnham, A., Eracleous, A., & Chamorro-Premuzic, T. (2009). Personality, motivation and job satisfaction: Hertzberg meets the Big Five. Journal of Managerial Psychology, 24 (8), 765-779

Götz, M., Bollmann, G., and O'Boyle, E. H. (2018). Contextual undertow of workplace deviance by and within units: A systematic review. Small Group Research, 50(1), 188-203

Hatch, M. J., & Schultz, M. (1997). Relations between organizational culture, identity and image. European Journal of Marketing, 31(5-6), 356-365.

Hiller, N. J., Sin, H. P., Ponnapalli, A. R., & Ozgen, S. (2019). Benevolence and authority as weirdly unfamiliar: A multi-language meta-analysis of paternalistic leadership behaviors from 152 studies. The Leadership Quarterly, 30(1), 165-184.

Hjerto, K. B. (2017). Burning hearts in conflict: new perspectives on the intragroup conflict and team effectiveness relationship. International Journal of Conflict Management, 28(4), 536-536.

Knight, C., Patterson, M., & Dawson, J. (2016). Building work engagement: A systematic review and meta-analysis investigating the effectiveness of work engagement interventions. Journal of Organizational Behavior, 38(6), 792-812.

Kudret, S., Erdogan, B., & Bauer, T. N. (2019). Self-monitoring personality trait at work: An integrative narrative review and future research directions. Journal of Organizational Behavior, 40(2), 193-208.

Locke, E. A., & Latham, G. P. (1990). A Theory of Goal Setting & Task Performance. Prentice-Hall, Inc.

Luthans, F., & Youssef, C. M. (2007). Emerging positive organizational behavior. Journal of Management, 33(3), 321-349.

Maslow, A. H. (1943). A theory of human motivation. Psychological Review, 50(4), 370.

Mathieu, J., Maynard, M. T., Rapp, T., & Gilson, L. (2008). Team effectiveness 1997-2007: A review of recent advancements and a glimpse into the future. Journal of Management, 34(3), 410-476.

Pandey, J. (2019). Factors affecting job performance: An integrative review of literature. Management Research Review, 42(2), 263-289.

Putti, J. M., Aryee, S., and Phua, J. (1990). Communication relationship satisfaction and organizational commitment. Group & Organization Studies, 15(1), 44-52.

Rhoades, L., and Eisenberger, R. (2002). Perceived organizational support: A review of the literature. Journal of Applied Psychology, 87(4), 698-714.

Shen, J., & Benson, J. (2016). When CSR is a social norm. Journal of Management, 42(6), 1723-1746.

Smith, M. B., Hill, A. D., Wallace, J. C., Recendes, T., & Judge, T. A. (2018). Upsides to dark and downsides to bright personality: A multidomain review and future research agenda. Journal of Management, 44(1), 191-217.

Swab, R. G., & Johnson, P. D. (2019). Steel sharpens steel: A review of multilevel competition and competitiveness in organizations. Journal of Organizational Behavior, 40(2), 147-165

Upasna A. Agarwal, Vishal Gupta, (2018). Relationships between job characteristics, work engagement, conscientiousness and managers' turnover intentions: A moderated-mediation analysis. Personnel Review, 47(2), 353-377

Weikamp, J. G., and Göritz, A.S. (2016). Organizational citizenship behavior and job satisfaction: The impact of occupational future time perspective. Human Relations, 69(11), 2091-2115.

Youssef, C. M., and Luthans, F. (2007). Positive organizational behavior in the workplace. Journal of Management, 33(5), 774-800.

Zeidner, M., Matthews, G., & Roberts, R. (2004). Emotional intelligence in the workplace: A critical review. Applied Psychology, 33(3), 371-399.

(ProQuest: Appendix omitted.)

You have requested "on-the-fly" machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Show full disclaimer

Neither ProQuest nor its licensors make any representations or warranties with respect to the translations. The translations are automatically generated "AS IS" and "AS AVAILABLE" and are not retained in our systems. PROQUEST AND ITS LICENSORS SPECIFICALLY DISCLAIM ANY AND ALL EXPRESS OR IMPLIED WARRANTIES, INCLUDING WITHOUT LIMITATION, ANY WARRANTIES FOR AVAILABILITY, ACCURACY, TIMELINESS, COMPLETENESS, NON-INFRINGMENT, MERCHANTABILITY OR FITNESS FOR A PARTICULAR PURPOSE. Your use of the translations is subject to all use restrictions contained in your Electronic Products License Agreement and by using the translation functionality you agree to forgo any and all claims against ProQuest or its licensors for your use of the translation functionality and any output derived there from. Hide full disclaimer

© 2020. This work is published under https://creativecommons.org/licenses/by-nc/4.0/ (the “License”).  Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.

Purpose - The purpose of this paper is to present a step-by-step guide to facilitate understanding of emerging trends in the discipline of Organizational Behavior using the technique of Systematic Literature Review. Method - Literature review is done by systematically collecting the existing literature over the period of 1990-2019. The literature is categorized according to the Journal Name and Ranking, Database, and Geographical Distribution (country wise). Literature is also categorized on the basis of type of study (empirical/conceptual), variables used, scales used, sample studies and sub area of study (Leadership/Motivation etc). This classification can serve as a base for researchers who wish to conduct meta-analysis on emerging trends in Organizational Behavior. Findings - A disciplined screening process resulted in 81 relevant research papers appropriate for the study. These papers explain the emerging trends in the discipline since 1990. Limitations - Due to the vast areas and sub-areas covered under Organizational Behavior, it is not possible to study the entire discipline since 1990 in a single study. Hence the study only focuses on relevant and emerging trends in Organizational Behavior. Implications - The study aims to fill the gap of unavailability of a structured systematic literature review in the discipline of Organizational Behaviour. This may serve as an important source of information for Academicians, Practitioners. The study postulates new avenues for future research. Originality - The study contributes to the methodology for conducting Systematic Literature Reviews in the field of management, specifically in Organizational Behaviour. It highlights an effective method for mapping out thematically, and viewing holistically, emerging research trends.

Suggested sources

• About ProQuest
• Terms of Use
• Privacy Policy
• Cookie Policy

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

• View all journals
• Explore content
• About the journal
• Publish with us
• Sign up for alerts
• Published: 27 January 2022

The future of human behaviour research

• Janet M. Box-Steffensmeier 1 ,
• Jean Burgess 2 , 3 ,
• Maurizio Corbetta 4 , 5 ,
• Kate Crawford 6 , 7 , 8 ,
• Esther Duflo 9 ,
• Laurel Fogarty 10 ,
• Alison Gopnik 11 ,
• Sari Hanafi 12 ,
• Mario Herrero 13 ,
• Ying-yi Hong 14 ,
• Yasuko Kameyama 15 ,
• Tatia M. C. Lee 16 ,
• Gabriel M. Leung 17 , 18 ,
• Daniel S. Nagin 19 ,
• Anna C. Nobre 20 , 21 ,
• Merete Nordentoft 22 , 23 ,
• Aysu Okbay 24 ,
• Andrew Perfors 25 ,
• Laura M. Rival 26 ,
• Cassidy R. Sugimoto 27 ,
• Bertil Tungodden 28 &
• Claudia Wagner 29 , 30 , 31  

Nature Human Behaviour volume  6 ,  pages 15–24 ( 2022 ) Cite this article

64k Accesses

34 Citations

185 Altmetric

Metrics details

Human behaviour is complex and multifaceted, and is studied by a broad range of disciplines across the social and natural sciences. To mark our 5th anniversary, we asked leading scientists in some of the key disciplines that we cover to share their vision of the future of research in their disciplines. Our contributors underscore how important it is to broaden the scope of their disciplines to increase ecological validity and diversity of representation, in order to address pressing societal challenges that range from new technologies, modes of interaction and sociopolitical upheaval to disease, poverty, hunger, inequality and climate change. Taken together, these contributions highlight how achieving progress in each discipline will require incorporating insights and methods from others, breaking down disciplinary silos.

Genuine progress in understanding human behaviour can only be achieved through a multidisciplinary community effort. Five years after the launch of Nature Human Behaviour , twenty-two leading experts in some of the core disciplines within the journal’s scope share their views on pressing open questions and new directions in their disciplines. Their visions provide rich insight into the future of research on human behaviour.

Artificial intelligence

Kate Crawford

Much has changed in artificial intelligence since a small group of mathematicians and scientists gathered at Dartmouth in 1956 to brainstorm how machines could simulate cognition. Many of the domains that those men discussed — such as neural networks and natural language processing — remain core elements of the field today. But what they did not address was the far-reaching social, political, legal and ecological effects of building these systems into everyday life: it was outside their disciplinary view.

Since the mid-2000s, artificial intelligence (AI) has rapidly expanded as a field in academia and as an industry, and now a handful of powerful technology corporations deploy these systems at a planetary scale. There have been extraordinary technical innovations, from real-time language translation to predicting the 3D structures of proteins 1 , 2 . But the biggest challenges remain fundamentally social and political: how AI is widening power asymmetries and wealth inequality, and creating forms of harm that need to be prioritized, remedied and regulated.

The most urgent work facing the field today is to research and remediate the costs and consequences of AI. This requires a deeper sociotechnical approach that can contend with the complex effect of AI on societies and ecologies. Although there has been important work done on algorithmic fairness in recent years 3 , 4 , not enough has been done to address how training data fundamentally skew how AI models interpret the world from the outset. Second, we need to address the human costs of AI, which range from discrimination and misinformation to the widespread reliance on underpaid labourers (such as the crowd-workers who train AI systems for as little as US $2 per hour) 5 . Third, there must be a commitment to reversing the environmental costs of AI, including the exceptionally high energy consumption of the current large computational models, and the carbon footprint of building and operating modern tensor processing hardware 6 . Finally, we need strong regulatory and policy frameworks, expanding on the EU’s draft AI Act of 2021.

By building a more interdisciplinary and inclusive AI field, and developing a more rigorous account of the full impacts of AI, we give engineers and regulators alike the tools that they need to make these systems more sustainable, equitable and just.

Kate Crawford is Research Professor at the Annenberg School, University of Southern California, Los Angeles, CA, USA; Senior Principal Researcher at Microsoft Research New York, New York, NY, USA; and the Inaugural Visiting Chair of AI and Justice at the École Normale Supérieure, Paris, France.

Anthropology

Laura M. Rival

The field of anthropology faces fundamental questions about its capacity to intervene more effectively in political debates. How can we use the knowledge that we already have to heal the imagined whole while keeping people in synchrony with each other and with the world they aspire to create for themselves and others?

The economic systems that sustain modern life have produced pernicious waste cultures. Globalization has accelerated planetary degradation and global warming through the continuous release of toxic waste. Every day, like millions of others, I dutifully clean and prepare my waste for recycling. I know it is no more than a transitory measure geared to grant manufacturers time to adjust and adapt. Reports that most waste will not be recycled, but dumped or burned, upset me deeply. How can anthropology remain a critical project in the face of such orchestrated cynicism, bad faith and indifference? How should anthropologists deploy their skills and bring a sense of shared responsibility to the task of replenishing the collective will?

To help to find answers to these questions, anthropologists need to radically rethink the ways in which we describe the processes and relations that tie communities to their environments. The extinction of experience (loss of direct contact with nature) that humankind currently suffers is massive, but not irreversible. New forms of storytelling have successfully challenged modernist myths, particularly their homophonic promises 7 . But there remain persistent challenges, such as the seductive and rampant power of one-size-fits-all progress, and the actions of elites, who thrive on emulation, and in doing so fuel run-away consumerism.

To combat these challenges, I simply reassert that ‘nature’ is far from having outlasted its historical utility. Anthropologists must join forces and reanimate their common exploration of the immense possibilities contained in human bodies and minds. No matter how overlooked or marginalized, these natural potentials hold the key to what keeps life going.

Laura M. Rival is Professor of Anthropology of Nature, Society and Development, ODID and SAME, University of Oxford, Oxford, UK .

Communication and media studies

Jean Burgess

The communication and media studies field has historically been animated by technological change. In the process, it has needed to navigate fundamental tensions: communication can be understood as both transmission (of information), and as (social) ritual 8 ; relatedly, media can be understood as both technology and as culture 9 .

The most important technological change over the past decade has been the ‘platformization’ 10 of the media environment. Large digital platforms owned by the world’s most powerful technology companies have come to have an outsized and transformative role in the transmission (distribution) of information, and in mediating social practices (whether major events or intimate daily routines). In response, digital methods have transformed the field. For example, advances in computational techniques enabled researchers to study patterns of communication on social media, leading to disciplinary trends such as the quantitative description of ‘hashtag publics’ in the mid-2010s 11 .

Platforms’ uses of data, algorithms and automation for personalization, content moderation and governance constitute a further major shift, giving rise to new methods (such as algorithmic audits) that go well beyond quantitative description 12 . But platform companies have had a patchy — at times hostile — relationship to independent research into their societal role, leading to data lockouts and even public attacks on researchers. It is important in the interests of public oversight and open science that we coordinate responses to such attempts to suppress research 13 , 14 .

As these processes of digital transformation continue, new connections between the humanities and technical disciplines will be necessary, giving rise to a new wave of methodological innovation. This next phase will also require more hybrid (qualitative and quantitative; computational and critical) methods 15 , not only to get around platform lockouts but also to ensure more careful attention is paid to how the new media technologies are used and experienced in everyday life. Here, innovative approaches such as the use of data donations can both aid the ‘platform observability’ 16 that is essential to accountability, and ensure that our research involves the perspectives of diverse audiences.

Jean Burgess is Professor of Digital Media at the School of Communication and Digital Media Research Centre (DMRC), Queensland University of Technology, Brisbane, Queensland Australia; and Associate Director at the Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADM+S), Melbourne, Victoria, Australia .

Computational social science

Claudia Wagner

Computational social science has emerged as a discipline that leverages computational methods and new technologies to collect, model and analyse digital behavioural data in natural environments or in large-scale designed experiments, and combine them with other data sources (such as survey data).

While the community made critical progress in enhancing our understanding about empirical phenomena such as the spread of misinformation 17 and the role of algorithms in curating misinformation 18 , it has focused less on questions about the quality and accessibility of data, the validity, reliability and reusability of measurements, the potential consequences of measurements and the connection between data, measurement and theory.

I see the following opportunities to address these issues.

First, we need to establish privacy-preserving, shared data infrastructures that collect and triangulate survey data with scientifically motivated organic or designed observational data from diverse populations 19 . For example, longitudinal online panels in which participants allow researchers to track their web browsing behaviour and link these traces to their survey answers will not only facilitate substantive research on societal questions but also enable methodological research (for example, on the quality of different data sources and measurement models), and contribute to the reproducibility of computational social science research.

Second, best practices and scientific infrastructures are needed for supporting the development, evaluation and re-use of measurements and the critical reflection on potentially harmful consequences of measurements 20 . Social scientists have developed such best practices and infrastructural support for survey measurements to avoid using instruments for which the validity is unclear or even questionable, and to support the re-usability of survey scales. I believe that practices from survey methodology and other domains, such as the medical industry, can inform our thinking here.

Finally, the fusion of algorithmic and human behaviour invites us to rethink the various ways in which data, measurements and social theories can be connected 20 . For example, product recommendations that users receive are based on measurements of users’ interests and needs: however, users and measurements are not only influenced by those recommendations, but also influence them in turn. As a community we need to develop research designs and environments that help us to systematically enhance our understanding of those feedback loops.

Claudia Wagner is Head of Computational Social Science Department at GESIS – Leibniz Institute for the Social Sciences, Köln, Germany; Professor for Applied Computational Social Sciences at RWTH Aachen University, Aachen, Germany; and External Faculty Member of the Complexity Science Hub, Vienna, Austria .

Criminology

Daniel S. Nagin

Disciplinary silos in path-breaking science are disappearing. Criminology has had a longstanding tradition of interdisciplinarity, but mostly in the form of an uneasy truce of research from different disciplines appearing side-by-side in leading journals — a scholarly form of parallel play. In the future, this must change because the big unsolved challenges in criminology will require cooperation among all of the social and behavioural sciences.

These challenges include formally merging the macro-level themes emphasized by sociologists with the micro-, individual-level themes emphasized by psychologists and economists. Initial steps have been made by economists who apply game theory to model crime-relevant social interactions, but much remains to be done in building models that explain the formation and destruction of social trust, collective efficacy and norms, as they relate to legal definitions of criminal behaviour.

A second opportunity concerns the longstanding focus of criminology on crimes involving the physical taking of property and interpersonal physical violence. These crimes are still with us, but — as the daily news regularly reports — the internet has opened up broad new frontiers for crime that allow for thefts of property and identities at a distance, forms of extortion and human trafficking at a massive scale (often involving untraceable transactions using financial vehicles such as bitcoin) and interpersonal violence without physical contact. This is a new and largely unexplored frontier for criminological research that criminologists should dive into in collaboration with computer scientists who already are beginning to troll these virgin scholarly waters.

The final opportunity I will note also involves drawing from computer science, the primary home of what has come to be called machine learning. It is important that new generations of criminologists become proficient with machine learning methods and also collaborate with its creators. Machine learning and related statistical methods have wide applicability in both the traditional domains of criminological research and new frontiers. These include the use of prediction tools in criminal justice decision-making, which can aid in crime detection, and the prevention and measuring of crime both online and offline, but also have important implications for equity and fairness due to their consequential nature.

Daniel S. Nagin is Teresa and H. John Heinz III University Professor of Public Policy and Statistics at the Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA .

Behavioural economics

Bertil Tungodden

Behavioural and experimental economics have transformed the field of economics by integrating irrationality and nonselfish motivation in the study of human behaviour and social interaction. A richer foundation of human behaviour has opened many new exciting research avenues, and I here highlight three that I find particularly promising.

Economists have typically assumed that preferences are fixed and stable, but a growing literature, combining field and laboratory experimental approaches, has provided novel evidence on how the social environment shapes our moral and selfish preferences. It has been shown that prosocial role models make people less selfish 21 , that early-childhood education affects the fairness views of children 22 and that grit can be fostered in the correct classroom environment 23 . Such insights are important for understanding how exposure to different institutions and socialization processes influence the intergenerational transmission of preferences, but much more work is needed to gain systematic and robust evidence on the malleability of the many dimensions that shape human behaviour.

The moral mind is an important determinant of human behaviour, but our understanding of the complexity of moral motivation is still in its infancy. A growing literature, using an impartial spectator design in which study participants make consequential choices for others, has shown that people often disagree on what is morally acceptable. An important example is how people differ in their view of what is a fair inequality, ranging from the libertarian fairness view to the strict egalitarian fairness view 24 , 25 . An exciting question for future research is whether such moral differences reflect a concern for other moral values, such as freedom, or irrational considerations.

A third exciting development in behavioural and experimental economics is the growing set of global studies on the foundations of human behaviour 26 , 27 . It speaks to the major concern in the social sciences that our evidence is unrepresentative and largely based on studies with samples from Western, educated, industrialized, rich and democratic societies 28 . The increased availability of infrastructure for implementing large-scale experimental data collections and methodological advances carry promise that behavioural and experimental economic research will broaden our understanding of the foundations of human behaviour in the coming years.

Bertil Tungodden is Professor and Scientific Director of the Centre of Excellence FAIR at NHH Norwegian School of Economics, Bergen, Norway .

Development economics

Esther Duflo

The past three decades have been a wonderful time for development economics. The number of scholars, the number of publications and the visibility of the work has dramatically increased. Development economists think about education, health, firm growth, mental health, climate, democratic rules and much more. No topic seems off limits!

This progress is intimately connected with the explosion of the use of randomized controlled trials (RCTs) and, more generally, with the embrace of careful causal identification. RCTs have markedly transformed development economics and made it the field that it is today.

The past three decades (until the COVID-19 crisis) have also been very good for improving the circumstances of low-income people around the world: poverty rates have fallen; school enrolment has increased; and maternal and infant mortality has been halved. Although I would not dare imply that the two trends are causally related, one of the reasons for these improvements in the quality of life — even in countries where economic growth has been slow — is the greater focus on pragmatic solutions to the fundamental problems faced by people with few resources. In many countries, development economics researchers (particularly those working with RCTs) have been closely involved with policy-makers, helping them to develop, implement and test these solutions. In turn, this involvement has been a fertile ground for new questions, which have enriched the field.

I imagine future change will, once again, come from an unexpected place. One possible driver of innovation will come from this meeting between the requirements of policy and the intellectual ambition of researchers. This means that the new challenges of our planet must (and will) become the new challenges of development economics. Those challenges are, I believe, quite clear: rethinking social protection to be better prepared to face risks such as the COVID-19 pandemic; mitigating, but unfortunately also adapting to, climate changes; curbing pollution; and addressing gender, racial and ethnic inequality.

To address these critical issues, I believe the field will continue to rely on RCTs, but also start using more creatively (descriptively or in combination with RCTs) the huge amount of data that is increasingly available as governments, even in poor countries, digitize their operations. I cannot wait to be surprised by what comes next.

Esther Duflo is The Abdul Latif Jameel Professor of Poverty Alleviation and Development Economics at the Department of Economics, Massachusetts Institute of Technology, Cambridge MA, USA; and cofounder and codirector of the Abdul Latif Jameel Poverty Action Lab (J-PAL) .

Political science

Janet M. Box-Steffensmeier

Political science remains one of the most pluralistic disciplines and we are on the move towards engaged pluralism. This takes us beyond mere tolerance to true, sincere engagement across methods, methodologies, theories and even disciplinary boundaries. Engaged pluralism means doing the hard work of understanding our own research from the multiple perspectives of others.

More data are being collected on human behaviour than ever before and our advances in methods better address the inherent interdependencies of the data across time, space and context. There are new ways to measure human behaviour via text, image and video. Data creation can even go back in time. All these advancements bode well for the potential to better understand and predict behaviour. This ‘data century’ and ‘golden age of methods’ also hold the promise to bridge, not divide, political science, provided that there is engaged methodological pluralism. Qualitative methods provide unique insights and perspectives when joined with quantitative methods, as does a broader conception of the methodologies underlying and launching our research.

I remain a strong proponent of leveraging dynamics and focusing on heterogeneity in our research questions to advance our disciplines. Doing so brings in an explicit perspective of comparison around similarity and difference. Our questions, hypotheses and theories are often made more compelling when considering the dynamics and heterogeneity that emerges when thinking about time and change.

Striving for a better understanding of gender, race and ethnicity is driving deeper and fuller understandings of central questions in the social sciences. The diversity of the research teams themselves across gender, sex, race, ethnicity, first-generation status, religion, ideology, partisanship and cultures also pushes advancement. One area that we need to better support is career diversity. Supporting careers in government, non-profit organizations and industry, as well as academia, for graduate students will enhance our disciplines and accelerate the production of knowledge that changes the world.

Engaged pluralism remains a foundational key to advancement in political science. Engaged pluralism supports critical diversity, equity and inclusion work, strengthens political scientists’ commitment to democratic principles, and encourages civic engagement more broadly. It is an exciting time to be a social scientist.

Janet M. Box-Steffensmeier is Vernal Riffe Professor of Political Science, Professor of Sociology (courtesy) and Distinguished University Professor at the Department of Political Science, Ohio State University, Columbus OH, USA; and immediate past President of the American Political Science Association .

Cognitive psychology

Andrew Perfors

Cognitive psychology excels at understanding questions whose problem-space is well-defined, with precisely specified theories that transparently map onto thoroughly explored experimental paradigms. That means there is a vast gulf between the current state of the art and the richness and complexity of cognition in the real world. The most exciting open questions are about how to bridge that gap without sacrificing rigour and precision. This requires at least three changes.

First, we must move beyond typical experiments. Stimuli must become less artificial, with a naturalistic structure and distribution. Similarly, tasks must become more ecologically valid: less isolated, with more uncertainty, embedded in natural situations and over different time-scales.

Second, we must move beyond considering individuals in isolation. We live in a rich social world and an environment that is heavily shaped by other humans. How we think, learn and act is deeply affected by how other people think and interact with us; cognitive science needs to engage with this more.

Third, we must move beyond the metaphor of humans as computers. Our cognition is deeply intertwined with our emotions, motivations and senses. These are more than just parameters in our minds; they have a complexity and logic of their own, and interact in nontrivial ways with each other and more typical cognitive domains such as learning, reasoning and acting.

How do we make progress on these steps? We need reliable real-world data that are comparable across people and situations, reflect the cognitive processes involved and are not changed by measurement. Technology may help us with this, but challenges surrounding privacy and data quality are huge. Our models and analytic approaches must also grow in complexity — commensurate with the growth in problem and data complexity — without becoming intractable or losing their explanatory power.

Success in this endeavour calls for a different kind of science that is not centred around individual laboratories or small stand-alone projects. The biggest advances will be achieved on the basis of large, rich, real-world datasets from different populations, created and analysed in collaborative teams that span multiple domains, fields and approaches. This requires incentive structures that reward team-focused, slower science and prioritize the systematic construction of reliable knowledge over splashy findings.

Andrew Perfors is Associate Professor and Deputy Director of the Complex Human Data Hub, University of Melbourne, Melbourne, Victoria, Australia .

Cultural and social psychology

Ying-yi Hong

I am writing this at an exceptional moment in human history. For two years, the world has faced the COVID-19 pandemic and there is no end in sight. Cultural and social psychology are uniquely equipped to understand the COVID-19 pandemic, specifically examining how people, communities and countries are dealing with this extreme global crisis — especially at a time when many parts of the world are already experiencing geopolitical upheaval.

During the pandemic, and across different nations and regions, a diverse set of strategies (and subsequent levels of effectiveness) were used to curb the spread of the disease. In the first year of the pandemic, research revealed that some cultural worldviews — such as collectivism (versus individualism) and tight (versus loose) norms — were positively associated with compliance with COVID-19 preventive measures as well as with fewer infections and deaths 29 , 30 . These worldview differences arguably stem from different perspectives on abiding to social norms and prioritizing the collective welfare over an individual’s autonomy and liberty. Although in the short term it seems that a collectivist or tight worldview has been advantageous, it is unclear whether this will remain the case in the long term. Cultural worldviews are ‘tools’ that individuals use to decipher the meaning of their environment, and are dynamic rather than static 31 . Future research can examine how cultural worldviews and global threats co-evolve.

The pandemic has also amplified the demarcation of national, political and other major social categories. On the one hand, identification with some groups (for example, national identity) was found to increase in-group care and thus a greater willingness to sacrifice personal autonomy to comply with COVID-19 measures 32 . On the other hand, identification with other groups (for example, political parties) widened the ideological divide between groups and drove opposing behaviours towards COVID-19 measures and health outcomes 33 . As we are facing climate change and other pressing global challenges, understanding the role of social identities and how they affect worldviews, cognition and behaviour will be vital. How can we foster more inclusive (versus exclusive) identities that can unite rather than divide people and nations?

Ying-yi Hong is Choh-Ming Li Professor of Management and Associate Dean (Research) at the Department of Management, The Chinese University of Hong Kong, Hong Kong Special Administrative Region, China .

Developmental psychology

Alison Gopnik

Developmental psychology is similar to the kind of book or band that, paradoxically, everyone agrees is underrated. On the one hand, children and the people who care for them are often undervalued and overlooked. On the other, since Piaget, developmental research has tackled some of the most profound philosophical questions about every kind of human behaviour. This will only continue into the future.

Psychologists increasingly recognize that the minds of children are not just a waystation or an incomplete version of adult minds. Instead, childhood is a distinct evolutionarily adaptive phase of an organism, with its own characteristic cognitions, emotions and motivations. These characteristics of childhood reflect a different agenda than those of the adult mind — a drive to explore rather than exploit. This drive comes with motivations such as curiosity, emotions such as wonder and surprise and remarkable cognitive learning capacities. A new flood of research on curiosity, for example, shows that children actively seek out the information that will help them to learn the most.

The example of curiosity also reflects the exciting prospects for interdisciplinary developmental science. Machine learning is increasingly using children’s learning as a model, and developmental psychologists are developing more precise models as a result. Curiosity-based AI can illuminate both human and machine intelligence. Collaborations with biology are also exciting: for example, in work on evolutionary ‘life history’ explanations of the effects of adverse experiences on later life, and new research on plasticity and sensitive periods in neuroscience. Finally, children are at the cutting edge of culture, and developmental psychologists increasingly conduct a much wider range of cross-cultural studies.

But perhaps the most important development is that policy-makers are finally starting to realize just how crucial children are to important social issues. Developmental science has shown that providing children with the care that they need can decrease poverty, inequality, disease and violence. But that care has been largely invisible to policy-makers and politicians. Understanding scientifically how caregiving works and how to support it more effectively will be the most important challenge for developmental psychology in the next century.

Alison Gopnik is Professor of Psychology and Affiliate Professor of Philosophy at the Department of Psychology, University of California at Berkeley, Berkeley, CA, USA .

Science of science

Cassidy R. Sugimoto

Why study science? The goal of science is to advance knowledge to improve the human condition. It is, therefore, essential that we understand how science operates to maximize efficiency and social good. The metasciences are fields that are devoted to understanding the scientific enterprise. These fields are distinguished by differing epistemologies embedded in their names: the philosophy, history and sociology of science represent canonical metasciences that use theories and methods from their mother disciplines. The ‘science of science’ uses empirical approaches to understand the mechanisms of science. As mid-twentieth-century science historian Derek de Solla Price observed, science of science allows us to “turn the tools of science on science itself” 34 .

Contemporary questions in the science of science investigate, inter alia, catalysts of discovery and innovation, consequences of increased access to scientific information, role of teams in knowledge creation and the implications of social stratification on the scientific enterprise. Investigation of these issues require triangulation of data and integration across the metasciences, to generate robust theories, model on valid assumptions and interpret results appropriately. Community-owned infrastructure and collective venues for communication are essential to achieve these goals. The construction of large-scale science observatories, for example, would provide an opportunity to capture the rapidly expanding dataverse, collaborate and share data, and provide nimble translations of data into information for policy-makers and the scientific community.

The topical foci of the field are also undergoing rapid transformation. The expansion of datasets enables researchers to analyse a fuller population, rather than a narrow sample that favours particular communities. The field has moved from an elitist focus on ‘success’ and ‘impact’ to a more-inclusive and prosopographical perspective. Conversations have shifted from citations, impact factors and h -indices towards responsible indicators, diversity and broader impacts. Instead of asking ‘how can we predict the next Nobel prize winner?’, we can ask ‘what are the consequences of attrition in the scientific workforce?’. The turn towards contextualized measurements that use more inclusive datasets to understand the entire system of science places the science of science in a ripe position to inform policy and propel us towards a more innovative and equitable future.

Cassidy R. Sugimoto is Professor and Tom and Marie Patton School Chair, School of Public Policy, Georgia Institute of Technology, Atlanta, GA, USA .

Sari Hanafi

In the past few years, we have been living through times in which reasonable debate has become impossible. Demagogical times are driven by the vertiginous rise of populism and authoritarianism, which we saw in the triumph of Donald Trump in the USA and numerous other populist or authoritarian leaders in many places around the globe. There are some pressing tasks for sociology that can be, in brief, reduced to three.

First, fostering democracy and the democratization process requires disentangling the constitutive values that compose the liberal political project (personal liberty, equality, moral autonomy and multiculturalism) to address the question of social justice and to accommodate the surge in people’s religiosity in many parts in the globe.

Second, the struggle for the environment is inseparable from our choice of political economy, and from the nature of our desired economic system — and these connections between human beings and nature have never been as intimate as they are now. Past decades saw rapid growth that was based on assumptions of the long-term stability of the fixed costs of raw materials and energy. But this is no longer the case. More recently, financial speculation intensified and profits shrunk, generating distributional conflicts between workers, management, owners and tax authorities. The nature of our economic system is now in acute crisis.

The answer lies in a consciously slow-growing new economy that incorporates the biophysical foundations of economics into its functioning mechanisms. Society and nature cannot continue to be perceived each as differentiated into separate compartments. The spheres of nature, culture, politics, social, economy and religion are indeed traversed by common logics that allow a given society to be encompassed in its totality, exactly as Marcel Mauss 35 did. The logic of power and interests embodied in ‘ Homo economicus ’ prevents us from being able to see the potentiality of human beings to cultivate gift-giving practices as an anthropological foundation innate within social relationships.

Third, there are serious social effects of digitalized forms of labour and the trend of replacing labour with an automaton. Even if digital labour partially reduces the unemployment rate, the lack of social protection for digital labourers would have tremendous effects on future generations.

In brief, it is time to connect sociology to moral and political philosophy to address fundamentally post-COVID-19 challenges.

Sari Hanafi is Professor of Sociology at the American University of Beirut, Beirut, Lebanon; and President of the International Sociological Association .

Environmental studies (climate change)

Yasuko Kameyama

Climate change has been discussed for more than 40 years as a multilateral issue that poses a great threat to humankind and ecosystems. Unfortunately, we are still talking about the same issue today. Why can’t we solve this problem, even though scientists pointed out its importance and urgency so many years ago?

These past years have been spent trying to prove the causal relationship between an increase in greenhouse gas concentrations, global temperature rise and various extreme weather events, as well as developing and disseminating technologies needed to reduce emissions. All of these tasks have been handled by experts in the field. At the same time, the general public invested little time in this movement, probably expecting that the problem would be solved by experts and policy-makers. But that has not been the case. No matter how much scientists have emphasized the crisis of climate change or how many clean energy technologies engineers have developed, society has resisted making the necessary changes. Now, the chances of keeping the temperature rise within 1.5 °C of pre-industrial levels — the goal necessary to minimize the effects of climate change — are diminishing.

We seem to finally be realizing the importance of social scientific knowledge. People need to take scientific information seriously for clean technology to be quickly diffused. Companies are more interested in investing in newer technology and product development when they know that their products will sell. Because environmental problems are caused by human activity, research on human behaviour is indispensable in solving these problems.

Reports by the Intergovernmental Panel on Climate Change (IPCC) have not devoted many pages to the areas of human awareness and behaviour ( https://www.ipcc.ch/ ). The IPCC’s Third Working Group, which deals with mitigation measures, has partially spotlighted research on institutions, as well as on concepts such as fairness. People’s perception of climate change and the relationship between perception and behavioural change differ depending on the country, societal structure and culture. Additional studies in these areas are required and, for that purpose, more studies from regions such as Asia, Africa and South America, which are underrepresented in terms of the number of academic publications, are particularly needed.

Yasuko Kameyama is Director, Social Systems Division, National Institute for Environmental Studies, Tsukuba, Japan .

Sustainability (food systems)

Mario Herrero

The food system is in dire straits. Food demand is unprecedented, while malnutrition in all its forms (obesity, undernutrition and micronutrient deficiencies) is rampant. Environmental degradation is pervasive and increasing, and if it continues, the comfort zone for humanity and ecosystems to thrive will be seriously compromised. From bruises and shapes to sell-by dates, we tend to find many reasons to exclude perfectly edible food from our plates, whereas in other cases not enough food reaches hungry mouths owing to farming methods, pests and lack of adequate storage. These types of inequalities are common and — together with inherent perverse incentives that maintain the status quo of how we produce, consume and waste increasingly cheap and processed food — they are launching us towards a disaster.

We are banking on a substantial transformation of the food system to solve this conundrum. Modifying food consumption and waste patterns are central to the plan for achieving healthier diets, while increasing the sustainability of our food system. This is also an attractive policy proposition, as it could lead to gains in several sectors. Noncommunicable diseases such as obesity, diabetes and heart disease could decline, while reducing the effects of climate change, deforestation, excessive water withdrawals and biodiversity loss, and their enormous associated — and largely unaccounted — costs.

Modifying our food consumption and waste patterns is very hard, and unfortunately we know very little about how to change them at scale. Yes, many pilots and small examples exist on pricing, procurement, food environments and others, but the evidence is scarce, and the magnitude of the change required demands an unprecedented transdisciplinary research agenda. The problem is at the centre of human agency and behaviour, embodying culture, habits, values, social status, economics and all aspects of agri-food systems. Certainly, one of the big research areas for the next decade if we are to reach the Sustainable Development Goals leaving no one behind.

Mario Herrero is Professor, Cornell Atkinson scholar and Nancy and Peter Meinig Family Investigator in the Life Sciences at the Department of Global Development, College of Agriculture and Life Sciences and Cornell Atkinson Center for Sustainability, Cornell University, Ithaca, NY, USA .

Cultural evolution

Laurel Fogarty

Humans are the ultimate ‘cultural animals’. We are innovative, pass our cultures to one another across generations and build vast self-constructed environments that reflect our cultural biases. We achieve things using our cultural capacities that are unimaginable for any other species on earth. And yet we have only begun to understand the dynamics of cultural change, the drivers of cultural complexity or the ways that we adapt culturally to changing environments. Scholars — anthropologists, archaeologists and sociologists — have long studied culture, aiming to describe and understand its staggering diversity. The relatively new field of cultural evolution has different aims, one of the most important of which is to understand the mechanics in the background — what general principles, if any, govern human cultural change?

Although the analogy of culture as an evolutionary process has been made since at least the time of Darwin 36 , 37 , cultural evolution as a robust field of study is much younger. From its beginnings with the pioneering work of Cavalli-Sforza & Feldman 38 , 39 , 40 and Boyd & Richerson 41 , 42 , the field of cultural evolution has been heavily theoretical. It has drawn on models from genetic evolution 40 , 43 , 44 , 45 , ecology 46 , 47 and epidemiology 40 , 48 , extending and adapting them to account for unique and important aspects of cultural transmission. Indeed, in its short life, the field of cultural evolution has largely been dominated by a growing body of theory that ensured that the fledgling field started out on solid foundations. Because it underpins and makes possible novel applications of cultural evolutionary ideas, theoretical cultural evolution’s continued development is not only crucial to the field’s growth but also represents some of its most exciting future work.

One of the most urgent tasks for cultural evolution researchers in the next five years is to develop, alongside its theoretical foundations, robust principles of application 49 , 50 , 51 . In other words, it is vital to develop our understanding of what we can — and, crucially, cannot — infer from different types of cultural data. Where do we draw those boundaries and how can we apply cultural evolutionary theory to cultural datasets in a principled way? The tandem development of robust theory and principled application has the potential to strengthen cultural evolution as a robust, useful and ground-breaking inferential science of human behaviour.

Laurel Fogarty is Senior Scientist at the Department of Human Behaviour, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany .

Over the past decade, research using molecular genetic data has confirmed one of the main conclusions of twin studies: all human behaviour is partly heritable 52 , 53 . Attempts at examining the link between genetics and behaviour have been met with concerns that the findings can be abused to justify discrimination — and there are good historical grounds for these concerns. However, these findings also show that ignoring the contribution of genes to variation in human behaviour could be detrimental to a complete understanding of social phenomena, given the complex ways that genes and environment interact.

Uncovering these complex pathways has become feasible only recently thanks to rapid technological progress reducing the costs of genotyping. Sample sizes in genome-wide association studies (GWAS) have risen from tens of thousands to millions in the past decade, reporting thousands of genetic variants associated with different behaviours 54 , 55 , 56 , 57 . New ways to use GWAS results have emerged, the most important one arguably being a method to aggregate the additive effects of many genetic variants into a ‘polygenic index’ (PGI) (also known as a ‘polygenic score’) that summarizes an individual’s genetic propensity towards a trait or behaviour 58 , 59 . Being aggregate measures, PGIs capture a much larger share of the variance in the trait of interest compared to individual genetic variants 60 . Thus, they have paved the way for follow-up studies with smaller sample sizes but deeper phenotyping compared to the original GWAS, allowing researchers to, for example, analyse the channels through which genes operate 61 , 62 , how they interact with the environment 63 , 64 , and account for confounding bias and boost statistical power by controlling for genetic effects 65 , 66 .

Useful as they are, PGIs and the GWAS that they are based on can suffer from confounding due to environmental factors that correlate with genotypes, such as population stratification, indirect effect from relatives or assortative mating 67 . Now that the availability of genetic data enables large-scale within-family GWAS, the next big thing in behaviour genetic research will be disentangling these sources 68 . While carrying the progress further, it is important that the field prioritizes moving away from its currently predominant Eurocentric bias by extending data collection and analyses to individuals of non-European ancestries, as the exclusion of non-European ancestries from genetic research has the potential to exacerbate health disparities 69 . Researchers should also be careful to communicate their findings clearly and responsibly to the public and guard against their misappropriation by attempts to fuel discriminatory action and discourse 70 .

Aysu Okbay is Assistant Professor at the Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands .

Cognitive neuroscience

Anna C. Nobre

Since the ‘decade of the brain’ in the 1990s, ingenuity in cognitive neuroscience has focused on measuring and analysing brain signals. Adapting tools from statistics, engineering, computer science, physics and other disciplines, we studied activity, states, connectivity, interactions, time courses and dynamics in brain regions and networks. Unexpected findings about the brain yielded important insights about the mind.

Now is a propitious time to upgrade the brain–mind duumvirate to a brain–mind–behaviour triumvirate. Brain and mind are embodied, and their workings are expressed through various effectors. Yet, experimental tasks typically use simple responses to capture complex psychological functions. Often, a button press — with its limited dimensions of latency and accuracy — measures anticipating, focusing, evaluating, choosing, reflecting or remembering. Researchers venturing beyond such simple responses are uncovering how the contents of mind can be studied using various continuous measures, such as pupil diameter, gaze shifts and movement trajectories.

Most tasks also restrict participants’ movements to ensure experimental control. However, we are learning that principles of cognition derived in artificial laboratory contexts can fail to generalize to natural behaviour. Virtual reality should prove a powerful methodology. Participants can behave naturally, and experimenters can control stimulation and obtain quality measures of gaze, hand and body movements. Noninvasive neurophysiology methods are becoming increasingly portable. Exciting immersive brain–mind–behaviour studies are just ahead.

The next necessary step is out of the academic bubble. Today the richest data on human behaviour belong to the information and technology industries. In our routines, we contribute data streams through telephones, keyboards, watches, vehicles and countless smart devices in the internet of things. These expose properties such as processing speed, fluency, attention, dexterity, navigation and social context. We supplement these by broadcasting feelings, attitudes and opinions through social media and other forums. The richness and scale of the resulting big data offer unprecedented opportunities for deriving predictive patterns that are relevant to understanding human cognition (and its disorders). The outcomes can then guide further hypothesis-driven experimentation. Cognitive neuroscience is intrinsically collaborative, combining a broad spectrum of disciplines to study the mind. Its challenge now is to move from a multidisciplinary to a multi-enterprise science.

Anna C. Nobre is Chair in Translational Cognitive Neuroscience at the Department of Experimental Psychology, University of Oxford, UK; and Director of Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, UK .

Social and affective neuroscience

Tatia M. C. Lee

Social and affective neuroscience is a relatively new, but rapidly developing, field of neuroscience. Social and affective neuroscience research takes a multilevel approach to make sense of socioaffective processes, focusing on macro- (for example, social environments and structures), meso- (for example, social interactions) and micro (for example, socio-affective neural processes and perceptions)-level interactions. Because the products of these interactions are person-specific, the conventional application of group-averaged mechanisms to understand the brain in a socioemotional context has been reconsidered. Researchers turn to ecologically valid stimuli (for example, dynamic and virtual reality instead of static stimuli) and experimental settings (for example, real-time social interaction) 71 to address interindividual differences in social and affective responses. At the neural level, there has been a shift of research focus from local neural activations to large-scale synchronized interactions across neural networks. Network science contributes to the understanding of dynamic changes of neural processes that reflect the interactions and interconnection of neural structures that underpin social and affective processes.

We are living in an ever-changing socioaffective world, full of unexpected challenges. The ageing population and an increasing prevalence of depression are social phenomena on a global scale. Social isolation and loneliness caused by measures to tackle the current pandemic affect physical and psychological well-being of people from all walks of life. These global issues require timely research efforts to generate potential solutions. In this regard, social and affective neuroscience research using computational modelling, longitudinal research designs and multimodal data integration will create knowledge about the basis of adaptive and maladaptive social and affective neurobehavioural processes and responses 72 , 73 , 74 . Such knowledge offers important insights into the precise delineation of brain–symptom relationships, and hence the development of prediction models of cognitive and socioaffective functioning (for example, refs. 75 , 76 ). Therefore, screening tools for identifying potential vulnerabilities can be developed, and timely and precise interventions can be tailored to meet individual situations and needs. The translational application of social and affective neuroscience research to precision medicine (and policy) is experiencing unprecedented demand, and such demand is met with unprecedented clinical and research capabilities.

Tatia M. C. Lee is Chair Professor of Psychology at the State Key Laboratory of Brain and Cognitive Sciences and Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong Special Administrative Region, China .

Maurizio Corbetta

Focal brain disorders, including stroke, trauma and epilepsy, are the main causes of disability and loss of productivity in the world, and carry a cumulative cost in Europe of about € 500 billion per year 77 . The disease process affects a specific circuit in the brain by turning it off (as in stroke) or pathologically turning it on (as in epilepsy). The cause of the disabling symptoms is typically local circuit damage. However, there is now overwhelming evidence that symptoms reflect not only local pathology but also widespread (network) functional abnormalities. For instance, in stroke, an average lesion — the size of a golf ball — typically alters the activity of on average 25% of all brain connections. Furthermore, normalization of these abnormalities correlates with optimal recovery of function 78 , 79 .

One exciting treatment opportunity is ‘circuit-based’ stimulation: an ensemble of methods (optogenetic, photoacoustic, electrochemical, magnetic and electrical) that have the potential to normalize activity. Presently, this type of therapy is limited by numerous factors, including a lack of knowledge about the circuits, the difficulty of mapping these circuits in single patients and, most importantly, a principled understanding of where and how to stimulate to produce functional recovery.

A possible solution lies in a strategy (developed with G. Deco, M. Massimini and M. Sanchez-Vivez) that starts with an in-depth assessment of behaviour and physiological studies of brain activity to characterize the affected circuits and associated patterns of functional abnormalities. Such a multi-dimensional physiological map of a lesioned brain can be then fed to biologically realistic in silico models 80 . A model of a lesioned brain affords the opportunity to explore, in an exhaustive way, different kinds of stimulation to normalize faulty activity. Once a suitable protocol is found it can be exported first to animal models, and then to humans. Stimulation alone will not be enough. Pairing with behavioural training (rehabilitation) will stabilize learning and normalize connections.

The ability to interface therapy (stimulation, rehabilitation and drugs) with brain signals or other kinds of behavioural sensor offers another exciting opportunity, to open the ‘brain’s black box’. Most current treatments in neuroscience are given with no regard to their effect on the underlying brain signals or behaviour. Giving patients conscious access to their own brain signals may substantially enhance recovery, as the brain is now in the position to use its own powerful connections and learning mechanisms to cure itself.

Maurizio Corbetta is Professor and Chair of Neurology at the Department of Neuroscience and Director of the Padova Neuroscience Center (PNC), University of Padova, Italy; and Principal Investigator at the Venetian Institute of Molecular Medicine (VIMM), Padova, Italy .

Merete Nordentoft

Schizophrenia and related psychotic disorders are among the costliest and most debilitating disorders in terms of personal sufferings for those affected, for relatives and for society 81 . These disorders often require long-term treatment and, for a substantial proportion of the patients, the outcomes are poor. This has motivated efforts to prevent long-lasting illness by early intervention. The time around the onset of psychotic disorders is associated with an increased risk of suicide, of loss of affiliation with the labour market, and social isolation and exclusion. Therefore, prevention and treatment of first-episode psychosis will be a key challenge for the future.

There is now solid evidence proving that early intervention services can improve clinical outcomes 82 . This was first demonstrated in the large Danish OPUS trial, in which OPUS treatment — consisting of assertive outreach, case management and family involvement, provided by multidisciplinary teams over a two-year period — was shown to improve clinical outcomes 83 . Moreover, it was also cost-effective 84 . Although the positive effects on clinical outcomes were not sustainable after five and ten years, there was a long-lasting effect on use of supported housing facilities (indicating improved ability to live independently) 85 . Later trials proved that it is possible to maintain the positive clinical outcomes by extending the services to five years or by offering a stepped care model with continued intensive care for the patients who are most impaired 86 . However, even though both clinical and functional outcomes (such as labour market affiliation) can be improved by evidence-based treatments 82 , a large group of patients with first-episode psychosis still have psychotic symptoms after ten years. Thus, there is still an urgent need for identification of new and better options for treatment.

Most probably, some of the disease processes start long before first onset of a psychotic disorder. Thus, identifying disease mechanisms and possibilities for intervention before onset of psychosis will be extremely valuable. Evidence for effective preventive interventions is very limited, and the most burning question — of how to prevent psychosis — is still open.

The early intervention approach is also promising also for other disorders, including bipolar affective disorder, depression, anxiety, eating disorders, personality disorders, autism and attention-deficient hyperactivity disorder.

Merete Nordentoft is Clinical Professor at the Department of Clinical Medicine, University of Copenhagen, Copenhagen, Denmark; and Principal Investigator, CORE - Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark .

Epidemiology

Gabriel M. Leung

In a widely anthologized article from the business field of marketing, Levitt 87 pointed out that often industries failed to grow because they suffered from a limited market view. For example, Kodak went bust because it narrowly defined itself as a film camera company for still photography rather than one that should have been about imaging writ large. If it had had that strategic insight, it would have exploited and invested in digital technologies aggressively and perhaps gone down the rather more successful path of Fujifilm — or even developed into territory now cornered by Netflix.

The raison d’être of epidemiology has been to provide a set of robust scientific methods that underpin public health practice. In turn, the field of public health has expanded to fulfil the much-wider and more-intensive demands of protecting, maintaining and promoting the health of local and global populations, intergenerationally. At its broadest, the mission of public health should be to advance social justice towards a complete state of health.

Therefore, epidemiologists should continue to recruit and embrace relevant methodology sets that could answer public health questions, better and more efficiently. For instance, Davey Smith and Ebrahim 88 described how epidemiology adapted instrumental variable analysis that had been widely deployed in econometrics to fundamentally improve causal inference in observational epidemiology. Conversely, economists have not been shy in adopting the randomized controlled trial design to answer questions of development, and have recognized it with a Nobel prize 89 . COVID-19 has brought mathematical epidemiology or modelling to the fore. The foundations of the field borrowed heavily from population dynamics and ecological theory.

In future, classical epidemiology, which has mostly focused on studying how the exposome associates with the phenome, needs to take into simultaneous account the other layers of the multiomics universe — from the genome to the metabolome to the microbiome 90 . Another area requiring innovative thinking concerns how to harness big data to better understand human behaviour 91 . Finally, we must consider key questions that are amenable to epidemiologic investigation arising from the major global health challenges: climate change, harmful addictions and mental wellness. What new methodological tools do we need to answer these questions?

Epidemiologists must keep trying on new lenses that correct our own siloed myopia.

Gabriel M. Leung is Helen and Francis Zimmern Professor in Population Health at WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong; Chief Scientific Officer at Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park; and Dean of Medicine at the University of Hong Kong, Hong Kong Special Administrative Region, China .

Bahdanau, D., Cho, K. & Bengio, Y. Neural machine translation by jointly learning to align and translate. Preprint at https://arxiv.org/abs/1409.0473 (2014).

Jumper, J. et al. Nature 596 , 583–589 (2021).

Article   CAS   PubMed   PubMed Central   Google Scholar  

Dwork, C., Hardt, M., Pitassi, T., Reingold, O. & Zemel, R. Fairness through awareness. In Proc. 3rd Innovations in Theoretical Computer Science Conference , 214–226 (Association for Computing Machinery, 2012).

Chouldechova, A. & Roth, A. Commun. ACM 63 , 82–89 (2020).

Article   Google Scholar  

Hara, K. et al. A data-driven analysis of workers’ earnings on Amazon Mechanical Turk. In Proc. 2018 CHI Conf. on Human Factors in Computing Systems , 1–14 (Association for Computing Machinery, 2018).

Strubell, E., Ganesh, A. & McCallum, A. Energy and policy considerations for deep learning in NLP. Preprint at https://arxiv.org/abs/1906.02243 (2019).

Rival, L. Anthropol. Today 37 , 9–12 (2021).

Carey, J. W. Communication as Culture: Essays on Media and Society (Unwin Hyman, 1985).

Williams, R. Television: Technology and Cultural Form (Fontana, 1974).

Helmond, A. Soc. Media Soc . 1 , https://doi.org/10.1177/2056305115603080 (2015).

Rambukkana, N. (Ed.). Hashtag Publics: The Power and Politics of Discursive Networks (Peter Lang, 2015).

Burrell, J. Big Data Soc. 3 , 1–12 (2016).

Bruns, A. et al. Facebook shuts the gate after the horse has bolted, and hurts real research in the process. Internet Policy Review , https://go.nature.com/3IP2xYr (25 April 2018).

Article 19. EU: Stop platforms from suppressing public interest research. article.19.org , https://go.nature.com/3DTWgXT (13 September 2021).

Burgess, J. et al. Critical simulation as hybrid digital method for exploring the data operations and vernacular cultures of visual social media platforms. Preprint at https://doi.org/10.31235/osf.io/2cwsu (2021).

Rieder, B. & Hofmann, J. Internet Policy Review 9 , 1–28 (2020).

Vosoughi, S., Roy, D. & Aral, S. Science 359 , 1146–1151 (2018).

Article   CAS   PubMed   Google Scholar  

Hussein, E., Juneja, P. & Mitra, T. Measuring misinformation in video search platforms: an audit study on YouTube. In Proc. of the ACM on Human–Computer Interaction 4 (CSCW1) (eds. Lampe C. et al.) 1–27 (Association for Computing Machinery, 2020).

Lazer, D. M. J. et al. Science 369 , 1060–1062 (2020).

Wagner, C. et al. Nature 595 , 197–204 (2021).

Kosse, F., Deckers, T., Pinger, P., Schildberg-Hörisch, H. & Falk, A. J. Polit. Econ. 128 , 434–467 (2020).

Cappelen, A., List, J., Samek, A. & Tungodden, B. J. Polit. Econ. 128 , 2739–2758 (2020).

Article   PubMed   PubMed Central   Google Scholar  

Alan, S., Boneva, T. & Ertac, S. Q. J. Econ. 134 , 1121–1162 (2019).

Google Scholar  

Almås, I., Cappelen, A. & Tungodden, B. J. Polit. Econ. 128 , 1753–1788 (2020).

Müller, D. & Renes, S. Soc. Choice Welfare 56 , 679–711 (2021).

Falk, A. et al. Q. J. Econ. 133 , 1645–1692 (2018).

Almås, I., Cappelen, A., Sørensen, E. Ø. & Tungodden, B. Global evidence on the selfish rich inequality hypothesis. Proc. Natl Acad. Sci. USA (in the press).

Henrich, J., Root, H. & Henrich, J. The WEIRDest People in the World: How the West Became Psychologically Peculiar and Particularly Propserous (Farrar, Strauss, and Giroux, 2020).

Gelfand, M. J. et al. Lancet Planet. Health 5 , e135–e144 (2021).

Lu, J. G., Jin, P. & English, A. S. Proc. Natl Acad. Sci. USA 118 , e2021793118 (2021).

Hong, Y. Y., Morris, M. W., Chiu, C. Y. & Benet-Martínez, V. Am. Psychol. 55 , 709–720 (2000).

Chan, H.-W. et al. Polit. Psychol. 42 , 767–793 (2021).

Gollwitzer, A. et al. Nat. Hum. Behav. 4 , 1186–1197 (2020).

Article   PubMed   Google Scholar  

de Solla Price, D. Little Science, Big Science (Columbia Univ. Press, 1963).

Mauss, M. 1925. in Sociologie et Anthropologie (Réédition 1978) 143–275 (Presses Universitaires de France).

Darwin, C. The Descent of Man, and Selection in Relation to Sex (Penguin 2004) (reprint of 2nd edn, 1879).

Mesoudi, A. Proc. Natl Acad. Sci. USA 114 , 7853–7860 (2017).

Cavalli-Sforza, L. & Feldman, M. W. Theor. Popul. Biol. 4 , 42–55 (1973).

Cavalli-Sforza, L. L. & Feldman, M. W. Am. J. Hum. Genet. 25 , 618–637 (1973).

CAS   PubMed   PubMed Central   Google Scholar  

Cavalli-Sforza, L. L. & Feldman, M. W. Cultural Transmission and Evolution (Princeton Univ. Press, 1981).

Richerson, P. J. & Boyd, R. J. Social Biological Syst. 1 , 127–154 (1978).

Boyd, R. & Richerson, P. J. Culture and the Evolutionary Process (Chicago Univ. Press, 1985).

Shennan, S. J. Camb. Archaeol. J. 11 , 5–16 (2001).

Strimling, P., Sjöstrand, J., Enquist, M. & Eriksson, K. Theor. Popul. Biol. 76 , 77–83 (2009).

Aoki, K., Lehmann, L. & Feldman, M. W. Theor. Popul. Biol. 79 , 192–202 (2011).

Kandler, A. & Laland, K. N. Theor. Popul. Biol. 76 , 59–67 (2009).

Laland, K. N. & O’Brien, M. J. Biol. Theory 6 , 191–202 (2011).

Richerson, P. J. & Boyd, R. Not By Genes Alone: How Culture Transformed Human Evolution (Univ. Chicago Press, 2005).

Kandler, A. & Powell, A. Phil. Trans. R. Soc. Lond. B 373 , 20170056 (2018).

Kandler, A., Wilder, B. & Fortunato, L. R. Soc. Open Sci. 4 , 170949 (2017).

McElreath, R. et al. Phil. Trans. R. Soc. Lond. B 363 , 3515–3528 (2008).

Turkheimer, E. Curr. Dir. Psychol. Sci. 9 , 160–164 (2000).

Polderman, T. J. C. C. et al. Genet. 47 , 702–709 (2015).

CAS   Google Scholar  

Visscher, P. M. et al. Am. J. Hum. Genet. 101 , 5–22 (2017).

Karlsson Linnér, R. et al. Nat. Genet. 51 , 245–257 (2019).

Article   PubMed   CAS   Google Scholar  

Lee, J. J. et al. Nat. Genet. 50 , 1112–1121 (2018).

Liu, M. et al. Nat. Genet. 51 , 237–244 (2019).

Wray, N. R., Goddard, M. E. & Visscher, P. M. Genome Res. 17 , 1520–1528 (2007).

The International Schizophrenia Consortium. Nature 460 , 748–752 (2009).

Article   CAS   Google Scholar  

Becker, J. et al. Nat. Hum. Behav . (2021).

Belsky, D. W. et al. Psychol. Sci. 27 , 957–972 (2016).

Young, A. I., Benonisdottir, S., Przeworski, M. & Kong, A. Science 365 , 1396–1400 (2019).

Barcellos, S. H., Carvalho, L. S. & Turley, P. Proc. Natl Acad. Sci. USA 115 , E9765–E9772 (2018).

Papageorge, N. W. & Thom, K. J. Eur. Econ. Assoc. 18 , 1351–1399 (2020).

DiPrete, T. A., Burik, C. A. P. & Koellinger, P. D. Proc. Natl Acad. Sci. USA 115 , E4970–E4979 (2018).

Rietveld, C. A. et al. Science 340 , 1467–1471 (2013).

Kong, A., Benonisdottir, S. & Young, A. I. Family analysis with Mendelian imputations. Preprint at https://doi.org/10.1101/2020.07.02.185181 (2020).

Howe, L. J. et al. Within-sibship GWAS improve estimates of direct genetic effects. Preprint at https://doi.org/10.1101/2021.03.05.433935 (2021).

Martin, A. R. et al. Nat. Genet. 51 , 584–591 (2019).

Nuffield Council on Bioethics. Genetics and Human Behaviour: The Ethical Context (Nuffield Council on Bioethics, 2002).

Redcay, E. & Schilbach, L. Nat. Rev. Neurosci. 20 , 495–505 (2019).

Roeckner, A. R., Oliver, K. I., Lebois, L. A. M., van Rooij, S. J. H. & Stevens, J. S. Transl. Psychiatry 11 , 508 (2021).

Sevgi, M., Diaconescu, A. O., Henco, L., Tittgemeyer, M. & Schilbach, L. Biol. Psychiatry 87 , 185–193 (2020).

Wittmann, M. K. et al. Neuron 91 , 482–493 (2016).

Gao, M. et al. Neuroimage 223 , 117290 (2020).

Lee, K. M., Ferreira-Santos, F. & Satpute, A. B. Neurosci. Biobehav. Rev. 131 , 211–228 (2021).

Olesen, J., Gustavsson, A., Svensson, M., Wittchen, H. U. & Jönsson, B. Eur. J. Neurol. 19 , 155–162 (2012).

Corbetta, M., Siegel, J. S. & Shulman, G. L. Cortex 107 , 229–237 (2018).

Griffis, J. C., Metcalf, N. V., Corbetta, M. & Shulman, G. L. Cell Rep. 28 , 2527–2540 (2019).

Deco, G. et al. J. Neurosci. 33 , 11239–11252 (2013).

Patel, V. et al. Lancet 392 , 1553–1598 (2018).

Correll, C. U. et al. JAMA Psychiatry 75 , 555–565 (2018).

Petersen, L. et al. Br. Med. J. 331 , 602 (2005).

Hastrup, L. H. et al. Br. J. Psychiatry 202 , 35–41 (2013).

Secher, R. G. et al. Schizophr. Bull. 41 , 617–626 (2015).

Albert, N. et al. Br. Med. J. 356 , i6681 (2017).

Levitt, T. Harv. Bus. Rev. 38 , 45–56 (1960).

Davey Smith, G. & Ebrahim, S. Int. J. Epidemiol. 32 , 1–22 (2003).

Callaway, E. ‘Randomistas’ who used controlled trials to fight poverty win economics Nobel. Nature, https://www.nature.com/articles/d41586-019-03125-y (14 October 2019).

Topol, E. J. Cell 157 , 241–253 (2014).

Subrahmanian, V. S. & Kumar, S. Science 355 , 489 (2017).

Download references

Author information

Authors and affiliations.

Department of Political Science, Ohio State University, Columbus, OH, USA

School of Communication and Digital Media Research Centre (DMRC), Queensland University of Technology, Brisbane, Queensland, Australia

Australian Research Council Centre of Excellence for Automated Decision-Making and Society (ADM+S), Melbourne, Victoria, Australia

Department of Neuroscience and Padova Neuroscience Center (PNC), University of Padova, Padova, Italy

Venetian Institute of Molecular Medicine (VIMM), Padova, Italy

Annenberg School for Communication and Journalism, University of Southern California, Los Angeles, CA, USA

Microsoft Research New York, New York, NY, USA

École Normale Supérieure, Paris, France

Department of Economics, Massachusetts Institute of Technology, Cambridge, MA, USA

Department of Human Behavior, Ecology, and Culture, Max Planck Institute for Evolutionary Anthropology, Leipzig, Germany

Department of Psychology, University of California at Berkeley, Berkeley, CA, USA

American University of Beirut, Beirut, Lebanon

Department of Global Development, College of Agriculture and Life Sciences and Cornell Atkinson Center for Sustainability, Cornell University, Ithaca, NY, USA

Department of Management, The Chinese University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China

Center for Social and Environmental Systems Research, Social Systems Division, National Institute for Environmental Studies, Tsukuba, Japan

State Key Laboratory of Brain and Cognitive Sciences and Laboratory of Neuropsychology and Human Neuroscience, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China

WHO Collaborating Centre for Infectious Disease Epidemiology and Control, School of Public Health, LKS Faculty of Medicine, The University of Hong Kong, Hong Kong, Hong Kong Special Administrative Region, China

Laboratory of Data Discovery for Health, Hong Kong Science and Technology Park, Hong Kong, Hong Kong Special Administrative Region, China

Heinz College of Information Systems and Public Policy, Carnegie Mellon University, Pittsburgh, PA, USA

Department of Experimental Psychology, University of Oxford, Oxford, UK

Oxford Centre for Human Brain Activity, Wellcome Centre for Integrative Neuroimaging, Department of Psychiatry, University of Oxford, Oxford, UK

CORE - Copenhagen Research Centre for Mental Health, Mental Health Centre Copenhagen, Copenhagen University Hospital, Copenhagen, Denmark

Department of Clinical Medicine, Faculty of Health and Medical Sciences, University of Copenhagen, Copenhagen, Denmark

Department of Economics, School of Business and Economics, Vrije Universiteit Amsterdam, Amsterdam, The Netherlands

Complex Human Data Hub, University of Melbourne, Melbourne, Victoria, Australia

ODID and SAME, University of Oxford, Oxford, UK

School of Public Policy, Georgia Institute of Technology, Atlanta, GA, USA

Centre of Excellence FAIR, NHH Norwegian School of Economics, Bergen, Norway

GESIS – Leibniz Institute for the Social Sciences, Köln, Germany

RWTH Aachen University, Aachen, Germany

Complexity Science Hub Vienna, Vienna, Austria

You can also search for this author in PubMed   Google Scholar

Corresponding authors

Correspondence to Janet M. Box-Steffensmeier , Jean Burgess , Maurizio Corbetta , Kate Crawford , Esther Duflo , Laurel Fogarty , Alison Gopnik , Sari Hanafi , Mario Herrero , Ying-yi Hong , Yasuko Kameyama , Tatia M. C. Lee , Gabriel M. Leung , Daniel S. Nagin , Anna C. Nobre , Merete Nordentoft , Aysu Okbay , Andrew Perfors , Laura M. Rival , Cassidy R. Sugimoto , Bertil Tungodden or Claudia Wagner .

Ethics declarations

Competing interests.

The authors declare no competing interests.

Rights and permissions

Reprints and permissions

About this article

Cite this article.

Box-Steffensmeier, J.M., Burgess, J., Corbetta, M. et al. The future of human behaviour research. Nat Hum Behav 6 , 15–24 (2022). https://doi.org/10.1038/s41562-021-01275-6

Download citation

Published : 27 January 2022

Issue Date : January 2022

DOI : https://doi.org/10.1038/s41562-021-01275-6

Share this article

Anyone you share the following link with will be able to read this content:

Sorry, a shareable link is not currently available for this article.

Provided by the Springer Nature SharedIt content-sharing initiative

This article is cited by

Corporate social responsibility and individual behaviour.

• Herman Aguinis
• Deborah E. Rupp
• Ante Glavas

Nature Human Behaviour (2024)

Sustainable dietary choices improved by reflection before a nudge in an online experiment

• Sanchayan Banerjee
• Matteo M. Galizzi
• Susana Mourato

Nature Sustainability (2023)

Spatially Small-scale Approach-avoidance Behaviors Allow Learning-free Machine Inference of Object Preferences in Human Minds

• Tsung-Ren Huang
• Tzu-Chun Chen

International Journal of Social Robotics (2023)

Potential of quantum computing to effectively comprehend the complexity of brain

• Shyam R. Sihare

Applied Intelligence (2023)

Nature Human Behaviour turns five

Nature Human Behaviour (2022)

Quick links

• Explore articles by subject
• Guide to authors
• Editorial policies

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Organizational Behavior Research Paper Topics

This page provides a comprehensive list of 100 organizational behavior research paper topics that are divided into 10 categories, each containing 10 topics. These categories include communication and teamwork, organizational culture and climate, employee motivation and engagement, organizational leadership, diversity and inclusion, organizational communication, employee well-being and work-life balance, organizational change, human resource management, and organizational ethics and corporate social responsibility. In addition to the list of topics, the page also provides expert advice on how to choose a research topic and how to write an organizational behavior research paper. Finally, students can take advantage of iResearchNet’s writing services to order a custom organizational behavior research paper on any topic. With this page, students will be able to explore the wide range of topics in organizational behavior and excel in their academic pursuits.

Organizational Behavior Topics Guide

Organizational behavior is an important field of study that focuses on how individuals and groups behave in organizations. It is a multidisciplinary field that draws on insights from psychology, sociology, anthropology, economics, and management. Understanding organizational behavior is crucial for individuals who are interested in careers in management, human resources, or organizational development. Research papers are an important aspect of studying organizational behavior, as they allow students to explore various aspects of this field in-depth.

Academic Writing, Editing, Proofreading, And Problem Solving Services

Get 10% off with 24start discount code.

The purpose of this page is to provide students with a comprehensive list of organizational behavior research paper topics that will help them choose a topic for their research paper. The page is divided into 10 categories, each containing 10 topics. The categories include communication and teamwork, organizational culture and climate, employee motivation and engagement, organizational leadership, diversity and inclusion, organizational communication, employee well-being and work-life balance, organizational change, human resource management, and organizational ethics and corporate social responsibility. By providing a wide range of topics, students can find one that aligns with their interests and career goals.

100 Organizational Behavior Research Paper Topics

Communication and Teamwork

1. Communication barriers in the workplace 2. Interpersonal communication and conflict resolution 3. The effects of technology on communication and teamwork 4. Cultural diversity and communication in global organizations 5. Communication strategies for effective leadership 6. Group dynamics and team performance 7. Decision-making processes in teams 8. Motivation and satisfaction in team-based work environments 9. Leadership styles and their impact on team effectiveness 10. Team training and development programs

Organizational Culture and Climate

1. The impact of organizational culture on employee behavior 2. The role of leadership in shaping organizational culture 3. Organizational change and resistance to change 4. Organizational culture and innovation 5. Ethical climates in organizations 6. Managing cultural diversity in organizations 7. The impact of organizational culture on employee well-being 8. Measuring and assessing organizational culture 9. The relationship between organizational culture and performance 10. The impact of organizational climate on employee motivation and job satisfaction

Employee Motivation and Engagement

1. Theories of employee motivation and their application in the workplace 2. The role of incentives and rewards in employee motivation 3. The impact of job design on employee motivation and engagement 4. The relationship between job satisfaction and employee motivation 5. Employee engagement and its impact on organizational performance 6. Employee empowerment and motivation 7. The role of leadership in employee motivation and engagement 8. The impact of organizational culture on employee motivation 9. Employee motivation and retention strategies 10. Employee motivation and its impact on organizational change

Organizational Leadership

1. Theories of leadership and their application in the workplace 2. Transformational leadership and its impact on organizational performance 3. Authentic leadership and its impact on organizational culture 4. Situational leadership and its effectiveness in different contexts 5. Servant leadership and its impact on employee well-being 6. The relationship between leadership and employee motivation 7. The impact of gender and cultural diversity on leadership 8. The role of emotional intelligence in leadership 9. The impact of leadership on organizational change 10. Developing effective leadership skills

Diversity and Inclusion

1. Defining diversity and inclusion in the workplace 2. The business case for diversity and inclusion 3. The relationship between diversity and innovation 4. Overcoming diversity challenges in global organizations 5. Managing diversity and inclusion through leadership 6. The impact of cultural diversity on team performance 7. Addressing diversity and inclusion in performance evaluations 8. The role of diversity and inclusion in employee retention 9. The impact of diversity and inclusion on organizational culture 10. Strategies for developing and implementing effective diversity and inclusion initiatives

Organizational Communication

1. The impact of communication on organizational effectiveness 2. Organizational communication strategies 3. Internal communication and its impact on employee engagement 4. The role of communication in change management 5. The impact of technology on organizational communication 6. The relationship between communication and organizational culture 7. The impact of communication on employee motivation and satisfaction 8. The role of nonverbal communication in organizational behavior 9. The impact of communication on organizational reputation 10. The role of feedback in organizational communication

Employee Well-being and Work-Life Balance

1. The impact of work-life balance on employee well-being 2. The relationship between stress and employee performance 3. Mental health in the workplace 4. Workplace wellness programs 5. The role of leadership in promoting employee well-being 6. The impact of job demands and resources on employee well-being 7. The impact of work schedule flexibility on employee well-being 8. The impact of job security on employee well-being 9. Burnout and its impact on employee well-being 10. Developing effective work-life balance policies

  Organizational Change

1. Theories of organizational change 2. Managing resistance to change 3. The role of leadership in organizational change 4. The impact of organizational culture on change management 5. The role of communication in change management 6. The impact of technology on organizational change 7. The impact of organizational change on employee motivation and satisfaction 8. The role of employee involvement in change management 9. Change management strategies for global organizations 10. The impact of organizational change on organizational performance

Human Resource Management

1. Recruitment and selection strategies 2. Performance management and appraisal 3. Training and development programs 4. The impact of compensation and benefits on employee motivation 5. The role of HR in promoting diversity and inclusion 6. The impact of technology on HRM 7. The impact of employee turnover on organizational performance 8. Employee retention strategies 9. HR metrics and analytics 10. HR strategy and its impact on organizational performance

Organizational Ethics and Corporate Social Responsibility

1. The importance of ethical behavior in organizations 2. Ethical decision-making processes in organizations 3. The impact of corporate social responsibility on organizational performance 4. The relationship between ethics and organizational culture 5. Ethical leadership and its impact on employee behavior 6. The role of codes of ethics in organizations 7. The impact of social media on organizational ethics 8. The impact of globalization on organizational ethics 9. The role of stakeholders in promoting ethical behavior 10. Developing ethical organizational policies

Choosing an Organizational Behavior Topic

Choosing a research topic can be a daunting task, especially when there are so many organizational behavior research paper topics to choose from. The key to choosing a successful topic is to select one that is relevant, interesting, and manageable. In this section, we provide expert advice on how to choose an organizational behavior research paper topic that will help students succeed in their academic pursuits.

The importance of choosing a relevant and interesting topic

The first step in choosing an organizational behavior research paper topic is to select a relevant and interesting topic. A relevant topic is one that aligns with the course curriculum and the student’s area of interest. An interesting topic is one that is engaging and will hold the student’s attention throughout the research and writing process. Choosing a relevant and interesting topic is important because it will make the research and writing process more enjoyable and fulfilling.

Tips for choosing a topic that aligns with the student’s interests and career goals

To choose a topic that aligns with the student’s interests and career goals, it is important to consider what topics are relevant to the student’s area of study and future career aspirations. Students should consider their personal interests, as well as the interests of potential employers. They should also consider the latest trends and developments in the field of organizational behavior, and choose a topic that is timely and relevant.

How to narrow down a broad topic into a manageable research question

Once a broad topic has been selected, it is important to narrow it down into a manageable research question. This can be done by breaking the topic down into smaller, more manageable sub-topics. Students should consider the scope of the topic and the available resources, and choose a research question that is focused and manageable.

Examples of how to brainstorm ideas for research topics

Brainstorming is an effective way to generate ideas for research topics. Students can start by listing the topics that interest them and then narrowing down the list to the most relevant and interesting topics. They can also read academic journals and textbooks to identify current trends and issues in organizational behavior. Finally, they can talk to their instructors or peers to get ideas and feedback.

How to conduct preliminary research

Before choosing a research topic, it is important to conduct preliminary research to ensure that the topic is feasible and has enough available resources. Students can start by conducting a literature review to identify the latest research on the topic. They can also use online databases and search engines to find relevant articles and publications. Finally, they can consult with their instructors or academic advisors to get advice on the available resources and potential research topics.

Choosing the right organizational behavior research paper topic is essential for success in academic pursuits. By following these expert tips and advice, students can choose a relevant and interesting topic, narrow it down into a manageable research question, and conduct preliminary research to ensure the topic is feasible and has enough available resources.

How to Write an Organizational Behavior Research Paper

Once a research topic has been chosen, the next step is to write the research paper. Writing an organizational behavior research paper can be a challenging task, but with the right guidance and strategies, it can be a rewarding and fulfilling experience. In this section, we provide expert advice on how to write an organizational behavior research paper.

The structure and format of a research paper

The structure and format of an organizational behavior research paper should follow the standard guidelines for academic research papers. It should include an introduction, literature review, methodology, results, and discussion sections. The introduction should provide an overview of the research topic and the purpose of the study. The literature review should summarize the relevant research on the topic. The methodology section should describe the research design, sample, and data collection methods. The results section should present the findings of the study, and the discussion section should interpret the results and provide conclusions and recommendations.

How to conduct research and gather sources

To conduct research and gather sources for an organizational behavior research paper, students should start by conducting a literature review. This involves searching for relevant articles and publications on the research topic. Students can use online databases, search engines, and academic journals to find relevant sources. They should also consider the credibility and relevance of the sources they choose, and use a variety of sources to support their arguments.

How to organize and outline the paper

Organizing and outlining an organizational behavior research paper is an important step in the writing process. Students should start by creating an outline that includes the major sections of the paper and the key points they want to make in each section. They should then organize their sources and research findings according to the outline. This will help them write a clear and coherent paper.

How to write an introduction, literature review, methodology, results, and discussion sections

Each section of an organizational behavior research paper has a specific purpose and format. The introduction should provide an overview of the research topic and the purpose of the study. The literature review should summarize the relevant research on the topic. The methodology section should describe the research design, sample, and data collection methods. The results section should present the findings of the study, and the discussion section should interpret the results and provide conclusions and recommendations. Students should use clear and concise language and support their arguments with relevant sources and research findings.

How to properly cite sources and format the paper

Properly citing sources and formatting the paper is essential for academic integrity and professionalism. Students should follow the guidelines for the appropriate citation style, such as APA or MLA. They should also ensure that the paper is formatted according to the guidelines provided by their instructor or academic institution. This includes proper margins, headings, and references.

How to revise and edit the paper for clarity and coherence

Revising and editing the organizational behavior research paper is an important step in the writing process. Students should read the paper carefully and revise it for clarity, coherence, and organization. They should also check for spelling and grammar errors and ensure that the paper meets the requirements and guidelines provided by their instructor or academic institution.

Writing an organizational behavior research paper can be a challenging task, but with the right guidance and strategies, it can be a rewarding and fulfilling experience. By following these expert tips and advice, students can write a high-quality research paper that meets the academic standards and expectations.

Order Custom Organizational Behavior Research Papers from iResearchNet

Organizational behavior research is a dynamic and challenging field, and writing a research paper on the topic can be daunting. However, with the right guidance, strategies, and support, students can succeed in their academic pursuits and contribute to the ongoing discourse in the field.

We have provided a comprehensive list of organizational behavior research paper topics and expert advice on how to choose a topic, conduct research, and write a high-quality research paper. Additionally, iResearchNet offers writing services that provide customized solutions to students who need expert help with their organizational behavior research papers.

If you’re struggling to choose a topic, conduct research, or write your organizational behavior research paper, iResearchNet’s writing services can help. Our team of experienced writers can provide personalized assistance on any topic, ensuring that your paper meets the highest standards of quality. We offer flexible pricing, timely delivery, and a money-back guarantee, so you can trust us to provide the support you need to succeed.

Don’t let the challenges of writing an organizational behavior research paper hold you back. With the right tools and support, you can excel in your academic pursuits and make a valuable contribution to the field of organizational behavior. Contact iResearchNet today to get started!

ORDER HIGH QUALITY CUSTOM PAPER

• Tools and Resources
• Customer Services
• Affective Science
• Biological Foundations of Psychology
• Clinical Psychology: Disorders and Therapies
• Cognitive Psychology/Neuroscience
• Developmental Psychology
• Educational/School Psychology
• Forensic Psychology
• Health Psychology
• History and Systems of Psychology
• Individual Differences
• Methods and Approaches in Psychology
• Neuropsychology
• Organizational and Institutional Psychology
• Personality
• Psychology and Other Disciplines
• Social Psychology
• Sports Psychology
• Share This Facebook LinkedIn Twitter

Article contents

Human resource management and organizational psychology.

• David E. Guest David E. Guest School of Management and Business, King's College London
• https://doi.org/10.1093/acrefore/9780190236557.013.14
• Published online: 29 March 2017

Human resources (HR) management addresses those policies, practices, and activities concerned with the management of people in organizations. Although it is typically considered at multiple levels of analysis, it provides an important context for the application of work and organizational psychology. Core research questions address the determinants of HR strategy and practices adopted by organizations and how these are linked to outcomes including in particular organizational performance and employee wellbeing. Much research explores this linkage process including how far HR practices are able to ensure employee abilities, motivation, and opportunities to contribute; the distinctive role of human capital; how employees react to these practices; and the steps management can take to ensure their effective implementation. Most research confirms an association between the adoption of a greater number of what are typically termed “high performance” or “high involvement” HR practices and higher organizational performance and employee wellbeing. However, doubts remain about the causal direction of the association. Continuing research challenges include how best to measure HR practices, understanding more about contextual influences, and incorporating more fully the role of employee attitudes and behavior including employee attributions about the motives of management in their use of HR practices.

• human resources management
• organizational performance
• employee wellbeing
• human capital

Introduction

Human resources management (HRM) can be broadly defined as “all those activities associated with the management of work and people in organizations” (Boxall & Purcell, 2011 ). It serves as a focus of study but also as an occupation for specialists and a day-to-day component of the work of line managers. HRM is a relatively new area of study, but research has burgeoned in recent years, and this article will examine some of the central research debates and research findings.

HRM may not at first sight appear to be an obvious candidate for inclusion under the banner of work and organizational psychology. It is, after all, a multidisciplinary area of research, often conducted at the organizational rather than the individual level of analysis. But it also incorporates many of the core activities typically associated with work and organizational (W/O) psychology ranging from topics such as selection and training to outcomes such as wellbeing, absenteeism, and labor turnover. It therefore serves as an integrative context within which to consider the work of W/O psychologists. At the same time, HRM has emerged as a major field of theorizing and research in its own right, with several specialist academic journals and large numbers of practitioners who label themselves as HR professionals, and it offers the promise of some integration across disciplines and across levels of analysis.

The article starts with a brief overview of influences on the emergence of HRM, emphasizing those disciplinary perspectives that lie beyond the usual territory of W/O psychology. Subsequent sections examine the nature of HRM, the kind of outcomes it is expected to influence, and the processes whereby HRM and outcomes might be related. Each of these is a continuing focus of theorizing and research. In each section, conceptual and empirical issues and evidence will be reviewed.

Disciplinary Influences

Three broad disciplinary perspectives have been particularly influential in informing the development of HRM theory and research. The first, reflecting the historical traditions of the application of HRM, is the sub-discipline of industrial relations. The second is the influence of business strategy, reflecting the location of some researchers in business schools and the potentially important role of effective HRM for business performance. The third influence is W/O psychology and the overlapping field of organizational behavior.

The practice of what we now describe as HRM emerged in the early decades of the 20th century . Those working in the field were initially described as welfare officers and then personnel managers. When there was a need to address industrial conflict, the role of the industrial relations manager increasingly came to the fore. In the 1930s, the study of industrial relations and, more broadly, relations at work began to emerge within universities. Well-known examples over the decades include the Hawthorne studies (Roethlisberger & Dickson, 1939 ), the work of Whyte ( 1955 ) and others on the role of pay and restriction of output, and Walton and McKersie’s ( 1965 ) behavioral theory of labor negotiation. Those engaged in this type of research typically had backgrounds in sociology, economics, or psychology, providing an early multidisciplinary perspective. Topics for research included forms of industrial conflict ranging from strikes to absenteeism, systems for alleviating or preventing conflict such as collective bargaining, systems for workers’ participation and the influence of pay on behavior. By the 1970s, there were flourishing departments of industrial relations in universities in many countries, undertaking research and providing education to those seeking to pursue a career in industrial relations or personnel management. By the 1980s, patterns of industrial conflict began to change and eventually diminish, and academic industrial relations departments entered a slow decline, though several prominent journals remained. A number of researchers who once worked in these departments switched their research focus to HRM, often providing some of the most trenchant critical analysis of the field (see, e.g., Godard, 2004 ).

The influence of business strategy on HRM began to emerge in the 1980s. A major factor in this was the growth of teaching and research in the business schools, particularly in the U.S. The initial argument, proposed in general normative terms, most notably by Porter ( 1985 ), but applied to HRM by, for example, Miles and Snow ( 1984 ) was that organizations had strategic choices about how to compete, and this should influence the approach organizations adopt to HRM. The most obvious distinction was whether to compete on the basis of cost minimization or some combination of quality and innovation. Each required rather different ways of managing people at work. A clear exposition of this was outlined by Schuler and Jackson ( 1987 ) who set out five steps. First, an organization has to clarify its mission and values. Second, and building on this, it has to determine its competitive strategy. Third, it needs to determine the kinds of employees and the sorts of behavior that will enable the strategy to be achieved. Fourth, the organization needs to determine the HR policies and practices that will help to ensure that the right employees are performing appropriately. Finally, organizations should check that employee behavior is actually aligned with the strategic goals.

Further interest in HRM from a strategic perspective was provided by advocacy of the resource-based view of the firm (Barney, 1991 ). This argued that to compete effectively, organizations needed to acquire and utilize resources that are rare, expensive, hard to replace, and not easily replicable. Part of the analysis, developed further by Barney and Wright ( 1998 ), was that human resources fitted these criteria better than other resources such as finance or machinery, which could more easily be copied. This boosted the idea of employees as “human resources,” a term that causes distaste in some quarters.

The resource-based view of HRM placed considerable emphasis on the economic concept of human capital (Nyberg & Wright, 2015 ). For example, Lepak and Snell ( 1999 ), argued that organizations need to invest heavily in attracting, retaining, and utilizing “human capital” that is highly unique to the firm and highly valuable. In contrast, human capital that is valuable but plentiful is best acquired, perhaps by being brought in. Where human capital is unique but of low strategic value, it might be best to form an alliance. Finally, human capital that is low in value and uniqueness is perhaps best contracted in. This might appear to be a cost-effective strategy, and research has shown the benefits of a selective approach (Lepak & Snell, 2002 ). However, Peel and Boxall ( 2005 ) found that seeking to classify human capital is far from straightforward and likely to vary from firm to firm. We return to the topic of human capital later in the article.

The third major source of influence on HRM comes from work and organizational psychology and (OB) organizational behavior (hereafter just W/O psychology). The reason for this is straightforward; HR practices such as selection, training, appraisal, and reward are the bread and butter of the research and practice of W/O psychologists. HR practitioners are constantly on the lookout for the best practices to apply, and it is the W/O psychologists who undertake the research that provides them. Although the picture is mixed, many W/O psychologists and most of those who use the OB label now work in business schools and, with an interest in effective management, this makes the field of HRM a natural context for their research and consultancy. At the same time, W/O psychology has a particular focus on individual and group behavior and associated outcomes. This has helped to promote a more employee-centered, micro-level focus to HRM.

A distinctive feature of HRM is its ability to integrate features of the macro strategic perspective with the more micro-level perspective typically adopted by psychologists. Indeed, writers such as Wright and Boswell ( 2002 ) have argued that some integration of macro and micro areas is essential for the field to develop. A feature of an integrated perspective, and a key argument of advocates of HRM (see, e.g., Becker & Huselid, 1998 ; Jackson, Schuler, & Jiang, 2014 ), is that HRM should be viewed as a system. What this implies is that it is not enough to focus on selection, training, rewards, or job design; it is necessary to view the whole range of HR practices as an integrated whole and to ensure that they are aligned to provide “internal fit.” If this approach succeeds, there should be a kind of gestalt whereby the sum is more than the parts.

The dominant research topic has been the relationship between HRM and outcomes, and in particular, organizational performance. However, researchers are increasingly exploring the relationship with employee wellbeing and the feasibility of mutual gains (Van de Voorde, Paauwe, & van Veldhoven, 2012 ). Some years ago, Guest ( 1997 ) noted that if research on HRM is to progress, there needs to be clearer theory and research concerning the nature and measurement of HRM, of outcomes and the nature of the relationships among them. Since then, either directly or indirectly, much of the research has addressed these three core issues. In the following sections, we consider each of these in turn.

The Nature of HRM

A major and continuing challenge for research has been how to conceptualize and operationalize HRM. There are several interrelated issues that need to be addressed. What HR practices should be included in the general field of HRM? What is the underlying rationale for including specific practices? How much detail is required about each practice? Can and should practices be combined in any kind of bundles? Who should provide information about them? And what kinds of response categories are appropriate? All these questions have provided the focus for extensive conceptual and empirical work.

Diversity in Conceptualizations of HRM

In several earlier articles on HRM, it was conventional to identify four broad topics that reflected the field. These were recruitment and selection, training and development, performance appraisal, and rewards (see, e.g., Fombrun, Tichy, & Devanna, 1984 ). However, this list omitted a range of issues concerning the employment relationship, such as job security, communication, and flexible work arrangements. Writing for general managers at Harvard, Beer, Spector, Lawrence, Quinn Mills, and Walton ( 1985 ) suggested that broad core topics that needed to be addressed included employee influence, human resource flows, reward systems, and work systems. These two differing approaches highlight the scope for diversity when studying HRM. It is therefore perhaps not surprising that when Becker and Gerhart ( 1996 ) reviewed the existing studies, they found a wide variety of practices being measured. Indeed, no one practice appeared in every study they reviewed. Several years and many studies later, two extensive reviews (Boselie, Dietz, & Boon, 2005 ; Combs, Liu, Hall, & Ketchen, 2006 ) found that little had changed with respect to the variety of practices used in studies. There was also considerable difference in the number of practices used; indeed, Combs et al. found that the number ranged between 2 and 13 with an average of 6.2. The variety of practices used to measure HRM makes comparison across studies highly problematic. This has not stopped such comparisons being made, notably in meta-analyses.

Alternative Rationales for Determining the Content of HRM

There has clearly been a need to find some underlying rationale to determine which practices should be included in any study. One approach has been to focus on external and internal fit. In the case of external fit, as Porter ( 1985 ) and Schuler and Jackson ( 1987 ) have argued, the starting point is to determine the mission, values, and core goals of the organization and then determine its competitive strategy. Since the main goal of most private-sector organizations is to maximize financial performance, it is those HR practices that help to achieve this that should be included. As researchers have accepted this logic, one consequence has been a change in language, so that many studies now don’t refer to HR practices, but rather to high-performance work practices (HPWPs).

In public sector organizations, the mission and values may be rather different, and the concept of competitive strategy may be inappropriate. Furthermore, as Paauwe ( 2004 ) and others have pointed out, in Europe, with its focus on social partnership, legislation at European and national levels requires the application of a range of HR practices to promote issues such as health and safety at work, equal opportunities, and flexible working. Partly reflecting this perspective, and acknowledging the roots of HRM in the industrial relations tradition, scholars have outlined alternative bases for determining appropriate HR practices. In the U.S., Walton ( 1985 ) argued that effective management of the contemporary workforce requires a shift from policies and practices seeking control to those that promote employee commitment. This has led to advocacy of what is termed high commitment (Wood & Albanese, 1995 ) or high-involvement HRM (Boxall & Macky, 2009 ). These terms suggest a rather different approach, reflected in the writing of Beer et al. ( 1985 ) that recognized the legitimacy of outcomes of concern to employees and other stakeholders.

One problem with an approach to HRM that starts from mission, values, and stakeholder interests is that it still leaves open the choice of practices and it does not clearly specify how those practices should be deployed. Therefore, though there can be agreement about the need to include practices such as selection and training, the specific features of such practices can remain unclear. For example, selection can be measured through the use of certain types of psychometric tests or the use of assessment centers. Alternatively, it can be measured in relation to its aims, such as by hiring those who demonstrate immediate competence in a specified job or those with a positive attitude toward learning. The complexities and choices in measuring these variables are familiar to W/O psychologists. The problem in measuring them in the context of HRM is that each practice is just one among several. As a result, it is not surprising that researchers have measured a wide and varied range of practices, and have done so in often rather different ways.

Internal Fit and the Role of HR Bundles

The aim of internal fit is to identify sets of HR practices (sometimes described as bundles) that will complement each other. The most frequently cited approach to achieve this is the so-called AMO model. This draws on Lawler’s ( 1971 ) expanded version of expectancy theory. While expectancy theory proposes that motivation is a function of the perceived links among effort, performance, and rewards, Lawler extended this to propose that effective performance also depends on individuals having the appropriate ability and role. Applying this to HRM (Becker, Huselid, Pickus, & Spratt, 1997 ; Guest, 1997 ) it is suggested that the immediate goals of an HR system designed explicitly to ensure high performance are to ensure that employees have the ability (A), motivation (M), and opportunity (O) to contribute effectively. HR practices required to achieve these goals can then be clustered together in three broad bundles. For example, ability or competence may be generated through appropriate selection, training, and development practices. The quality of these practices can be greatly enhanced by building on the evidence base developed by W/O psychologists. However, this approach is not without its challenges. For example, there are potential substitution effects—should the focus be on selection of competence or the training of competence? Furthermore, some practices, including those linked to job design, can have an impact on both motivation and opportunity to contribute, thereby blurring the bundles.

The concept of bundles can also present a challenge for psychologists who have typically developed expertise in specific practices, since the argument concerning internal fit suggests that it is not enough to focus on practices that develop one of these outcomes because they are all important. For example, it is not helpful to have highly motivated but incompetent employees or to have highly competent employees who have no opportunity to use their knowledge and skills. So the notion of internal fit within an HR system implies that there need to be HR practices present that can contribute to each element of the AMO model.

Meta-analyses by Jiang, Lepak, Hu, and Baer ( 2012 ) and Subramony ( 2009 ) tested models based on the three AMO bundles of practices and also tested a single integrated measure of HRM. They found a better fit with the three bundles. Furthermore, each was associated with somewhat different outcomes. This is further support for the view that all three bundles need to be present to have a full impact. Subramony found that opportunity to contribute and motivation had a stronger impact than human capital, which on its own was non-significant. On the other hand, Jiang et al. found that each bundle on its own had a modest but significant impact on financial outcomes. Reflecting this, subsequent research has shown that human capital on its own can improve employee behavior and organizational performance (Crook, Todd, Combs, Woehr, & Ketchen, 2011 ). But the impact is not as great as the application of the three bundles. This is somewhat akin to research on the impact of selection and training effects that has consistently shown that high-quality application of both practices can enhance and benefit individual performance. When this is aggregated to the unit or organizational level, we might expect an impact on organizational performance (see, e.g., Aguinis & Kraiger, 2009 ; Schmidt & Hunter, 1998 ). Nevertheless, Subramony ( 2009 ) also showed that each bundle made a stronger contribution than any individual practice. Given these competing results, further research needs to establish the relative importance of individual HR practices, bundles of practices, and an aggregated measure.

Human Capital

Recent theorizing and research have given considerable prominence to the concept of human capital and the specific bundle of HR practices associated with it. As originally conceived by Becker ( 1964 ), the concept was quite wide-ranging and covered the knowledge and skills of individuals and also their information, ideas, and health. Ployhart and Moliterno ( 2011 ) have distinguished between cognitive abilities and other individual characteristics like personality, interests, and values, all of which, as they acknowledge, are typically considered at the individual level. However, they outline enabling factors such as task complexity and interdependencies that create conditions where these types of capital can be aggregated to the unit level and analyzed with respect to their impact on unit performance. Researchers have begun to consider human capital at the unit level as a collective set of capacities for management to utilize (see, e.g., Ployhart, Nyberg, Reilly, & Maltarich, 2014 ) and Nyberg and Wright ( 2015 ) argue that it offers an opportunity for multidisciplinary as well as multilevel research. Although interest in human capital is generating a large body of research, it is potentially limited by its focus on one element, the A within the AMO model.

Levels of Detail about HR Practices

After a decision about which HR practices to include in any study, there remains the issue of how much detail to seek. For example, it is possible with respect to training to ask about the presence of a training policy, hours of training provided, off-the-job versus on-the-job training, and so on. Indeed, the amount of formal training provision is one of the most frequently included items in studies of HRM. However, this is not without problems since it might refer to a goal to provide specified hours, it might refer to off-the-job formal training but ignore informal and incidental learning, and it may apply to only some of the employees. In short, even if the relevant HR practices can be identified, there are unresolved research questions about the level of detail and how far this should be standardized across practices.

Sources of Information about HR Practices

A further and increasingly widely researched question is who should provide information about HR practices. Researchers have noted a gap between intended and implemented practices (Khilji & Wang, 2006 ), and among those concerned with the impact of HRM on outcomes, it is argued that effective implementation is more important than the presence of a policy or practice (Bowen & Ostroff, 2004 ). Senior managers in HR departments may report that a practice such as universal annual appraisal is a firm company policy. However, employees will be in a better position to report whether they have actually received an appraisal in the past year or whether they have perceived and are actually aware of specific policies and practices even if they have not directly experienced them. An example might be policies and practices related to bullying and harassment. Therefore, while much of the research on HR practices has obtained information from senior managers, there is a strong case for collecting information from employees. This may not only increase accuracy, but also enhance reliability. However, the attractions of collecting data from senior managers include the ability to compare across many organizations and to collect data swiftly at an organizational level to permit assessment against organizational-level outcomes. While it is possible to aggregate employee data, collecting such data across many organizations is a complex and time-consuming activity. An alternative is to focus on an important category of employees and ask about the HR practices that apply to this group. This can offer some advantages in accuracy over asking about the workforce as a whole, but it risks ignoring the HR practices applied to the remainder of the workforce.

Response Categories for HR Practices

Researchers need to give consideration to the choice of response categories when collecting information about HR practices. Once again, the published research displays a wide range of approaches. In many cases, the logical response categories will be a straightforward “Yes/No” as in responses to questions such as “Have you received an appraisal in the past 12 months?” An alternative is to turn these questions into statements and use a Likert scale, typically from “strongly agree to strongly disagree,” which permits a factor analysis of the responses, but also invites potentially inaccurate responses to categorical items. When the questions are directed to managers, an alternative to asking for categorical answers is to ask about the percentage of workers who are likely to have experienced a particular practice. This permits a more flexible response, although the accuracy of such responses is open to question and they present potential problems of aggregation, particularly if different practices apply to different categories of employees. There are therefore choices concerning the approach to adopt for response categories, with no consensus in sight.

Aggregating HR Practices

A final issue concerns how to aggregate practices. This issue was first addressed some years ago by Delery and Doty ( 1996 ) who tested competing theories and different ways of combining data to address both external fit, through a contingency approach linking practices to strategy, and internal fit, based on a simple count of practices in place and a configurational model that examined interactions between bundles of practices. It was found that there was no clear advantage to a configurational model. Subramony ( 2009 ) and Jiang et al. ( 2012 ) also found no consistent evidence that one bundle in the AMO model or that any combination of A, M, and O is superior in terms of its impact. Interestingly, this is similar to the findings in a meta-analysis of expectancy theory (van Eerde & Thierry, 1996 ). The most widely used approach over the years has been to provide a count of the practices that are reported to be present on the grounds that a greater number of practices indicates the strength of the HR system and therefore increases the likelihood that they will have an impact. Although this is a plausible argument, it ignores the likelihood that certain practices will be more important than others. It also supports a universalist model that holds that the same broad set of practices applies, irrespective of the context and strategy, a view that is not well supported by the research and that supporters of contingency theory find inherently implausible.

Identifying and Measuring HR Practices: A Summary

This brief overview has shown that there are major problems in conceptualizing and operationalizing the presence and application of the HR practices that constitute the HRM system. Much of the difficulty can be attributed to the complexities that arise from the lack of clear definitions of the content and boundaries of any HRM system, from the variety of perceived goals of the system and therefore the practices that deserve priority, and from the various levels of analysis at which the research is undertaken. These challenges are of a different order than those faced by W/O psychologists who have typically focused more narrowly on a specific practice at the individual or group level. However, the lesson of HRM for W/O psychology is that this type of detailed focus needs to be understood in its wider context, recognizing the risk that a specific practice can act as a proxy for a wider set of practices unless some way can be found of controlling for their influence. Researchers need to be clear about the underlying rationale for the kind of HRM they are exploring and be explicit about the reasons certain HR practices are included and what assumptions are being made about aggregation. Too many studies have lacked a theory or even an explanation for their choices of practices. It is also worth noting that the research, with its focus on HR practices likely to enhance performance, omits a number of important topics that are likely to be of interest to employees and have been the focus of extensive research by W/O psychologists, such as the role of careers and career management, equal opportunities, and work-life balance. Despite all the problems of identifying and measuring HR practices, and the unreliability that the diversity of practice indicates, the large body of research, reflected in the various meta-analyses (see, e.g., Combs et al., 2006 ; Jiang et al., 2012 ) consistently reveals a positive association at the organizational level between the use of more HR practices and financial outcomes.

The Outcomes of HRM

Most of the early research was concerned with the relationship between HRM and organizational performance and was conducted at the level of the organization. For example, in the early seminal study by Huselid ( 1995 ) who surveyed leading U.S. companies, outcomes included aggregated labor turnover and productivity, but the main focus was on various financial indicators, including market value of shareholder equity. In Jiang et al.’s ( 2012 ) meta-analysis, the main dependent variable was financial performance reflected in a variety of measures, including return on assets, return on equity, and a general measure of overall financial performance. The problem with the use of financial indicators is that they are subject to a wide variety of influences, including the vagaries of the economic system. Therefore, as a distal outcome, the size of the association with HRM is always likely to be quite weak. An alternative is to utilize more proximal measures that are organizationally relevant in the sense that they could have a financial impact but are more likely to be influenced by HRM. In other words, they can provide a test of mediation. This has led to the use of outcomes like labor turnover, productivity, and service quality. Two early studies in strip steel mills (Arthur, 1994 ; Ichniowski, Shaw, & Prennushi, 1997 ) explored the link between HRM and productivity. However, productivity has proved particularly challenging to measure, especially in the service sector, and in their meta-analysis, Combs et al. ( 2006 ) found that there was a stronger association between HRM and financial performance than between HRM and productivity. What this perhaps illustrates is that there are questions concerning both the reliability and validity of these outcome measures.

Identifying outcome measures can become greater at the unit level rather than the organizational level. One way of addressing this has been to obtain subjective assessments of outcomes from managers. This is the approach that has been adopted over the years by the British Workplace Employment Relations surveys that collect data from about 2000 workplaces (see van Wanrooy et al., 2013 ). They ask managers to rate their performance on a variety of criteria against competitors they know about in the same sector. Analyses of the results where it is possible to compare against independent financial reports (e.g., in single unit organizations) show that there is a modest positive association between the subjective and more objective indicators (Forth & McNabb, 2008 ; see also Wall et al., 2004 ). However, in their meta-analysis, Combs et al. ( 2006 ) reported higher associations between HRM and performance where subjective rather than objective indicators of performance are used. There are some sectors where unit-level comparisons are feasible, including retail and banking, because organizations have a large number of more-or-less identical branches. Similar arguments are increasingly made about public-sector organizations such as hospitals and local authorities, and benchmarking has become popular based on assumptions about the validity of such comparisons. For relevant research on hospitals, see Givan, Avgar, and Liu, ( 2010 ) and West, Guthrie, Dawson, Borrill, and Carter ( 2006 ), and for local authorities, see Messersmith, Patel, Lepak, and Gould-Williams ( 2011 ).

Psychologists have been more interested in employee outcomes, and a growing number of studies explore the relationship between HRM and employee attitudes, behavior, and wellbeing. The choice of measure depends on whether the primary interest lies in organizational performance or employee wellbeing. In the case of the former, it can include individual-level performance, organizational citizenship behavior, absence, and labor turnover. When the main interest is in wellbeing, outcome measures include psychological contract fulfillment, perceptions of employment security, and perceived organizational support, as well as measures of stress, burnout, and engagement, and standard measures of job satisfaction and wellbeing (for a review, see Clinton & van Veldhoven, 2013 ). Almost all the research shows a positive association between the presence of more HR practices and more positive employee responses (see Clinton & van Veldhoven, 2013 ). However, a small minority of studies have revealed increases in levels of stress (see, e.g., Ramsay, Scholarios, & Harley, 2000 ). This has led critics such as Godard ( 2004 ) to argue that HRM is bad for workers because it is likely to result in work intensification and the consequent stress.

Although the evidence of negative consequences for employees is weak, the topic has generated interest in the extent to which HRM is associated with both higher organizational performance and improved employee wellbeing. The relatively few reported studies in which both have been measured have been reviewed by van de Voorde, Paauwe, and van Veldhoven ( 2012 ) and Peccei, van de Voorde, and van Veldhoven ( 2013 ). They find that the presence of more HR practices is associated with both higher performance and higher job satisfaction and organizational commitment. However, the evidence from the very few studies that have included health-related wellbeing measures, mainly indications of stress, is somewhat more equivocal, revealing a mix of positive, neutral, and negative outcomes for employees. It is unclear whether the studies with more negative results were utilizing high-performance work systems to enhance performance or high-commitment/high-involvement approaches that give higher priority to employee roles and outcomes. Future research exploring this issue will need to be clearer about the HRM strategy that underpins the type of practices adopted.

In summary, the research on HRM has predominantly explored outcomes that reflect organizational and managerial interests associated with performance. These have often been quite distal measures, such as financial performance, and have usually been collected at the organizational level. A smaller stream of research has explored employee outcomes like job satisfaction and wellbeing. As more proximal measures, these might be expected to reveal a stronger association with HRM. Relatively few studies have explored both organizational and employee outcomes. Those that have done so tend to show mutual benefits, but the results are somewhat inconsistent and seem to depend in part on the type of employee outcome under investigation. This is an area that would benefit from further research.

Understanding the Relationship between HRM and Outcomes

The early research was primarily concerned with establishing a relationship between HRM and organizational performance, but much of the focus shifted to seek explanations for how or why there appears to be an association. The relatively limited body of research exploring the role of external fit of HR practices with the business strategy has failed to show any consistent impact on outcomes (Jackson, Schuler, & Jiang, 2014 ). Instead, most subsequent research has been based on internal fit and development and testing of linkage models. These typically propose that HR practices influence employee perceptions that in turn affect employee attitudes and behavior and subsequently employee performance. This can then be aggregated to proximal (e.g., productivity, service quality) and distal (e.g., financial) organizational performance. Elements and sometimes a complete linkage model have been tested, and research has typically reported support for the expected associations indicating full or partial mediation. The AMO model has been the most extensively tested, and the meta-analysis by Jiang et al. ( 2012 ) provides a good example of this. They linked measures of the HR bundles to indicators of human capital and motivation, and linked those in turn to labor turnover and internal measures of performance, and finally linked both of those to financial performance. They reported good evidence for these linkages and for partial mediation.

The AMO model suggests that HR practices succeed by leveraging employee behavior. Alternative models based on high-commitment or high-involvement rather than high-performance HRM utilize social exchange theory (Gong, Chang, & Cheun, 2010 ; Piening, Baluch, & Salge, 2013 ). The core argument is that if HR practices are used to enhance the commitment and involvement of employees and to ensure a positive employment relationship, this will in turn be positively perceived by employees at both an individual and collective level. It might, for example, be perceived in terms of fulfillment of the psychological contract (Rousseau & Greller, 1994 ) or in the form of perceived organizational support (Eisenberger, Cummings, Armeli, & Lynch, 1997 ). Based on the norm of reciprocity (Gouldner, 1960 ), employees can be expected to respond with positive attitudes and behavior. Research supports these linkages and shows an association with organizational commitment, organizational citizenship behavior, higher individual performance, and a lower propensity to quit the organization or be voluntarily absent (e.g., Kehoe & Wright, 2013 ; Takeuchi, Chen, & Lepak, 2009 ). Overall, therefore, there is consistent support for a linkage model. More research is needed to test competing explanations for these linkages and to understand why the strength of the association varies. Some issues, to which we now turn, offer possible explanations.

The Role of Employee Attributions

As the role of employees takes center stage in the analysis of the impact of HRM, it is recognized that to understand the effect of HRM on attitudes and behavior, it is first necessary to consider how employees perceive HR practices. Researchers have begun to use a form of attribution theory to explore how employees interpret management motives for adopting certain HR practices and to examine how their interpretation affects their attitudes and behavior. Nishii, Lepak, and Schneider ( 2008 ) researched attributions among employees in a large Japanese retail chain. They hypothesized that if employees attributed management’s use of HR practices to a desire to enhance quality of service or employee wellbeing, then the response would be positive and would, in turn, have a positive effect on customer service. In contrast, if they were attributed to management’s desire to enhance control over employees or to intensify work, then these negative attributions would feed through into less enthusiastic employee behaviors that would be reflected in customer evaluation of service quality in the branches. Their findings supported these hypotheses. Subsequent research by van de Voorde & Beijer ( 2015 ) tested the impact of wellbeing and performance attributions on individual employee outcomes and found that, as predicted, wellbeing attributions had a positive impact on commitment to the organization and on employee wellbeing, reflected in lower levels of job strain, whereas performance attributions resulted in higher levels of job strain. Both studies confirm the importance of understanding employee attributions in any model seeking to explain the links between HRM and outcomes.

Research on employee attributions highlights the potential role of signaling theory (Connelly, Certo, Ireland, & Reutzel, 2011 ), a variation on communication theory. To put it at its simplest, what do HR practices, singly or in combination, signal to employees? Rousseau and Greller ( 1994 ) used signaling theory to explain how HR practices communicated to workers the content of the psychological contract. Signaling theory formed the basis for an influential conceptual article by Bowen and Ostroff ( 2004 ) concerning the implementation of HRM. They support the view that it is not sufficient to have good HR practices in place; implementation is only likely to be effective if management can clearly signal the intentions behind the HR practices. They argue that this is more likely to be achieved when there is what they call a “strong” HR system. They hypothesize that this will entail three features that need to be clearly signaled: high consensus, implying agreement among the relevant stakeholders about the viability and fairness of the HR practices; high distinctiveness, implying that HR practices should be visible, understandable, and relevant; and high consistency, implying that HR practices complement each other and are seen as aiding goal achievement. Bowen and Ostroff’s approach suggests that strong leadership signaling support from the top of the organization is required to ensure a strong HR system and therefore an increased likelihood of effective implementation of HR practices.

Researchers have begun to test Bowen and Ostroff’s propositions. A first step has been to develop measures of the three core components and the sub-elements that Bowen and Ostroff outline (see, e.g., Delmotte, De Winne, & Sels, 2012 ; Coelho, Cunha, Gomes, & Correia, 2015 ). A second step has been to test the validity of the model by studying the association of the dimensions with performance outcomes (see, e.g., Sanders, Dorenbosch, & De Reuver, 2008 ; Li, Frenkel, & Sanders, 2011 ; Pereira & Gomes, 2012 ). The results of these studies highlight the complexity of the model, suggesting that it would benefit from some simplification. Secondly, they indicate that the distinctiveness dimension appears to be more important than the other dimensions, and that the relative importance of the three dimensions of HRM system strength seems to vary across studies and perhaps across national cultures. Despite the enthusiasm with which some researchers have been exploring the Bowen and Ostroff model, there may be a case for revisiting some of the underlying dimensions.

The HR Implementation Process and Actors

Research on attribution theory, signaling theory, and the strength of the HR system is concerned with HR implementation. It is based on recognition that the presence of HR practices is not enough to ensure that they have an impact. A related stream of research has explored the process of HR implementation by focusing more directly on the roles of the main actors. Guest and Bos-Nehles ( 2013 ) have outlined a descriptive framework that implicated several parties in the implementation process. Top management and senior HR managers have responsibility for deciding whether certain practices should be present. HR managers, perhaps with outside help from consultants and W/O psychologists, shape the quality of the practices. Line managers, with support from local HR managers, have to implement practices on a day-to-day basis, and in addition they need to be motivated to ensure that they are implemented in a high-quality rather than a ritualistic way. Finally, their impact depends on employees’ perceptions of and attributions about the practices. There has been some concern that line managers may be a weak link in this process. Case studies led Hope Hailey, Farndale, and Truss ( 2005 ) to conclude that in the U.K., line managers were neither willing nor able to accept their HR implementation role. In contrast, Bos-Nehles ( 2010 ) found that Dutch managers were motivated to ensure effective implementation of HR but often lacked the time to do so (Bos-Nehles, 2010 ). A study of the implementation of policy and practice to address bullying and harassment in healthcare (Woodrow & Guest, 2014 ) found that although best HR practices were in place, they were invariably poorly implemented due mainly to lack of senior management support, but also to employees’ perceptions that the HR systems were ineffective in helping to resolve incidents of bullying and harassment. This would appear to support Bowen and Ostroff’s argument about the need for a strong HR system with top-level support.

The interest in HRM implementation has increased the focus on the role of HR specialists. There has been a longstanding stream of research on the role of HR managers reflecting concerns about their lack of power and influence (see, e.g., Legge, 1978 ; Ritzer & Trice, 1969 ; Guest & King, 2004 ). In a highly influential attempt to boost the role, Ulrich has presented a stream of writing and research outlining evolving ideas about the HR department structure, the various HR roles, and HR competencies required for effective performance by HR professionals (see Ulrich, 1997 ; Ulrich & Brockbank, 2005 : Ulrich, Younger, Brockbank, & Ulrich, 2013 ). Underpinning his research was a desire to see the HR function contributing to effective HR implementation or, as he expressed it, moving from “doing” to “delivering.”

Ulrich’s ideas generated considerable excitement among HR professionals in several countries, resulting in a rush to implement them. However, they have also been the subject of extensive conceptual critiques (see, e.g., Caldwell, 2008 ) and empirical research (see, e.g., Buyens & De Vos, 2001 ; Wright, 2008 ), raising serious questions about the feasibility of implementing them beyond the context of large, predominantly U.S. private-sector organizations, something Ulrich himself recognized. Nevertheless, his work is important in highlighting the role of HR professionals who often serve as gatekeepers for the application of the research of W/O psychologists in organizations.

The Role of Individual Differences

As psychologists have become more interested in HRM, attention has begun to focus on individual differences. One illustration of this has been a broadening of the conceptualization of the characteristics that constitute human capital, reflected in the work of Ployhart and Moliterno ( 2011 ), including the role of personality and values as human capital. Another stream of research has been considering age and the question of whether specific HR practices or bundles of practices have a greater impact at different ages. The rationale for expecting that this might be the case draws on selection, optimization, and compensation (SOC) theory (Baltes, Staudinger, & Lindenberger, 1999 ). For example, Bal, Kooij, and De Jong ( 2013 ) and Kooij et al. ( 2013 ) have shown how developmental HR practices among younger workers and accommodative HR practices among older workers can enhance commitment and wellbeing. There would appear to be room to extend this approach to consider other individual differences such as gender and education, but also variations in employment circumstances like temporary employment and other forms of employment flexibility. For example, what sort of HR practices are most suitable for long-distance workers including those working from home?

The Use of Multilevel Analysis

Bowen and Ostroff’s ( 2004 ) model builds on previous work by Ostroff and Bowen ( 2000 ) in arguing for a multilevel approach for understanding HRM processes and their impact. Ployhart and Moliterno ( 2011 ) make a similar point with respect to the aggregation of human capital. There is a strong case for multilevel analysis when employee attitudes and behavior form part of the study but the primary concern is with organizational performance, something that has become relatively common in recent research (see, e.g., Liao et al., 2009 ; Messersmith et al., 2011 ; Piening, Baluch, & Salge, 2013 ). Another context is when moderating variables are hypothesized to affect outcomes, requiring the use of moderated mediation. The kinds of moderating variables that have attracted most research attention are organizational climate and leadership, but there is room to extend this type of research to consider a potentially wide range of moderating variables, including exogenous factors like business sector and market conditions.

Comparative HRM

HRM is potentially a very broad field, and its extensive scope can be illustrated through the large body of research and writing on comparative HR systems. While most multilevel analysis uses the organization as the highest level of analysis, a distinct body of research has explored HRM at the country level. This research studies comparative HR systems and the impact of national institutions and cultural factors in shaping the kind of HR practices that are likely to be acceptable and have impact. European countries typically have a stronger institutional framework, including legislation that requires certain practices to be in place. In a country such as the U.S., organizations have fewer constraints on the HR practices they can choose whether or not to apply. Along with the major comparative studies of national cultures and leadership, the Cranet project (see, e.g., Mayehofer & Brewster, 2005 ) has for years been conducting standard surveys in many countries collecting data on HR practices, the structure of the HR function, and perceptions of impact. Rabl, Jayasinghe, Gerhart, and Kuhlmann ( 2014 ) have analyzed country differences in the strength of the HRM-performance relationship across studies reported in 29 countries. Although in all cases, the associations were positive, there were wide country differences in the average strength of the association, and their hypotheses about the influence of two dimensions of national culture, namely tight-loose properties and degree of flexibility, were not supported.

In policy terms, research on comparative HRM is particularly relevant for international organizations sending managers on overseas assignments. Schuler, Dowling, and De Cieri ( 1993 ) have provided an integrative framework within which to consider international HRM, including overseas assignments. Black and Mendenhall ( 1990 ) have explored issues in selection and more particularly cross-cultural training methods, while Black, Mendenhall, and Oddou ( 1991 ) have outlined the steps necessary for effective adjustment to an overseas assignment. Doherty, Dickmann, and Mills ( 2011 ) have explored motives among company-initiated and self-initiated overseas assignments, while Bolino ( 2007 ) has analyzed the implications of such assignments for career success. Comparative HRM therefore provides a good example of how HRM research can be considered at different levels of analysis, from different disciplinary perspectives, and from both conceptual and applied perspectives.

The Importance of Longitudinal Research

Much of the reported research linking HRM and outcomes has been cross-sectional, raising questions about causality and leading to calls for longitudinal studies. Researchers have begun to answer this call. Birdi et al. ( 2008 ) examined the impact of three HR practices (training, teamwork, and empowerment) and four operational practices (total quality management, just-in-time, supply chain management, and advanced manufacturing techniques) on productivity in a large sample of manufacturing firms over a 22-year period. They found a positive impact of HR practices but not operational practices, and they also found no interaction between them. They reported a lengthy time lag of several years before any impact was significant. In contrast, Piening, Baluch, and Salge ( 2013 ), in a longitudinal study in healthcare, found support for a causal chain from employee perceptions to changes in job satisfaction to changes in patient satisfaction. However, they found that the impact was greatest in the first year and diminished thereafter. The longitudinal study in healthcare by West et al. ( 2006 ) reported a more direct association between the presence of more HR practices and mortality rates after controlling for a range of other potential influences.

Longitudinal studies have generally supported a causal ordering whereby HR practices affect outcomes. However, they have rarely considered the possibility of reverse causality. The potential for reverse causality is based on the assumption that high performance and, in particular, high financial performance create room for investment, including investment in human resources. There is also the possibility that working for a successful organization is a source of satisfaction that in turn further enhances performance, a conclusion that might be drawn from the longitudinal study of company-level performance and job satisfaction over a number of years reported by Schneider, Hanges, Smith, and Salvaggio ( 2003 ). In the context of HRM, Guest, Michie, Conway, and Sheehan ( 2003 ) reported an association between HRM and subsequent financial performance. However, when they controlled for prior performance, this association disappeared, raising questions about the causal ordering. It also raises wider questions about the size of impact of HRM, since few studies have taken into account prior financial performance. This point is strongly reinforced in a study by Shin and Konrad ( 2016 ) that used a longitudinal Canadian company-level dataset to explore the relation over time between HRM and productivity. After controlling for past performance and past HRM, they found a modest positive two-way causal link between the variables, with each having an influence on the other over three two-year time lags. The study by Piening, Baluch, and Salge ( 2013 ) found support for a cyclical process whereby HRM affected outcomes and these in turn affected HR practices. But Van de Voorde, Paauwe, and van Veldhoven ( 2010 ), in a cross-lagged study, found that an “HR-indexed” measure of organizational climate had an impact on organizational performance, though there was no evidence of performance influencing climate.

These studies help to highlight the challenges of establishing the causal direction in the HRM-outcomes relationship and challenge the size of the associations reported in cross-sectional studies. When the outcome is financial performance, one of the problems is that it tends to be very stable from year to year, leaving only a small amount of variance to explain. The same may be the case for HR practices. There are also major challenges in controlling for other endogenous and exogenous variables. What may be needed are naturally occurring quasi-experimental studies, possibly at branch levels. At a micro level, W/O psychologists have been more successful in demonstrating causality with respect, for example, to interventions for improving selection, training, or job design. Since the distinctive feature of HRM is that it needs to be considered as a system of practices and is more typically explored at the unit or organizational level, this presents distinctive challenges of access over time and interpretation of results when other factors are hard to control for. Understanding the dynamics of changes in the use of HR practices may require in-depth longitudinal, qualitative studies along with the dominant quantitative research.

HRM provides an important context for research in W/O psychology. It incorporates the core practices and activities that constitute W/O psychologists’ areas of expertise. HR departments often act as gatekeepers for W/O psychologists from outside the organization or as hosts for those working within it. HRM extends the traditional domain of W/O psychologists by incorporating strategic issues, and it raises ethical issues in terms of the “utilization” of employees that can sometimes spill over into “exploitation.” It is therefore important that research on outcomes addresses the impact of employee wellbeing while at the same time recognizing the pragmatic political requirement to explore those contexts, conditions, policies, and practices that offer the potential for both high performance and high wellbeing. HRM is a broad topic that has attracted an extensive and growing body of research. It also raises a lot of challenging research questions. Its multilevel, multidisciplinary characteristics pose additional challenges for W/O psychologists. But it is an important applied subject with room to link theory, research, and application, and it is one to which W/O psychology is making an increasingly significant contribution.

Further Reading

• Bockerman, P. , Bryson, A. , & Ilmakunnas, P. (2012). Does high involvement management improve worker well-being? Journal of Economic Behavior and Organization , 84 , 660–680.
• Boxall, P. , Purcell, J. , & Wright, P. (Eds.). (2007). The Oxford handbook of human resource management . Oxford: Oxford University Press.
• Brewster, C. , & Mayrhofer, W. (Eds.). (2012). Handbook of research on comparative HRM . Cheltenham, U.K.: Edward Elgar.
• Cascio, W. , & Boudreau, J. (2012). A short introduction to strategic human resource management . New York: Cambridge University Press.
• Legge, K. (2005). Human resource management: Rhetorics and realities . Basingstoke, U.K.: Palgrave Macmillan.
• Paauwe, J. , Guest, D. , & Wright, P. (2013). HRM and performance: Achievements and challenges . Chichester, U.K.: Wiley.
• Pfeffer, J. (1998). The human equation: Building profits by putting people first . Boston: Harvard Business School Press.
• Rynes, S. , Giluk, T. , & Brown, G. (2007). The very separate worlds of academic and practitioner periodicals in human resources management: Implications for evidence-based management. Academy of Management Journal , 50 (5), 987–1008.
• Thompson, P. (2011). The trouble with HRM. Human Resource Management Journal , 21 (4), 355–367.
• Warner, M. (Ed.). (2011). Society and HRM in China . London: Routledge.
• Aguinis, H. , & Kraiger, K. (2009). Benefits of training and development for individuals and teams, organizations and society. Annual Review of Psychology , 60 , 451–474.
• Arthur, J. (1994). Effects of human resource management systems on manufacturing performance and turnover. Academy of Management Journal , 37 (3), 670–687.
• Bal, M. , Kooij, T. , & De Jong, S. (2013). How do developmental and accommodative hrm enhance employee engagement and commitment? The role of the psychological contract and SOC strategies. Journal of Management Studies , 50 (4), 545–572.
• Baltes, P. , Staudinger, U. , & Lindenberger, U. (1999). Lifespan psychology: Theory and application to intellectual functioning. Annual Review of Psychology , 50 , 471–507.
• Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management , 17 (1), 99–120.
• Barney, J. , & Wright, P. (1998). On becoming a strategic partner: The role of human resources in gaining competitive advantage. Human Resource Management , 37 (1), 31–46.
• Becker, G. (1964). Human capital . New York: Columbia University Press.
• Becker, B. , & Gerhart, B. (1996). The impact of human resource management on organizational performance: Progress and prospects. Academy of Management Journal , 39 (4), 779–801.
• Becker, B. , & Huselid, M. (1998). High performance work systems and firm performance: A synthesis of research and managerial implications. In K. Rowland & G. Ferris (Eds.), Research in personnel and human resource management (pp. 53–101). Greenwich, CT: JAI Press.
• Becker, B. , Huselid, M. , Pickus, P. , & Spratt, M. (1997). HR as a source of shareholder value: Research and recommendations. Human Resource Management , 36 (1), 39–48.
• Beer, M. , Spector, B. , Lawrence, P. , Quinn Mills, D. , & Walton, R. (1985). Human resource management: A general manager perspective . New York: Free Press.
• Birdi, K. , Clegg, C. , Patterson, M. , Robinson, A. , Stride, C. , Wall, T. , & Wood, S. (2008). The impact of human resource and operational management practices on company productivity: A longitudinal study. Personnel Psychology , 61 (3), 467–501.
• Black, S. , & Mendenhall, M. (1990). Cross-cultural training effectiveness: A review and theoretical framework for further research. Academy of Management Review , 15 (1), 113–136.
• Black, S. , Mendenhall, M. , & Oddou, G. (1991). Towards a comprehensive model of international adjustment: An integration of multiple theoretical perspectives. Academy of Management Review , 16 (2), 291–317.
• Bolino, M. (2007). Expatriate assignments and intra-organizational career success: Implications for individuals and organizations. Journal of International Business Studies , 38 (5), 819–835.
• Boselie, P. , Dietz, G. , & Boon, C. (2005). Commonalities and contradictions in HRM and performance research. Human Resource Management Journal , 15 (3), 67–94.
• Bos-Nehles, A. (2010). The line makes the difference: Line managers as effective hr partners . Zutphen, The Netherlands: CPI Wohrmann.
• Bowen, D. , & Ostroff, C. (2004). Understanding HRM-performance linkages: The role of the “strength” of the HRM system. Academy of Management Review , 29 (2), 203–221.
• Boxall, P. , & Macky, K. (2009). Research and theory on high performance work systems: Progressing the high involvement work stream. Human Resource Management Journal , 19 (1), 3–23.
• Boxall, P. , & Purcell, J. (2011). Strategy and human resource management (3d ed.). Basingstoke, U.K.: Palgrave Macmillan.
• Buyens, D. , & De Vos, A. (2001). Perceptions of the value of the HR function. Human Resource Management Journal , 11 (3), 70–89.
• Caldwell, R. (2008). HR business partner competency models: Re-contextualising effectiveness. Human Resource Management Journal , 18 (3), 275–294.
• Clinton, M. , & van Veldhoven, M. (2013). HRM and employee well-being. In S. Bach & M. Edwards (Eds.), Managing human resources (5th ed., pp. 364–388). Chichester, U.K.: Wiley.
• Coelho, J. , Cunha, R. , Gomes, J. , & Correia, A. (2015). Strength of the HR system: The development of a measure. Journal of Industrial Engineering and Management , 8 (4), 1069–1086.
• Combs, J. , Liu, Y. , Hall, A. , & Ketchen, D. (2006). How much do high-performance work systems matter? A meta-analysis of their effects on organizational performance. Personnel Psychology , 59 (3), 501–528.
• Connelly, B. , Certo, T. , Ireland, D. , & Reutzel, C. (2011). Signaling theory: A review and assessment. Journal of Management , 37 (1), 39–67.
• Crook, T. , Todd, S. , Combs, J. , Woehr, D. , & Ketchen, D. (2011). Does human capital matter? A meta-analysis of the relationships between human capital and firm performance. Journal of Applied Psychology , 96 (3), 443–456.
• Delery, J. , & Doty, D. (1996). Modes of theorizing in strategic human resource management: Tests of universalistic, contingency and configurational performance predictions. Academy of Management Journal , 39 (4), 802–835.
• Delmotte, J. , DeWinne, S. , & Sels, L. (2012). Toward an assessment of perceived HRM system strength: Scale development and validation. International Journal of Human Resource Management , 23 (7), 1481–1506.
• Doherty, N. , Dickmann, M. , & Mills, T. (2011). Exploring the motives of company-based and self-initiated expatriates. International Journal of Human Resource Management , 22 (3), 595–611.
• Eisenberger, R. , Cummings, J. , Armeli, S. , & Lynch, P. (1997). Perceived organizational support, discretionary treatment and job satisfaction. Journal of Applied Psychology , 82 (5), 812–820.
• Fombrun, C. , Tichy, N. , & Devanna, M. (1984). Strategic human resource management . New York: Wiley.
• Forth, J. , & McNabb, R. (2008). Workforce performance: A comparison of subjective and objective measures in the 2004 WERS. Industrial Relations Journal , 39 (2), 104–123.
• Givan, R. , Avgar, A. , & Liu, M. (2010). Having your cake and eating it? The relationship between HR and organizational performance in healthcare. Advances in Industrial and Labor Relations , 17 , 31–67.
• Godard, J. (2004). A critical assessment of the high performance paradigm. British Journal of Industrial Relations , 42 (2), 439–478.
• Gong, Y. , Chang, S. , & Cheung, S. (2010). High-performance work system and collective OCB: A collective social exchange perspective. Human Resource Management Journal , 20 (2), 119–137.
• Gouldner, A. (1960). The norm of reciprocity: A preliminary statement. American Sociological Review , 25 (2), 161–178.
• Guest, D. (1997). Human resource management and performance: A review and research agenda. International Journal of Human Resource Management , 8 (3), 263–276.
• Guest, D. , & Bos-Nehles, A. (2013). HRM and performance: The role of effective implementation. In J. Paauwe , D. Guest , & P. Wright (Eds.), HRM and performance: Achievements and challenges (pp. 79–98). Chichester, U.K.: Wiley.
• Guest, D. , & King, Z. (2004). Power, innovation and problem-solving: The personnel manager’s three steps to heaven? Journal of Management Studies , 41 (3), 401–423.
• Guest, D. , Michie, J. , Conway, N. , & Sheehan, M. (2003). Human resource management and corporate performance in the UK. British Journal of Industrial Relations , 41 (2), 291–314.
• Hope, H. , Farndale, E. , & Truss, K. (2005). The HR department’s role in organizational performance. Human Resource Management Journal , 15 (3), 49–66.
• Huselid, M. (1995). The impact of human resource management practices on turnover, productivity and organizational financial performance. Academy of Management Journal , 38 (3), 635–672.
• Ichniowski, C. , Shaw, K. , & Prennushi, G. (1997). The effects of human resource management practices on productivity: A study of steel finishing mills. The American Economic Review , 87 (3), 291–313.
• Jackson, S. , Schuler, R. , & Jiang, K. (2014). An aspirational framework for strategic human resource management. Academy of Management Annals , 8 (1), 1–56.
• Jiang, K. , Lepak, D. , Hu, J. , & Baer, J. (2012). How does human resource management influence organizational outcomes? A meta-analytic investigation of mediating mechanisms. Academy of Management Journal , 55 (6), 1264–1294.
• Kehoe, R. , & Wright, P. (2013). The impact of high-performance human resource practices on employees’ attitudes and behaviors. Journal of Management , 39 (2), 366–391.
• Khilji, S. , & Wang, X. (2006). “Intended” and “implemented” HRM: The missing linchpin in strategic human resource management research. International Journal of Human Resource Management , 17 (7), 1171–1189.
• Kooij, D. , Guest, D. , Clinton, M. , Knight, T. , Janson, P. , & Dikkers, J. (2013). How the impact of HR practices on employee well-being changes with age. Human Resource Management Journal , 23 (1), 18–35.
• Lawler, E. (1971). Pay and organizational effectiveness: A psychological view . New York: McGraw-Hill.
• Legge, K. (1978). Power, innovation and problem-solving in personnel management . London: McGraw-Hill.
• Lepak, D. , & Snell, S. (1999). The human resource architecture: Toward a theory of human capital allocation and development. Academy of Management Review , 24 (1), 31–48.
• Lepak, D. , & Snell, S. (2002). Examining the human resource architecture: The relationships among human capital, employment and human resource configurations. Journal of Management , 28 (4), 517–543.
• Li, X. , Frenkel, S. , & Sanders, K. (2011). Strategic HRM as process: How HR system and organizational climate strength influence Chinese employee attitudes. International Journal of Human Resource Management , 22 (9), 1825–1842.
• Liao, H. , Toya, K. , Lepak, D. , & Hong, Y. (2009). Do they see eye to eye? Management and employee perspectives of high-performance work systems and influence processes on service quality. Journal of Applied Psychology , 94 (2), 371–391.
• Mayrhofer, W. , & Brewster, C. (2005). European human resource management: Researching developments over time. Management Revue , 16 (1), 36–62.
• Messersmith, J. , Patel, P. , Lepak, D. , & Gould-Williams, J. (2011). Unlocking the black box: Exploring the link between high-performance work systems and performance. Journal of Applied Psychology , 96 (6), 1105–1118.
• Miles, R. , & Snow, C. (1984). Fit, failure and the hall of fame. California Management Review , 26 , 10–28.
• Nishii, L. , Lepak, D. , & Schneider, B. (2008). Employee attributions of the “why” of HR practices: Their effects on employee attitudes and behaviors, and customer satisfaction.” Personnel Psychology , 61 (3), 503–545.
• Nyberg, A. , & Wright, P. (2015). 50 years of human capital research: Assessing what we know, exploring where we go. Academy of Management Perspectives , 29 (3), 287–295.
• Ostroff, C. , & Bowen, D. (2000). Moving HR to a higher level: Human resource practices and organizational effectiveness. In K. Klein & W. Kozlowski (Eds.), Multilevel theory , research and methods in organizations (pp. 211–266). San Francisco: Jossey Bass.
• Paauwe, J. (2004). HRM and performance: Achieving long-term viability . Oxford: Oxford University Press.
• Peccei, R. , van de Voorde, K. , & van Veldhoven, M. (2013). HRM, well-being and performance: A theoretical and empirical view. In J. Paauwe , D. Guest , & P. Wright (Eds.), HRM and performance: Achievements and challenges (pp. 15–46). Chichester, U.K.: Wiley.
• Peel, S. , & Boxall, P. (2005). When is contracting preferable to employment? An exploration of management and worker perspectives. Journal of Management Studies , 42 (8), 1675–1699.
• Pereira, C. , & Gomes, J. (2012). The strength of human resource practices and transformational leadership: Impact on organisational performance. International Journal of Human Resource Management , 23 (20), 4301–4318.
• Piening, E. , Baluch, A. , & Salge, T. (2013). The relationship between employees’ perceptions of human resource systems and organizational performance: Examining mediating mechanisms and temporal dynamics. Journal of Applied Psychology , 98(6), 926–947.
• Ployhart, R. , & Moliterno, T. (2011). Emergence of the human capital resource: A multi-level model. Academy of Management Review , 36 (1), 127–150.
• Ployhart, R. , Nyberg, A. , Reilly, G. , & Maltarich, M. (2014). Human capital is dead: Long live human capital resources. Journal of Management , 40 (2), 371–398.
• Porter, M. (1985). Competitive advantage: Creating and sustaining superior performance . New York: Free Press.
• Rabl, T. , Jayasinghe, M. , Gerhart, B. , & Kuhlmann, T. (2014). A meta-analysis of country differences in the high-performance work system-business performance relationship: The roles of national culture and managerial discretion. Journal of Applied Psychology , 99 (6), 1011–1041.
• Ramsay, H. , Scholarios, D. , & Harley, B. (2000). Employees and high-performance work systems: Testing inside the black box. British Journal of Industrial Relations , 38 (4), 501–531.
• Ritzer, G. , & Trice, A. (1969). An occupation in conflict . Ithaca, NY: Cornell University Press.
• Roethlisberger, F. , & Dickson, W. (1939). Management and the worker . Cambridge, MA: Harvard University Press.
• Rousseau, D. , & Greller, M. (1994). Human resource practices: Administrative contract makers. Human Resource Management , 33 (3), 385–401.
• Sanders, K. , Dorenbosch, L. , & De Reuver, R. (2008). The impact of individual and shared employee perceptions of HRM on affective commitment: Considering climate strength. Personnel Review , 37 (4), 412–425.
• Schmidt, F. , & Hunter, J. (1998). The Validity and Utility of Selection Methods in Personnel Psychology : Practical and theoretical implications over 85 years of research findings. Psychological Bulletin , 124 (2), 262–274.
• Schneider, B. , Hanges, P. , Smith, D. , & Salvaggio, A. (2003). Which comes first: Employee attitudes or financial and market performance?” Journal of Applied Psychology , 88 (5), 836–851.
• Schuler, R. , & Jackson, S. (1987). Linking competitive strategies with human resource management practices. Academy of Management Executive , 1 (3), 207–219.
• Schuler, R. , Dowling, P. , & De Cieri, H. (1993). An integrative framework of strategic international human resource management. Journal of Management , 19 (2), 419–459.
• Shin, D. , & Konrad, A. (2016). Causality between high-performance work systems and organizational performance. Journal of Management .
• Subramony, M. (2009). A meta-analytic investigation of the relationship between HRM bundles and firm performance. Human Resource Management , 48 (5), 745–768.
• Takeuchi, R. , Chen, G. , & Lepak, D. (2009). Through the looking glass of a social system: Cross-lagged effects of high-performance work systems on employee attitudes. Personnel Psychology , 62 (1), 1–29.
• Ulrich, D. (1997). Human resource champions . Boston: Harvard Business School Press.
• Ulrich, D. , & Brockbank, W. (2005). The HR value proposition . Boston: Harvard Business School Press.
• Ulrich, D. , Younger, J. , Brockbank, W. , & Ulrich, M. (2013). The state of the HR profession. Human Resource Management , 52 (3), 457–471.
• Van de Voorde, K. , & Beijer, S. (2015). The role of employee HR attributions in the relationship between high-performance work systems and employee outcomes. Human Resource Management Journal , 25 (1), 62–78.
• Van de Voorde, K. , Paauwe, J. , & van Veldhoven, M. (2010). Predicting business unit performance using employee surveys: Monitoring HRM-related changes. Human Resource Management Journal , 20 (1), 44–63.
• Van de Voorde, K. , Paauwe, J. , & Van Veldhoven, M. (2012). Employee Well-being and the HRM-performance relationship: A review of quantitative studies. International Journal of Management Reviews , 14 (4), 391–407.
• Van Eerde, W. , & Thierry, H. (1996). Vroom’s expectancy model and work-related criteria: A meta-analysis. Journal of Applied Psychology , 81 (5), 575–586.
• Van Wanrooy, B. , Bewley, H. , Bryson, A. , Forth, J. , Freeth, S. , Stokes, L. , & Wood, S. (2013). Employment relations in the shadow of recession . Basingstoke, U.K.: Macmillan.
• Wall, T. , Michie, J. , Patterson, M. , Wood, S. , Sheehan, M. , Clegg, C. , & West, M. (2004). On the validity of subjective measures of company performance. Personnel Psychology , 57 (1), 95–118.
• Walton, R. (1985). From control to commitment in the workplace. Harvard Business Review , 63 (2), 77–84.
• Walton, R. , & McKersie, R. (1965). A behavioral theory of labor negotiations . New York: McGraw-Hill.
• West, M. , Guthrie, J. , Dawson, J. , Borrill, C. , & Carter, M. (2006). Reducing patient mortality in hospitals: The role of human resource management. Journal of Organizational Behavior , 27 (7), 983–1002.
• Whyte, W. (1955). Money and motivation: An analysis of incentives in industry . New York: Harper.
• Woodrow, C. , & Guest, D. (2014). When good HR gets bad results: Exploring the challenge of HR implementation in the case of workplace bullying. Human Resource Management Journal , 24 (1), 38–56.
• Wright, C. (2008). Reinventing human resource management: Business partners, internal consultants and limits to professionalization. Human Relations , 61 (8), 1063–1086.
• Wright, P. , & Boswell, W. (2002). Desegregating HRM: A review and synthesis of micro and macro human resource management research. Journal of Management , 28 (3), 247–276.
• Wood, S. , & Albanese, M. (1995). Can we speak of high commitment management on the shop floor? Journal of Management Studies , 3 (2), 215–247.

Related Articles

• Personnel Selection
• Organizational Behavior
• Creativity at Work
• Organizational Sensemaking
• Organizational Climate and Culture
• Corporate Social Responsibility: An Overview from an Organizational and Psychological Perspective

Printed from Oxford Research Encyclopedias, Psychology. Under the terms of the licence agreement, an individual user may print out a single article for personal use (for details see Privacy Policy and Legal Notice).

date: 23 August 2024

• Cookie Policy
• Privacy Policy
• Legal Notice
• Accessibility
• [81.177.180.204]
• 81.177.180.204

Character limit 500 /500

Academia.edu no longer supports Internet Explorer.

To browse Academia.edu and the wider internet faster and more securely, please take a few seconds to  upgrade your browser .

Enter the email address you signed up with and we'll email you a reset link.

• We're Hiring!
• Help Center

Human Behavior In Organization

Related Papers

Mesfin Lemma

Arpit Bhatia

BIKORIMANA JEAN BOSCO

Plarent Aleksi

When it comes to organization, implicitly, we essentially are talking about the man and his social nature, but at the same time when you try to build any motivational theory on increasing organizational collaboration we analyze the nature and essence of the human being as individual. Without considering for the moment the economic systems overlaid into the social structure, there is a great work to be done on understanding the needs of the Organization.

Martika Erry

Abubakar Sadiq Junaidu

Hartwell T P Davis

Atusaye Mwafulirwa

Loading Preview

Sorry, preview is currently unavailable. You can download the paper by clicking the button above.

RELATED PAPERS

Benjie Ubpon

Andrew Kampolo

Jeffrey Goldberg

Ruchira Bhargava

Springer International Publishing AG 2017 A. Farazmand (ed.), Global Encyclopedia of Public Administration, Public Policy, and Governance,

Francesca Flood

sandamali Ekanayake

rama prasad

Anam Ansari

Rimla Masood

European Journal of Business and Management

Md. Shaniul Alam

jean perdue

Choi Sun Moo

IJIRIS:: AM Publications

IJIRIS Journal Division

Jamel Chafra

Nazia Dharejo

Hersh Glueck

Artūras Visockas

Faizzudin Rosli

rakesh kumar

Omesha Pathumini

•   We're Hiring!
•   Help Center
• Find new research papers in:
• Health Sciences
• Earth Sciences
• Cognitive Science
• Mathematics
• Computer Science
• Academia ©2024

Eliciting Thresholds for Interdependent Behavior

Threshold models have been widely used to analyze interdependent behavior, yet empirical research identifying people’s thresholds is nonexistent. We introduce an incentivized method for eliciting thresholds and use it to study support for affirmative action in a large, stratified sample of the U.S. population. Most Asian, Black, Hispanic, and White men and women condition their support for affirmative action on the number of others supporting it. In line with preregistered hypotheses, thresholds are influenced by one’s perceived benefits and pressure to conform. We demonstrate how our method can offer unique insights for policy design and enhance understanding of social dynamics.

We thank seminar participants at the University of Bologna, University of Cologne, Middlebury College, Norwegian Business School, New York University, University of Arizona, University of Texas at Dallas, University of Verona, and audiences at the 2024 Social Norms Workshop Ascona, 2024 Barcelona Summer Forum, the 2024 Dynamics of Social Change workshop at NYU Abu Dhabi, the 2023 World ESA conference in Lyon, and the 2023 ESA Africa conference in Cape Town. The project was pre-registered at AEARCTR-0010895 on March 03, 2023. IRB approval has been obtained by the NYUAD (HRPP-2022-74) and UT Dallas (IRB-22-582) Institutional Review Boards. MJ and NN gratefully acknowledge financial support from Tamkeen under NYU Abu Dhabi Research Institute Award CG005. NN and SS gratefully acknowledge financial support from the National Science Foundation (grant #2242443). The views expressed herein are those of the author and do not necessarily reflect the views of the National Bureau of Economic Research.

MARC RIS BibTeΧ

Download Citation Data

More from NBER

In addition to working papers , the NBER disseminates affiliates’ latest findings through a range of free periodicals — the NBER Reporter , the NBER Digest , the Bulletin on Retirement and Disability , the Bulletin on Health , and the Bulletin on Entrepreneurship  — as well as online conference reports , video lectures , and interviews .

arXiv's Accessibility Forum starts next month!

Help | Advanced Search

Computer Science > Robotics

Title: dvrp-mhsi: dynamic visualization research platform for multimodal human-swarm interaction.

Abstract: In recent years, there has been a significant amount of research on algorithms and control methods for distributed collaborative robots. However, the emergence of collective behavior in a swarm is still difficult to predict and control. Nevertheless, human interaction with the swarm helps render the swarm more predictable and controllable, as human operators can utilize intuition or knowledge that is not always available to the swarm. Therefore, this paper designs the Dynamic Visualization Research Platform for Multimodal Human-Swarm Interaction (DVRP-MHSI), which is an innovative open system that can perform real-time dynamic visualization and is specifically designed to accommodate a multitude of interaction modalities (such as brain-computer, eye-tracking, electromyographic, and touch-based interfaces), thereby expediting progress in human-swarm interaction research. Specifically, the platform consists of custom-made low-cost omnidirectional wheeled mobile robots, multitouch screens and two workstations. In particular, the mutitouch screens can recognize human gestures and the shapes of objects placed on them, and they can also dynamically render diverse scenes. One of the workstations processes communication information within robots and the other one implements human-robot interaction methods. The development of DVRP-MHSI frees researchers from hardware or software details and allows them to focus on versatile swarm algorithms and human-swarm interaction methods without being limited to fixed scenarios, tasks, and interfaces. The effectiveness and potential of the platform for human-swarm interaction studies are validated by several demonstrative experiments.

Submission history

Access paper:.

• Other Formats

References & Citations

• Google Scholar
• Semantic Scholar

BibTeX formatted citation

Bibliographic and Citation Tools

Code, data and media associated with this article, recommenders and search tools.

• Institution

arXivLabs: experimental projects with community collaborators

arXivLabs is a framework that allows collaborators to develop and share new arXiv features directly on our website.

Both individuals and organizations that work with arXivLabs have embraced and accepted our values of openness, community, excellence, and user data privacy. arXiv is committed to these values and only works with partners that adhere to them.

Have an idea for a project that will add value for arXiv's community? Learn more about arXivLabs .