job quality thesis

What is a good job? Modelling, measuring and improving job quality

Publication date, ethos persistent id, administrator link.

• https://repository.lboro.ac.uk/account/articles/9355418

Usage metrics

• Design not elsewhere classified

Scope and limitations of a capability-based measure of Job Quality in Central America

Original bundle

License bundle

Collections.

Digitalization, Job Quality, and Subjective Well-being

• Living reference work entry
• First Online: 11 November 2022
• Cite this living reference work entry

• Ludivine Martin 2 , 3 , 4 &
• Laetitia Hauret 2  

266 Accesses

2 Citations

4 Altmetric

The public debate on the consequences of digitalization for the labor market focuses mainly on the quantity of jobs. However, the potential consequences of digitalization regarding the quality of employment should not be forgotten. The current chapter reviews the literature for developed countries on the link between digitalization and employees’ well-being in its objective and subjective dimensions. Six facets of job quality generally studied in the literature are examined: labor income, safety at work, working time and work-life balance, job security, skill development and training, employment-related relationships and work motivation. The chapter also reviews the related literature on the impacts of digitalization on subjective well-being, captured by self-reported feelings of employees at work, such as job satisfaction, job stress, and life satisfaction. The key findings in the literature are highlighted and relevant knowledge is identified. Researchers have extensively studied the links between digitalization and job quality in terms of labor income and work-life balance. However, studies on the link between digitalization and safety at work, job security, skills development, relationships at work, work motivation, or self-reported feelings remain scarce, and this calls for further research. Regardless of the outcome variable, studies report mixed results. Differences in how technology and outcome variables are measured and conceptualized, as well as the national and time context and employees’ characteristics, may explain these divergent results and conclusions.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Institutional subscriptions

Similar content being viewed by others

Digitalisation and Employees’ Subjective Job Quality in the Second Half of Working Life in Germany

Decomposing the effects of digitalization on workers’ job satisfaction

The Impact of New Technologies on the Quality of Work

Abeliansky AL, Beulmann M (2021) Are they coming for us? Industrial robots and the mental health of workers. Cent Eur Gov Econ Dev Res Discuss Pap No. 379

Google Scholar  

Acemoglu D, Autor DH (2011) Skills, tasks and technologies: Implications for employment and earnings. In: Card D, Ashenfelter OC (eds) Handbook of labor economics. Elsevier Inc, pp 1043–1171

Acemoglu D, Lelarge C, Restrepo P (2020) Competing with robots: Firm-level evidence from France. AEA Pap Proc 110:383–388. https://doi.org/10.1257/pandp.20201003

Article   Google Scholar  

Acemoglu D, Restrepo P (2020) Robots and jobs: Evidence from US labor markets. J Polit Econ 128:2188–2244. https://doi.org/10.1086/705716

Acemoglu D, Restrepo P (2019) Artificial Intelligence, automation and work. In: Agrawal A, Gans JS, Goldfarb A (eds) The economics of artificial intelligence: An agenda. National Bureau of Economic Research conference report. The University of Chicago Press, Chicago/London

Aghion P, Antonin C, Bunel S, Jaravel X (2020) What are the labor and product market effects of automation? New evidence from France. Harvard Univ, Mimeo

Aksoy CG, Ozcan B, Philipp J (2020) Robots and the gender pay gap in Europe. IZA Discuss. Pap. No 13482, pp 1–32

Ang MCH, Ramayah T, Amin H (2015) The experience of work life balance for Irish senior managers. Equal Divers Incl 34:186–200. https://doi.org/10.1108/GM-12-2013-0140

Anton J-I, Fernandez-Macias E, Winter-Ebmer R (2020) Does robotization affect job quality? Evidence from European regional labour markets. CEPR Discuss. Pap. No 15586

Book   Google Scholar  

Arlinghaus A, Nachreiner F (2013) When work calls-associations between being contacted outside of regular working hours for work-related matters and health. Chronobiol Int 30:1197–1202. https://doi.org/10.3109/07420528.2013.800089

Arntz M, Gregory T, Zierahn U (2019) In: Zimmermann KF (ed) Digitalization and the future of work: Macroeconomic consequences. Handbook of Labor, Human Resources and Population Economics

Arntz M, Gregory T, Zierahn U (2016) The risk of automation for jobs in OECD countries: A comparative analysis. OECD Work. Pap. Ser. No 189

Askenazy P, Caroli E (2010) Innovative work practices, information technologies, and working conditions: Evidence for France. Ind Relat (Berkeley) 49:544–565. https://doi.org/10.1111/j.1468-232X.2010.00616.x

Atalay E, Phongthiengtham P, Sotelo S, Tannenbaum D (2018) New technologies and the labor market. J Monet Econ 97:48–67. https://doi.org/10.1016/j.jmoneco.2018.05.008

Autor DH, Dorn D (2013) The growth of low-skill service jobs and the polarization of the US labor market. Am Econ Rev 103:1553–1597. https://doi.org/10.1257/aer.103.5.1553

Autor DH, Handel MJ (2013) Putting tasks to the test: Human capital, job tasks, and wages. J Labor Econ 31:S59–S96. https://doi.org/10.1086/669332

Autor DH, Katz LF (1999) Changes in the wage structure and earnings inequality. In: Ashenfelter O, Card D (eds) Handbook of Labor Economics, vol 3A. Elsevier, Amsterdam, pp 1463–1555

Autor DH, Levy F, Murnane RJ (2003) The skill content of recent technological change: An empirical exploration. Q J Econ 118:1279–1333. https://doi.org/10.1162/003355303322552801

Bachmann R, Gonschor M, Lewandowski P, Madoń K (2021) The impact of robots on labour market transitions in Europe. H2020 UNTANGLED Proj. Work. Pap

Bala H, Venkatesh V (2016) Adaptation to information technology: A holistic nomological network from implementation to job outcomes. Manag Sci 62:156–179. https://doi.org/10.1287/mnsc.2014.2111

Bartel A, Ichniowski C, Shaw K (2007) How does information technology affect productivity? Plant-level comparisons of product innovation, process improvement and worker skills. Q J Econ 122:1721–1758. https://doi.org/10.1162/qjec.2007.122.4.1721

Barth E, Røed M, Schøne P, Umblijs J (2020) How robots change within-firm wage inequality. IZA Discuss Pap No 13605

Baumeister VM, Kuen LP, Bruckes M, Schewe G (2021) The relationship of work-related ICT use with well-being, incorporating the role of resources and demands: A meta-analysis. SAGE Open 11. https://doi.org/10.1177/21582440211061560

Bessen JE, Goos M, Salomons AM, Van Den Berge W (2019) Automatic reaction – What happens to workers at firms that automate? Available SSRN 3328877. https://doi.org/10.2139/ssrn.3328877

Bittman M, Brown JE, Wajcman J (2009) The mobile phone, perpetual contact and time pressure. Work Employ Soc 23:673–691. https://doi.org/10.1177/0950017009344910

Bloom N, Garicano L, Sadun R, Van Reenen J (2014) The distinct effects of information technology and communication technology on firm organization. Manag Sci 60:2859–2885. https://doi.org/10.1287/mnsc.2014.2013

Boswell WR, Olson-Buchanan J (2007) The use of communication technologies after hours: The role of work attitudes and work-life conflict. J Manage 33:592–610

Brougham D, Haar J (2018) Smart technology, Artificial intelligence, Robotics, and Algorithms (STARA): Employees’ perceptions of our future workplace. J Manag Organ 24:239–257. https://doi.org/10.1017/jmo.2016.55

Brown R, Duck J, Jimmieson N (2014) E-mail in the workplace: The role of stress appraisals and normative response pressure in the relationship between e-mail stressors and employee strain. Int J Stress Manag 21:325–347. https://doi.org/10.1037/a0037464

Brussevich M, Dabla-Norris E, Khalid S (2019) Is technology widening the gender gap? Automation and the future of female employment. IMF Work Pap 19/91

Brynjolfsson E, Rock D, Syverson C (2019) In: Agrawal A, Gans J, Goldfarb A (eds) Artificial Intelligence and the modern productivity paradox: A clash of expectations and statistics. The Economics of Artifical intelligence: An Agenda

Chapter   Google Scholar  

Carbonero F, Ernst E, Weber E (2018) Robots worldwide: The impact of automation on employment and trade

Carlson JR, Carlson DS, Zivnuska S et al (2017) Applying the job demands resources model to understand technology as a predictor of turnover intentions. Comput Hum Behav 77:317–325. https://doi.org/10.1016/j.chb.2017.09.009

Caselli F, Manning A (2019) Robot arithmetic: New technology and wages. Am Econ Rev Insights 1:1–12. https://doi.org/10.1257/aeri.20170036

Caselli M, Fracasso A, Marcolin A, Scicchitano S (2021) The reassuring effect of firms’ technological innovations on workers’ job insecurity. GLO Discuss. Pap. No. 938

Castellacci F, Tveito V (2018) Internet use and well-being: A survey and a theoretical framework. Res Policy 47:308–325. https://doi.org/10.1016/j.respol.2017.11.007

Castellacci F, Viñas-Bardolet C (2019) Internet use and job satisfaction. Comput Hum Behav 90:141–152. https://doi.org/10.1016/j.chb.2018.09.001

Chesley N (2005) Blurring boundaries? Linking technology use, spillover, individual distress, and family satisfaction. J Marriage Fam 67:1237–1248. https://doi.org/10.1111/j.1741-3737.2005.00213.x

Chiacchio F, Petropoulos G, Pichler D (2018) The impact of industrial robots on EU employment and wages: A local labour market approach. Bruegel Work. Pap. 02

Cirillo V, Rinaldini M, Staccioli J, Virgillito ME (2021) Technology vs. workers: the case of Italy’s Industry 4.0 factories. Struct Chang Econ Dyn 56:166–183. https://doi.org/10.1016/j.strueco.2020.09.007

Clark AE (2005) Your money or your life: Changing job quality in OECD countries. Br J Ind Relations 43:377–400. https://doi.org/10.1111/j.1467-8543.2005.00361.x

Cortes GM, Oliveira A, Salomons A (2020) Do technological advances reduce the gender wage gap? Oxford Rev Econ Policy 36:903–924. https://doi.org/10.1093/oxrep/graa051

Coupe T (2019) Automation, job characteristics and job insecurity. Int J Manpow 40:1288–1304. https://doi.org/10.1108/IJM-12-2018-0418

Currie J, Eveline J (2011) E-technology and work/life balance for academics with young children. High Educ 62:533–550. https://doi.org/10.1007/s10734-010-9404-9

Damiani M, Pompei F, Kleinknecht A (2020) When robots do (not) enhance job quality: The role of innovation regimes. Available SSRN 3698317. https://doi.org/10.2139/ssrn.3698317

Dauth W, Findeisen S, Suedekum J, Woessner N (2021) The adjustment of labor markets to robots. J Eur Econ Assoc. https://doi.org/10.1093/jeea/jvab012

Day A, Paquet S, Scott N, Hambley L (2012) Perceived information and communication technology (ICT) demands on employee outcomes: The Moderating effect of organizational ICT support. J Occup Health Psychol 17:473–491. https://doi.org/10.1037/a0029837

De La Rica S, Gortazar L, Lewandowski P (2020) Job tasks and wages in developed countries: Evidence from PIAAC. Labour Econ 65

Deming DJ (2017) The growing importance of social skills in the workplace. Q J Econ 132:1593–1640. https://doi.org/10.1093/qje/qjx022.Advance

Dengler K, Gundert S (2021) Digital Transformation and Subjective Job Insecurity in Germany. Eur Sociol Rev 37:799–817. https://doi.org/10.1093/esr/jcaa066

Derks D, Bakker AB, Peters P, Van Wingerden P (2016) Work-related smartphone use, work-family conflict and family role performance: The role of segmentation preference. Hum Relat 69:1045–1068. https://doi.org/10.1177/0018726715601890

Dery K, Kolb D, Maccormick J (2014) Working with connective flow: How smartphone use is evolving in practice. Eur J Inf Syst 23:558–570. https://doi.org/10.1057/ejis.2014.13

DeSanctis G, Poole MS (1994) Capturing the complexity in advanced technology use: Adaptive Structuration Theory. Organ Sci 5:121–147. https://doi.org/10.1287/orsc.5.2.121

Dettmers J, Vahle-Hinz T, Bamberg E et al (2016) Extended work availability and its relation with start-of-day mood and cortisol. J Occup Health Psychol 21:105–118. https://doi.org/10.1037/a0039602

Diaz I, Chiaburu DS, Zimmerman RD, Boswell WR (2012) Communication technology: Pros and cons of constant connection to work. J Vocat Behav 80:500–508. https://doi.org/10.1016/j.jvb.2011.08.007

Domini G, Grazzi M, Moschella D, Treibich T (2020) For whom the bell tolls: the effects of automation on wage and gender inequality within firm. Available SSRN 3701517. https://doi.org/10.2139/ssrn.3701517

Domini G, Grazzi M, Moschella D, Treibich T (2021) Threats and opportunities in the digital era : automation spikes, trade and employment dynamics. Res Policy 50:104137. https://doi.org/10.1016/j.respol.2020.104137

Duxbury L, Higgins C, Smart R, Stevenson M (2014) Mobile technology and boundary permeability. Br J Manag 25:570–588. https://doi.org/10.1111/1467-8551.12027

Edin PA, Evans T, Hernnäs S et al (2021) Individual consequences of occupational decline. IZA DP No 12434

Eisele S, Schneider MR (2020) What do unions do to work design? Computer use, union presence, and tayloristic jobs in Britain. Ind Relat (Berkeley) 59:604–626. https://doi.org/10.1111/irel.12266

European Commission (2016) The impact of ICT on job quality: Evidence from 12 job profiles. Intermed. Rep. from study “ICT Work Digit. Ski. Work. – SMART 2014/0048” 1–98

European Commission High-Level Expert Group (2019) The impact of the digital transformation on EU labour markets. Eur Comm Rep:1–52

Falck O, Heimisch-Roecker A, Wiederhold S (2021) Returns to ICT skills. Res Policy 50:104064. https://doi.org/10.1016/j.respol.2020.104064

Felten E, Raj M, Seamans R (2019) The occupational impact of Artificial Intelligence: Labor, skills, and polarization. NYU Stern Sch. Bus

Fenner GH, Renn RW (2010) Technology-assisted supplemental work and work-to-family conflict: The role of instrumentality beliefs, organizational expectations and time management. Hum Relat 63:63–82. https://doi.org/10.1177/0018726709351064

Fossen FM, Sorgner A (2019) New digital technologies and heterogeneous employment and wage dynamics in the United States: Evidence from individual-level data. IZA Discuss Pap Ser No 12242

Frey CB, Osborne MA (2017) The future of employment: How susceptible are jobs to computerisation? Technol Forecast Soc Change 114:254–280. https://doi.org/10.1016/j.techfore.2016.08.019

Gallie D, Felstead A, Green F, Inanc H (2017) The hidden face of job insecurity. Work Employ Soc 31:36–53. https://doi.org/10.1177/0950017015624399

Galván E (2021) Why has technological change not closed the gender wage gap? Mimeo, Aix-Marseille Univ

Ge S, Zhou Y (2020) Robots, computers, and the gender wage gap. J Econ Behav Organ 178:194–222. https://doi.org/10.1016/j.jebo.2020.07.014

Genz S, Gregory T, Janser M et al (2021) How do workers adjust when firms adopt new technologies? IZA Discuss. Pap. No 14626

Genz S, Janser M, Lehmer F (2019) The impact of investments in new digital technologies on wages – Worker-level evidence from Germany. J Econ Stat 239:483–521

Genz S, Schnabel C (2021) Digging into the digital divide: Workers’ exposure to digitalization and its consequences for individual employment. Available SSRN 390864. https://doi.org/10.2139/ssrn.3908864

Georgieff A, Hyee R (2021) Artificial intelligence and employment: New cross-country evidence. OECD Soc. Employ. Migr. Work. Pap. No. 265

Georgieff A, Milanez A (2021) What happened to jobs at high risk of automation? OECD Soc. Employ. Migr. Work. Pap. No. 255

Gerten E, Beckmann M, Bellmann L (2019) Controlling working crowds: The impact of digitalization on worker autonomy and monitoring across hierarchical levels. J Econ Stat 239:441–481. https://doi.org/10.1515/jbnst-2017-0154

Gihleb R, Giuntella O, Stella L, Wang T (2020) Industrial robots, workers’ safety, and health. IZA Discuss Pap No 13672

Goldfarb A, Taska B, Teodoridis F (2019) Could machine learning be a General-Purpose Technology? Evidence from Online Job Postings. SSRN Electron. J. No 3468822

Goos M, Manning A, Salomons AM (2009) Job polarization in Europe. Am Econ Rev 99:58–63. https://doi.org/10.1257/aer.99.2.58

Goos M, Manning A, Salomons AM (2014) Explaining job polarization: Routine-biased technological change and offshoring. Am Econ Rev 104:2509–2526. https://doi.org/10.1257/aer.104.8.2509

Goos M, Rademakers E, Röttger R (2021) Routine-Biased technical change: Individual-Level evidence from a plant closure. Res Policy 50:104002. https://doi.org/10.1016/j.respol.2020.104002

Gorny PM, Woodard RC (2020) Don’t fear the robots: automatability and job satisfaction. MPRA Pap No 103424

Graetz G, Michaels G (2018) Robots at work. Rev Econ Stat C:753–768. https://doi.org/10.1162/rest_a_00754

Grande R, Vallejo-Peña A, Urzi-Brancati C (2021) The impact of IoT and 3D printing on job quality and work organisation: a snapshot from Spain. JRC Work Pap Ser Labour, Educ Technol No 2021/10

Green F (2012) Employee involvement, technology and evolution in job skills: a task-based analysis. Ind Labor Relat Rev 65:36–67. https://doi.org/10.1177/001979391206500103

Gunadi C, Ryu H (2021) Does the rise of robotic technology make people healthier? Health Econ Forthcoming. https://doi.org/10.1002/hec.4361

Haepp T (2021) New technologies and employee well-being: the role of training provision. Appl Econ Lett 1:1–6. https://doi.org/10.1080/13504851.2021.1922579

Hinds PJ, Roberts TL, Jones H (2004) Whose job is it anyway? A study of human-robot interaction in a collaborative task. Human-Computer Interact 19:151–181. https://doi.org/10.1207/s15327051hci1901%262_7

Hislop D, Axtell C, Collins A et al (2015) Variability in the use of mobile ICTs by homeworkers and its consequences for boundary management and social isolation. Inf Organ 25:222–232. https://doi.org/10.1016/j.infoandorg.2015.10.001

Huang L-C, Ahlstrom D, Lee AY-P et al (2016) High performance work systems, employee well-being, and job involvement: an empirical study. Pers Rev 45:296–314. https://doi.org/10.1108/PR-09-2014-0201

Hudomiet P, Willis RJ (2021) Computerization, obsolescence and the length of working life. Labour Econ First publ:102005. https://doi.org/10.1016/j.labeco.2021.102005

Humlum A (2019) Robot adoption and labor market dynamics. Work. Pap. Princet. Univ.

Janicke-Bowles SH, Rieger D, Connor W (2019) Finding meaning at work: The role of inspiring and funny YouTube videos on work-related well-being. J Happiness Stud 20:619–640. https://doi.org/10.1007/s10902-018-9959-1

Karimikia H, Singh H, Joseph D (2020) Negative outcomes of ICT use at work: meta-analytic evidence and the role of job autonomy. Internet Res 31:159–190. https://doi.org/10.1108/INTR-09-2019-0385

Kiener F, Gnehm A-S, Clematide S, Backes-Gellner U (2019) Different types of IT Skills in Occupational Training Curricula and Labor Market Outcomes. Univ. Zurich Work. Pap. No159

Koch M, Manuylov I, Smolka M (2021) Robots and firms Econ J 131:2553–2584. https://doi.org/10.1093/ej/ueab009

Leonardi PM (2018) Social media and the development of shared cognition: The roles of network expansion, content integration, and triggered recalling. Organ Sci 29:547–568. https://doi.org/10.1287/orsc.2017.1200

Li L, Singleton P (2021) The effect of industrial robots on workplace safety. Cent Policy Res 276

Lingmont DNJ, Alexiou A (2020) The contingent effect of job automating technology awareness on perceived job insecurity: Exploring the moderating role of organizational culture. Technol Forecast Soc Change 161:120302. https://doi.org/10.1016/j.techfore.2020.120302

Lordan G, Stringer E (2022) People versus machines: The impact of being in an automatable job on Australian worker’s mental health and life satisfaction. Econ Hum Biol 46:101144. https://doi.org/10.1016/j.ehb.2022.101144

Mark GJ, Iqbal ST, Czerwinski M et al (2016) E-mail duration, batching and self-interruption: Patterns of e-mail use on productivity and stress. Proc 2016 CHI Conf Hum Factors Comput Syst – CHI’16, pp 1717–1728

Martin L (2017) Do innovative work practices and use of information and communication technologies motivate employees? Ind Relat (Berkeley) 56:263–292. https://doi.org/10.1111/irel.12173

Martin L (2020) How to retain motivated employees in their jobs? Econ Ind Democr 41:910–953. https://doi.org/10.1177/0143831X17741528

Martin L, Omrani N (2015) An assessment of trends in technology use, innovative work practices and employees’ attitudes in Europe. Appl Econ 47:623–638. https://doi.org/10.1080/00036846.2014.978072

Martin L, Pénard T, Poussing N (2022) Are employees happier when staying connected with their companies outside working hours? Soc Sci Comput Rev First Publ. https://doi.org/10.1177/08944393211061273

McGuinness S, Pouliakas K, Redmond P (2021) Skills-displacing technological change and its impact on jobs: Challenging technological alarmism? Econ Innov New Technol. https://doi.org/10.1080/10438599.2021.1919517

Melzer SM, Diewald M (2020) How individual involvement with digitalized work and digitalization at the workplace level impacts supervisory and coworker bullying in German workplaces. Soc Sci 9. https://doi.org/10.3390/SOCSCI9090156

Menon S, Salvatori A, Zwysen W (2020) The effect of computer use on work discretion and work intensity: Evidence from Europe. Br J Ind Relations 58:1004–1038. https://doi.org/10.1111/bjir.12504

Michaels G, Natraj A, Van Reenen J (2014) Has ICT polarized skill demand? Evidence from eleven countries over 25 years. Rev Econ Stat 96:60–77. https://doi.org/10.1162/REST_a_00366

Middleton CA, Cukier W (2006) Is mobile e-mail functional or dysfunctional? Two perspectives on mobile e-mail usage. Eur J Inf Syst 15:252–260. https://doi.org/10.1057/palgrave.ejis.3000614

Moqbel M, Nevo S, Kock N (2013) Organizational members’ use of social networking sites and job performance: an exploratory study. Inf Technol People 26:240–264. https://doi.org/10.1108/ITP-10-2012-0110

Morikawa MW (2017) Who are afraid of losing their jobs to Artificial Intelligence and robots? Evidence from a survey. GLO Discuss Pap 71:1–22

Nam T (2014) Technology use and work-life balance. Appl Res Qual Life 9:1017–1040. https://doi.org/10.1007/s11482-013-9283-1

Nam T (2019) Technology usage, expected job sustainability, and perceived job insecurity. Technol Forecast Soc Change 138:155–165. https://doi.org/10.1016/j.techfore.2018.08.017

Nedelkoska L, Quintini G (2018) Automation, skills use and training. OECD Soc. Employ. Migr. Work. Pap. Ser. No 202

Nikolova M, Cnossen F (2020) What makes work meaningful and why economists should care about it. Labour Econ 65. https://doi.org/10.1016/j.labeco.2020.101847

Ninaus K, Diehl S, Terlutter R (2021) Employee perceptions of information and communication technologies in work life, perceived burnout, job satisfaction and the role of work-family balance. J Bus Res 136:652–666. https://doi.org/10.1016/j.jbusres.2021.08.007

Nöhammer E, Stichlberger S (2019) Digitalization, innovative work behavior and extended availability. J Bus Econ 89:1191–1214. https://doi.org/10.1007/s11573-019-00953-2

Nurski L, Hoffmann M (2022) Beating burnout: identifying bad jobs and improving job quality. Policy Contrib 07/2022, Bruegel

Ohly S, Latour A (2014) Work-related smartphone use and well-being in the evening: the role of autonomous and controlled motivation. J Pers Psychol 13:174–183. https://doi.org/10.1027/1866-5888/a000114

Oksanen A, Oksa R, Savela N et al (2021) COVID-19 crisis and digital stressors at work: a longitudinal study on the Finnish working population. Comput Hum Behav 122:106853. https://doi.org/10.1016/j.chb.2021.106853

Oswald AJ, Proto E, Sgroi D (2015) Happiness and productivity. J Labor Econ 33:789–822. https://doi.org/10.1086/681096

Parker SK, Grote G (2020) Automation, algorithms, and beyond: why work design matters more than ever in a digital world. Appl Psychol 0:1–45. https://doi.org/10.1111/apps.12241

Parris MA, Vickers MH, Wilkes L (2008) Caught in the middle: organizational impediments to middle managers’ work-life balance. Empl Responsib Rights J 20:101–117. https://doi.org/10.1007/s10672-008-9069-z

Peruffo E, Schmidlechner L, Contreras RR, Molinuevo D (2017) Automation of work – Literature review. Eurofound Work Pap WPEF17039EN 26

Richardson K, Benbunan-Fich R (2011) Examining the antecedents of work connectivity behavior during non-work time. Inf Organ 21:142–160. https://doi.org/10.1016/j.infoandorg.2011.06.002

Ross MB (2017) Routine-biased technical change: Panel evidence of task orientation and wage effects. Labour Econ 48:198–214. https://doi.org/10.1016/j.labeco.2017.08.007

Salanova M, Cifre E, Martin P (2004) Information technology implementation styles and their relation with workers’ subjective well-being. Int J Oper Prod Manag 24:42–54. https://doi.org/10.1108/01443570410510988

Sayah S (2013) Managing work-life boundaries with information and communication technologies: the case of independent contractors. New Technol Work Employ 28:179–196. https://doi.org/10.1111/ntwe.12016

Schaufeli WB, Bakker AB (2004) Job demands, job resources, and their relationship with burnout and engagement: a multi-sample study. J Organ Behav 25:293–315. https://doi.org/10.1002/job.248

Schieman S, Young MC (2013) Are communications about work outside regular working hours associated with work-to-family conflict, psychological distress and sleep problems? Work Stress 27:244–261. https://doi.org/10.1080/02678373.2013.817090

Schmidpeter B, Winter-Ebmer R (2019) Automation, offshoring, and the role of public policies. Mimeo

Schwabe H, Castellacci F (2020) Automation, workers’ skills and job satisfaction. PLoS One 15:1–26. https://doi.org/10.1371/journal.pone.0242929

Siampou F, Komis V, Tselios NK (2014) Online versus face-to-face collaboration in the context of a computer-supported modeling task. Comput Hum Behav 37:369–376. https://doi.org/10.1016/j.chb.2014.04.032

Siegert S, Löwstedt J (2019) Online boundary work tactics: an affordance perspective. New Technol Work Employ 34:18–36. https://doi.org/10.1111/ntwe.12126

Smith A, Anderson J (2014) AI, robotics, and the future of jobs. Pew Res Center, August 1–73

So BCL, Cheng ASK, Szeto GPY (2017) Cumulative IT use is associated with psychosocial stress factors and musculoskeletal symptoms. Int J Environ Res Public Health 14:1541. https://doi.org/10.3390/ijerph14121541

Solow R (1987) We’d better watch out. New York Times B. Rev. New York Times, New York

Srivastava SC, Chandra S, Shirish A (2015) Technostress creators and job outcomes: Theorising the moderating influence of personality traits. Inf Syst J 25:355–401. https://doi.org/10.1111/isj.12067

Tolan S, Pesole A, Martínez-Plumed F et al (2021) Measuring the occupational impact of AI beyond automation: tasks, cognitive abilities and AI benchmarks. J Artif Intell Res 71:191–236

Turel O, Serenko A, Bontis N (2011) Family and work-related consequences of addiction to organizational pervasive technologies. Inf Manage 48:88–95. https://doi.org/10.1016/j.im.2011.01.004

UNECE (2015) Handbook on measuring quality of employment: a statistical framework. United Nations Econ. Comm. Eur. Rep

Warr PB (1999) Well-being and the workplace. In: Kahneman D, Diener E, Schwarz N (eds) Well-being: the Foundations of Hedonic Psychology. Russell Sage Foundation, New York, pp 392–412

Webb M (2020) The impact of Artificial Intelligence on the labor market. Available SSRN 3482150

Wood S, van Veldhoven M, Croon MA, de Menezes LM (2012) Enriched job design, high involvement management and organizational performance: The mediating roles of job satisfaction and well-being. Hum Relations 65:419–446. https://doi.org/10.1177/0018726711432476

Wright KB, Abendschein B, Wombacher K et al (2014) Work-related communication technology use outside of regular work hours and work life conflict: The influence of communication technologies on perceived work life conflict, burnout, job satisfaction, and turnover intentions. Manag Commun Q 28:507–530. https://doi.org/10.1177/0893318914533332

Zelenski JM, Murphy SA, Jenkins DA (2008) The happy-productive worker thesis revisited. J Happiness Stud 9:521–537. https://doi.org/10.1007/s10902-008-9087-4

Download references

Acknowledgments

Responsible Section Editor: Milena Nikolova.

The chapter has benefitted from the valuable comments of the editors and anonymous referees. This research has received funding from the European Union’s Horizon 2020 Research and Innovation Programme (project “UNTANGLED”) under grant agreement No. 101004776. There is no conflict of interest.

Author information

Authors and affiliations.

Labour Market Department, LISER – Luxembourg Institute of Socio-Economic Research, Esch-sur-Alzette, Luxembourg

Ludivine Martin & Laetitia Hauret

CREM – Center for Research in Economics and Management (UMR CNRS 6211), Rennes, France

Ludivine Martin

IZA, Institute for the Study of Labor, Bonn, Germany

You can also search for this author in PubMed   Google Scholar

Corresponding author

Correspondence to Ludivine Martin .

Editor information

Editors and affiliations.

UNU-MERIT & Princeton University, Maastricht, The Netherlands

Klaus F. Zimmermann

Section Editor information

Faculty of Economics and Business, Global Economics and Management, University of Groningen, Groningen, The Netherlands

Milena Nikolova

Rights and permissions

Reprints and permissions

Copyright information

© 2022 Springer Nature Switzerland AG

About this entry

Cite this entry.

Martin, L., Hauret, L. (2022). Digitalization, Job Quality, and Subjective Well-being. In: Zimmermann, K.F. (eds) Handbook of Labor, Human Resources and Population Economics. Springer, Cham. https://doi.org/10.1007/978-3-319-57365-6_388-1

Download citation

DOI : https://doi.org/10.1007/978-3-319-57365-6_388-1

Received : 06 July 2022

Accepted : 02 August 2022

Published : 11 November 2022

Publisher Name : Springer, Cham

Print ISBN : 978-3-319-57365-6

Online ISBN : 978-3-319-57365-6

eBook Packages : Springer Reference Economics and Finance Reference Module Humanities and Social Sciences Reference Module Business, Economics and Social Sciences

• Publish with us

Policies and ethics

• Find a journal
• Track your research

• Erasmus School of Economics
• Erasmus School of History, Culture and Communication
• Erasmus School of Law
• Erasmus School of Philosophy
• Erasmus School of Social and Behavioural Sciences
• Erasmus School of Health Policy & Management
• International Institute of Social Studies
• Rotterdam School of Management
• Tinbergen Institute
• Institute for Housing and Urban Development Studies
• RSM Parttime Master Bedrijfskunde
• Erasmus University Library
• Thesis Repository.
• Erasmus School of Economics /
• Business Economics /
• Master Thesis
• Search: Search

Tsakiri, Kyriaki

job satisfaction, organizational commitment, job quality and training:

Publication.

evidence from the workplace employment relations survey

In this master thesis I examine the relationship between employees’ perceptions of their job quality, organizational commitment, training and their level of job satisfaction with specific facets. These include satisfaction with achievement, pay, influence and work itself. In order to investigate these issues, I use data from the sixth wave of the Workplace Employment Relations Survey (WERS), a representative British dataset. After controlling for individual and job characteristics, I find significant effects for the selected measures of job quality (perceived effort, job security, climate of relations between managers and employees), organizational commitment and training on each of the four facets of job satisfaction. In particular, in line with my hypotheses, higher job security, higher levels of perceived climate of relations between managers and employees, higher levels of organizational commitment and higher levels of access to training are associated with higher levels of each of the four facets of satisfaction. The results also suggest that effort is negatively related to satisfaction with pay, but positively related to satisfaction with achievement, influence and work itself.

Add Content

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

PHD thesis: Changes in the Structure of Employment and Job Quality in Europe, 1995-2007

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

An official website of the United States government

The .gov means it’s official. Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

The site is secure. The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

• Publications
• Account settings

Preview improvements coming to the PMC website in October 2024. Learn More or Try it out now .

• Advanced Search
• Journal List
• Glob J Health Sci
• v.7(2); 2015 Mar

The Relationship Between Quality of Work Life and Job Satisfaction of Faculty Members in Zahedan University of Medical Sciences

Fatihe kermansaravi.

1 Pregnancy Health Research Center, Zahedan University of Medical Sciences, Zahedan, Iran

Ali Navidian

Shahindokht navabi rigi, fariba yaghoubinia, background:.

Quality of work life is one of the most important factors for human motivating and improving of job satisfaction.

The current study was carried out aimed to determine the relationship between quality of work life and job satisfaction in faculty members of Zahedan University of Medical Sciences.

In this descriptive-analytic study, 202 faculty members of Zahedan University of Medical Sciences in 2012 were entered the study through census. The job satisfaction questionnaire of Smith and Kendall and Walton Quality of Work Life questionnaire were used for data collection. Validity and reliability of questionnaires were confirmed in previous studies. Data analysis was done using SPSS 18. The Pearson correlation coefficient and multiple regression tests were used for data analysis.

The mean score of quality of work life was 121/30±37/08 and job satisfaction was 135/98±33/78. There was a significant and positive correlation between job satisfaction of faculty members and their quality of work life (P=0.003). In addition, two components of quality of work life “adequate and fair compensation” (β=0.3) and “Social Integration” (β=0.4) can predict job satisfaction of faculty members.

Conclusion:

According to correlation between job satisfaction and quality of work life in faculty members, job satisfaction can be improved through the changing and manipulating the components of quality of work life and in this way; the suitable environment for organization development should be provided.

1. Background

Quality of work life is a comprehensive concept which is consisted of physical and psychological health, economic situations, personal belief and interaction with environment ( Khorsandi et al., 2010 ). In contemporary management, the concept of quality of work life has been changed to a social issue, while in the past decades only the personal life was emphasized ( Mirkamali & Narenji Sani, 2008 ). The meaning of quality of work life is subjective imagination and the perception of organization personnel about the physical and psychological desirability of work environment and their work situations ( Yavari, Amir Tash, & Tondnevis, 2009 ).

Walton (1973) defined the quality of work life as the personnel reaction to work; especially its essential outcome in relation to job needs satisfaction and psychological health. According to this definition, quality of work life emphasizes on personal outcomes, work experiences and how to improve the work in order to meeting the personal needs. Walton presented a theoretical model for explaining the quality of work life that is consisted of adequate and fair compensation, safe and healthy environment, constitutionalism in organization, preparing the opportunity for continued growth and security, social relevance of work life, social integration, development of human capabilities and the total life space ( Walton, 1973 ).

From 1980 to 2006, many researches have been done about quality of work life and results showed that there is positive relationship between quality of work life and some variables in organization such as job satisfaction. Job satisfaction has been defined as idea, perception and positive attitudes and emotions of individuals about profession which are affected by some factors such as work environment, organizational system, work environment relationship and socio-cultural factors ( Mirkamali & Narenji Sani, 2008 ; Armstrong, 2006 ).

Qualitative and quantitative researches show that the most experts have consensus on factors such as work situations and work type, interactions with manager and colleagues, ways of preferment in organization, salary and benefit as the major predictor factors of job satisfaction ( HongLu, While, & Barriball, 2007 ).

The mission of quality of work life is the creating of job satisfaction for personnel and helping to organization for employee selection and retention. Quality of work life is one of the most important factors for human motivating and improving job satisfaction ( Royuela, Jordi, & Jourdi, 2009 ).

University as the most important educational and research center has an effective role in community promotion toward educational, social, cultural and economic goals and the faculty member is one of the main components of educational system. Supporting of human resources and helping to appropriate efficiency of these resources and academic elite is the guarantee of community development and progress ( Oplatka, 2009 ).

According to expanded duties of faculty members such as training of skilled and committed human resources, research, therapeutic services, executive activity and personal development, attention to this topic is very important ( Eklund, 2008 ).

Previous studies showed that there is positive relationship between job satisfaction and quality of work life. In study which was conducted about faculty members in Bangladesh, results showed that all of the aspects of quality of work life have a positive relationship with job satisfaction ( Tabassum, 2012 ).

Results of Ballou’s study (2007) also showed that the satisfied employees work with favorites in work environment and are loyal to organization and help to increase the efficiency and capital in organization ( Ballou, Norman, & Goodwin, 2007 ). Results of other studies in Columbia also showed that the faculty’s knowledge of work life has strong and direct impact on satisfaction or incentive to withdraw from the university ( Dolan et al., 2008 ).

This relationship also has been reported in studies which were done in Iran ( Mirkamali & Narenji Sani, 2008 ; Teymouri, 2008 ). In study by Soltanzadeh (2012) , components such as constitutionalism in organization, social relevance of work life, social integration were the best predictors of job satisfaction in faculty members ( Soltanzadeh, Ghalvandy, & Fatahy, 2012 ).

In universities in Iran, formal employment and job security changed to stressful issues because of some factors such as the long process of faculty recruitment, scholarships allocation, stated the need. Workload and teaching hours of faculty also hinder some activities in other areas such as research and service ( Noor Shahi & Samie, 2011 ). Many studies have been done in other countries about job satisfaction of faculty members.

But, the conducted studies about quality of work life in Iran are less and limit, thus it is necessary that the more and comprehensive research conduct in this topic. It is very important especially when the increase of quality of work life and its relationship with job satisfaction is propounded.

No study has been done concerning of quality of work life and job satisfaction in faculty members in Zahedan University of medical sciences. Moreover; according to importance of these two variables for advancing the academic goals and creating more efficiency and also some situations in Sistan & Baluchestan province in Iran such as shortage of amenities, this study conducted aimed to determine the relationship between quality of work life and job satisfaction in faculty members.

In this descriptive-analytical study, all of the faculty members who were 202 people and were employed in Zahedan University of medical sciences in 2012 entered to study through census. The contract, committed to serving and tuition teachers were excluded from the study. Data were gathered through information form (age, gender, marital status, work experience, academic degree and employment status) and the Walton quality of work life questionnaire ( Walton, 1973 ) and Job Descriptive Index by Kendall and Smith ( Smith, Kendall, & Hulin, 1969 ).

Quality of work life questionnaire is consisting of 40 items which has been designed in 5-point Likert scale (never 1, rarely 2, sometimes 3, most of time 4, always 5). 5 items are related to adequate and fair compensation, 5 items are about safe and healthy work environment, 5 items are about constitutionalism in organization, 5 about preparing the opportunity for continued growth and security, 5 items are related to social relevance of working life, 5 about social integration, 5 about development of human capabilities and 5 about the total life space.

The score of each item is from 1 to 5. Thus, the overall score of this questionnaire will be in range of 40–200. Validity and reliability of questionnaire was confirmed in many studies and α=0.92 has been reported ( Mirkamali & Narenji Sani, 2008 ; Yavari, Amir Tash, & Tondnevis, 2009 ). Job Descriptive Index questionnaire was made by Kendall in 1969 and it is one of the most common tools for measuring job satisfaction. This scale assess the 5 various aspects of job satisfaction.

There are some criteria for each aspect that measure the individual’s feelings about job. The five aspects of this index are consisting of five scales of work type (10 items), supervisor or manager (10 items), colleagues (10 items), preferment in organization (5 items) and salary and benefit (6 items).

Score of each item is in range of 1–5. Thus; the overall scores of job satisfaction varies in range of 41-205. The more score of this questionnaire is indicative of the more job satisfaction. The internal consistency of this questionnaire was reported as 0.89–0.92 by Kendal and Halin ( Smith, Kendall, & Hulin, 1969 ). This questionnaire was used in many studies in Iran and its validity and reliability was confirmed ( Heydari, 1998 ; Ranjbar, & Vahidshahi, 2007 ).

In study by Zamini and Hoseyninasab, this questionnaire was completed by 20 people and chronbach’s alpha=0.92 was obtained for the whole of questionnaire and for subscales was 0.85, 0.96, 0.92, 0.87 and 0.84 respectively ( Zamini & Hoseyninasab, 2008 ). The mean score was calculated for each of the components of jab satisfaction and also total score of questionnaire. In current study questionnaires were delivered to faculty members by educational employees for completing during three weeks and then were returned to researcher.

Ethical considerations were adhered, informed consent was obtained and assurance of confidentiality and anonymity was done. Data analysis was done using SPSS 18. Central tendency indexes were used for description of quantitative data and for qualitative variables, frequency and percentage were used. Also, Pearson correlation coefficient and multiple regression were used for measuring the correlation between quality of work life and job satisfaction.

The mean age of faculty members was 40.91±8 with range of 28–59 years old and the mean of their work experience was 11.9±8.14 with range of 1–33. Demographic characteristics of subjects are presented in Table 1 .

Demographic characteristics of faculty members

The mean score of quality of work life was 121.3 (SD=37.08). The highest mean was related to development of human capabilities (18.78±4.5) and the least mean was for constitutionalism in organization (12.84±3.92). The mean score of job satisfaction was 135.98±33.78 and the highest mean was related to job characteristics aspect (36.65±7.29) and the least mean was for ways of preferment (16.44±5.19)

A direct and significant correlation was found between quality of work life and job satisfaction of faculty members (r=0.23, p=0.003). Also, there was direct and significant correlation between aspects of social relevance, the total life space and social integration with job satisfaction ( Table 2 ).

Correlation between quality of work life score and its components with job satisfaction

According to significant values (p=0.000, F=4.92) and the multiple regression analysis about components of quality of work life with job satisfaction, it can be concluded that the regression model was composed of 8 independent variables (aspects of quality of work life) and 1 dependent variable that can explain the changes in job satisfaction.

Based on Multiple regression equations (Y=a+b 1 x 1 +b 2 x 2 +……b k x k), R 2 value shows that the 17 percent of all of the changes in job satisfaction are associated to 8 independence variables in this equation (aspects of quality of work life). In other words, set of independent variables predict the 17 percent of variance of job satisfaction.

β Coefficient (regression coefficients) is indicated that the adequate and fair compensation (β=0.3) and social integration (β=0.4) are predictors of job satisfaction ( Table 3 ).

Multiple regression analysis of each component of quality of work life with job satisfaction 1 1 , 2 2

4. Discussion

According to study results, there is positive and significant relationship between quality of work life and job satisfaction which was indicating that better quality of work life is associated with more job satisfaction in faculty members.

Results of studies which have been done in Iran such as Soltanzadeh et al. (2012) , Zakerian et al. (2012), Shahbazi et al. (2011), Heidarie et al. (2010), Goudarznand-Chegini et al. (2010), Saedi et al. (2010) , Mirkamali and NarenjiSani (2008) corroborated the results of current study.

Also, the results of studies in other countries such as HongLu (2007) , Hua (2006) , Conklin (2008) , Heinonen and Sarima (2009) , Adhikari (2010) and Rose (2006) confirmed the relationship between quality of work life and job satisfaction ( HongLu, While, & Barriball, 2007 ; Hua, 2006 ; Conklin, 2008 ; Heinonen, & Saarimaa, 2009 ; Adhikari, & Gautam, 2010 ; Rose et al., 2006 ).

Recognition of related factors with job satisfaction in faculty members is very important, because we can increase job satisfaction and prepare the conditions in order to organizational growth with manipulating and changing the components of quality of work life. The existence of components of quality of work life provide situation for satisfaction and peace, responsibility, optimal use of Physical space and educational tools for faculty members.

The study by Conklin (2008) showed that there is a positive and significant relationship between quality of work life and job satisfaction and its changes ( Heinonen & Saarimaa, 2009 ). Results of study in Europe (2008) concerning the health and management efficiency demonstrated that the style of work life as a psychological factor in work environment can increase the efficiency of staff ( Kirsten, 2008 ).

The results of current study about relationship between components of quality of work life and job satisfaction showed that there is a direct and significant relationship between aspects of social dependency, life space and social integration. Zakerian (2012), Hosseini (2008) , Othman (2009) and Lawler (2007) stated a significant relationship between aspects of work life and job satisfaction ( Zakerian et al., 2014 ; Hosseini et al., 2008 ; Othman, & Mok, 2009 ; Lawler, Chan Huang, & Yilei, 2007 ).

According to direct relationship of component of social relevance which is referred to the perception of faculty about social responsibility in system and managers valuing of community rules, thus; it can be created a sense of duty through participation of members in decision making and team working. Also, it can be realized this aspect with using of faculty’s thought and idea in policy.

Thus, the organizations can improve all of the aspects of quality of work life in order to increase of job satisfaction. They can create the situations in work environment for demonstrating the abilities and creativities of staff and create proper opportunities for success, safety, job preferment and staff dynamics.

The aspect of work life space can be strengthened through establishment a balance between work life and other parts of life such as leisure time, education, family life and; with reduction of sensible and insensible job stress.

Results of regression analysis which was done in order to prediction of job satisfaction through the components of quality of work life showed that social integration and adequate and fair compensation are the most important predictors of job satisfaction respectively.

In other studies; constitutionalism, social integration and preparing the opportunity for continued growth and security ( Mirkamali & NarenjiSani, 2008 ), professional satisfaction and status of life space ( Zakerian et al., 2014 ) and organizational climate (safety work environment, providing job opportunities) were as the most important predictors of job satisfaction. Lawler et al. (2007) believed that the safe and healthy work environment, adequate and fair compensation; and job security have positive effect on organizational commitment ( Lawler, Chan Huang & Yilei, 2007 ). The reasons of some differences between results of previous studies with current study are the difference in research population, level of education or difference in data collection methods.

Social integration was one of the factors affecting on quality of work life in faculty members. According to study results, the faculty members were dissatisfied about the work space that is the most important factor in encouraging them for doing their duties and responsibilities and creating a sense of belonging to the organization.

As a result, it is recommended that the university encourage faculty members to creativity and innovation through the preparing of appropriate context for teaching and supporting them by colleagues and managers.

Judging faculty members about objective and observable conditions of organization is affected by their perception and interpretation of organizational environment. Thus; the university can strengthen the sense of belongingness to organization in faculty members through the creating of appropriate and positive working climate and also, can create the proper perception about social responsibility in organization through the using of their expertise and experiences for problem solving in organization.

The next influential factor in job satisfaction with the least mean in both groups of basic science and clinical faculty was fair compensation. Result showed that there is no a proper balance between workload and consumed time and energy and also community standards in financial payment system from viewpoint of faculty members. Thus; it is necessary to revise the appropriateness of salary according to community situations concerning standards and inflation.

5. Conclusion

According to study results, quality of work life has the predictability of job satisfaction of faculty members and can be effective in improving their job satisfaction. Thus; job satisfaction can be improved through the changing and manipulating of the quality of work life components. The universities can increase the job satisfaction in faculty members through the proper program such as monetary and non-monetary rewards, creating opportunity for optimal use of faculty’s abilities and skills, payment pattern according to the teachers’ quality and quantity performance and community situations, fellowships and creating opportunities for faculty participation in decision making. Also, it is recommended that some interventions should be planned concerning the improving quality of work life and its efficiency should be evaluated.

Acknowledgements

This research has been approved and funded by vice dean Chancellor Research, Zahedan University of Medical Sciences, Iran coded 2530. The authors gratefully acknowledge their assistance in supporting this study. The authors would like to thank the faculty members involved in this study for their valuable contribution.

• Adhikari D. R, Gautam D. K. Labor Legislations for Improving Quality of Work Life in Nepal. International Journal of Law and Management. 2010; 52 (1):40–53. http://dx.doi.org/10.1108/17542431011018534 . [ Google Scholar ]
• Armstrong M. 10th ed. Kogan Page Publishing; 2006. A handbook of human resource management practice; p. 264. [ Google Scholar ]
• Ballou B, Norman H, Goodwin N. Quality of Work Life. Strategic Finance. 2007; 89 (4):41–45. [ Google Scholar ]
• Che Rose R, Beh L, Uli J, Idris K. An analysis of quality of work life (QWL) and career-related variables. American Journal of Applied Sciences. 2006; 12 :2151–2159. [ Google Scholar ]
• Conklin M. H. Duquesne University; 2008. An Examination of Pharmacy Faculty Quality of Work Life: Work Satisfaction, Turnover Intentions, and Self-Efficacy (MSc Dissertation) [ Google Scholar ]
• Dolan S. L, Garcia S, Cabezas C, Tzafrir S. S. Predictors of Quality of Work and Poor Health among Primary Health care Personnel in Catalonia. International Journal of Health Care Quality Assurance. 2008; 21 (2):203–218. http://dx.doi.org/10.1108/09526860810859058 . [ PubMed ] [ Google Scholar ]
• Eklund N. Search Institute Press; 2008. How was your day at school? Improving dialogue about teacher job satisfaction. [ Google Scholar ]
• Goudarznand-Chegini M, Mirdoozandeh G. Relationship between quality of work-life and job satisfaction of the employees in public hospitals in Rasht. Zahedan J Res Med Sci (ZJRMS) 2012; 14 :108–111. In Persian. [ Google Scholar ]
• Heidarie A, Askary P, Saedi S, Gorjian B. Relationship between Quality of Work Life, Organizational Health and Commitment with Job Satisfaction. Life Science Journal. 2012; 9 :2300–2306. [ Google Scholar ]
• Heinonen S, Saarimaa R. Better job satisfaction through quality of work life–how can telework help? 2009 [ Google Scholar ]
• Heydari S. The relationship between burnout and job satisfaction of teachers. Gachsaran. J Marvdasht Univ, 1998. 1998 In Persian. [ Google Scholar ]
• HongLu H, While A. E, Barriball K. Job satisfaction and its related factors: A questionnaire survey of hospital nurses in Mainland China. International journal of nursing studies. 2007; 44 :574–588. http://dx.doi.org/10.1016/j.ijnurstu.2006.07.007 . [ PMC free article ] [ PubMed ] [ Google Scholar ]
• Hosseini S, Naderian M, Homaye R, Mosavi Z. Relation between quality of work life and organizational management for staffs of sport office of Esfahan. Journal of Sport management. 2008; 2 :168–181. In Persian. [ Google Scholar ]
• Hua J. A study of relationship on bureau of investigation officials, quality of work life, work pressure and job satisfaction (Master’s thesis, Public Affairs Management) 2006 [ Google Scholar ]
• Khorsandi M, Jahani F, Rafie M, Farazi A. Health- Related quality of life in staff and hospital personnel of arak university of Medical sciences in 2009. Journal of Arak Medical University. 2010; 13 (1):40–48. In Persian. [ Google Scholar ]
• Kirsten W. Health and Productivity Management in Europe. International Journal of Workplace Health Management. 2008; 1 (2):136–144. http://dx.doi.org/10.1108/17538350810893928 . [ Google Scholar ]
• Lawler J, Chan Huang T, Yilei C. The Effects of Quality of Work Life on Commitment and Turnover Intention. Social Behavior and Personality. 2007; 35 (6):735–750. http://dx.doi.org/10.2224/sbp.2007.35.6.735 . [ Google Scholar ]
• Mirkamali S, Narenji Sani F. A study on the Relationship between the Quality of work life and Jab Satisfaction among the Faculty Members of Tehran and Sharif University of Technology. Journal of Research and Planning in Higher Education. 2008; 48 (1):73–96. In Persian. [ Google Scholar ]
• Noor shahi N, Samie H. Quality of work life of faculty members and offers some solutions to improve its public universities in Iran. Journal of Planning Research on Higher Education. 2011; 59 (2):91–114. In Persian. [ Google Scholar ]
• Oplatka I. Organizational citizenship behavior in teaching: The consequences for teachers, pupils, and the school. Int J Educ Manag. 2009; 23 :375–389. http://dx.doi.org/10.1108/09513540910970476 . [ Google Scholar ]
• Othman A, Mok C. L. Kuantan: Pahang ISBN 978-967-5080-51-57; 2009. Relationship between quality of work life (QWL) and job satisfaction: A case Study of enterprise “XYZ” in Malacca. International Conference on Human Capital Development (ICONHCD 2009). 25-27 May 2009. [ Google Scholar ]
• Ranjbar M, Vahidshahi K. Effective factors on faculty members’ job satisfaction in Mazandaran University of medical sciences, school of medicine 2006. Strides Dev Med Educ. 2007; 4 :92–99. In Persian. [ Google Scholar ]
• Royuela V, Jordi L. T, Jourdi S. Result of Quality of Work Life Index in Spain a Comparison of Survey Result and Aggregate Social Indicators. Social Indicators Research. 2009; 90 :225–241. http://dx.doi.org/10.1007/s11205-008-9254-3 . [ Google Scholar ]
• Saedi S, Khalatbari J, Murray Najafabadi N. Relationship between quality of work life and organizational health with job satisfaction. Journal of Modern Industrial/Organization Psycholo. 2010; 1 (4):55–64. In Persian. [ Google Scholar ]
• Shahbazi B, Vaezi M, Sanai poor H. Explain the relationship between the quality of working life and performance management departments of universities. Journal of Public Administration. 2009; 3 (1):69–84. In Persian. [ Google Scholar ]
• Smith P. C, Kendall L. M, Hulin C. L. Chicago: Rand McNally; 1969. The Measurement of Satisfaction in Work and Retirement. [ Google Scholar ]
• Soltanzadeh V, Ghalvandy H, Fatahy M. A Study of the Relationship between the Quality of Work Life and Job Satisfaction among the Faculty Members of Shiraz University. Journal of Human Resource Management Researches. 2012; 4 (2):125–149. In Persian. [ Google Scholar ]
• Tabassum A. Interrelations between Quality of Work Life Dimensions and Faculty Member Job Satisfaction in the Private Universities of Bangladesh. European Journal of Business and Management. 2012:78–89. [ Google Scholar ]
• Teymouri M, Tootoonchi M, Salehi M, Hassan zadeh A. Job Satisfaction among Faculty Members of Isfahan University of Medical Sciences. Iranian Journal of Medical Education. 2008; 7 (2):227–235. In Persian. [ Google Scholar ]
• Walton R. E. Quality of Work Life, What Is It? Sloan Management Review Journal. 1973:11–21. [ Google Scholar ]
• Yavari U, Amir Tash A, Tondnevis F. Compare the quality of working life and its subscales in the faculty of physical education colleges and public universities. Journal of Movement and Exercise Science. 2009; 7 (1):99–109. In Persian. [ Google Scholar ]
• Zakerian S. A, Teymuri G. H, Ahmadnezhad I, Abbassinia M, Rahmani A, Asghari M. Investigating the Dimensions of Quality of Work Life and Its Relation to Job Satisfaction in an Automotive Industry. Journal of Ergonomics. 2014; 1 (3):36–45. In Persian. [ Google Scholar ]
• Zamini S, Hoseyninasab D. The relationship between organizational culture and job satisfaction among the faculty and staff, University of Tabriz. Journal of Management enterprise culture. 2008; 7 (20):121–138. In Persian. [ Google Scholar ]

MAKING GIGS WORK: CAREER STRATEGIES, JOB QUALITY AND MIGRATION IN THE GIG ECONOMY

Add to collection, downloadable content.

• March 22, 2019
• Affiliation: College of Arts and Sciences, Department of Sociology
• The early-21st century has witnessed a transformation in both technological advancement and the nature of the employment relationship. Flexible workforce strategies have been adopted (Kalleberg 2003); internal labor markets have disappeared (Cappelli 2001); and large, vertically integrated firms have vanished as well (Davis 2016a). These trends have all led to a dramatic rise in the use of independent contractors. In conjunction, we have witnessed a shift in employment, from the career, to the job, to the task (Davis 2015). At the confluence of changes in the nature of employment relationships and technological advancements lies the gig economy — the focal point of this study. What differentiates work in the gig economy is that it operates within a new work ecosystem that is managed by online platforms, which broker work between employers and workers. Using in-depth interviews and secondary sources, this study examines the gig economy through three main lines of inquiry. First, it investigates the role of gig work in a worker’s labor market and career strategy. To do this, the study demarcates who is completing gig work and examines why they are completing it. Next, the project considers job quality through two lenses: a platform perspective and a worker perspective. In examining job quality from both these angles, it tries to answer the question: is gig work a good or a bad job? Finally, the project examines in what ways, if any, digital platforms and gig work may be affecting worker migration decisions.
• Sociology of Work
• Labor relations
• Precarious Work
• Gig Economy
• Non-standard Work
• https://doi.org/10.17615/3d4z-7y37
• Dissertation
• Tufekci, Zeynep
• Davis, Jerry
• Aldrich, Howard
• Hagan, Jacqueline
• Kalleberg, Arne
• Doctor of Philosophy
• University of North Carolina at Chapel Hill

This work has no parents.

Select type of work

Master's papers.

Deposit your masters paper, project or other capstone work. Theses will be sent to the CDR automatically via ProQuest and do not need to be deposited.

Scholarly Articles and Book Chapters

Deposit a peer-reviewed article or book chapter. If you would like to deposit a poster, presentation, conference paper or white paper, use the “Scholarly Works” deposit form.

Undergraduate Honors Theses

Deposit your senior honors thesis.

Scholarly Journal, Newsletter or Book

Deposit a complete issue of a scholarly journal, newsletter or book. If you would like to deposit an article or book chapter, use the “Scholarly Articles and Book Chapters” deposit option.

Deposit your dataset. Datasets may be associated with an article or deposited separately.

Deposit your 3D objects, audio, images or video.

Poster, Presentation, Protocol or Paper

Deposit scholarly works such as posters, presentations, research protocols, conference papers or white papers. If you would like to deposit a peer-reviewed article or book chapter, use the “Scholarly Articles and Book Chapters” deposit option.

• Bibliography
• More Referencing guides Blog Automated transliteration Relevant bibliographies by topics
• Automated transliteration
• Relevant bibliographies by topics
• Referencing guides

Research: Resume Gaps Still Matter

• Boris Groysberg

While attitudes about gaps are changing, data shows that they can still be damaging to job applicants.

Without knowing the details of a person’s history, employers rely on signals of quality to make bets on who will make quality employees with a strong organizational fit. Resume gaps used to be clear negative signals, but attitudes seem to be changing today. For example, LinkedIn recently adopted a new “Career Breaks” feature in which users can showcase skills acquired during a professional pause. While tempting to declare the present day a new age of tolerance and compassion, a deeper analysis suggests it might be wise to take a more guarded perspective, as the reality of the post-pandemic labor market is still unfolding. Drawing on both current studies as well as executive compensation data from the 2008 Great Recession period, the authors show that resume gaps hurt job seekers, both in their ability to get jobs and their pay.

Attitudes toward resume gaps seem to be changing. While they once were considered a serious red flag for job candidates, today we’re seeing more people talking openly and without reservation about taking a break from employment. A 2022 LinkedIn survey of 23,000 global workers indicated that nearly two-thirds of respondents indicated that they had taken some sort of career break. LinkedIn released this survey data while introducing a new “Career Breaks” feature, allowing its users to showcase non-employment experiences and skills acquired during a professional pause.

• BG Boris Groysberg is a professor of business administration in the Organizational Behavior unit at Harvard Business School and a faculty affiliate at the school’s Race, Gender & Equity Initiative. He is the coauthor, with Colleen Ammerman, of Glass Half-Broken: Shattering the Barriers That Still Hold Women Back at Work (Harvard Business Review Press, 2021). bgroysberg
• Eric Lin is an associate professor of business and co-chair of the business program at Oberlin College and Conservatory. His research focuses on human capital and talent management. LinXEric

Partner Center

Quality Engineer

Job Description:

At Bank of America, we are guided by a common purpose to help make financial lives better through the power of every connection. Responsible Growth is how we run our company and how we deliver for our clients, teammates, communities and shareholders every day.

One of the keys to driving Responsible Growth is being a great place to work for our teammates around the world. We’re devoted to being a diverse and inclusive workplace for everyone. We hire individuals with a broad range of backgrounds and experiences and invest heavily in our teammates and their families by offering competitive benefits to support their physical, emotional, and financial well-being.

Bank of America believes both in the importance of working together and offering flexibility to our employees. We use a multi-faceted approach for flexibility, depending on the various roles in our organization.

Working at Bank of America will give you a great career with opportunities to learn, grow and make an impact, along with the power to make a difference. Join us!

Job Summary:

Brings a ‘testing mindset’ to the team and is responsible for testing and delivering complex software requirements to accomplish business outcomes. Ensures the testing strategy and processes are well-defined and continuously improved for the team or teams. Establishes a test and automation strategy, creating common test frameworks, defining, and managing test processes including defect management and reporting. Creates and optimizes test processes including defect management and reporting. Contributes to building quality into the SDLC using best practices and tools. Creates a test automation strategy across the application stack (UI, API, and Backend, etc.). Creates and optimizes test automation frameworks and use of test automation tools. Leads test planning for complex features that span across the platform or multiple teams. Ensures alignment and sign off for test cases from business and other stakeholders. Optimizes test suites employing techniques such risk-based testing.

Manages test execution and assists with resolving, communicating, or escalating any issues that may result in test plan variance. Contributes to test data management approach and processes. Designs test data and ensures data compliance requirements are met on all levels of test environments. Assists in identifying and managing sensitive test data. Participates in triaging reported issues/defects and assists with resolving or escalating them as necessary. Creates and manages traceability. Traces tests forwards/backwards through the development lifecycle and back to requirements. Uses testing tools and follows processes to complete testing on a given test environment and assists with fulfillment of necessary steps required to promote code base to higher level environments. Individual contributor.

Required Qualifications :

• 7+ years of experience in automation testing with technologies like Java and Selenium, Webdriver, TestNG , Cucumber BDD , Junit, Core Java , Maven, Jenkins, Sauce labs, Applitools
• Experience in working in an Agile team and using JIRA
• Experience in test management tools - ALM, qTest

Desired Qualifications:

• Experience with accessibility testing
• Technical Strategy Development
• Test Engineering
• Solution Delivery Process
• Solution Design
• Stakeholder Management
• Agile Practices
• DevOps Practices

Hours Per Week:

Weekly Schedule:

Referral Bonus Amount:

Hours Per Week: 

Learn more about this role

JR-24030743

Manages People: Yes

Travel: Yes, 5% of the time

Street Address

Primary location:, important notice: you are now leaving bank of america.

By clicking Continue, you will be taken to a website that is not affiliated with Bank of America and may offer a different privacy policy and level of security. Bank of America is not responsible for and does not endorse, guarantee or monitor content, availability, viewpoints, products or services that are offered or expressed on other websites.

You can click the Return to Bank of America button now to return to the previous page or you can use the Back button on your browser after you leave.