Papers

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Journal Article
Metcalf, L., Askay, D. A., & Rosenberg, L. B.. (2019). Pooling knowledge through artificial swarm intelligence to improve business decision making. California Management Review, 61(4), 84 - 109. https://doi.org/10.1177/0008125619862256
Parker, S. K., Morgeson, F. P., & Johns, G.. (2017). One hundred years of work design research: Looking back and looking forward. Journal Of Applied Psychology, 102(3), 403 - 420. https://doi.org/10.1037/apl0000106
N. Meyer, D. (1982). Office automation: A progress report. Office Technology And People, 1(1), 107 - 121. https://doi.org/10.1108/eb022608
Seeber, I., Bittner, E., Briggs, R. O., de Vreede, T., de Vreede, G. Jan, Elkins, A., et al.. (2020). Machines as teammates: A research agenda on AI in team collaboration. Information And Management, 57, 103174. https://doi.org/10.1016/j.im.2019.103174
Seeber, I., Bittner, E., Briggs, R. O., de Vreede, T., de Vreede, G. Jan, Elkins, A., et al.. (2020). Machines as teammates: A research agenda on AI in team collaboration. Information And Management, 57, 103174. https://doi.org/10.1016/j.im.2019.103174
Moore, M. M., Slonimsky, E., Long, A. D., Sze, R. W., & Iyer, R. S.. (2019). Machine learning concepts, concerns and opportunities for a pediatric radiologist. Pediatric Radiology, 49(4), 509 - 516. https://doi.org/10.1007/s00247-018-4277-7
Morgeson, F. P., & Humphrey, S. E.. (2008). Job and team design: Toward a more integrative conceptualization of work design. Research In Personnel And Human Resources Managementresearch In Personnel And Human Resources Management, 27, 39–91.
Mehic, A. (2018). Industrial employment and income inequality: Evidence from panel data. Structural Change And Economic Dynamics, 45, 84 - 93. https://doi.org/10.1016/j.strueco.2018.02.006
Jennings, N. R., Moreau, L., Nicholson, D., Ramchurn, S., Roberts, S., Rodden, T., & Rogers, A.. (2014). Human-agent collectives. Communications Of The Acm, 57(12), 80 - 88. https://doi.org/10.1145/269296510.1145/2629559
Mukhalipi, A. (2018). Human capital management and future of work; job creation and unemployment: a literature review. Oalib, 05(09), 1 - 17. https://doi.org/10.4236/oalib.1104859
Bærøe, K., Miyata-Sturm, A., & Henden, E.. (2020). How to achieve trustworthy artificial intelligence for health. Bulletin Of The World Health Organization, 98, 257–262. https://doi.org/10.2471/BLT.19.237289
Cascio, W. F., & Montealegre, R.. (2016). How technology is changing work and organizations. Annual Review Of Organizational Psychology And Organizational Behavior, 3(1), 349 - 375. https://doi.org/10.1146/annurev-orgpsych-041015-062352
Mendling, J., Decker, G., Hull, R., Reijers, H. A., & Weber, I.. (2018). How do machine learning, robotic process automation, and blockchains affect the human factor in business process management?. Communications Of The Association For Information Systems, 297 - 320. https://doi.org/10.17705/1CAIS.04319
Mokyr, J., Vickers, C., & Ziebarth, N. L.. (2015). The history of technological anxiety and the future of economic growth: Is this time different?. Journal Of Economic Perspectives, 29(3), 31 - 50. https://doi.org/10.1257/jep.29.3.31
Moody, K. (2018). High tech, low growth: Robots and the future of work abstract. Historical Materialism, 26(4), 3 - 34. https://doi.org/10.1163/1569206X-00001745
Madakam, S., Holmukhe, R. M., & Jaiswal, D. Kumar. (2019). The future digital work force: Robotic process automation (RPA). Journal Of Information Systems And Technology Management, 16. https://doi.org/10.4301/S1807-1775201916001
Makridakis, S. (2017). The forthcoming Artificial Intelligence (AI) revolution: Its impact on society and firms. Futures, 90, 46 - 60. https://doi.org/10.1016/j.futures.2017.03.006

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