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B
Barley, S. R., & Kunda, G.. (2001). Bringing work back in. Organization Science, 12, 76–95. https://doi.org/10.1287/orsc.12.1.76.10122
Bednarek, A. T., Wyborn, C., Cvitanovic, C., Meyer, R., Colvin, R. M., Addison, P. F. E., et al.. (2018). Boundary spanning at the science–policy interface: the practitioners’ perspectives. Sustainability Science, 13(4), 1175 - 1183. https://doi.org/10.1007/s11625-018-0550-9
Seering, J., Luria, M., Kaufman, G., & Hammer, J.. (2019). Beyond Dyadic Interactions: Considering Chatbots as Community Members (S. Brewster, Fitzpatrick, G., Cox, A., & Kostakos, V., Trans.). In Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems - CHI '19 (1-13). https://doi.org/10.1145/3290605
C
Crews, A. (2015). The big move toward big data in employment. In Employment& Labor Law Solutions Worldwide. Retrieved de https://www.littler.com/files/wp_big_data_8-04-15.pdf
Crowston, K., Østerlund, C., & Lee, T. Kyoung. (2017). Blending machine and human learning processes. In Hawai'i International Conference on System Sciences. https://doi.org/10.24251/HICSS.2017.009
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D
Moore, P. V. (2019). Benefits and risks of artificial intelligence tools in workplaces (Vol. 11581, pp. 292 - 315; V. G. Duffy, Ed.). In (Vol. 11581, pp. 292 - 315). https://doi.org/10.1007/978-3-030-22216-1_22
J
Johnson, R. D., Stone, D. L., & Lukaszewski, K. M.. (2020). The benefits of eHRM and AI for talent acquisition. Journal Of Tourism Futures. https://doi.org/10.1108/JTF-02-2020-0013
S
Smith, Z. (2019). Blame the boss, not the robot. New Labor Forum, 28(2), 66 - 69. https://doi.org/10.1177/1095796019837947