Skip to main content Accessibility help

We use cookies to distinguish you from other users and to provide you with a better experience on our websites. Close this message to accept cookies or find out how to manage your cookie settings.

Close cookie message
×
Hostname: page-component-cd9895bd7-p9bg8 Total loading time: 0 Render date: 2024-12-26T17:43:04.744Z Has data issue: false hasContentIssue false

17 - Implications of the Changing Nature of Work for Training

from Part III - Implications for Talent Management and Impact on Employees

Published online by Cambridge University Press:  02 April 2020

By
Tiffany M. Bisbey ,
Allison Traylor  and
Eduardo Salas
Edited by
Brian J. Hoffman ,
Mindy K. Shoss  and
Lauren A. Wegman
Brian J. Hoffman
Affiliation:
University of Georgia
Mindy K. Shoss
Affiliation:
University of Central Florida
Lauren A. Wegman
Affiliation:
University of Georgia
Get access

Summary

Training and development serve as important mechanisms through which organizations can prepare employees for the future of work. This chapter outlines implications for training, including how extant research can inform future interventions and how these approaches might adapt to account for technological, demographic, and behavioral shifts in the workplace.

Keywords

trainingdevelopmentlearningtechnologychangeworkforce readinessfuture of work
Type
Chapter
Information
The Cambridge Handbook of the Changing Nature of Work , pp. 364 - 382
Publisher: Cambridge University Press
Print publication year: 2020

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

References

Adler, P. S. (2001). Market, hierarchy, and trust: The knowledge economy and the future of capitalism. Organization Science, 12, 215–234. doi: 10.1287/orsc.12.2.215.10117Google Scholar
Baldwin, T. T., Ford, J. K., & Blume, B. D. (2017). The state of transfer of training research: Moving toward more consumer‐centric inquiry. Human Resource Development Quarterly, 28, 17–28. doi: 10.1002/hrdq.21278Google Scholar
Bartel, A., Ichniowski, C., & Shaw, K. (2007). How does information technology affect productivity? Plant-level comparisons of product innovation, process improvement and worker skills. Quarterly Journal of Economics, 122, 1721–1758. doi: 10.1162/qjec.2007.122.4.1721Google Scholar
Beier, M. E. (2008). International review of industrial and organizational psychology. In Hodgkinson, G. P. & Ford, J. K. (Eds.), International Review of Industrial and Organizational Psychology, 2008. Chichester, UK: John Wiley & Sons.Google Scholar
Beier, M. E., Teachout, M. S., & Cox, C. B. (2012). The training and development of an aging workforce. In Borman, W. C. & Hedge, J. W. (Eds.), The Oxford handbook of work and aging (pp. 436–453). New York, NY: Oxford University PressGoogle Scholar
Bell, B. S., Tannenbaum, S. I., Ford, J. K., Noe, R. A., & Kraiger, K. (2017). 100 years of training and development research: What we know and where we should go. Journal of Applied Psychology, 102, 305–323. doi: 10.1037/apl0000142Google Scholar
Berman, E., Bound, J., & Griliches, Z. (1994). Changes in the demand for skilled labor within US manufacturing: evidence from the annual survey of manufactures. Quarterly Journal of Economics, 109(2), 367–397.Google Scholar
Bezrukova, K., Spell, C. S., Perry, J. L., & Jehn, K. A. (2016). A meta-analytical integration of over 40 years of research on diversity training evaluation. Psychological Bulletin, 142, 1227–1274. doi: 10.1037/bul0000067CrossRefGoogle ScholarPubMed
Bird, A., Mendenhall, M., Stevens, M. J., & Oddou, G. (2010). Defining the content domain of intercultural competence for global leaders. Journal of Managerial Psychology, 25, 810–828. doi: 10.1108/02683941011089107Google Scholar
Black, J. S., & Mendenhall, M. (1990). Cross-cultural training effectiveness: A review and a theoretical framework for future research. Academy of Management Review, 15, 113–136. doi: 10.2307/258109Google Scholar
Bonet, R., Cappelli, P., & Hamori, M. (2013). Labor market intermediaries and the new paradigm for human resources. Academy of Management Annals, 7, 339–390. doi: 10.1080/19416520.2013.774213Google Scholar
Boothby, D., Dufour, A., & Tang, J. (2010). Technology adoption, training and productivity performance. Research Policy, 39, 650–661. doi: 10.1016/j.respol.2010.02.011Google Scholar
Boudreau, J. W., & Ramstad, P. M. (2005). Talentship, talent segmentation, and sustainability: A new HR decision science paradigm for a new strategy definition. Human Resource Management, 44, 129–136. doi: 10.1002/hrm.20054CrossRefGoogle Scholar
Brynjolfsson, E., Rock, D., & Syverson, C. (2017). Artificial intelligence and the modern productivity paradox: A clash of expectations and statistics (No. w24001). Cambridge, MA: National Bureau of Economic Research. doi: 10.3386/w24001Google Scholar
Burke, L. A., & Hutchins, H. M. (2008). A study of best practices in training transfer and proposed model of transfer. Human Resource Development Quarterly, 19, 107–128. doi: 10.1002/hrdq.1230Google Scholar
Burke, R. J., & Ng, E. (2006). The changing nature of work and organizations: Implications for human resource management. Human Resource Management Review, 16, 86–94. doi: 10.1016/j.hrmr.2006.03.006Google Scholar
Callahan, J. S., Kiker, D. S., & Cross, T. (2003). Does method matter? A meta-analysis of the effects of training method on older learner training performance. Journal of Management, 29, 663–680. doi: 10.1016/S0149-2063_03_00029-1Google Scholar
Cannon-Bowers, J. A., Rhodenizer, L., Salas, E., & Bowers, C. A. (1998). A framework for understanding pre‐practice conditions and their impact on learning. Personnel Psychology, 51, 291–320. doi: 10.1111/j.1744-6570.1998.tb00727.xGoogle Scholar
Carnevale, A. P., Strohl, J., & Gulish, A. (2015). College is just the beginning: Employers’ role in the $1.1 trillion postsecondary education and training system (Report No. ED558166). Washington, DC: Georgetown University Center on Education and the Workforce. Retrieved from https://files.eric.ed.gov/fulltext/ED558166.pdfGoogle Scholar
Cascio, W. F. (2019). Training trends: Macro, micro, and policy issues. Human Resource Management Review, 29, 284–297.Google Scholar
Cascio, W. F., & Montealegre, R. (2016). How technology is changing work and organizations. Annual Review of Organizational Psychology and Organizational Behavior, 3, 349–375. doi: 10.1146/annurev-orgpsych-041015-062352Google Scholar
Charness, N. (2009). Skill acquisition in older adults: Psychological mechanisms. In Czaja, S. J. & Sharit, J. (Eds.), Aging and work (pp. 232–258). Baltimore, MD: Johns Hopkins University Press.Google Scholar
Chebium, R. (2015, January 7). How to create an effective cross-cultural training program. Retrieved from www.shrm.org/hr-today/news/hr-magazine/pages/010215-cross-cultural-training.aspxGoogle Scholar
Chen, G., Gully, S. M., Whiteman, J. A., & Kilcullen, R. N. (2000). Examination of relationships among trait-like individual differences, state-like individual differences, and learning performance. Journal of Applied Psychology, 85, 835–847. doi: 10.1037/0021-9010.85.6.835Google Scholar
Cooke, P. (2001). Regional innovation systems, clusters, and the knowledge economy. Industrial and Corporate Change, 10, 945–974. doi: 10.1093/icc/10.4.945Google Scholar
Cross, R., Rebele, R., & Grant, A. (2016). Collaborative overload. Harvard Business Review, 94, 74–79.Google Scholar
Dobbin, F., & Kalev, A. (2016). Why diversity programs fail. Harvard Business Review, 94(7), 14.Google Scholar
Equal Employment Opportunity Commission. (2018). Charge statistics. Retrieved from www1.eeoc.gov/eeoc/statistics/enforcement/charges.cfmGoogle Scholar
Gatta, M. (2008). Low-skill workers, technology, and education: A new vision for workforce development policy. Economic & Labour Relations Review, 19, 109–127. doi: 10.1177/103530460801900108Google Scholar
Goldstein, I. L., & Ford, K. J. (1993). Training in organizations: Needs assessment, development, and evaluation. Pacific Grove, CA: Brooks.Google Scholar
Haccoun, R. R., & Hamtiaux, T. (1994). Optimizing knowledge tests for inferring learning acquisition levels in single group training evaluation designs: The internal referencing strategy. Personnel Psychology, 47, 593–604. doi: 10.1111/j.1744-6570.1994.tb01739.xGoogle Scholar
Hirschman, C., & Mogford, E. (2009). Immigration and the American industrial revolution from 1880 to 1920. Social Science Research, 38, 897–920. doi: 10.1016/j.ssresearch.2009.04.001Google Scholar
Hughes, A. M., Gregory, M. E., Joseph, D. L., Sonesh, S. C., Marlow, S. L., Lacerenza, C. N., … & Salas, E. (2016). Saving lives: A meta-analysis of team training in healthcare. Journal of Applied Psychology, 101, 1266–1304. doi: 10.1037/apl0000120CrossRefGoogle ScholarPubMed
Job, M. A., & Ogalo, H. S. (2012). Micro-learning as innovative process of knowledge strategy. International Journal of Scientific and Technology Research, 1(11). Retrieved from www.ijstr.org/final-print/dec2012/Micro-Learning-As-Innovative-Process-Of-Knowledge-Strategy.pdfGoogle Scholar
Keith, N., & Frese, M. (2008). Effectiveness of error management training: A meta-analysis. Journal of Applied Psychology, 93, 59–69. doi: 10.1037/0021-9010.93.1.59Google Scholar
Kirkpatrick, D. L. (1994). Evaluating training programs: The four levels. San Francisco, CA: Berrett-Koehler. (Original work published 1959.)Google Scholar
Knowles, M. S., Holton, E. F., & Swanson, R. A. (2005). The adult learner: The definitive classic in adult education and human resource development (6th ed.). Boston, MA: Elsevier.Google Scholar
Kraiger, K. (2002). Decision-based evaluation. In Kraiger, K. (Ed.), Creating, implementing, and maintaining effective training and development: State-of-the-art lessons for practice (pp. 331–375). San Francisco, CA: Jossey-Bass.Google Scholar
Kraiger, K. (2008). Transforming our models of learning and development: Web‐based instruction as enabler of third‐generation instruction. Industrial and Organizational Psychology, 1, 454–467. doi: 10.1111/j.1754-9434.2008.00086.xGoogle Scholar
Kraiger, K. (2014). Looking back and looking forward: Trends in training and development research. Human Resource Development Quarterly, 25, 401–408. doi: 10.1002/hrdq.21203Google Scholar
Kubeck, J. E., Delp, N. D., Haslett, T. K., & McDaniel, M. A. (1996). Does job-related training performance decline with age? Psychology and Aging, 11, 92–107. doi: 10.1037/0882-7974.11.1.92Google Scholar
Lacerenza, C. N., Reyes, D. L., Marlow, S. L., Joseph, D. L., & Salas, E. (2017). Leadership training design, delivery, and implementation: A meta-analysis. Journal of Applied Psychology. doi: 10.1037/apl0000241CrossRefGoogle Scholar
Landers, R. N., & Armstrong, M. B. (2017). Enhancing instructional outcomes with gamification: An empirical test of the Technology-Enhanced Training Effectiveness Model. Computers in Human Behavior, 71, 499–507. doi: 10.1016/j.chb.2015.07.031Google Scholar
Lim, H., Lee, S.-G., & Nam, K. (2007). Validating E-learning factors affecting training effectiveness. International Journal of Information Management, 27, 22–35. doi: 10.1016/j.ijinfomgt.2006.08.002Google Scholar
Malone, T. (2004). The future of work: How the new order of business will shape your organization, your management style, and your life. Boston, MA: Harvard Business School Press.Google Scholar
Martin, H. J. (2010). Workplace climate and peer support as determinants of training transfer. Human Resource Development Quarterly, 21, 87–104. doi: 10.1002/hrdq.20038Google Scholar
Mayer, R. E. (1979). Can advance organizers influence meaningful learning? Review of Educational Research, 49, 371–383. doi: 10.3102/00346543049002371Google Scholar
McGovern, M. (2017). Thriving in the gig economy: How to capitalize and compete in the new world of work. Wayne, NJ: Career Press.Google Scholar
Moseley, J. L., & Dessigner, J. C. (2007). Training older workers and learners: Maximizing the performance of an aging workforce. San Francisco, CA: Wiley & Sons.Google Scholar
Ng, E. S. W., Schweitzer, L., & Lyons, S. T. (2010). New generation, great expectations: A field study of the millennial generation. Journal of Business and Psychology, 25, 281–292. doi: 10.1007/s10869-010-9159-4CrossRefGoogle Scholar
Noe, R. A. (1986). Trainees’ attributes and attitudes: Neglected influences on training effectiveness. Academy of Management Review, 11, 736–749. doi: 10.5465/AMR.1986.4283922Google Scholar
Noe, R. A., & Colquitt, J. A. (2002). Planning for training impact: Principles of training effectiveness. In Kraiger, K. (Ed.), Creating, implementing, and managing effective training and development (pp. 53–79). San Francisco, CA: Jossey-Bass.Google Scholar
Ouadahi, J. (2008). A qualitative analysis of factors associated with user acceptance and rejection of a new workplace information system in the public sector: A conceptual model. Canadian Journal of Administrative Sciences, 25, 201–213. doi: 10.1002/cjas.65Google Scholar
PayScale (2016). 2016 workforce-skills preparedness report. Seattle, WA: PayScale, Inc. Retrieved from www.payscale.com/data-packages/job-skillsGoogle Scholar
Phillips, J. J. (2012). Handbook of training evaluation and measurement methods. London, UK: Routledge.Google Scholar
Powell, W. W., & Snellman, K. (2004). The knowledge economy. Annual Review of Sociology, 30, 199–220. doi: 10.1146/annurev.soc.29.010202.100037Google Scholar
Quiñones, M. A., Ford, J. K., Sego, D. J., & Smith, E. M. (1995). The effects of individual and transfer environment characteristics on the opportunity to perform trained tasks. Training Research Journal, 1, 29–48.Google Scholar
Rau, B. L., & Hyland, M. A. M. (2002). Role conflict and flexible work arrangements: The effects on applicant attraction. Personnel Psychology, 55, 111–136. doi: 10.1111/j.1744-6570.2002.tb00105.xGoogle Scholar
Roberson, L., Kulik, C. T., & Tan, R. Y. (2012). Effective diversity training. In Roberson, Q. M. (Ed.), The Oxford handbook of diversity and work (pp. 341–365). New York, NY: Oxford University Press.Google Scholar
Robles, M. M. (2012). Executive perceptions of the top soft skills needed in today’s workplace. Business Communication Quarterly, 75, 453–465. doi: 10.1177/1080569912460400Google Scholar
Salas, E., & Cannon-Bowers, J. A. (2001). The science of training: A decade of progress. Annual Review of Psychology, 52, 471–499. doi: 10.1146/annurev.psych.52.1.471Google Scholar
Salas, E., Tannenbaum, S. I., Kraiger, K., & Smith-Jentsch, K. A. (2012). The science of training and development in organizations: What matters in practice. Psychological Science in the Public Interest, 13(2), 74–101. doi: 10.1177/1529100612436661Google Scholar
Senge, P. M., Kleiner, A., Roberts, C., Ross, R. B., & Smith, B. J. (2014). The fifth discipline fieldbook: Strategies and tools for building a learning organization. New York, NY: Crown Publishing Group.Google Scholar
Simon, S. J., & Werner, J. M. (1996). Computer training through behavior modeling, self-paced, and instructional approaches: A field experiment. Journal of Applied Psychology, 81, 648–659. doi: 10.1037/0021-9010.81.6.648Google Scholar
Singh, P. (2008). Job analysis for a changing workplace. Human Resource Management Review, 18, 87–99. doi: 10.1016/j.hrmr.2008.03.004Google Scholar
Sitzmann, T., Bell, B. S., Kraiger, K., & Kanar, A. M. (2009). A multilevel analysis of the effect of prompting self‐regulation in technology‐delivered instruction. Personnel Psychology, 62, 697–734. doi: 10.1111/j.1744-6570.2009.01155.xGoogle Scholar
Sitzmann, T., Kraiger, K., Stewart, D., & Wisher, R. (2006). The comparative effectiveness of web-based and classroom instruction: A meta-analysis. Personnel Psychology, 59, 623–664. doi: 10.1111/j.1744-6570.2006.00049.xGoogle Scholar
Smith-Jentsch, K. A., Cannon-Bowers, J. A., Tannenbaum, S. I., & Salas, E. (2008). Guided team self-correction: Impacts on team mental models, processes, and effectiveness. Small Group Research, 39, 303–327. doi: 10.1177/1046496408317794Google Scholar
Sommers, D., & Franklin, J. C. (2012). Overview of projections to 2020. Monthly Labor Review, 135(1), 3–20.Google Scholar
Tannenbaum, S. I., Mathieu, J. E., Salas, E., & Cannon-Bowers, J. A. (1991). Meeting trainees’ expectations: The influence of training fulfillment on the development of commitment, self-efficacy, and motivation. Journal of Applied Psychology, 76, 759–769. doi: 10.1037/0021-9010.76.6.759Google Scholar
Toossi, M. (2012). Projections of the labor force to 2050: A visual essay. Monthly Labor Review, 135(10), 3–16.Google Scholar
Tracey, J. B., Hinkin, T. R., Tannenbaum, S., & Mathieu, J. E. (2001). The influence of individual characteristics and the work environment on varying levels of training outcomes. Human Resource Development Quarterly, 12, 5–23.Google Scholar
Wenger, E., McDermott, R. A., & Snyder, W. (2002). Cultivating communities of practice: A guide to managing knowledge. Boston, MA: Harvard Business School Press.Google Scholar
Wolfson, N. E., Cavanagh, T. M., & Kraiger, K. (2014). Older adults and technology-based instruction: Optimizing learning outcomes and transfer. Academy of Management Learning & Education, 13, 26–44. doi: 10.5465/amle.2012.0056Google Scholar
Wolfson, N. E., & Kraiger, K. (2014). Cognitive aging and training: The role of instructional coherence and advance organizers. Experimental Aging Research, 40, 164–186. doi: 10.1080/0361073X.2014.882206Google Scholar
Yan, B. (2006). Demand for skills in Canada: the role of foreign outsourcing and information‐communication technology. Canadian Journal of Economics/Revue canadienne d'économique, 39(1), 53–67.Google Scholar
Young, C. K. (2017). Age and training: A meta-analysis examining training features (Doctoral dissertation). Retrieved from ProQuest Dissertations & Theses. (Accession No. 2018-13260-247).Google Scholar

Save book to Kindle

To save this book to your Kindle, first ensure no-reply@cambridge.org is added to your Approved Personal Document E-mail List under your Personal Document Settings on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part of your Kindle email address below. Find out more about saving to your Kindle.

Note you can select to save to either the @free.kindle.com or @kindle.com variations. ‘@free.kindle.com’ emails are free but can only be saved to your device when it is connected to wi-fi. ‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.

Find out more about the Kindle Personal Document Service.

Available formats
×

Save book to Dropbox

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Dropbox.

Available formats
×

Save book to Google Drive

To save content items to your account, please confirm that you agree to abide by our usage policies. If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account. Find out more about saving content to Google Drive.

Available formats
×