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The Future of Work: Identifying Future-ready Capabilities for the Industrial Distribution Workforce

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Conference

2021 ASEE Virtual Annual Conference Content Access

Location

Virtual Conference

Publication Date

July 26, 2021

Start Date

July 26, 2021

End Date

July 19, 2022

Conference Session

New Directions for Engineering Technology

Tagged Division

Engineering Technology

Page Count

15

Permanent URL

https://peer.asee.org/37864

Download Count

34

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Paper Authors

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Shaoping Qiu Texas A&M University Orcid 16x16 orcid.org/0000-0002-2857-4415

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Shaoping Qiu, Ph.D. is a postdoctoral Researcher in the Department of Engineering Technology and Industrial Distribution, Texas A&M University. His research interests include organizational leadership, organizational
change, stress and well-being, training & development, and quantitative methods such
as multiple regression, structural equation modelling (SEM), hierarchical linear model (HLM), and item response theory
(IRT).

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Malini Natarajarathinam Texas A&M University Orcid 16x16 orcid.org/0000-0003-1684-6476

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Dr. Malini Natarajarathinam joined the faculty of Industrial Distribution Program at Texas A&M University in 2007. Natarajarathinam received her Ph.D. in Supply Chain Management from The University of Alabama. She received her Bachelor of Engineering (Major: Industrial and Systems Engineering) from Anna University [Tamilnadu, India], her MS in Industrial Engineering from Auburn University, her MA in Management Science and MS in Applied Statistics from The University of Alabama. She has experience working with many industries such as automotive, chemical distribution etc. on transportation and operations management projects. She works extensively with food banks and food pantries on supply chain management and logistics focused initiatives. Her graduate and undergraduate students are integral part of her service-learning based logistics classes.

She teaches courses in strategic relationships among industrial distributors and distribution logistics. Her recent research focuses on engineering education and learning sciences with a focus on how to engage students better to prepare their minds for the future. Her other research interests include empirical studies to assess impact of good supply chain practices such as coordinated decision making in stochastic supply chains, handling supply chains during times of crisis and optimizing global supply chains on the financial health of a company. She has published her research in Journal of Business Logistics, International Journal of Physical Distribution and Logistics Management and peer-reviewed proceedings of the American Society for Engineering Education.

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Michael D. Johnson Texas A&M University Orcid 16x16 orcid.org/0000-0001-5328-8763

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Dr. Michael D. Johnson is a professor in the Department of Engineering Technology and Industrial Distribution at Texas A&M University. Prior to joining the faculty at Texas A&M, he was a senior product development engineer at the 3M Corporate Research Laboratory in St. Paul, Minnesota. He received his B.S. in mechanical engineering from Michigan State University and his S.M. and Ph.D. from the Massachusetts Institute of Technology. Dr. Johnson’s research focuses on engineering education; design tools; specifically, the cost modeling and analysis of product development and manufacturing systems; and computer-aided design methodology.

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Elizabeth A. Roumell Texas A&M University

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Elizabeth A. Roumell, Ph.D., is an Associate Professor in the Educational Administration and Human Resource Development department at Texas A&M University. Dr. Roumell teaches classes related to adult learning, teaching and training for adults, evaluation and performance assessment, and instructional design for remote and online learning. Dr. Roumell's research areas include adult and workforce education policy development and analysis, learning in technology rich environments, and supporting adults through learning and career transitions.

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Abstract

We are now living on the threshold of the new production revolution. Industry 4.0 technologies such as autonomous robots, the Industrial Internet of Things (IoT), cobots, hands-free wearables, data analytics are bringing widespread automation and irreversible shifts in the structure of jobs (Kergroach, 2017). Warehouses are the heart of a company’s operations – be it manufacturing, wholesale, or retail. Adoptions of these emerging technologies are likely to contribute to greater productivity and create enormous economic benefits in warehouses. However, these emerging technological developments raise major challenges in labor markets and for policymakers responsible for promoting the necessary skills and employment. Emerging evidence in the past five years has indicated that major labor gaps are bound to occur due to Industry 4.0 technologies (NASEM, 2017). Therefore, it is imperative to better understand and track these trends in the labor market and the future of work (FOW) so that strategies to inform, prepare for, and respond to changes in the industrial distribution workplace can be developed. This study is exploratory in nature. It will explore the experience of workers in the warehousing and industrial distribution sectors, and ultimately this paper will provide preliminary findings of how workers view their work and training evolving in the new few years due to Industry 4.0 technologies. The purposes of this study are to (1) explore workers’ perceptions of the influence of FOW technologies within current workplace practices, (2) to identify barriers to future-ready capabilities, and (3) better understand how low-skilled workers will be impacted by FOW changes. This work will adopt a grounded theory research study and employ snowball sampling method to identify research participants in both small and large enterprises in the industrial distribution sector. A total of about 20-30 workers will be recruited from 10-12 companies. Interviews and focus groups will be conducted to collect the data. For the data analysis, Strauss and Corbin’s (1990) guidelines will be followed and open coding, axial coding, and selective coding will be used to extract the main themes that constitute works’ perceptions of the influence of FOW technologies, as well as barriers and skills gaps faced by low-skilled workers impacted by FOW changes. On the basis of research results, strategies to inform, prepare for, and respond to changes in the industrial distribution workplace will be presented. Preliminary findings of this study will serve as practical suggestions for industry leaders, workplace training, workforce development, and upskilling for workers. The findings will also provide guidelines for adult learning practice, program delivery, professional development for adult educators, and evidence-based practices for the development of digital literacy within underserved populations.

Qiu, S., & Natarajarathinam, M., & Johnson, M. D., & Roumell, E. A. (2021, July), The Future of Work: Identifying Future-ready Capabilities for the Industrial Distribution Workforce Paper presented at 2021 ASEE Virtual Annual Conference Content Access, Virtual Conference. https://peer.asee.org/37864

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