Handheld Technology Selection, Evaluation, and Risk Mitigation Using Stochastic Analytical Hierarchical Process: A Standardization of the Request for Proposal Process

Abstract

Organizations deploying ruggedized handhelds experience complex device selection processes. The engineering manager-led decision-making process combines device-to-task fit and field service life. This selection process includes request for proposal processes, vendor negotiations, and device selection. The lengthy depreciation lifecycle often ensures a different practitioner team is organized to choose each new device iteration. A stochastic Analytical Hierarchy Process (AHP) is introduced for device selection. A criterions-derived list from real-world data contrasting ruggedized solutions is proposed illustrating the stochastic AHP process. Results indicate the most preferred device. Scenario-specific selection cases based on work culture, environment, and function are represented through sensitivity analyses.

Keywords:

• Request for Proposal
• Device Selection
• Multi-Criteria Decision-Making
• Stochastic AHP
• Ruggedized Handheld Devices

EMJ Focus Areas:

• Decision Making & Risk Management
• Engineering Management Profession
• Strategic Management
• Technology Management

Acknowledgements

The authors would like to thank the engineers at the industrial companies who provided their invaluable, real-world experience and feedback into our methods design. The authors would also like to thank the reviewers who made the narrative in this paper much stronger and applicable to the engineering managers who may use it.

Disclosure Statement

There is no conflict of interest.

Additional information

Notes on contributors

Farjana Nur

Farjana Nur, PhD, is working as a Data Scientist at Amazon.com. She has her PhD in Industrial & Systems Engineering from Mississippi State University. Nur’s research interests lie in optimization, simulation, and decision-making. In addition to many conference proceedings, her research appears in multiple reputed journals such as, OR Spectrum, IISE Transactions, and Computers & Industrial Engineering. She is an active member of INFORMS, WORMS, and IISE and is actively involved in different voluntary organizations.

Reuben F. Burch V

Reuben F. Burch, PhD, is an Associate Director of Human Factors & Athlete Engineering at the Center for Advanced Vehicular Systems (CAVS) and Assistant Professor of Industrial & Systems Engineering at Mississippi State University. He is a Faculty Research Fellow at the National Strategic Planning & Analysis Research Center (NSPARC), the Technology Fellow in Human Factors for The Communiversity at East Mississippi Community College, and the founder of the Athlete Engineering research program.

Mohammad Marufuzzaman

Mohammad Marufuzzaman, PhD, currently is an Associate Professor in the Industrial & Systems Engineering department at Mississippi State University. His main areas of interest lie in developing mathematical models and solution approaches to solve various real-life problems, with applications in transportation, energy, and security. Dr. Marufuzzaman secured approximately $7.8M research grants and published 56 peer-reviewed journal articles. He is a member of IISE and INFORMS.

Brian K. Smith

Brian K. Smith, PhD, CPEM, is an Associate Professor of Industrial & Systems Engineering at Mississippi State University. He holds a Bachelor of Science degree in Industrial Engineering from Mississippi State University along with Master of Science and PhD degrees in Industrial Engineering from University of Arkansas. He is a Professional Engineering Manager, certified by the American Society for Engineering Management. Dr. Smith has over ten years of engineering and management experience.