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E-Business and Management Science: Mutual Impacts (Part 1 of 2)

Author

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  • Arthur M. Geoffrion

    (Decisions, Operations, and Technology Management, John E. Anderson Graduate School of Management, University of California, Box 951481, Los Angeles, California 90095-1481)

  • Ramayya Krishnan

    (The Heinz School of Public Policy and Management, Carnegie Mellon University, Pittsburgh, Pennsylvania 15213)

Abstract

This begins a two-part commentary on management science and e-business, the theme of this two-part special issue. After explaining the topical clusters that give organization to both parts, we pose two key questions concerning the impact of the emerging digital economy on management science research: What fundamentally new research questions arise, and what kind of research enables progress on them. We sketch the papers appearing in this part from the perspective of both these questions, and offer summary comments on the first question based on the papers in both parts. The principal conclusion is that the digital economy is giving birth to new research questions in three main ways (not all independent): by enabling and popularizing several types of technology-mediated interactions, by spawning large-scale digital data sources, and by creating recurring operational decisions that need to be automated.

Suggested Citation

  • Arthur M. Geoffrion & Ramayya Krishnan, 2003. "E-Business and Management Science: Mutual Impacts (Part 1 of 2)," Management Science, INFORMS, vol. 49(10), pages 1275-1286, October.
    • Handle: RePEc:inm:ormnsc:v:49:y:2003:i:10:p:1275-1286
    DOI: 10.1287/mnsc.49.10.1275.17311
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    4. Amit V. Deokar & Omar F. El-Gayar, 2011. "Decision-enabled dynamic process management for networked enterprises," Information Systems Frontiers, Springer, vol. 13(5), pages 655-668, November.
    5. ManMohan S. Sodhi & Christopher S. Tang, 2008. "The OR/MS Ecosystem: Strengths, Weaknesses, Opportunities, and Threats," Operations Research, INFORMS, vol. 56(2), pages 267-277, April.
    6. H-V Seow, 2010. "Question selection responding to information on customers from heterogeneous populations to select offers that maximize expected profit," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(3), pages 443-454, March.
    7. Kevin Zhu & Kenneth L. Kraemer & Sean Xu, 2006. "The Process of Innovation Assimilation by Firms in Different Countries: A Technology Diffusion Perspective on E-Business," Management Science, INFORMS, vol. 52(10), pages 1557-1576, October.
    8. Ying-Ju Chen & Tinglong Dai & C. Gizem Korpeoglu & Ersin Körpeoğlu & Ozge Sahin & Christopher S. Tang & Shihong Xiao, 2020. "OM Forum—Innovative Online Platforms: Research Opportunities," Manufacturing & Service Operations Management, INFORMS, vol. 22(3), pages 430-445, May.
    9. Arthur M. Geoffrion & Ramayya Krishnan, 2003. "E-Business and Management Science: Mutual Impacts (Part 2 of 2)," Management Science, INFORMS, vol. 49(11), pages 1445-1456, November.
    10. Xintian Wang & Hai Wang, 2019. "A Study on Sustaining Corporate Innovation with E-Commerce in China," Sustainability, MDPI, vol. 11(23), pages 1-16, November.
    11. Doukidis, Georgios I. & Pramatari, Katerina & Lekakos, Georgios, 2008. "OR and the management of electronic services," European Journal of Operational Research, Elsevier, vol. 187(3), pages 1296-1309, June.
    12. Martínez-Caro, Eva & Cegarra-Navarro, Juan Gabriel & Alfonso-Ruiz, Francisco Javier, 2020. "Digital technologies and firm performance: The role of digital organisational culture," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    13. Amit Basu & Thomas F. Siems, 2004. "The impact of e-business technologies on supply chain operations: a macroeconomic perspective," Working Papers 0404, Federal Reserve Bank of Dallas.
    14. Gabriela Andrisan & Andra Modreanu, 2021. "The Chain Reactions of Business Models and Strategies," Ovidius University Annals, Economic Sciences Series, Ovidius University of Constantza, Faculty of Economic Sciences, vol. 0(1), pages 449-454, August.
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    16. Seow, Hsin-Vonn & Thomas, Lyn C., 2006. "Using adaptive learning in credit scoring to estimate take-up probability distribution," European Journal of Operational Research, Elsevier, vol. 173(3), pages 880-892, September.

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