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Managing Software‐as‐a‐Service: Pricing and operations

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  • Bo Li
  • Subodha Kumar

Abstract

Software‐as‐a‐service (SaaS) applications have experienced a decade of explosive growth, eliminating barriers in reaching users and enabling real‐time interchanges and intelligence. Using business analytics, SaaS applications are increasingly embedded in the day‐to‐day activities of businesses and consumers with competition and innovative pricing. Due to the evolution in cloud business models, new issues are surfacing to challenge practitioners and scholars. A number of issues encountered in the practice have not been properly addressed or even recognized. In this paper, we attempt to fill this important gap. We propose a framework of recent business research on SaaS in light of wide adoption of the SaaS business model. This framework broadly classifies SaaS research into two basic themes. For each theme, we review past work that has been instrumental in setting the direction of this line of research and discuss how emerging research opportunities can be addressed. For each research opportunity, we also propose an initial model and the applicable methodology. Further, in order to aid researchers, we identify the data sources wherever applicable, and even present some of the initial results. We conclude by describing promising directions on a roadmap for future research and explain why an integrative perspective of operations, marketing, and information systems is critical to SaaS. In this paper, we bridge the gap between research and practice by identifying the relevant industry problems that would help researchers who are interested in working in this area both to get a starting point and to address important theoretical and practical challenges.

Suggested Citation

  • Bo Li & Subodha Kumar, 2022. "Managing Software‐as‐a‐Service: Pricing and operations," Production and Operations Management, Production and Operations Management Society, vol. 31(6), pages 2588-2608, June.
  • Handle: RePEc:bla:popmgt:v:31:y:2022:i:6:p:2588-2608
    DOI: 10.1111/poms.13729
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    1. Li, Bo & Tan, Zhen & Arreola-Risa, Antonio & Huang, Yiwei, 2023. "On the improvement of uncertain cloud service capacity," International Journal of Production Economics, Elsevier, vol. 258(C).

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