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Achieving dynamic capabilities with cloud computing: an empirical investigation

Author

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  • Douglas A Battleson
  • Barry C West
  • Jongwoo Kim
  • Balasubramaniam Ramesh
  • Pamela S Robinson

Abstract

Cloud computing enables convenient and on-demand access to a shared pool of configurable computing resources. While cloud computing‘s ability to improve operational efficiency has gained much attention in the literature, there has been limited research on how it can help organizations achieve dynamic capabilities. Drawing from dynamic capabilities theory, we conducted a field study using a multiple case study design to examine the following research question: How do organizations achieve dynamic capabilities by using Cloud Computing? We develop a framework that explains how organizations respond to market dynamism by developing sense-and-response strategies that enable them to achieve dynamic capabilities using business process redesign, business network redesign, and business scope redefinition. We discuss how these transformations, in turn, improve organizational outcomes such as service effectiveness and efficiency. Our study also identifies factors that support and hinder the development of dynamic capabilities. Our study contributes to the literature on dynamic capabilities by examining how IT capabilities like cloud computing may accelerate the ability of an organization to achieve dynamic capabilities. We also identify transformational changes of business processes and inter-organizational networks that are enabled by cloud computing. Further, we identify how the essential characteristics of cloud computing support sense and respond strategies.

Suggested Citation

  • Douglas A Battleson & Barry C West & Jongwoo Kim & Balasubramaniam Ramesh & Pamela S Robinson, 2016. "Achieving dynamic capabilities with cloud computing: an empirical investigation," European Journal of Information Systems, Taylor & Francis Journals, vol. 25(3), pages 209-230, May.
  • Handle: RePEc:taf:tjisxx:v:25:y:2016:i:3:p:209-230
    DOI: 10.1057/ejis.2015.12
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    Cited by:

    1. Sullivan, Yulia & Fosso Wamba, Samuel, 2024. "Artificial intelligence and adaptive response to market changes: A strategy to enhance firm performance and innovation," Journal of Business Research, Elsevier, vol. 174(C).
    2. Agag, Gomaa & Shehawy, Yasser Moustafa & Almoraish, Ahmed & Eid, Riyad & Chaib Lababdi, Houyem & Gherissi Labben, Thouraya & Abdo, Said Shabban, 2024. "Understanding the relationship between marketing analytics, customer agility, and customer satisfaction: A longitudinal perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 77(C).
    3. Jiyong Park & Kunsoo Han & Byungtae Lee, 2023. "Green Cloud? An Empirical Analysis of Cloud Computing and Energy Efficiency," Management Science, INFORMS, vol. 69(3), pages 1639-1664, March.
    4. Lange, Francie & Tomini, Nino & Brinkmann, Florian & Kanbach, Dominik K. & Kraus, Sascha, 2023. "Demystifying massive and rapid business scaling – An explorative study on driving factors in digital start-ups," Technological Forecasting and Social Change, Elsevier, vol. 196(C).
    5. Dirk Schneckenberg & Jose Benitez & Christoph Klos & Vivek Velamuri & Patrick Spieth, 2021. "Value creation and appropriation of software vendors: A digital innovation model for cloud computing," Post-Print hal-03329065, HAL.
    6. Pinto, Marcelo Rezende & Salume, Paula Karina & Barbosa, Marcelo Werneck & de Sousa, Paulo Renato, 2023. "The path to digital maturity: A cluster analysis of the retail industry in an emerging economy," Technology in Society, Elsevier, vol. 72(C).
    7. Abdul Ismail Hj Mohd Jawi & Malvern Abdullah & Chung Siew Mee Ellen Chung, 2023. "Recent Development on Information System Capabilities and Sustainable Competitive Advantages: A Research Model, Review and Directions for Future Research," Information Management and Business Review, AMH International, vol. 15(2), pages 44-56.

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