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Drivers and Inhibitors of Big Data as a Service Adoption in India

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Listed:
  • Surabhi Verma
  • Som Sekhar Bhattacharyya

Abstract

The purpose of this research articles is to analyze the characteristics of big data as a service (BDaaS) markets which is currently in its initial stages from adoption driving and inhibiting perspectives. This study theoretically classifies the BDaaS market into drivers and inhibitors through the PEST analysis based on previous literature. Analytic hierarchy process (AHP) matrix was used to analyze the segmentation, drivers and inhibitors, to understand the nature of the early BDaaS market. This study has proposed a new theoretical methodology for analyzing the early market of BDaaS and it is expected that this methodology may be used in the market analysis of other fields beyond the BDaaS market. Customer factors in the consumerization phenomenon and social, political, and technological factors in the PEST analysis were the important drivers of BDaaS adoption. Suppliers from the consumerization phenomenon and political factors in the PEST analysis were the most important inhibitors of BDaaS adoption. The results have important implications for policymaking and fostering other newly established BDaaS markets in emerging economies.

Suggested Citation

  • Surabhi Verma & Som Sekhar Bhattacharyya, 2017. "Drivers and Inhibitors of Big Data as a Service Adoption in India," Emerging Economy Studies, International Management Institute, vol. 3(1), pages 68-85, May.
    • Handle: RePEc:sae:emecst:v:3:y:2017:i:1:p:68-85
    DOI: 10.1177/2394901517696606
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    References listed on IDEAS

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    1. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    2. Rameshwar Dubey & Angappa Gunasekaran & Anindya Chakrabarty, 2015. "World-class sustainable manufacturing: framework and a performance measurement system," International Journal of Production Research, Taylor & Francis Journals, vol. 53(17), pages 5207-5223, September.
    3. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    4. Saaty, Thomas L., 1990. "How to make a decision: The analytic hierarchy process," European Journal of Operational Research, Elsevier, vol. 48(1), pages 9-26, September.
    5. Fosso Wamba, Samuel & Akter, Shahriar & Edwards, Andrew & Chopin, Geoffrey & Gnanzou, Denis, 2015. "How ‘big data’ can make big impact: Findings from a systematic review and a longitudinal case study," International Journal of Production Economics, Elsevier, vol. 165(C), pages 234-246.
    6. Prasanna Tambe, 2014. "Big Data Investment, Skills, and Firm Value," Management Science, INFORMS, vol. 60(6), pages 1452-1469, June.
    7. Shang, Jen & Sueyoshi, Toshiyuki, 1995. "A unified framework for the selection of a Flexible Manufacturing System," European Journal of Operational Research, Elsevier, vol. 85(2), pages 297-315, September.
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