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Big data prioritization in SCM decision-making: Its role and performance implications

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  • Wilkin, Carla
  • Ferreira, Aldónio
  • Rotaru, Kristian
  • Gaerlan, Luigi Red

Abstract

Given exponential growth in the size of big data, its multi-channel sources and variability in quality that create challenges concerning cost-effective use, firms have invested significantly in databases and analytical tools to inform decision-making. In this regard, one means to avoid the costs associated with producing less than insightful reports and negative effects on performance through wasted resources is prioritizing data in terms of relevance and quality. The aim of this study is to investigate this approach by developing and testing a scale to evaluate Big Data Availability and the role of Big Data Prioritization for more effective use of big data in decision-making and performance. Focusing on the context of supply chain management (SCM), we validate this scale through a survey involving 84 managers. Findings support a positive association between Big Data Availability and its use in SCM decision-making, and suggest that Big Data Prioritization, as conceptualized in the study, has a positive impact on the use of big data in SCM decision-making and SCM performance. Through developing a scale to evaluate association between Big Data Availability and use in SCM decision-making, we make an empirical contribution to value generation from big data.

Suggested Citation

  • Wilkin, Carla & Ferreira, Aldónio & Rotaru, Kristian & Gaerlan, Luigi Red, 2020. "Big data prioritization in SCM decision-making: Its role and performance implications," International Journal of Accounting Information Systems, Elsevier, vol. 38(C).
    • Handle: RePEc:eee:ijoais:v:38:y:2020:i:c:s1467089520300385
    DOI: 10.1016/j.accinf.2020.100470
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    as
    1. Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
    2. Yuanzhu Zhan & Kim Hua Tan & Yina Li & Ying Kei Tse, 2018. "Unlocking the power of big data in new product development," Annals of Operations Research, Springer, vol. 270(1), pages 577-595, November.
    3. Yingxu Wang & Guenther Ruhe, 2007. "The Cognitive Process of Decision Making," International Journal of Cognitive Informatics and Natural Intelligence (IJCINI), IGI Global, vol. 1(2), pages 73-85, April.
    4. Trevor J. Bihl & William A. Young II & Gary R. Weckman, 2016. "Defining, Understanding, and Addressing Big Data," International Journal of Business Analytics (IJBAN), IGI Global, vol. 3(2), pages 1-32, April.
    5. Ittner, Christopher D. & Larcker, David F., 2001. "Assessing empirical research in managerial accounting: a value-based management perspective," Journal of Accounting and Economics, Elsevier, vol. 32(1-3), pages 349-410, December.
    6. Grafton, Jennifer & Lillis, Anne M. & Widener, Sally K., 2010. "The role of performance measurement and evaluation in building organizational capabilities and performance," Accounting, Organizations and Society, Elsevier, vol. 35(7), pages 689-706, October.
    7. Muhammad Imran Chaudhry & Abdoul G. Sam, 2018. "Herding behaviour and the declining value relevance of accounting information: evidence from an emerging stock market," Applied Economics, Taylor & Francis Journals, vol. 50(49), pages 5335-5353, October.
    8. Sivarajah, Uthayasankar & Kamal, Muhammad Mustafa & Irani, Zahir & Weerakkody, Vishanth, 2017. "Critical analysis of Big Data challenges and analytical methods," Journal of Business Research, Elsevier, vol. 70(C), pages 263-286.
    9. Gunasekaran, Angappa & Papadopoulos, Thanos & Dubey, Rameshwar & Wamba, Samuel Fosso & Childe, Stephen J. & Hazen, Benjamin & Akter, Shahriar, 2017. "Big data and predictive analytics for supply chain and organizational performance," Journal of Business Research, Elsevier, vol. 70(C), pages 308-317.
    10. Jarvis, Cheryl Burke & MacKenzie, Scott B & Podsakoff, Philip M, 2003. "A Critical Review of Construct Indicators and Measurement Model Misspecification in Marketing and Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 30(2), pages 199-218, September.
    11. Côrte-Real, Nadine & Oliveira, Tiago & Ruivo, Pedro, 2017. "Assessing business value of Big Data Analytics in European firms," Journal of Business Research, Elsevier, vol. 70(C), pages 379-390.
    12. Tsan‐Ming Choi & Stein W. Wallace & Yulan Wang, 2018. "Big Data Analytics in Operations Management," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1868-1883, October.
    13. repec:cup:judgdm:v:5:y:2010:i:5:p:411-419 is not listed on IDEAS
    14. Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
    15. Samuel Fosso Wamba & Angappa Gunasekaran & Rameshwar Dubey & Eric W. T. Ngai, 2018. "Big data analytics in operations and supply chain management," Annals of Operations Research, Springer, vol. 270(1), pages 1-4, November.
    16. Rikhardsson, Pall & Yigitbasioglu, Ogan, 2018. "Business intelligence & analytics in management accounting research: Status and future focus," International Journal of Accounting Information Systems, Elsevier, vol. 29(C), pages 37-58.
    17. Janssen, Marijn & van der Voort, Haiko & Wahyudi, Agung, 2017. "Factors influencing big data decision-making quality," Journal of Business Research, Elsevier, vol. 70(C), pages 338-345.
    18. Maleen Z. Gong & Aldónio Ferreira, 2014. "Does consistency in management control systems design choices influence firm performance? An empirical analysis," Accounting and Business Research, Taylor & Francis Journals, vol. 44(5), pages 497-522, October.
    19. Alex Dontoh & Suresh Radhakrishnan & Joshua Ronen, 2004. "The Declining Value†relevance of Accounting Information and Non†Information†based Trading: An Empirical Analysis," Contemporary Accounting Research, John Wiley & Sons, vol. 21(4), pages 795-812, December.
    20. Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
    21. Appelbaum, Deniz & Kogan, Alexander & Vasarhelyi, Miklos & Yan, Zhaokai, 2017. "Impact of business analytics and enterprise systems on managerial accounting," International Journal of Accounting Information Systems, Elsevier, vol. 25(C), pages 29-44.
    22. Coppock, Alexander, 2019. "Generalizing from Survey Experiments Conducted on Mechanical Turk: A Replication Approach," Political Science Research and Methods, Cambridge University Press, vol. 7(3), pages 613-628, July.
    23. Kevin E. Levay & Jeremy Freese & James N. Druckman, 2016. "The Demographic and Political Composition of Mechanical Turk Samples," SAGE Open, , vol. 6(1), pages 21582440166, March.
    24. Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
    25. Mundy, Julia, 2010. "Creating dynamic tensions through a balanced use of management control systems," Accounting, Organizations and Society, Elsevier, vol. 35(5), pages 499-523, July.
    26. Wamba, Samuel Fosso & Gunasekaran, Angappa & Akter, Shahriar & Ren, Steven Ji-fan & Dubey, Rameshwar & Childe, Stephen J., 2017. "Big data analytics and firm performance: Effects of dynamic capabilities," Journal of Business Research, Elsevier, vol. 70(C), pages 356-365.
    27. Erik Hofmann, 2017. "Big data and supply chain decisions: the impact of volume, variety and velocity properties on the bullwhip effect," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5108-5126, September.
    28. Chen, Wei & Han, Jun & Tan, Hun-Tong, 2016. "Investor reactions to management earnings guidance attributions: The effects of news valence, attribution locus, and outcome controllability," Accounting, Organizations and Society, Elsevier, vol. 55(C), pages 83-95.
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