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Agility Through BDA and Ambidexterity: Some Empirical Evidence from Managers’ Experiences

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Ambidextrous Organizations in the Big Data Era

Abstract

This chapter describes the micro-linkages that exist between Big Data Analytics (BDA) capabilities and an organization’s pursuit of strategic agility. One of the factors that influence this relationship is organizational ambidexterity. In order to assess this, dynamic capabilities are considered as the main theoretical framework. Multiple regressions are the main methodological approach used for this. The developed structural model is used to test on 250 survey responses collected from managers of large European organizations. The results show that the capabilities of BDA are an important precursor of an organization’s strategic agility. In this sense, managers, who want to exploit the potential of big data completely, must invest in the improvement of procedures of knowledge management across their organizations.

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References

  • Al Ahbabi, S. A., Singh, S. K., Balasubramanian, S., & Gaur, S. S. (2019). Employee perception of impact of knowledge management processes on public sector performance. Journal of Knowledge Management, 23(2), 351–373.

    Article  Google Scholar 

  • Akter, S., Fosso Wamba, S., & Dewan, S. (2017). Why PLS-SEM is suitable for complex modelling? An empirical illustration in big data analytics quality. Production Planning & Control, 28(11–12), 1011–1021.

    Article  Google Scholar 

  • Arbuckle, J. L. (2013). Amos 22 user’s guide. Chicago, IL: SPSS.

    Google Scholar 

  • Bagozzi, R. P., & Yi, Y. (1989). The degree of intention formation as a moderator of the attitude-behavior relationship. Social Psychology Quarterly, 52(4), 266–279.

    Article  Google Scholar 

  • Bedford, D. S., Bisbe, J., & Sweeney, B. (2019). Performance measurement systems as generators of cognitive conflict in ambidextrous firms. Accounting, Organizations and Society, 72, 21–37.

    Article  Google Scholar 

  • Caputo, A., Marzi, G., & Pellegrini, M. M. (2016). The internet of things in manufacturing innovation processes: Development and application of a conceptual framework. Business Process Management Journal, 22(2), 383–402.

    Article  Google Scholar 

  • Cegarra-Navarro, J. G., Soto-Acosta, P., & Wensley, A. K. (2016). Structured knowledge processes and firm performance: The role of organizational agility. Journal of Business Research, 69(5), 1544–1549.

    Article  Google Scholar 

  • Chen, H., Chiang, R. H., & Storey, V. C. (2012). Business intelligence and analytics: From big data to big impact. MIS Quarterly, 36(4), 1165–1188.

    Article  Google Scholar 

  • De Mauro, A., Greco, M., Grimaldi, M., & Ritala, P. (2018). Human resources for big data professions: A systematic classification of job roles and required skill sets. Information Processing and Management, 54(5), 807–817.

    Article  Google Scholar 

  • Dezi, L., Santoro, G., Gabteni, H., & Pellicelli, A. C. (2018). The role of big data in shaping ambidextrous business process management: Case studies from the service industry. Business Process Management Journal, 24(5), 1163–1175.

    Article  Google Scholar 

  • Dubey, R., Gunasekaran, A., & Childe, S. J. (2018). Big data analytics capability in supply chain agility: The moderating effect of organizational flexibility. Management Decision, 57(8), 2092–2211.

    Article  Google Scholar 

  • Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities: What are they? Strategic Management Journal, 21(10–11), 1105–1121.

    Article  Google Scholar 

  • Erevelles, S., Fukawa, N., & Swayne, L. (2016). Big data consumer analytics and the transformation of marketing. Journal of Business Research, 69(2), 897–904.

    Article  Google Scholar 

  • Ferraris, A., Mazzoleni, A., Devalle, A., & Couturier, J. (2018). Big data analytics capabilities and knowledge management: Impact on firm performance. Management Decision, 57(8), 1923–1936.

    Article  Google Scholar 

  • George, G., Haas, M. R., & Pentland, A. (2014). Big data and management. Academy of Management Journal, 57(2), 2–8.

    Article  Google Scholar 

  • Gibson, C. B., & Birkinshaw, J. (2004). The antecedents, consequences, and mediating role of organizational ambidexterity. Academy of Management Journal, 47(2), 209–226.

    Google Scholar 

  • Gupta, S., & Giri, V. (2018). Ensure high availability of data lake. In S. Gupta & V. Giri (Eds.), Practical enterprise data lake insights (pp. 261–295). Berkeley, CA: Apress.

    Google Scholar 

  • Gupta, M., & George, J. F. (2016). Toward the development of a big data analytics capability. Information & Management, 53(8), 1049–1064.

    Article  Google Scholar 

  • Labrinidis, A., & Jagadish, H. V. (2012). Challenges and opportunities with big data. Proceedings of the VLDB Endowment, 5(12), 2032–2033.

    Article  Google Scholar 

  • Lee, O. K., Sambamurthy, V., Lim, K. H., & Wei, K. K. (2015). How does IT ambidexterity impact organizational agility? Information Systems Research, 26(2), 398–417.

    Article  Google Scholar 

  • Lu, Y., & Ramamurthy, K. (2011). Understanding the link between information technology capability and organizational agility: An empirical examination. MIS Quarterly, 35(4), 931–954.

    Article  Google Scholar 

  • Lubatkin, M. H., Simsek, Z., Ling, Y., & Veiga, J. F. (2006). Ambidexterity and performance in small-to medium-sized firms: The pivotal role of top management team behavioral integration. Journal of Management, 32(5), 646–672.

    Article  Google Scholar 

  • Mardi, M., Arief, M., Furinto, A., & Kumaradjaja, R. (2018). Sustaining organizational performance through organizational ambidexterity by adapting social technology. Journal of the Knowledge Economy, 9(3), 1049–1066.

    Article  Google Scholar 

  • Jansen, J. J., Tempelaar, M. P., Van den Bosch, F. A., & Volberda, H. W. (2009). Structural differentiation and ambidexterity: The mediating role of integration mechanisms. Organization Science, 20(4), 797–811.

    Article  Google Scholar 

  • Obitade, P. O. (2019). Big data analytics: A link between knowledge management capabilities and superior cyber protection. Journal of Big Data, 6(1), 71.

    Article  Google Scholar 

  • O’Connor, C., & Kelly, S. (2017). Facilitating knowledge management through filtered big data: SME competitiveness in an agri-food sector. Journal of Knowledge Management, 21(1), 156–179.

    Article  Google Scholar 

  • O’Reilly, C. A., III, & Tushman, M. L. (2013). Organizational ambidexterity: Past, present, and future. Academy of Management Perspectives, 27(4), 324–338.

    Article  Google Scholar 

  • Raisch, S., & Birkinshaw, J. (2008). Organizational ambidexterity: Antecedents, outcomes, and moderators. Journal of Management, 34(3), 375–409.

    Article  Google Scholar 

  • Rialti, R., Marzi, G., Silic, M., & Ciappei, C. (2018). Ambidextrous organization and agility in big data era: The role of business process management systems. Business Process Management Journal, 24(5), 1091–1109.

    Article  Google Scholar 

  • Rialti, R., Marzi, G., Caputo, A., & Mayah, K. A. (2019). Achieving strategic flexibility in the era of big data: The importance of knowledge management and ambidexterity (Working Paper).

    Google Scholar 

  • Sarmento, M., & Simões, C. (2019). Trade fairs as engagement platforms: The interplay between physical and virtual touch points. European Journal of Marketing, 53(9), 1782–1807.

    Article  Google Scholar 

  • Scuotto, V., Del Giudice, M., Bresciani, S., & Meissner, D. (2017). Knowledge-driven preferences in informal inbound open innovation modes: An explorative view on small to medium enterprises. Journal of Knowledge Management, 21(3), 640–655.

    Google Scholar 

  • Trequattrini, R., Shams, R., Lardo, A., & Lombardi, R. (2016). Risk of an epidemic impact when adopting the internet of things: The role of sector-based resistance. Business Process Management Journal, 22(2), 403–419.

    Article  Google Scholar 

  • Tuan, L. T. (2016). Organisational ambidexterity and supply chain agility: The mediating role of external knowledge sharing and moderating role of competitive intelligence. International Journal of Logistics Research and Applications, 19(6), 583–603.

    Article  Google Scholar 

  • Vera-Baquero, A., Colomo-Palacios, R., & Molloy, O. (2013). Business process analytics using a big data approach. IT Professional, 15(6), 29–35.

    Article  Google Scholar 

  • Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J. F., Dubey, R., & Childe, S. J. (2017). Big data analytics and firm performance: Effects of dynamic capabilities. Journal of Business Research, 70, 356–365.

    Article  Google Scholar 

  • Wei, Z., Yi, Y., & Guo, H. (2014). Organizational learning ambidexterity, strategic flexibility, and new product development. Journal of Product Innovation Management, 31(4), 832–847.

    Article  Google Scholar 

  • Xu, L. D., & Duan, L. (2019). Big data for cyber physical systems in industry 4.0: A survey. Enterprise Information Systems, 13(2), 148–169.

    Google Scholar 

  • Xu, Z., Frankwick, G. L., & Ramirez, E. (2016). Effects of big data analytics and traditional marketing analytics on new product success: A knowledge fusion perspective. Journal of Business Research, 69(5), 1562–1566.

    Article  Google Scholar 

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Correspondence to Riccardo Rialti .

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Rialti, R., Marzi, G. (2020). Agility Through BDA and Ambidexterity: Some Empirical Evidence from Managers’ Experiences. In: Ambidextrous Organizations in the Big Data Era. Palgrave Pivot, Cham. https://doi.org/10.1007/978-3-030-36584-4_4

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