How to cite this paper
Abbady, M., Akkaya, M & Sari, A. (2019). Big data governance, dynamic capability and decision-making effectiveness: Fuzzy sets approach.Decision Science Letters , 8(4), 429-440.
Refrences
Abubakar, A. M., Elrehail, H., Alatailat, M. A., & Elçi, A. (2017). Knowledge management, decision-making style and organizational performance. Journal of Innovation & Knowledge, 4(2), 104-114.
Abubakar, A. M., Karadal, H., Bayighomog, S. W., & Merdan, E. (2018). Workplace injuries, safety climate and behaviors: application of an artificial neural network. International Journal of Occupational Safety and Ergonomics, 1-11 https://doi.org/10.1080/10803548.2018.1454635
Abubakar, A. M., Behravesh, E., Rezapouraghdam, H., & Yildiz, S. B. (2019). Applying artificial intelligence technique to predict knowledge hiding behavior. International Journal of Information Management, 49, 45-57.
Arend, R. J. (2014). Entrepreneurship and dynamic capabilities: how firm age and size affect the “capability enhancement–SME performance” relationship. Small Business Economics, 42(1), 33–57.
Brynjolfsson, E., Hitt, L. M., & Kim, H. H. (2011). Strength in numbers: How does data-driven decisionmaking affect firm performance? Social Science Research Network (SSRN). Retrieved from https://pdfs.semanticscholar.org/dde1/9e960973068e541f634b1a7054cf30573035.pdf
Carayannopoulos, S. (2009). How Technology-Based New Firms Leverage Newness and Smallness to Commercialize Disruptive Technologies. Entrepreneurship Theory and Practice, 33(2), 419–438.
Chan, Y. E., Sabherwal, R., & Thatcher, J. B. (2006). Antecedents and outcomes of strategic IS alignment: an empirical investigation. IEEE Transactions on Engineering Management, 53(1), 27–47.
Chen, M., Mao, S., Liu, Y., Chen, M., Mao, S., & Liu, Y. (2014). Big data: A Survey. Mobile Network Application, 19, 171–209.
Cole, Z. (2017). The Top 6 Benefits of Data Governance. Retrieved February 8, 2019, from https://erwin.com/blog/top-6-benefits-of-data-governance/.
Davenport, T., & Harris, J. (2017). Competing on Analytics: Updated, with a New Introduction: The New Science of Winning. Harvard Business Press. R
De Haes, S., & Van Grembergen, W. (2015). Enterprise Governance of IT, Alignment and Value. In Enterprise governance of information technology. Achieving Alignment and Value, Featuring COBIT, 5. springer .
Fainshmidt, S., Pezeshkan, A., Lance, F. M., Nair, A., & Markowski, E. (2016). Dynamic capabilities and organizational performance: A meta-analytic evaluation and extension. Journal of Management Studies, 53(8), 1348–1380.
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144.
Günther, W. A., Rezazade, M. ., Huysman, M., & Feldberg, F. (2017). Debating big data: A literature review on realizing value from big data. The Journal of Strategic Information Systems, 26(3), 191–209.
Helfat, C. E., Finkelstein, S., Mitchell, W., Peteraf, M., Singh, H., Teece, D., & Winter, S. G. (2009). Dynamic capabilities: Understanding strategic change in organizations. John Wiley & Sons.
Henke, N., Bughin, J., Chui, M., Manyika, J., Saleh, T., Wiseman, B., & Sethupathy, G. (2016). The Age of Analytics: Competing in a data-driven world. Retrieved from www.mckinsey.com/mgi.
Hervas-Oliver, J.L., Sempere-Ripoll, F., & Arribas, I. (2015). Asymmetric modeling of organizational innovation. Journal of Business Research, 68(12), 2654-2662
Jahmani, K., Fadiya, S. O., Abubakar, A. M., & Elrehail, H. (2018). Knowledge content quality, perceived usefulness, KMS use for sharing and retrieval: A flock leadership application. VINE Journal of Information and Knowledge Management Systems, 48(4), 470-490.
Janssen, M., van der Voort, H., & Wahyudi, A. (2017). Factors influencing big data decision-making quality. Journal of Business Research, 70, 338–345.
Jantunen, A., Tarkiainen, A., Chari, S., & Oghazi, P. (2018). Dynamic capabilities, operational changes, and performance outcomes in the media industry. Journal of Business Research, 89, 251–257.
Karna, A., Richter, A., & Riesenkampff, E. (2016). Revisiting the role of the environment in the capabilities-financial performance relationship: A meta-analysis. Strategic Management Journal, 37(6), 1154–1173.
Kung, L., Kung, H.-J., Jones-Farmer, A., & Wang, Y. (2015). Managing Big Data for Firm Performance: a Configurational Approach. In Twenty-first Americas Conference on Information Systems. Puerto Rico.
Lee, I. (2017). Big data: Dimensions, evolution, impacts, and challenges. Business Horizons, 60(3), 293–303.
Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Hung Byers, A. (2011). Big data: The next frontier for innovation, competition, and productivity. Retrieved from https://www.mckinsey.com/~/media/mckinsey/business functions/mckinsey digital/our insights/big data the next frontier for innovation/mgi_big_data_exec_summary.ashx
McAfee, A., & Brynjolfsson, E. (2012, October). Big data: The Management Revolution. Harvard Business Review. Retrieved from http://tarjomefa.com/wp-content/uploads/2017/04/6539-English-TarjomeFa-1.pdf
Mithas, S., Ramasubbu, N., & Sambamurthy, V. (2011). How information management capability influences firm performance. MIS quarterly, 35(1), 237.
Mikalef, P., & Krogstie, J. (2018). Big Data Governance and Dynamic Capabilities: The Moderating effect of Environmental Uncertainty. In Twenty-Second Pacific Asia Conference on Information Systems. Japan.
Mikalef, P., Pateli, A., Batenburg, R. S., & Van De Wetering, R. (2015). Purchasing alignment under multiple contingencies: A configuration theory approach. Industrial Management and Data Systems, 115(4), 625–645.
Olya, H. G., & Gavilyan, Y. (2017). Configurational models to predict residents’ support for tourism development. Journal of Travel Research, 56(7), 893-912.
Pezeshkan, A., Fainshmidt, S., Nair, A., Lance, F. M., & Markowski, E. (2016). An empirical assessment of the dynamic capabilities–performance relationship. Journal of Business Research, 69(8), 2950–2956.
Podsakoff, P., MacKenzie, S., Lee, J., & Podsakoff, N. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–69
Ragin, C.C. (1987). The Comparative Method: Moving beyond Qualitative and Quantitative Strategies. University of California Press, Berkeley and Los Angeles, CA.
Ragin, C. (2008). Redesigning Social Inquiry. University of Chicago Press, Chicago, CA.
Ragin, C. C., & Fiss, P. C. (2008). Net effects analysis versus configurational analysis: An empirical demonstration. In Redesigning social inquiry: Fuzzy sets and beyond (pp. 190–212).
Shamim, S., Zeng, J., Shariq, S. ., & Khan, Z. (2018). Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view. Information & Management. https://doi.org/10.1016/J.IM.2018.12.003.
Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350.
Torres, R., Sidorova, A., & Jones, M. C. (2018). Enabling firm performance through business intelligence and analytics: A dynamic capabilities perspective. Information & Management, 55(7), 822–839.
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.
Wang, Y., & Byrd, T. A. (2017). Business analytics-enabled decision-making effectiveness through knowledge absorptive capacity in health care. Journal of Knowledge Management, 21(3), 517-539.
Weber, K., Otto, B., & Österle, H. (2009). One Size Does Not Fit All---A Contingency Approach to Data Governance. Journal of Data and Information Quality, 1(1), 1–27.
Weill, P. (2004). Don’t just lead, govern: How top-performing firms govern IT. (No. CISR WP No. 341 and Sloan WP No. 4493-04) (Vol. 8). Cambridge, MA. Retrieved from http://mitsloan.mit.edu/cisr
Wilhelm, H., Schlömer, M., & Maurer, I. (2015). How Dynamic Capabilities Affect the Effectiveness and Efficiency of Operating Routines under High and Low Levels of Environmental Dynamism. British Journal of Management, 26(2), 327–345.
Woodside, A.G. (2013). Moving beyond multiple regression analysis to algorithms: calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. Journal of Business Research, 66(4), 463-472.
Zollo, M., & Winter, S. G. (2002). Deliberate Learning and the Evolution of Dynamic Capabilities. Organization Science, 13(3), 339–351.
Abubakar, A. M., Karadal, H., Bayighomog, S. W., & Merdan, E. (2018). Workplace injuries, safety climate and behaviors: application of an artificial neural network. International Journal of Occupational Safety and Ergonomics, 1-11 https://doi.org/10.1080/10803548.2018.1454635
Abubakar, A. M., Behravesh, E., Rezapouraghdam, H., & Yildiz, S. B. (2019). Applying artificial intelligence technique to predict knowledge hiding behavior. International Journal of Information Management, 49, 45-57.
Arend, R. J. (2014). Entrepreneurship and dynamic capabilities: how firm age and size affect the “capability enhancement–SME performance” relationship. Small Business Economics, 42(1), 33–57.
Brynjolfsson, E., Hitt, L. M., & Kim, H. H. (2011). Strength in numbers: How does data-driven decisionmaking affect firm performance? Social Science Research Network (SSRN). Retrieved from https://pdfs.semanticscholar.org/dde1/9e960973068e541f634b1a7054cf30573035.pdf
Carayannopoulos, S. (2009). How Technology-Based New Firms Leverage Newness and Smallness to Commercialize Disruptive Technologies. Entrepreneurship Theory and Practice, 33(2), 419–438.
Chan, Y. E., Sabherwal, R., & Thatcher, J. B. (2006). Antecedents and outcomes of strategic IS alignment: an empirical investigation. IEEE Transactions on Engineering Management, 53(1), 27–47.
Chen, M., Mao, S., Liu, Y., Chen, M., Mao, S., & Liu, Y. (2014). Big data: A Survey. Mobile Network Application, 19, 171–209.
Cole, Z. (2017). The Top 6 Benefits of Data Governance. Retrieved February 8, 2019, from https://erwin.com/blog/top-6-benefits-of-data-governance/.
Davenport, T., & Harris, J. (2017). Competing on Analytics: Updated, with a New Introduction: The New Science of Winning. Harvard Business Press. R
De Haes, S., & Van Grembergen, W. (2015). Enterprise Governance of IT, Alignment and Value. In Enterprise governance of information technology. Achieving Alignment and Value, Featuring COBIT, 5. springer .
Fainshmidt, S., Pezeshkan, A., Lance, F. M., Nair, A., & Markowski, E. (2016). Dynamic capabilities and organizational performance: A meta-analytic evaluation and extension. Journal of Management Studies, 53(8), 1348–1380.
Gandomi, A., & Haider, M. (2015). Beyond the hype: Big data concepts, methods, and analytics. International Journal of Information Management, 35(2), 137–144.
Günther, W. A., Rezazade, M. ., Huysman, M., & Feldberg, F. (2017). Debating big data: A literature review on realizing value from big data. The Journal of Strategic Information Systems, 26(3), 191–209.
Helfat, C. E., Finkelstein, S., Mitchell, W., Peteraf, M., Singh, H., Teece, D., & Winter, S. G. (2009). Dynamic capabilities: Understanding strategic change in organizations. John Wiley & Sons.
Henke, N., Bughin, J., Chui, M., Manyika, J., Saleh, T., Wiseman, B., & Sethupathy, G. (2016). The Age of Analytics: Competing in a data-driven world. Retrieved from www.mckinsey.com/mgi.
Hervas-Oliver, J.L., Sempere-Ripoll, F., & Arribas, I. (2015). Asymmetric modeling of organizational innovation. Journal of Business Research, 68(12), 2654-2662
Jahmani, K., Fadiya, S. O., Abubakar, A. M., & Elrehail, H. (2018). Knowledge content quality, perceived usefulness, KMS use for sharing and retrieval: A flock leadership application. VINE Journal of Information and Knowledge Management Systems, 48(4), 470-490.
Janssen, M., van der Voort, H., & Wahyudi, A. (2017). Factors influencing big data decision-making quality. Journal of Business Research, 70, 338–345.
Jantunen, A., Tarkiainen, A., Chari, S., & Oghazi, P. (2018). Dynamic capabilities, operational changes, and performance outcomes in the media industry. Journal of Business Research, 89, 251–257.
Karna, A., Richter, A., & Riesenkampff, E. (2016). Revisiting the role of the environment in the capabilities-financial performance relationship: A meta-analysis. Strategic Management Journal, 37(6), 1154–1173.
Kung, L., Kung, H.-J., Jones-Farmer, A., & Wang, Y. (2015). Managing Big Data for Firm Performance: a Configurational Approach. In Twenty-first Americas Conference on Information Systems. Puerto Rico.
Lee, I. (2017). Big data: Dimensions, evolution, impacts, and challenges. Business Horizons, 60(3), 293–303.
Manyika, J., Chui, M., Brown, B., Bughin, J., Dobbs, R., Roxburgh, C., & Hung Byers, A. (2011). Big data: The next frontier for innovation, competition, and productivity. Retrieved from https://www.mckinsey.com/~/media/mckinsey/business functions/mckinsey digital/our insights/big data the next frontier for innovation/mgi_big_data_exec_summary.ashx
McAfee, A., & Brynjolfsson, E. (2012, October). Big data: The Management Revolution. Harvard Business Review. Retrieved from http://tarjomefa.com/wp-content/uploads/2017/04/6539-English-TarjomeFa-1.pdf
Mithas, S., Ramasubbu, N., & Sambamurthy, V. (2011). How information management capability influences firm performance. MIS quarterly, 35(1), 237.
Mikalef, P., & Krogstie, J. (2018). Big Data Governance and Dynamic Capabilities: The Moderating effect of Environmental Uncertainty. In Twenty-Second Pacific Asia Conference on Information Systems. Japan.
Mikalef, P., Pateli, A., Batenburg, R. S., & Van De Wetering, R. (2015). Purchasing alignment under multiple contingencies: A configuration theory approach. Industrial Management and Data Systems, 115(4), 625–645.
Olya, H. G., & Gavilyan, Y. (2017). Configurational models to predict residents’ support for tourism development. Journal of Travel Research, 56(7), 893-912.
Pezeshkan, A., Fainshmidt, S., Nair, A., Lance, F. M., & Markowski, E. (2016). An empirical assessment of the dynamic capabilities–performance relationship. Journal of Business Research, 69(8), 2950–2956.
Podsakoff, P., MacKenzie, S., Lee, J., & Podsakoff, N. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63, 539–69
Ragin, C.C. (1987). The Comparative Method: Moving beyond Qualitative and Quantitative Strategies. University of California Press, Berkeley and Los Angeles, CA.
Ragin, C. (2008). Redesigning Social Inquiry. University of Chicago Press, Chicago, CA.
Ragin, C. C., & Fiss, P. C. (2008). Net effects analysis versus configurational analysis: An empirical demonstration. In Redesigning social inquiry: Fuzzy sets and beyond (pp. 190–212).
Shamim, S., Zeng, J., Shariq, S. ., & Khan, Z. (2018). Role of big data management in enhancing big data decision-making capability and quality among Chinese firms: A dynamic capabilities view. Information & Management. https://doi.org/10.1016/J.IM.2018.12.003.
Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350.
Torres, R., Sidorova, A., & Jones, M. C. (2018). Enabling firm performance through business intelligence and analytics: A dynamic capabilities perspective. Information & Management, 55(7), 822–839.
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.
Wang, Y., & Byrd, T. A. (2017). Business analytics-enabled decision-making effectiveness through knowledge absorptive capacity in health care. Journal of Knowledge Management, 21(3), 517-539.
Weber, K., Otto, B., & Österle, H. (2009). One Size Does Not Fit All---A Contingency Approach to Data Governance. Journal of Data and Information Quality, 1(1), 1–27.
Weill, P. (2004). Don’t just lead, govern: How top-performing firms govern IT. (No. CISR WP No. 341 and Sloan WP No. 4493-04) (Vol. 8). Cambridge, MA. Retrieved from http://mitsloan.mit.edu/cisr
Wilhelm, H., Schlömer, M., & Maurer, I. (2015). How Dynamic Capabilities Affect the Effectiveness and Efficiency of Operating Routines under High and Low Levels of Environmental Dynamism. British Journal of Management, 26(2), 327–345.
Woodside, A.G. (2013). Moving beyond multiple regression analysis to algorithms: calling for adoption of a paradigm shift from symmetric to asymmetric thinking in data analysis and crafting theory. Journal of Business Research, 66(4), 463-472.
Zollo, M., & Winter, S. G. (2002). Deliberate Learning and the Evolution of Dynamic Capabilities. Organization Science, 13(3), 339–351.