APAKAH BIG DATA ANALYTICS CAPABILITY MENINGKATKAN NILAI BISNIS DAN KINERJA PERUSAHAAN: STUDI KASUS INDONESIA

Authors

  • Mochamad Chairul Ihsan Universitas Padjadjaran

DOI:

https://doi.org/10.53363/buss.v3i2.172

Keywords:

resource-based view, nilai bisnis, kinerja perusahaan, big data analytics capability, business value, firm performance

Abstract

In the era of data economy, the development of Big Data Analytics Capability (BDAC) has changed the face of competitiveness in many sectors. Organizations have intensively utilized BDAC as a competitive force to improve firm performance. Conveying from the resource-based view and sociomaterialism entanglement, BDAC has a huge potential to enhance business value and firm performance. This study extends the literature on BDAC impacts on organizations, especially in developing countries, by proposing a model and validating the direct effects of BDAC on firm performance and business value, along with the mediating effects of business value on the relationship between BDAC and firm performance. Toward this goal, an online survey was conducted and collected 86 data from IT managers, business analysts, and data analyst that are currently working in companies that have implemented Big Data Analytics (BDA) in Indonesia. The data was afterward analyzed using Partial Least Square Structural-Equation Model (PLS-SEM). The findings showed that BDAC has a positive impact on firm performance in terms of financial and market performance relative to competitors. The results also revealed that BDAC enhances business value. However, it was found that there is no significant mediating effects of business value on the relationship between BDAC and firm performance

Downloads

Download data is not yet available.

References

Abbasi, A., Sarker, S., & Chiang, R. H. L. (2016). Big data research in information systems: Toward an inclusive research agenda. Journal of the Association for Information Systems, 17, 1–32.

Akter, S., Fosso Wamba, S., Gunasekaran, A., Dubey, R., & Childe, S. J. (2016). How to improve firm performance using big data analytics capability and business strategy alignment? International Journal of Production Economics, 182, 113–131.

Amit, R., & Schoemaker, P. J. H. (1993). Strategic assets and organizational rent. Strategic Management Journal, 14, 33–46.

Anand, A., Wamba, S. F., & Sharma, R. (2013). The effects of firm IT capabilities on firm performance?: the mediating effects of process improvement. In 24th Australasian Conference on Information Systems. Melbourne, Australia.

Asosiasi Penyelenggara Jasa Internet Indonesia. (2017). Penetrasi & perilaku pengguna internet indonesia.

Barney, J., Wright, M., & Ketchen, D. J. (2001). The resource-based view of the firm?: Ten years after 1991. Journal of Management, 27, 625–641.

Barton, D., & Court, D. (2012). Making advanced analytics work for you. Harvard Business Review.

Barua, A., Kriebel, C. H., & Mukhopadhyay, T. (1995). Information technologies and business value: An analytic and empirical investigation. Information Systems Research, 6(1), 3–23.

Becker, J., Klein, K., & Wetzels, M. (2012). Hierarchical latent variable models in PLS-SEM?: Guidelines for using reflective-formative type models. Long Range Planning, 45(5–6), 359–394.

Bharadwaj, A. S. (2000). A resource-based perspective on information technology capability and firm performance: An empirical investigation. MIS Quarterly, 24(1), 169–196.

Bhatt, G. D., & Grover, V. (2005). Types of information technology capabilities and their role in competitive advantage: An empirical study. Journal of Management Information Systems, 22(2), 253–277.

Carr, N. G. (2003). IT doesn’t matter. Harvard Business Review, 81(5), 41–49.

Chang, J. C., & King, W. R. (2005). Measuring the performance of information systems: A functional scorecard. Journal of Management Information Systems, 22(1), 85–115.

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

Chin, W. W. (1998). The Partial Least Squares Approach to Structural Equation Modeling. In G. A. Marc (Eds.), Modern methods for business research (pp. 295–333). Mahwah, New Jersey: Lawrence Erlbaum Associates.

Chin, W. W., & Newsted, P. R. (1999). Structural equation modeling analysis with small samples using partial least square. In Hoyle RH (Eds.), Statistical strategies for small sample research (Hoyle RH, pp. 334–342). Thousand Oaks, CA: Sage Publications.

Columbus, L. (2014). 84% of enterprises see big data analytics changing their industries’ competitive landscapes in the next year. Retrieved October 29, 2018, from https://www.forbes.com/sites/louiscolumbus/2014/10/19/84-of-enterprises-see-big-data-analytics-changing-their-industries-competitive-landscapes-in-the-next-year/#630568d217de

Court, D., Perrey, J., McGuire, T., Gordon, J., & Spillecke, D. (2015). Big data, analytics, and the future of marketing & sales (e-book). McKinsey & Company.

Davenport, T. H. (2006). Competing on analytics. Harvard Business Review.

Davenport, T. H. (2014). How strategists use “big data" to support internal business decisions, discovery and production. Strategy and Leadership, 42(4), 45–50.

Davenport, T. H., Barth, P., & Bean, R. (2012). How ‘big data’ is different. MIT Sloan Management Review, 54(1).

Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning. Boston: Harvard Business School Press.

de Camargo Fiorini, P., Roman Pais Seles, B. M., Chiappetta Jabbour, C. J., Barberio Mariano, E., & de Sousa Jabbour, A. B. L. (2018). Management theory and big data literature: From a review to a research agenda. International Journal of Information Management, 43(5), 112–129.

Fosso Wamba, S., Akter, S., & de Bourmont, M. (2018). Quality dominant logic in big data analytics and firm performance. Business Process Management Journal.

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

Fosso Wamba, S., & Mishra, D. (2017). Big data integration with business processes: A literature review. Business Process Management Journal, 23(3).

Ghozali, I. (2014). Structural equation modeling metode alternatif dengan Partial Least Squares (PLS) dilengkapi software SmartPLS 3.0. Xlstat 2014 dan WarpPLS 4.0. Semarang: Badan Penerbit Universitas Diponegoro.

Ghozali, I., & Latan, H. (2015). Partial least squares: Konsep, teknik dan aplikasi menggunakan SmartPLS 3.0 (2nd ed.). Universitas Diponegoro.

Goes, P. B. (2014). Big data and IS research. MIS Quarterly, 38(3–8).

Gold, A. H., Malhotra, A., & Segars, A. H. (2001). Knowledge management: An organizational capabilities perspective. Journal of Management Information Systems, 18(1), 185–214.

Grant, R. M. (1991). The resource-based theory of competitive advantage: Implications for strategy formulation. California Management Review, 333(3), 114–135.

Gregor, S., Martin, M., Fernandez, W., Stern, S., & Vitale, M. (2006). The transformational dimension in the realization of business value from information technology. Journal of Strategic Information Systems, 15, 249–270.

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

Henseler, J., Ringle, C. M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43(1), 115–135.

Jayachandran, S., Sharma, S., Kaufman, P., & Raman, P. (2005). The role of relational information processes and technology use in customer relationship management. Journal of Marketing, 69(4), 177–192.

Ji-fan Ren, S., Fosso Wamba, S., Akter, S., Dubey, R., & Childe, S. J. (2016). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research.

Kaiser, H. F. (1958). The varimax criterion for analytic rotation in factor analysis. Psychometrika, 23(3).

Kim, G., Shin, B., Kim, K. K., & Lee, H. G. (2011). IT capabilities, process-oriented dynamic capabilities, and firm financial performance. Journal of the Association for Information Systems, 12(7), 487–517.

Kim, G., Shin, B., & Kwon, O. (2012). Investigating the value of sociomaterialism in conceptualizing IT capability of a firm. Journal of Management Information Systems, 29(3), 327–362.

Kiron, D., Prentice, P. K., & Ferguson, R. B. (2014a). Raising the bar with analytics. MIT Sloan Management Review, 55(2), 29–33.

Kiron, D., Prentice, P. K., & Ferguson, R. B. (2014b). The analytics mandate. MIT Sloan Management Review, 55(4), 1–25.

Lavalle, S., Lesser, E., Shockley, R., Hopkins, M. S., & Kruschwitz, N. (2011). Big data, analytics and the path from insights to value. MIT Sloan Management Review, 52(2), 21–32.

Makadok, R. (2001). Toward a synthesis of the resource-based and dynamic-capability views of rent creation. Strategic Management Journal, 22, 387–401.

McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, (October).

Mooney, J. G., Gurbaxani, V., & Kraemer, K. L. (1996). A process oriented framework for assessing the business value of information technology. SIGMIS Database, 27, 68–81.

Osborne, J. W. (2014). Best practices in exploratory factor analysis. Scotts Valley, CA: CreateSpace Independent Publishing.

Powell, T. C., & Dent-Micallef, A. (1997). Information technology as competitive advantage: The role of human, business, and technology resources. Strategic Management Journal, 18(5), 375.

Ramadhan, H. A., & Putri, D. A. (2018). Big data, kecerdasan buatan, blockchain, dan teknologi finansial di Indonesia.

Ransbotham, S., Kiron, D., & Prentice, P. K. (2015). Minding the analytics gap. MIT Sloan Management Review, 63–68.

Ransbotham, S., Kiron, D., & Prentice, P. K. (2016). Beyond the hype: The hard work behind analytics success. MIT Sloan Management Review, 57(3), 1–19.

Rumata, V. M. (2016). Peluang dan tantangan big data dalam penelitian ilmu sosial: Sebuah kajian literatur. Puslitbang APTIKA-IKP, 13.

Santhanam, R., & Hartono, E. (2003). Issues in linking information technology capability to firm performance. MIS Quarterly, 27(1), 125–153.

Sena, V., Demirbag, M., Bhaumik, S., & Sengupta, A. (2017). Big data And performance. British Journal of Management, 2019(1-6 Special Issue).

Sirait, E. R. E. (2016). Implementasi teknologi big data di lembaga pemerintahan indonesia. Jurnal Penelitian Pos Dan Informatika, 6(2), 113.

Sobel, M. E. (1982). Asymptotic confidence intervals for indirect effects in structural equation models. Sociological Methodology, 13, 290–312.

Tan, K. H., Ji, G., Lim, C. P., & Tseng, M. (2017). Using big data to make better decisions in the digital economy. International Journal of Production Research.

Teo, T. S. H., Srivastava, S. C., & Jiang, L. (2008). Trust and electronic government success: An empirical study. Journal of Management Information Systems, 25(3), 99–132.

Tippins, M. J., & Sohi, R. S. (2003). IT competency and firm performance: Is organizational learning a missing link? Strategic Management Journal, 24, 745–761.

Verbraken, T., Lessmann, S., & Baesens, B. (2012). Toward profit-driven churn modeling with predictive marketing analytics. In Proceedings of the 11th Workshop on e-Business. Orlando, FL.

Wu, J., Li, H., Cheng, S., & Lin, Z. (2016). The promising future of healthcare services: When big data analytics meets wearable technology. Information and Management.

Xie, K., Wu, Y., Xiao, J., & Hu, Q. (2016). Value co-creation between firms and customers: The role of big data-based cooperative assets. Information and Management, 53(8), 1034–1048.

Zhan, Y., Tan, K. H., Ji, G., Chung, L., & Tseng, M. (2017). A big data framework for facilitating product innovation processes. Business Process Management Journal, 23(3).

Downloads

Published

2023-08-24

How to Cite

Ihsan, M. C. . (2023). APAKAH BIG DATA ANALYTICS CAPABILITY MENINGKATKAN NILAI BISNIS DAN KINERJA PERUSAHAAN: STUDI KASUS INDONESIA. Bussman Journal : Indonesian Journal of Business and Management, 3(2), 808–827. https://doi.org/10.53363/buss.v3i2.172