Factors Impacting E-Commerce Performance via Big Data Analytics in Hangzhou
DOI:
https://doi.org/10.14456/au-ejir.2025.11Keywords:
Big Data Analytics, Global Sourcing, Satisfaction, Business Value, Firm PerformanceAbstract
Purpose: This study investigates the factors influencing firm performance (FP) through big data analytics (BDA) in E-commerce companies. Specifically, it examines the effects of integration (INT), global sourcing (GS), competitive advantage (CA), business value (BVAL), and satisfaction (SAT) on FP, along with the effect of INT on GS and BVAL on SAT. Research design, data and methodology: Based on the resource-based view (RBV), dynamic capability view (DCV), and information systems (IS) success model, a quantitative approach was adopted. Data were collected from 500 employees across eight types of E-commerce companies in Hangzhou using stratified random sampling. Confirmatory factor analysis (CFA) and structural equation modeling (SEM) were used to test hypotheses and analyze relationships among variables. Results: BVAL has the strongest effect on SAT, INT significantly enhances GS, but its direct effect on FP is unsupported. GS, BVAL, CA, and SAT significantly impact FP. This study highlights the strategic value of BDA in driving performance outcomes. Conclusions: This offers actionable insights for E-commerce firms to strengthen integration, optimize sourcing, create business value, and enhance satisfaction. By focusing on these areas, businesses can better navigate the global digital marketplace, build sustainable competitive advantages, and improve overall firm performance.
References
Alkire, L., Liu, Y., & Wang, Y. (2023). Data-driven global sourcing: Enhancing performance through digital supply chain integration. Journal of Purchasing and Supply Management, 29(2), 100812. https://doi.org/10.1016/j.pursup.2023.100812
Arbuckle, L. J. (2008). AMOS 17.0 User’s Guide. IBM SPSS.
Barney, J. (1991). Firm resources and sustained competitive advantage. Journal of Management, 17(1), 99-120.
https://doi.org/10.1177/014920639101700108
Barrett, P. (2007). Structural equation modeling: Adjudging model fit. Personality and Individual Differences, 42(5), 815-824. https://doi.org/10.1016/j.paid.2006.09.018
Behl, A. (2022). Building sustainable competitive advantage through big data analytics capability. Journal of Strategic Marketing, 30(3), 267-285. https://doi.org/10.1080/0965254X.2020.1814772
Bresciani, S., Ciampi, F., Meli, F., & Ferraris, A. (2021). Using big data for co-innovation processes: Mapping the field of data-driven innovation, proposing theoretical developments and providing a research agenda. International Journal of Information Management, 60, 102347. https://doi.org/10.1016/j.ijinfomgt.2021.102347
Cagliano, A. C., De Marco, A., Rafele, C., & Arese, M. (2012). A decision-making approach for investigating the potential effects of near sourcing on supply chain. Strategic Outsourcing: An International Journal, 5(2), 100-120.
https://doi.org/10.1108/17538291211257534
Chong, A. Y. L. (2013). Understanding mobile commerce continuance intentions: An empirical analysis of Chinese consumers. Journal of Computer Information Systems, 53(4), 22-30. https://doi.org/10.1080/08874417.2013.11645653
Deb, M., Roy, S. K., & Jayawardhena, C. (2023). Workplace satisfaction and firm performance: A multi-perspective view. Journal of Business Research, 159, 113705.
https://doi.org/10.1016/j.jbusres.2023.113705
DeLone, W. H., & McLean, E. R. (2003). The DeLone and McLean model of information systems success: A ten-year update. Journal of Management Information Systems, 19(4), 9-30. https://doi.org/10.1080/07421222.2003.11045748
Fahy, J. (2000). The resource‐based view of the firm: Some stumbling‐blocks on the road to understanding sustainable competitive advantage. Journal of European Industrial Training, 24(2/3/4), 94-104.
https://doi.org/10.1108/03090590010321061
Flynn, B. B., Huo, B., & Zhao, X. (2010). The impact of supply chain integration on performance: A contingency and configuration approach. Journal of Operations Management, 28, 58-71. https://doi.org/10.1016/j.jom.2009.06.001
Foerstl, K., Hartmann, E., Wynstra, F., & Moser, R. (2013). Cross-functional integration and functional coordination in purchasing and supply management. International Journal of Operations and Production Management, 33(6), 689-721. https://doi.org/10.1108/IJOPM-09-2011-0349
Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39-50. https://doi.org/10.1177/002224378101800104
Frohlich, M. T., & Westbrook, R. (2001). Arcs of integration: An international study of supply chain strategies. Journal of Operations Management, 19(2), 185-200. https://doi.org/10.1016/S0272-6963(00)00055-3
Galbreath, J., Lucianetti, L., Thomas, B., & Tisch, D. (2020). Entrepreneurial orientation and firm performance in Italian firms: The moderating role of competitive strategy. International Journal of Entrepreneurial Behavior and Research, 26(4), 629-646. https://doi.org/10.1108/IJEBR-05-2019-0272
Ghasemaghaei, M. (2022). Does data quality matter? An empirical investigation of big data analytics success and business value. Decision Support Systems, 157, 113738. https://doi.org/10.1016/j.dss.2021.113738
Gregor, S., Martin, M., Fernandez, W., Stern, S., & Vitale, M. (2006). The transformational dimension in the realization of business value from information technology. The Journal of Strategic Information Systems, 15(3), 249-270.
https://doi.org/10.1016/j.jsis.2006.04.001
Gualandris, J., Golini, R., & Kalchschmidt, M. (2014). Do supply management and global sourcing matter for firm sustainability performance? An international study. SCM: An International Journal, 19(3), 258-274. https://doi.org/10.1108/SCM-12-2013-0446
Gupta, S., Kar, A. K., Baabdullah, A., & Al-Khowaiter, W. A. (2018). Big data with cognitive computing: A review for the future. International Journal of Information Management, 42, 78-89. https://doi.org/10.1016/j.ijinfomgt.2018.06.005
Hair, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2010). Multivariate data analysis (7th ed.). Prentice Hall.
Hair, J. F., Black, W., Babin, B., Anderson, R., & Tatham, R. (2006). Multivariate data analysis (6th ed.). Pearson Education.
Ismail, A. I., Rose, R. C., Abdullah, H., & Uli, J. (2010). The relationship between organisational competitive advantage and performance moderated by the age and size of firms. Asian Academy of Management Journal, 15(2), 157-173.
Jia, F., Orzes, G., Sartor, M., & Nassimbeni, G. (2017). Global sourcing strategy and structure: Towards a conceptual framework. International Journal of Operations & Production Management, 37(7), 840-864. https://doi.org/10.1108/IJOPM-10-2015-0620
Ji-Fan Ren, S., Fosso Wamba, S., Akter, S., Dubey, R., & Childe, S. J. (2017). Modelling quality dynamics, business value and firm performance in a big data analytics environment. International Journal of Production Research, 55(17), 5011-5026. https://doi.org/10.1080/00207543.2016.1154209
Kahn, K. B., & Mentzer, J. T. (1996). Logistics and interdepartmental integration. International Journal of Physical Distribution and Logistics Management, 26(8), 6-14. https://doi.org/10.1108/09600039610126578
Kalinić, Z., Marinković, V., Djordjević, A., & Liebana-Cabanillas, F. (2019). What drives customer satisfaction and word of mouth in mobile commerce services? A UTAUT2-based analytical approach. Journal of Enterprise Information Management, 33(1), 71-94. https://doi.org/10.1108/JEIM-01-2019-0015
Khan, N., Yaqoob, I., Hashem, I. A. T., Inayat, Z., Mahmoud Ali, W. K., Alam, M., & Gani, A. (2014). Big data: Survey, technologies, opportunities, and challenges. The Scientific World Journal, 2014(1), 712826.
https://doi.org/10.1155/2014/712826
Khan, R. A., & Qudrat-Ullah, H. (2021). Adoption of LMS in higher educational institutions of the Middle East. Springer.
Kline, R. B. (2011). Principles and practice of structural equation modeling (3rd ed.). Guilford Press.
Kong, X., & Liu, H. (2023). Digital satisfaction and organizational agility: Evidence from technology-intensive firms. Information & Management, 60(4), 103695. https://doi.org/10.1016/j.im.2023.103695
Langenberg, K. U., Seifert, R. W., & Tancrez, J. S. (2012). Aligning supply chain portfolios with product portfolios. International Journal of Production Economics, 35(1), 500-513. https://doi.org/10.1016/j.ijpe.2012.01.013
Lee, H., & Yang, Y. (2023). Data-driven dynamic capabilities and firm performance in E-commerce. Information & Management, 60(5), 103717. https://doi.org/10.1016/j.im.2023.103717
Li, M., & Liu, Y. (2023). How big data analytics create business value: The mediating role of decision-making quality and firm agility. Information & Management, 60(1), 103670. https://doi.org/10.1016/j.im.2022.103670
Lin, N., Tan, H., & Chen, S. (2017). Global offshoring portfolio diversity and performance implications. International Journal of Physical Distribution & Logistics Management, 47(2/3), 114-136. https://doi.org/10.1108/IJPDLM-03-2016-0080
Lu, Y., Wu, Y., & Chang, C. (2021). Work-life balance and job satisfaction in digital workplaces. Sustainability, 13(3), 1158. https://doi.org/10.3390/su13031158
Luo, X., & Homburg, C. (2008). Satisfaction, complaint, and the stock value gap. Journal of Marketing, 72(4), 29-43.
https://doi.org/10.1509/jmkg.72.4.29
Marinkovic, V., & Kalinic, Z. (2017). Antecedents of customer satisfaction in mobile commerce: Exploring the moderating effect of customization. Online Information Review, 41(2), 138-154. https://doi.org/10.1108/OIR-11-2015-0366
McAfee, A., & Brynjolfsson, E. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 60-68.
Miah, S. J., Vu, H. Q., Gammack, J., & McGrath, M. A. (2017). A big data analytics method for tourist behaviour analysis. Information & Management, 54(6), 771-785. https://doi.org/10.1016/j.im.2016.11.011
Mikalef, P., Krogstie, J., Pappas, I. O., & Pavlou, P. (2020). Exploring the relationship between big data analytics capability and competitive performance: The mediating roles of dynamic and operational capabilities. Information and Management, 57(2), 103169. https://doi.org/10.1016/j.im.2019.05.004
Potjanajaruwit, P. (2018). Competitive advantage effects on firm performance: A case study of startups in Thailand. Journal of International Studies, 10(1), 104-111. https://doi.org/10.14254/2071-8330.2018/11-1/8
Pratono, A. H. (2024). The role of digital capabilities in developing competitive advantage: Evidence from emerging markets. Technological Forecasting and Social Change, 198, 122933. https://doi.org/10.1016/j.techfore.2023.122933
Razaghi, S., & Shokouhyar, S. (2021). Impacts of big data analytics management capabilities and supply chain integration on global sourcing: A survey on firm performance. The Bottom Line, 34(2), 198-223. https://doi.org/10.1108/BL-12-2020-0080
Sarmento, R. P., & Costa, V. (2019). Confirmatory factor analysis—A case study. arXiv preprint arXiv:1905.05598. https://doi.org/10.48550/arXiv.1905.05598
Sica, C., & Ghisi, M. (2007). The Italian versions of the Beck Anxiety Inventory and the Beck Depression Inventory-II: Psychometric properties and discriminant power. In M. C. Gullotta (Ed.), Leading-edge psychological tests and testing research (pp. 27-50). Nova Science Publishers.
Spreng, R. A., Mackenzie, S. B., & Olshavsky, R. W. (1996). A reexamination of the determinants of consumer satisfaction. The Journal of Marketing, 60(3), 15-32. https://doi.org/10.1177/002224299606000302
Stank, T. P., Keller, S. B., & Closs, D. J. (2001). Performance benefits of supply chain logistical integration. Transportation Journal, 41(2/3), 32-46.
Swink, M., Narasimhan, R., & Wang, C. (2007). Managing beyond the factory walls: Effects of four types of strategic integration on manufacturing plant performance. Journal of Operations Management, 25(1), 148-164.
https://doi.org/10.1016/j.jom.2006.02.006
Teece, D., & Pisano, G. (1994). The dynamic capabilities of firms: An introduction. Industrial and Corporate Change, 3(3), 537-556. https://doi.org/10.1093/icc/3.3.537
Vitari, C., & Raguseo, E. (2020). Big data analytics business value and firm performance: Linking with environmental context. International Journal of Production Research, 58(18), 5456-5476. https://doi.org/10.1080/00207543.2020.1730463
Wamba, S. F., Akter, S., Trinchera, L., & Bourmont, M. D. (2018). Turning information quality into firm performance in the big data economy. Management Decision, 57(8), 1756-1783. https://doi.org/10.1108/MD-08-2018-0830
Wang, L., Chen, J., & Zhao, Y. (2023). Digital integration capabilities and supply chain resilience: Evidence from Chinese E-commerce firms. Information & Management, 60(3), 103700. https://doi.org/10.1016/j.im.2023.103700
Webster, P. B. (1966). Etymology in Webster's Third New International Dictionary. Word, 22(1-3), 7-82.
Wernerfelt, B. (1984). A resource‐based view of the firm. Strategic Management Journal, 5(2), 171-180.
https://doi.org/10.1002/smj.4250050207
Wixom, B. H., & Todd, P. A. (2005). A theoretical integration of user satisfaction and technology acceptance. Information Systems Research, 16(1), 85-102. https://doi.org/10.1287/isre.1050.0042
Wu, J. H., & Wang, S. C. (2005). What drives mobile commerce? An empirical evaluation of the revised technology acceptance model. Information & Management, 42(5), 719-729. https://doi.org/10.1016/j.im.2004.07.001
Yu, D., & Fang, A. (2023). The knowledge trajectory and structure of the supply chain integration: A main path and cluster analysis. Journal of Enterprise Information Management, 36(4), 1056-1079. https://doi.org/10.1108/JEIM-09-2022-0410
Zhao, Y., & Wang, L. (2022). Strategic value of big data analytics in digital transformation: Evidence from Chinese E-commerce firms. Technological Forecasting and Social Change, 180, 121670.https://doi.org/10.1016/j.techfore.2022.121670
Zuboff, S. (1988). In the age of the smart machine: The future of work and power. Basic Books.
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