Impact of Big Data Analytics on Indian E-Tailing from SCM to TCS
0
조회
0
다운로드
1
인용
0
참고문헌
키워드
초록
Purpose: The study aims to recognize the relationship between big data analytics capabilities, big data analytics process, and perceived business performance from supply chain management to total customer satisfaction. Research design, data and methodology: The study followed a quantitative approach with a descriptive design. The data was collected from leading e-commerce companies in India using a structured questionnaire, and the data was coded and decoded using MS Excel, SPSS, and R language. It was further tested using Cronbach's alpha, KMO, and Bartlett’s test for reliability and internal consistency. Results: The results showed that the big data analytics process acts as a robust mediator between big data analytics capabilities and perceived business performance. The ‘direct, indirect and total effect of the model’ and ‘PLS-SEM model’ showed that the big data analytics process directly impacts business performance. Conclusions: A complete indirect relationship exists between big data analytics capabilities and perceived business performance through the big data analytics process. The research contributes to e-commerce companies' understanding of the importance of big data analytics capabilities and processes.
Abstract
Purpose: The study aims to recognize the relationship between big data analytics capabilities, big data analytics process, and perceived business performance from supply chain management to total customer satisfaction. Research design, data and methodology: The study followed a quantitative approach with a descriptive design. The data was collected from leading e-commerce companies in India using a structured questionnaire, and the data was coded and decoded using MS Excel, SPSS, and R language. It was further tested using Cronbach's alpha, KMO, and Bartlett’s test for reliability and internal consistency. Results: The results showed that the big data analytics process acts as a robust mediator between big data analytics capabilities and perceived business performance. The ‘direct, indirect and total effect of the model’ and ‘PLS-SEM model’ showed that the big data analytics process directly impacts business performance. Conclusions: A complete indirect relationship exists between big data analytics capabilities and perceived business performance through the big data analytics process. The research contributes to e-commerce companies' understanding of the importance of big data analytics capabilities and processes.
참고문헌 (49)
- Akter, S., "How to improve firm performance using big data analytics capability and business strategy alignment?", International Journal of Production Economics, 182, pp.113~131 (2016)
- Akter, S., "Big data analytics in Ecommerce : a systematic review and agenda for future research", Electronic Markets, 26, pp.173~194 (2016)
- Al-Sakran, H., "B2C E-commerce fact-based negotiation using big data analytics and agent-Based technologies", International Journal of Advanced Computer Science and Applications, 5(12), pp.30~37 (2014)
- Bharadwaj, A., "Digital business strategy : toward a next generation of insights", MIS Quarterly, 37(2), pp.471~482 (2013)
- Brown, B., "Are you ready for the era of ‘big data’", McKinsey Quarterly, 4(1), pp.24~35 (2011)
- Chang, R. M., "Understanding the paradigm shift to computational social science in the presence of big data", Decision support systems, 63, pp.67~80 (2014)
- Chang, Y. W., "What motivates customers to shop in smart shops? The impacts of smart technology and technology readiness", Journal of Retailing and Consumer Services, 58, pp.102325~ (2021)
- Chen, J. S., "Performance effects of IT capability, service process innovation, and the mediating role of customer service", Journal of Engineering and Technology Management, 29(1), pp.71~94 (2012)
- Colton, D. A., "Drivers of international e-tail performance : the complexities of orientations and resources", Journal of International Marketing, 18(1), pp.1~22 (2010)
- Dobusch, L., "Open strategy-making with crowds and communities : Comparing Wikimedia and Creative Commons", Long range planning, 51(4), pp.561~579 (2018)
- Dubey, R., "Big data analytics capability in supply chain agility : The moderating effect of organizational flexibility", Management decision, 57(8), pp.2092~2112 (2019)
- Eisenhardt, K. M., "Dynamic capabilities:what are they?", Strategic management journal, 21(10‐11), pp.1105~1121 (2000)
- Erevelles, S., "Big Data consumer analytics and the transformation of marketing", Journal of business research, 69(2), pp.897~904 (2016)
- "Eurostat statistics explained : e-commerce statistics" (2017)[URL]
- Ferraris, A., "Big data analytics capabilities and knowledge management : impact on firm performance", Management Decision, 57(8), pp.1923~1936 (2019)
- Fisher, D., "Interactions with big data analytics", interactions, 19(3), pp.50~59 (2012)
- Fozooni, A., "Prioritizing big data applications in E-commerce considering sustainable development indicators", Journal of Future Sustainability, 4(3), pp.169~178 (2024)
- Gandomi, A., "Beyond the hype : Big data concepts, methods, and analytics", International journal of information management, 35(2), pp.137~144 (2015)
- Gauri, D. K., "Evolution of retail formats : Past, present, and future", Journal of Retailing, 97(1), pp.42~61 (2021)
- Ghandour, A, "Ecommerce website value model for SMEs", ~ (2015)
- Grossman, R., "Organizational models for big data and analytics", Journal of Organization Design, 3(1), pp.20~25 (2014)
- "Retail industry report" (2023)[URL]
- "E-commerce industry in India : E-commerce industry report" (2023)[URL]
- "UPI leading the boom of digital transactions in India" (2022)[URL]
- Johnson, J. S., "Big data facilitation, utilization, and monetization : Exploring the 3Vs in a new product development process", Journal of Product Innovation Management, 34(5), pp.640~658 (2017)
- Kautish, P., "Consumer values, fashion consciousness and behavioural intentions in the online fashion retail sector", International Journal of Retail & Distribution Management, 46(10), pp.894~914 (2018)
- Kibe, L. W., "Relationship between big data analytics and organisational performance of the Technical University of Kenya and Strathmore University in Kenya", Global Knowledge, Memory and Communication, 69(6, pp.7) (2020), 537~556
- Kim, D., "Drivers of virtual interfirm integration and its impact on performance in international customer–supplier relationships", Management international review, 58(3), pp.495~522 (2018)
- Kwon, O., "Data quality management, data usage experience and acquisition intention of big data analytics", International journal of information management, 34(3), pp.387~394 (2014)
- Lanzolla, G., "Pioneering strategies in the digital world. Insights from the Axel Springer case", Business History, 59(5), pp.744~777 (2017)
- Big data: The next frontier for innovation, competition (Vol. 5, No. 6). and productivity, "Manyika, J.", McKinsey Global Institute, ~ (2011)
- Olabode, O. E., "Big data analytics capability and market performance : The roles of disruptive business models and competitive intensity", Journal of Business Research, 139, pp.1218~1230 (2022)
- Papadopoulos, T., "Big data and analytics in operations and supply chain management: managerial aspects and practical challenges", Production Planning & Control, 28(11-12), pp.873~876 (2017)
- Potluri, R. M., "Data Analytics in Marketing, Entrepreneurship, and Innovation", pp.83~106 (2021), Auerbach Publications
- Potluri, R. M, "Global Risk and Contingency Management Research in Times of Crisis", pp.210~223 (2022), IGI Global
- Potluri, R. M., "Advancing SMEs Toward E-Commerce Policies for Sustainability", pp.235~247 (2023), IGI Global
- Potluri, R. M., "Sustainability in Supply Chain Management : A Case Study of the Indian Retailing Industry", Engineering Proceedings, 59(1), pp.64~ (2023)
- Real-time data, BI, and analytics. Accelerating Business to Leverage Customer Relations, Competitiveness, and Insights, "Russom, P.", TDWI, 5~25 (2014)
- "Why Big Data Is All Retailers Want for Christmas" (2012)[URL]
- Sheng, J., "A multidisciplinary perspective of big data in management research", International Journal of Production Economics, 191, pp.97~112 (2017)
- Srinivasan, R., "An investigation of visibility and flexibility as complements to supply chain analytics : An organizational information processing theory perspective", Production and Operations Management, 27(10), pp.1849~1867 (2018)
- "India’s growing internet connectivity" (2023)[URL]
- "Volume of UPI-based digital payments across India financial year 2017-2023" (2023)[URL]
- Tambe, P., "Big data investment, skills, and firm value", Management science, 60(6), pp.1452~1469 (2014)
- "Policy framework will pave the way for wider government outreach in the digital era" (2023)[URL]
- Wamba, S. F., "How ‘big data’can make big impact : Findings from a systematic review and a longitudinal case study", International journal of production economics, 165, pp.234~246 (2015)
- Wang, Y., "Leveraging big data analytics to improve quality of care in healthcare organizations : A configurational perspective", British Journal of Management, 30(2), pp.362~388 (2019)
- Wixom, B. H., "A theoretical integration of user satisfaction and technology acceptance", Information systems research, 16(1), pp.85~102 (2005)
- Zhu, S., "How Does E-commerce Industry Benefit from Big Data", SHS Web of Conferences, 181, pp.01029~ (2024), EDP Sciences