The role of absorptive capacity and big data analytics in strategic purchasing and supply chain management decisions
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DOI: 10.1016/j.technovation.2023.102814
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- Wang, Gang & Gunasekaran, Angappa & Ngai, Eric W.T. & Papadopoulos, Thanos, 2016. "Big data analytics in logistics and supply chain management: Certain investigations for research and applications," International Journal of Production Economics, Elsevier, vol. 176(C), pages 98-110.
- Lamba, Kuldeep & Singh, Surya Prakash, 2019. "Dynamic supplier selection and lot-sizing problem considering carbon emissions in a big data environment," Technological Forecasting and Social Change, Elsevier, vol. 144(C), pages 573-584.
- Božič, Katerina & Dimovski, Vlado, 2019. "Business intelligence and analytics for value creation: The role of absorptive capacity," International Journal of Information Management, Elsevier, vol. 46(C), pages 93-103.
- Ala Pazirandeh Arvidsson & Patrik Jonsson & Riikka Kaipia, 2021. "Big data in purchasing and supply management: a research agenda," International Journal of Procurement Management, Inderscience Enterprises Ltd, vol. 14(2), pages 185-212.
- Erevelles, Sunil & Fukawa, Nobuyuki & Swayne, Linda, 2016. "Big Data consumer analytics and the transformation of marketing," Journal of Business Research, Elsevier, vol. 69(2), pages 897-904.
- Rialti, Riccardo & Zollo, Lamberto & Ferraris, Alberto & Alon, Ilan, 2019. "Big data analytics capabilities and performance: Evidence from a moderated multi-mediation model," Technological Forecasting and Social Change, Elsevier, vol. 149(C).
- Kwon, Ohbyung & Lee, Namyeon & Shin, Bongsik, 2014. "Data quality management, data usage experience and acquisition intention of big data analytics," International Journal of Information Management, Elsevier, vol. 34(3), pages 387-394.
- Thanos Papadopoulos & Angappa Gunasekaran & Rameshwar Dubey & Samuel Fosso Wamba, 2017. "Big data and analytics in operations and supply chain management: managerial aspects and practical challenges," Post-Print hal-02279562, HAL.
- Arunachalam, Deepak & Kumar, Niraj & Kawalek, John Paul, 2018. "Understanding big data analytics capabilities in supply chain management: Unravelling the issues, challenges and implications for practice," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 114(C), pages 416-436.
- Mahmood, Tarique & Mubarik, Muhammad Shujaat, 2020. "Balancing innovation and exploitation in the fourth industrial revolution: Role of intellectual capital and technology absorptive capacity," Technological Forecasting and Social Change, Elsevier, vol. 160(C).
- Ciampi, Francesco & Demi, Stefano & Magrini, Alessandro & Marzi, Giacomo & Papa, Armando, 2021. "Exploring the impact of big data analytics capabilities on business model innovation: The mediating role of entrepreneurial orientation," Journal of Business Research, Elsevier, vol. 123(C), pages 1-13.
- Ravi Srinivasan & Morgan Swink, 2018. "An Investigation of Visibility and Flexibility as Complements to Supply Chain Analytics: An Organizational Information Processing Theory Perspective," Production and Operations Management, Production and Operations Management Society, vol. 27(10), pages 1849-1867, October.
- van Raaij, E.M., 2016. "Purchasing Value: Purchasing and Supply Management's Contribution to Health Service Performance," ERIM Inaugural Address Series Research in Management 93665, Erasmus Research Institute of Management (ERIM), ERIM is the joint research institute of the Rotterdam School of Management, Erasmus University and the Erasmus School of Economics (ESE) at Erasmus University Rotterdam..
- Alharthi, Abdulkhaliq & Krotov, Vlad & Bowman, Michael, 2017. "Addressing barriers to big data," Business Horizons, Elsevier, vol. 60(3), pages 285-292.
- Sachin S. Kamble & Angappa Gunasekaran, 2020. "Big data-driven supply chain performance measurement system: a review and framework for implementation," International Journal of Production Research, Taylor & Francis Journals, vol. 58(1), pages 65-86, January.
- Mattia Bianchi & Giacomo Marzi & Lamberto Zollo & Andrea Patrucco, 2019. "Developing software beyond customer needs and plans: an exploratory study of its forms and individual-level drivers," International Journal of Production Research, Taylor & Francis Journals, vol. 57(22), pages 7189-7208, November.
- Roßmann, Bernhard & Canzaniello, Angelo & von der Gracht, Heiko & Hartmann, Evi, 2018. "The future and social impact of Big Data Analytics in Supply Chain Management: Results from a Delphi study," Technological Forecasting and Social Change, Elsevier, vol. 130(C), pages 135-149.
- Pereira, Carla Roberta & Lago da Silva, Andrea & Tate, Wendy Lea & Christopher, Martin, 2020. "Purchasing and supply management (PSM) contribution to supply-side resilience," International Journal of Production Economics, Elsevier, vol. 228(C).
- Leeflang, Peter S.H. & Verhoef, Peter C. & Dahlström, Peter & Freundt, Tjark, 2014. "Challenges and solutions for marketing in a digital era," European Management Journal, Elsevier, vol. 32(1), pages 1-12.
- Flatten, Tessa C. & Engelen, Andreas & Zahra, Shaker A. & Brettel, Malte, 2011. "A measure of absorptive capacity: Scale development and validation," European Management Journal, Elsevier, vol. 29(2), pages 98-116, April.
- Neirotti, Paolo & Pesce, Danilo & Battaglia, Daniele, 2021. "Algorithms for operational decision-making: An absorptive capacity perspective on the process of converting data into relevant knowledge," Technological Forecasting and Social Change, Elsevier, vol. 173(C).
- Urbinati, Andrea & Bogers, Marcel & Chiesa, Vittorio & Frattini, Federico, 2019. "Creating and capturing value from Big Data: A multiple-case study analysis of provider companies," Technovation, Elsevier, vol. 84, pages 21-36.
- Hazen, Benjamin T. & Boone, Christopher A. & Ezell, Jeremy D. & Jones-Farmer, L. Allison, 2014. "Data quality for data science, predictive analytics, and big data in supply chain management: An introduction to the problem and suggestions for research and applications," International Journal of Production Economics, Elsevier, vol. 154(C), pages 72-80.
- Knoppen, Desirée & Saris, Willem & Moncagatta, Paolo, 2022. "Absorptive capacity dimensions and the measurement of cumulativeness," Journal of Business Research, Elsevier, vol. 139(C), pages 312-324.
- Erik Hofmann, 2017. "Big data and supply chain decisions: the impact of volume, variety and velocity properties on the bullwhip effect," International Journal of Production Research, Taylor & Francis Journals, vol. 55(17), pages 5108-5126, September.
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Keywords
Absorptive capacity; Big data analytics; Knowledge management; Purchasing management; Supply chain management;All these keywords.
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