References
- Agusa, A., & Hassan, Z. (2008). The strategic supplier partnership in a supply chain management with quality and business performance. International Journal of Business and Management Science, 1(2), 129–145.
- Agus, A., & Hajinoor, M. S. (2012). Lean production supply chain management as driver towards enhancing product quality and business performance: Case study of manufacturing companies in Malaysia. International Journal of Quality & Reliability Management, 29(1), 92–121.
- Anderson, J. C., & Gerbing, D. W. (1988). Structural equation modeling in practice: A review and recommended two-step approach. Psychological Bulletin, 103(3), 411–423.
- Arndt, F., & Pierce, L. (2018). The behavioral and evolutionary roots of dynamic capabilities. Industrial and Corporate Change, 27(2), 413–424.
- Ashrafi, A., Ravasan, A. Z., Trkman, P., & Afshari, S. (2019). The role of business analytics capabilities in bolstering firms’ agility and performance. International Journal of Information Management, 47, 1–15.
- Ataseven, C., & Nair, A. (2017). Assessment of supply chain integration and performance relationships: A meta-analytic investigation of the literature. International Journal of Production Economics, 185, 252–265.
- Bagozzi, R. P., & Yi, Y. (1988). On the evaluation of structural equation models. Journal of the Academy of Marketing Science, 16(1), 74–94.
- Barringer, B. R., & Harrison, J. S. (2000). Walking a tightrope: Creating value through interorganizational relationships. Journal of Management, 26(3), 367–403.
- 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.
- Bhimani, A. (2015). Exploring big data’s strategic consequences. Journal of Information Technology, 30(1), 66–69.
- Boddy, D., Cahill, C., Charles, M., Fraser-Kraus, H., & Macbeth, D. (1998). Success and failure in implementing supply chain partnering: An empirical study. European Journal of Purchasing & Supply Management, 4(2), 143–151.
- Brattström, A., & Faems, D. (2020). Interorganizational relationships as political battlefields: How fragmentation within organizations shapes relational dynamics between organizations. Academy of Management Journal, 63(5), 1591–1620.
- Briggs, L. L. (2011). Business analytics helps tame data at Cincinnati Zoo. Business Intelligence Journal, 16(2), 36–38.
- Browder, R. E., Koch, H., Long, A., & Hernandez, J. M. (2022). Learning to innovate with big data analytics in interorganizational relationships. Academy of Management Discoveries, 8(1), 139–166.
- Brown, S. L., & Eisenhardt, K. M. (1997). The art of continuous change: Linking complexity theory and time-paced evolution in relentlessly shifting organizations. Administrative Science Quarterly, 42(1), 1–34.
- Brynjolfsson, E., Malone, T. W., Gurbaxani, V., & Kambil, A. (1994). Does information technology lead to smaller firms? Management Science, 40(12), 1628–1644.
- Brynjolfsson, E., & McAfee, A. (2012). Winning the race with ever-smarter machines. MIT Sloan Management Review, 53(2), 53–60.
- Cao, M., & Zhang, Q. (2011). Supply chain collaboration: Impact on collaborative advantage and firm performance. Journal of Operations Management, 29(3), 163–180.
- Carr, N. G. (2003). IT doesn’t matter. Educause Review, 38(May), 24–38.
- Cepa, K. (2021). Understanding interorganizational big data technologies: How technology adoption motivations and technology design shape collaborative dynamics. Journal of Management Studies, 58(7), 1761–1799.
- Cepa, K., & Schildt, H. (2023). Data-induced rationality and unitary spaces in interfirm collaboration. Organization Science, 34(1), 1–27.
- Chehbi-Gamoura, S., Derrouiche, R., Damand, D., & Barth, M. (2020). Insights from big data analytics in supply chain management: An all-inclusive literature review using the SCOR model. Production Planning & Control, 31(5), 355–382.
- 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.
- Chen, D. Q., Mocker, M., Preston, D. S., & Teubner, A. (2010). Information systems strategy: Reconceptualization, measurement, and implications. MIS Quarterly, 34(2), 233–259.
- Chen, D. Q., Preston, D. S., & Swink, M. (2015). How the use of big data analytics affects value creation in supply chain management. Journal of Management Information Systems, 32(4), 4–39.
- Chen, Y., Wang, Y., Nevo, S., Jin, J., Wang, L., & Chow, W. S. (2014). IT capability and organizational performance: The roles of business process agility and environmental factors. European Journal of Information Systems, 23(3), 326–342.
- Choi, T. -M., (2016). Incorporating social media observations and bounded rationality into fashion quick response supply chains in the big data era: Transportation Research Part E: Logistics and Transportation Review, 114.
- Churchill, G. A. (1979). A paradigm for developing better measures of marketing constructs. Journal of Marketing Research, 16(1), 64–73.
- Combs, J. G., & Ketchen, D. J., Jr. (1999). Explaining interfirm cooperation and performance: Toward a reconciliation of predictions from the resource-based view and organizational economics. Strategic Management Journal, 20(9), 867–888.
- Côrte-Real, N., Oliveira, T., & Ruivo, P. (2017). Assessing business value of big data analytics in European firms. Journal of Business Research, 70, 379–390.
- Curchod, C., Patriotta, G., Cohen, L., & Neysen, N. (2020). Working for an algorithm: Power asymmetries and agency in online work settings. Administrative Science Quarterly, 65(3), 644–676.
- Daneshvar Kakhki, M., & Gargeya, V. B. (2019). Information systems for supply chain management: A systematic literature analysis. International Journal of Production Research, 57(15–16), 5318–5339.
- Daneshvar Kakhki, M., Mousavi, R., & Palvia, P. (2021). Evidence quality, transparency, and translucency for replication in information systems survey research. Communications of the Association for Information Systems, 49(1), 3.
- Daneshvar Kakhki, M., Rea, A., & Deiranlou, M. (2023). Data analytics dynamic capabilities for triple-A supply chains. Industrial Management & Data Systems, In Press.
- Davenport, T. H., & Harris, J. G. (2007). Competing on analytics: The new science of winning. Harvard Business Press.
- Davenport, T. H., & Ronanki, R. (2018). Artificial intelligence for the real world. Harvard Business Review, 96(1), 108–116.
- Deken, F., Berends, H., Gemser, G., & Lauche, K. (2018). Strategizing and the initiation of interorganizational collaboration through prospective resourcing. Academy of Management Journal, 61(5), 1920–1950.
- Doz, Y. L., & Kosonen, M. (2010). Embedding strategic agility: A leadership agenda for accelerating business model renewal. Long Range Planning, 43(2), 370–382.
- Dubey, R., Gunasekaran, A., Childe, S. J., Fosso Wamba, S., Roubaud, D., & Foropon, C. (2021). Empirical investigation of data analytics capability and organizational flexibility as complements to supply chain resilience. International Journal of Production Research, 59(1), 110–128.
- Dutton, J. E., & Jackson, S. E. (1987). Categorizing strategic issues: Links to organizational action. Academy of Management Review, 12(1), 76–90.
- Eckstein, D., Goellner, M., Blome, C., & Henke, M. (2015). The performance impact of supply chain agility and supply chain adaptability: The moderating effect of product complexity. International Journal of Production Research, 53(10), 3028–3046.
- Elliot, S. (2011). Transdisciplinary perspectives on environmental sustainability: A resource base and framework for IT-enabled business transformation. MIS Quarterly, 35(1), 197–236.
- El Sawy, O. A., Kræmmergaard, P., Amsinck, H., & Vinther, A. L. (2020). How LEGO built the foundations and enterprise capabilities for digital leadership. MIS Quarterly Executive, 15(2), 141–166.
- Exact, B. (2004). Case study v: Bt exact: Intelligent business analytics - turning data into business benefit. Journal of Database Marketing & Customer Strategy Management, 12(1), 73–80.
- Faems, D., Janssens, M., Madhok, A., & Van Looy, B. (2008). Toward an integrative perspective on alliance governance: Connecting contract design, trust dynamics, and contract application. Academy of Management Journal, 51(6), 1053–1078.
- Fainshmidt, S., Pezeshkan, A., Lance Frazier, 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.
- Fink, L., Yogev, N., & Even, A. (2017). Business intelligence and organizational learning: An empirical investigation of value creation processes. Information & Management, 54(1), 38–56.
- 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(1), 58–71.
- Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50.
- Franco-Santos, M., Kennerley, M., Micheli, P., Martinez, V., Mason, S., Marr, B., Gray, D., & Neely, A. (2007). Towards a definition of a business performance measurement system. International Journal of Operations & Production Management, 27(8), 784–801.
- Galliers, R. D. (2020). On Confronting Some of the Common Myths of Information: Systems Strategy Discourse. In Strategic Information Management (5th Edition). Routledge.
- Gefen, D., Rigdon, E. E., & Straub, D. (2011). An update and extension to SEM guidelines for administrative and social science research. MIS Quarterly, 35(2), 3–14.
- Ghasemaghaei, M., Hassanein, K., & Turel, O. (2017). Increasing firm agility through the use of data analytics: The role of fit. Decision Support Systems, 101(September), 95–105.
- Ghoshal, A., Larson, E., Subramanyam, R., & Shaw, M. (2014). The impact of business analytics strategy on social, mobile, and cloud computing adoption. Thirty Fifth International Conference on Information Systems, Auckland, New Zealand, 1–11.
- Gillon, K., Aral, S., Lin, C. -Y., Mithas, S., & Zozulia, M. (2014). Business analytics: Radical shift or incremental change? Communications of the Association for Information Systems, 34(1), 287–296.
- Grover, V., Chiang, R. H. L., Liang, T. -P., & Zhang, D. (2018). Creating strategic business value from big data analytics: A research framework. Journal of Management Information Systems, 35(2), 388–423.
- Groves, R. M. (2006). Nonresponse rates and nonresponse bias in household surveys. Public Opinion Quarterly, 70(5), 646–675.
- Groves, R. M., & Peytcheva, E. (2008). The impact of nonresponse rates on nonresponse bias a meta-analysis. Public Opinion Quarterly, 72(2), 167–189.
- Gulati, R., & Singh, H. (1998). The architecture of cooperation: Managing coordination costs and appropriation concerns in strategic alliances. Administrative Science Quarterly, 43(4), 781–814.
- Gulati, R., Wohlgezogen, F., & Zhelyazkov, P. (2012). The two facets of collaboration: Cooperation and coordination in strategic alliances. The Academy of Management Annals, 6(1), 531–583.
- Günther, W. A., Mehrizi, M. H. R., Huysman, M., & Feldberg, F. (2017). Debating big data: A literature review on realizing value from big data. Journal of Strategic Information Systems, 26(3), 191–209.
- Gupta, A. K., Smith, K. G., & Shalley, C. E. (2006). The interplay between exploration and exploitation. Academy of Management Journal, 49(4), 693–706.
- Hair, J. F., Ringle, C. M., & Sarstedt, M. (2011). PLS-SEM: Indeed a silver bullet. Journal of Marketing Theory and Practice, 19(2), 139–152.
- Hambrick, D. C., & Mason, P. A. (1984). Upper echelons: The organization as a reflection of its top managers. Academy of Management Review, 9(2), 193–206.
- Hammer, M., & Champy, J. (2001). Reengineering the corporation: Manifesto for business revolution. Colling Business Essentials.
- Han, L., Hou, H., Bi, Z. M., Yang, J., & Zheng, X. (2021). Functional requirements and supply chain digitalization in industry 4.0. Information Systems Frontiers, 1–13. doi:10.1007/s10796-021-10173-1
- Helfat, C. E., & Peteraf, M. A. (2003). The dynamic resource-based view: Capability lifecycles. Strategic Management Journal, 24(10), 997–1010.
- Hess, T., Matt, C., Benlian, A., & Wiesböck, F. (2016). Options for formulating a digital transformation strategy. MIS Quarterly Executive, 15(2), 123–139.
- Hoetker, G., & Mellewigt, T. (2009). Choice and performance of governance mechanisms: Matching alliance governance to asset type. Strategic Management Journal, 30(10), 1025–1044.
- Hooper, D., Coughlan, J., & Mullen, M. (2008). Structural equation modelling: Guidelines for determining model fit. Electronic Journal of Business Research Methods, 6(1), 53–60.
- Jackson, D. L., Gillaspy, J. A., Jr., & Purc-Stephenson, R. (2009). Reporting practices in confirmatory factor analysis: An overview and some recommendations. Psychological Methods, 14(1), 6.
- Jain, A., & Kogut, B. (2013). Memory and organizational evolvability in a neutral landscape. Organization Science, 25(2), 479–493.
- Jarvenpaa, S. L., & Välikangas, L. (2022). Toward temporally complex collaboration in an interorganizational research network. Strategic Organization, 20(1), 110–134.
- Kappelman, L., Torres, R., McLean, E., Srivastava, S., Johnson, V., Maurer, C., & Guerra, K. (2021). A preview of the 2021 SIM IT trends study. MIS Quarterly Executive, 20(4), 3.
- Karimi, J., Bhattacherjee, A., Gupta, Y. P., & Somers, T. M. (2000). The effects of MIS steering committees on information technology management sophistication. Journal of Management Information Systems, 17(2), 207–230.
- Kim, S. W. (2009). Quality management strategy in supply chain for performance improvement. Asian Journal on Quality, 10(3), 43–64.
- Kline, R. B. (2015). Principles and practice of structural equation modeling. Guilford publications.
- Kohli, R. (2007). Innovating to create IT-Based new business opportunities at united parcel service. MIS Quarterly Executive, 6(4), 199–210.
- Kohli, R., & Grover, V. (2008). Business value of IT: An essay on expanding research directions to keep up with the times. Journal of the Association for Information Systems, 9(1), 23–39.
- Kumar, K., Subramanian, R., & Yauger, C. (1998). Examining the market orientation-performance relationship: A context-specific study. Journal of Management, 24(2), 201–233.
- 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.
- Lavie, D. (2006). The competitive advantage of interconnected firms: An extension of the resource-based view. Academy of Management Review, 31(3), 638–658.
- Lavie, D., Haunschild, P. R., & Khanna, P. (2012). Organizational differences, relational mechanisms, and alliance performance. Strategic Management Journal, 33(13), 1453–1479.
- Lavie, D., & Rosenkopf, L. (2006). Balancing exploration and exploitation in alliance formation. Academy of Management Journal, 49(4), 797–818.
- Lee, H. L. (2004). The triple-A supply chain. Harvard Business Review, 82(10), 102–112.
- Leuschner, R., Rogers, D. S., & Charvet, F. (2013). A meta-analysis of supply chain integration and firm performance. The Journal of Supply Chain Management, 49(2), 34–57.
- Levinthal, D. A., & Rerup, C. (2021). The plural of goal: Learning in a world of ambiguity. Organization Science, 32(3), 1–17.
- Li, S., Ragu-Nathan, B., Ragu-Nathan, T. S., & Subba Rao, S. (2006). The impact of supply chain management practices on competitive advantage and organizational performance. Omega, 34(2), 107–124.
- Maghrabi, R. O., Oakley, R. L., Thambusamy, R., & Iyer, L. S. (2011). The role of business intelligence (bi) in service innovation: An ambidexterity perspective. Proceedings of the 17th Americas Conference on Information Systems, Detroit, MI, Paper 319.
- Majchrzak, A., Markus, M. L., & Wareham, J. (2016). Designing for digital transformation. MIS Quarterly, 40(2), 267–278.
- Mandal, S. (2018). The influence of big data analytics management capabilities on supply chain preparedness, alertness and agility: An empirical investigation. Information Technology & People, 32(2), 297–318.
- March, J. G. (1991). Exploration and exploitation in organizational learning. Organization Science, 2(1), 71–87.
- Matsuno, K., Mentzer, J. T., & Özsomer, A. (2002). The effects of entrepreneurial proclivity and market orientation on business performance. Journal of Marketing, 66(3), 18–32.
- McAfee, A., Brynjolfsson, E., Davenport, T. H., Patil, D. J., & Barton, D. (2012). Big data: The management revolution. Harvard Business Review, 90(10), 61–67.
- Mikalef, P., & Pateli, A. (2017). Information technology-enabled dynamic capabilities and their indirect effect on competitive performance: Findings from PLS-SEM and fsQCA. Journal of Business Research, 70, 1–16.
- Mintzberg, H. (1978). Patterns in strategy formation. Management Science, 24(9), 934–948.
- Mintzberg, H. (1979). The structuring of organization: A synthesis of the research. Prentice-Hall.
- Mitchell, W., Dussauge, P., & Garrette, B. (2002). Alliances with competitors: How to combine and protect key resources? Creativity and Innovation Management, 11(3), 203–223.
- Mithas, S., Ramasubbu, N., & Sambamurthy, V. (2011). How information management capability influences firm performance. MIS Quarterly, 35(1), 237–256.
- Mithas, S., & Rust, R. T. (2016). How information technology strategy and investments influence firm performance: Conjectures and empirical evidence. MIS Quarterly, 40(1), 223–245.
- Moeini, M., Rahrovani, Y., & Chan, Y. E. (2019). A review of the practical relevance of is strategy scholarly research. Journal of Strategic Information Systems, 28(2), 196–217.
- Najib, M., & Kiminami, A. (2011). Innovation, cooperation and business performance: Some evidence from Indonesian small food processing cluster. Journal of Agribusiness in Developing and Emerging Economies, 1(1), 75–96.
- Neely, A., Gregory, M., & Platts, K. (2005). Performance measurement system design: A literature review and research agenda. International Journal of Operations & Production Management, 25(12), 1228–1263.
- Nguyen, T., Li, Z., Spiegler, V., Ieromonachou, P., & Lin, Y. (2018). Big data analytics in supply chain management: A state-of-the-art literature review. Computers & Operations Research, 98, 254–264.
- Nwokah, N. G. (2008). Strategic market orientation and business performance: The study of food and beverages organisations in Nigeria. European Journal of Marketing, 42(3/4), 279–286.
- Palvia, P., Daneshvar Kakhki, M., Ghoshal, T., Uppala, V., & Wang, W. (2015). Methodological and topic trends in information systems research: A meta-analysis of is journals. Communications of the Association for Information Systems, 37(1), 630–655.
- Paulraj, A., Lado, A. A., & Chen, I. J. (2008). Inter-organizational communication as a relational competency: Antecedents and performance outcomes in collaborative buyer–supplier relationships. Journal of Operations Management, 26(1), 45–64.
- Perry, M. L., Sengupta, S., & Krapfel, R. (2004). Effectiveness of horizontal strategic alliances in technologically uncertain environments: Are trust and commitment enough? Journal of Business Research, 57(9), 951–956.
- Petricevic, O., & Verbeke, A. (2019). Unbundling dynamic capabilities for inter-organizational collaboration: The case of nanotechnology. Cross Cultural & Strategic Management, 26(3), 422–428.
- Phelps, C. C. (2010). A longitudinal study of the influence of alliance network structure and composition on firm exploratory innovation. Academy of Management Journal, 53(4), 890–913.
- Podsakoff, P. M., MacKenzie, S. B., Lee, J. -Y., & Podsakoff, N. P. (2003). Common method biases in behavioral research: A critical review of the literature and recommended remedies. The Journal of Applied Psychology, 88(5), 879–903.
- Posen, H. E., & Levinthal, D. A. (2012). Chasing a moving target: Exploitation and exploration in dynamic environments. Management Science, 58(3), 587–601.
- Posen, H. E., & Martignoni, D. (2018). Revisiting the imitation assumption: Why imitation may increase, rather than decrease, performance heterogeneity. Strategic Management Journal, 39(5), 1350–1369.
- Preacher, K. J., & Coffman, D. L. (2006). Computing power and minimum sample size for RMSEA [Computer software]. http://quantpsy.org/
- Putnam, L. L., Fairhurst, G. T., & Banghart, S. (2016). Contradictions, dialectics, and paradoxes in organizations: A constitutive approach. The Academy of Management Annals, 10(1), 65–171.
- Ramakrishnan, T., Khuntia, J., Kathuria, A., & Saldanha, T. J. V. (2020). An integrated model of business intelligence & analytics capabilities and organizational performance. Communications of the Association for Information Systems, 46(1), 722–750.
- Rivkin, J. W., & Siggelkow, N. (2003). Balancing search and stability: Interdependencies among elements of organizational design. Management Science, 49(3), 290–311.
- Sahin, F., & Robinson, E. P. (2002). Flow coordination and information sharing in supply chains: Review, implications, and directions for future research. Decision Sciences, 33(4), 505–536.
- Salleh, N. A. M., Jusoh, R., & Isa, C. R. (2010). Relationship between information systems sophistication and performance measurement. Industrial Management & Data Systems, 110(7), 993–1017.
- Sánchez, A. M., & Pérez, M. P. (2005). Supply chain flexibility and firm performance: A conceptual model and empirical study in the automotive industry. International Journal of Operations & Production Management, 25(7), 681–700.
- Sandberg, E., Kindström, D., & Haag, L. (2021). Delineating interorganizational dynamic capabilities: A literature review and a conceptual framework. Journal of Inter-Organizational Relationships, 27(3–4), 98–113.
- Schad, J., Lewis, M. W., Raisch, S., & Smith, W. K. (2016). Paradox research in management science: Looking back to move forward. The Academy of Management Annals, 10(1), 5–64.
- Schilke, O. (2014). Second-order dynamic capabilities: How do they matter? Academy of Management Perspectives, 28(4), 368–380.
- Schilke, O., Hu, S., & Helfat, C. E. (2018). Quo vadis, dynamic capabilities? A content-analytic review of the current state of knowledge and recommendations for future research. The Academy of Management Annals, 12(1), 390–439.
- Schmoltzi, C., & Wallenburg, C. M. (2012). Operational governance in horizontal cooperations of logistics service providers: Performance effects and the moderating role of cooperation complexity. The Journal of Supply Chain Management, 48(2), 53–74.
- Seddon, P. B., Constantinidis, D., Tamm, T., & Dod, H. (2017). How does business analytics contribute to business value? Information Systems Journal, 27(3), 237–269.
- Seo, D., & La Paz, A. I. (2008). Exploring the dark side of is in achieving organizational agility. Communications of the ACM, 51(11), 136–139.
- Shanks, G., & Bekmamedova, N. (2012a). Achieving benefits with business analytics systems: An evolutionary process perspective. Journal of Decision Systems, 21(3), 231–244.
- Shanks, G., & Bekmamedova, N. (2012b). The impact of strategy on business analytics success. ACIS 2012: Proceedings of the 23rd Australasian Conference on Information Systems 2012, Geelong, Australia, 1–11.
- Sheffi, Y. (2020). The new (ab) normal: Reshaping business and supply chain strategy beyond Covid-19. MIT CTL Media.
- Siggelkow, N., & Rivkin, J. W. (2005). Speed and search: Designing organizations for turbulence and complexity. Organization Science, 16(2), 101–122.
- Sirén, C. A., Kohtamäki, M., & Kuckertz, A. (2012). Exploration and exploitation strategies, profit performance, and the mediating role of strategic learning: Escaping the exploitation trap. Strategic Entrepreneurship Journal, 6(1), 18–41.
- Spekman, R. E. (1988). Strategic supplier selection: Understanding long-term buyer relationships. Business Horizons, 31(4), 75–81.
- Spekman, R. E., Jr., K, J. W., & Myhr, N. (1998). An empirical investigation into supply chain management: A perspective on partnerships. Supply Chain Management: An International Journal, 3(2), 53–67.
- Spekman, R. E., Spear, J., & Kamauff, J. (2002). Supply chain competency: Learning as a key component. Supply Chain Management: An International Journal, 7(1), 41–55.
- Srimarut, T., & Mekhum, W. (2020). From supply chain connectivity (SCC) to supply chain agility (SCA), adaptability and alignment: Mediating role of big data analytics capability. International Journal of Supply Chain Management, 9(1), 183–189.
- Srinivasan, M., Mukherjee, D., & Gaur, A. S. (2011). Buyer–supplier partnership quality and supply chain performance: Moderating role of risks, and environmental uncertainty. European Management Journal, 29(4), 260–271.
- Srinivasan, R., & Swink, M. (2018). An investigation of visibility and flexibility as complements to supply chain analytics: An organizational information processing theory perspective. Production and Operations Management, 27(10), 1849–1867.
- Tallon, P. P., & Pinsonneault, A. (2011). Competing perspectives on the link between strategic information technology alignment and organizational agility: Insights from a mediation model. MIS Quarterly, 33(2), 463–486.
- Tamayo-Torres, J., Gutierrez-Gutierrez, L., & Ruiz-Moreno, A. (2014). The relationship between exploration and exploitation strategies, manufacturing flexibility and organizational learning: An empirical comparison between Non-ISO and ISO certified firms. European Journal of Operational Research, 232(1), 72–86.
- Tan, K. C. (2001). A framework of supply chain management literature. European Journal of Purchasing & Supply Management, 7(1), 39–48.
- Teece, D. J. (1998). Capturing value from knowledge assets: The new economy, markets for know-how, and intangible assets. California Management Review, 40(3), 55–79.
- Teece, D. J. (2007). Explicating dynamic capabilities: The nature and microfoundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350.
- Teece, D. J., Peteraf, M., & Leih, S. (2016). Dynamic capabilities and organizational agility: Risk, uncertainty, and strategy in the innovation economy. California Management Review, 58(4), 13–35.
- Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic capabilities and strategic management. Strategic Management Journal, 18(7), 509–533.
- Teubner, R. A., & Stockhinger, J. (2020). Literature review: Understanding information systems strategy in the digital age. Journal of Strategic Information Systems, 29(4), 101642.
- Tippins, M. J., & Sohi, R. S. (2003). IT competency and firm performance: Is organizational learning a missing link? Strategic Management Journal, 24(8), 745–761.
- 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.
- Trieu, V. -H. (2017). Getting value from business intelligence systems: A review and research agenda. Decision Support Systems, 93, 111–124.
- Trkman, P., McCormack, K., de Oliveira, M. P. V., & Ladeira, M. B. (2010). The impact of business analytics on supply chain performance. Decision Support Systems, 49(3), 318–327.
- Tushman, M. L., & O’Reilly, C. A. (1996). The ambidextrous organizations: Managing evolutionary and revolutionary change. California Management Review, 38(4), 8–30.
- van Rijmenam, M., Erekhinskaya, T., Schweitzer, J., & Williams, M. -A. (2019). Avoid being the Turkey: How big data analytics changes the game of strategy in times of ambiguity and uncertainty. Long Range Planning, 52(5), 1–21.
- Venkatraman, N. (1989). The concept of fit in strategy research: Toward verbal and statistical correspondence. Academy of Management Review, 14(3), 423–444.
- Vukšić, V. B., Bach, M. P., & Popovič, A. (2013). Supporting performance management with business process management and business intelligence: A case analysis of integration and orchestration. International Journal of Information Management, 33(4), 613–619.
- Wamba, S. F., & Akter, S. (2019). Understanding supply chain analytics capabilities and agility for data-rich environments. International Journal of Operations & Production Management, 39(6/7/8), 887–912.
- Wamba, S. F., Gunasekaran, A., Akter, S., Ren, S. J., 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., Tian, Q., Li, X., & Xiao, X. (2022). Different roles, different strokes: How to leverage two types of digital platform capabilities to fuel service innovation. Journal of Business Research, 144, 1121–1128.
- Watson, H. J., Wixom, B. H., Hoffer, J. A., Anderson Lehman, R., & Reynolds, A. M. (2006). Real-time business intelligence: Best practices at continental airlines. Information Systems Management, 23(1), 7–18.
- Whitten, G. D., Jr., G, K. W., & Zelbst, P. J. (2012). Triple-A supply chain performance. International Journal of Operations & Production Management, 32(1), 28–48.
- Wiengarten, F., Li, H., Singh, P. J., & Fynes, B. (2019). Re-evaluating supply chain integration and firm performance: Linking operations strategy to supply chain strategy. Supply Chain Management: An International Journal, 24(4), 540–559.
- Woerner, S. L., & Wixom, B. H. (2015). Big data: Extending the business strategy toolbox. Journal of Information Technology, 30(1), 60–62.
- Wu, S.P. -J., Straub, D. W., & Liang, T. -P. (2015). How information technology governance mechanisms and strategic alignment influence organizational performance: Insights from a matched survey of business and it managers. MIS Quarterly, 39(2), 497–518.
- Yeung, K., Lee, P. K. C., Yeung, A. C. L., & Cheng, T. C. E. (2013). Supplier partnership and cost performance: The moderating roles of specific investments and environmental uncertainty. International Journal of Production Economics, 144(2), 546–559.
- Yıldız, S., & Karakaş, A. (2012). Defining methods and criteria for measuring business performance: A comparative research between the literature in Turkey and Foreign. Procedia - Social and Behavioral Sciences, 58, 1091–1102.
- Yu, W., Wong, C. Y., Chavez, R., & Jacobs, M. A. (2021). Integrating big data analytics into supply chain finance: The roles of information processing and data-driven culture. International Journal of Production Economics, 236, 108135.
- Yu, W., Zhao, G., Liu, Q., & Song, Y. (2021). Role of big data analytics capability in developing integrated hospital supply chains and operational flexibility: An organizational information processing theory perspective. Technological Forecasting and Social Change, 163, 120417.