References
- Agahi, F., & Dmytrenko, N. (2016). Chunking decision information: A way to make big data actionable. Journal of Decision Systems, 25(sup1), 11–22. https://doi.org/https://doi.org/10.1080/12460125.2016.1187402
- Alamro, A.S., Awwad, A.S., & Anouze, A.L.M. (2018). The integrated impact of new product and market flexibilities on operational performance. Journal of Manufacturing Technology Management, 29(7), 1163–1187. https://doi.org/https://doi.org/10.1108/JMTM-01-2017-0001
- Asamoah, D., Agyei-Owusu, B., Andoh-Baidoo, F.K., & Ayaburi, E. (2019, June). Effect of inter-organizational systems use on supply chain capabilities and performance. In: Dwivedi Y., Ayaburi E., Boateng R., Effah J. (eds.), ICT Unbounded, Social Impact of Bright ICT Adoption. TDIT 2019. IFIP Advances in Information and Communication Technology, vol 558. Springer, Cham. https://doi.org/https://doi.org/10.1007/978-3-030-20671-0_20
- Banker, R.D., Bardhan, I.R., Chang, H., & Lin, S. (2006). Plant information systems, manufacturing capabilities, and plant performance. MIS Quarterly, 30(2), 315–337. https://doi.org/https://doi.org/10.2307/25148733
- Barratt, M. (2016). Exploring supply chain relationships and information exchange in UK grocery supply chains: Some preliminary findings. In: Pawar K.S., Rogers H., Potter A., Naim M. (eds.), Developments in logistics and supply chain management (pp. 181–188). Palgrave Macmillan, London. https://doi.org/https://doi.org/10.1057/9781137541253_16
- Bayramusta, M., & Nasir, V.A. (2016). A fad or future of IT?: A comprehensive literature review on the cloud computing research. International Journal of Information Management, 36(4), 635-644. https://doi.org/https://doi.org/10.1016/j.ijinfomgt.2016.04.006
- Bidar, F., Lobo, A., & Hawthorn, M. (2010). Development of a framework for electronically-enabled supply chains: Channel relationships and firm performance.
- Carr, A. (2016). Relationships among information technology, organizational cooperation and supply chain performance. Journal of Managerial Issues, 28(3/4), 171-190. http://www.jstor.org/stable/44113703
- Chan, A.T., Ngai, E.W., & Moon, K.K. (2017). The effects of strategic and manufacturing flexibilities and supply chain agility on firm performance in the fashion industry. European Journal of Operational Research, 259(2), 486–499. https://doi.org/https://doi.org/10.1016/j.ejor.2016.11.006
- Chan, F.T.S., Bhagwat, R., & Wadhwa, S. (2009). Study on suppliers’ flexibility in supply chains: Is real-time control necessary? International Journal of Production Research, 47(4), 965–987. https://doi.org/https://doi.org/10.1080/00207540701255917
- Chang, H.H., Wong, K.H., & Chiu, W.S. (2019). The effects of business systems leveraging on supply chain performance: Process innovation and uncertainty as moderators. Information & Management, 56(6), 103140. https://doi.org/https://doi.org/10.1016/j.im.2019.01.002
- Chege, S.M., Wang, D., & Suntu, S.L. (2019). Impact of information technology innovation on firm performance in Kenya. Information technology for development, Taylor and Francis, 26(2), 316-345 . https://doi.org/https://doi.org/10.1080/02681102.2019.1573717
- Chengalur-Smith, I., Duchessi, P., & Gil-Garcia, J.R. (2012). Information sharing and business systems leveraging in supply chains: An empirical investigation of one web-based application. Information & Management, 49(1), 58–67. https://doi.org/https://doi.org/10.1016/j.im.2011.12.001
- Chiang, C.Y., Kocabasoglu‐Hillmer, C., & Suresh, N. (2012). An empirical investigation of the impact of strategic sourcing and flexibility on firm’s supply chain agility. International Journal of Operations & Production Management, 32(1), 49-78. https://doi.org/https://doi.org/10.1108/01443571211195736
- De Mattos, C.A., & Laurindo, F.J.B. (2017). Information technology adoption and assimilation: Focus on the suppliers portal. Computers in Industry, 85, 48–57. https://doi.org/https://doi.org/10.1016/j.compind.2016.12.009
- Dhaigude, A., & Kapoor, R. (2017). The mediation role of supply chain agility on supply chain orientation-supply chain performance link. Journal of Decision Systems, 26(3), 275–293. https://doi.org/https://doi.org/10.1080/12460125.2017.1351862
- Drnevich, P.L., & Croson, D.C. (2013). Information Technology and Business-Level Strategy: Toward an Integrated Theoretical Perspective. MIS Quarterly, 37(2), 483–509. https://doi.org/https://doi.org/10.25300/MISQ/2013/37.2.08
- Fantazy, K.A., Kumar, V., & Kumar, U. (2009). An empirical study of the relationships among strategy, flexibility, and performance in the supply chain context. Supply Chain Management: An International Journal, 14(3), 177–188. https://doi.org/https://doi.org/10.1108/13598540910954520
- Fayoumi, A. (2016). Ecosystem-inspired enterprise modelling framework for collaborative and networked manufacturing systems. Computers in Industry, 80, 54–68. https://doi.org/https://doi.org/10.1016/j.compind.2016.04.003
- Garrison, G., Kim, S., & Wakefield, R.L. (2015). Success factors for deploying cloud computing. Communications of the ACM, 55(9), 62–68. https://doi.org/https://doi.org/10.1145/2330667.2330685
- Giannakis, M., Spanaki, K., & Dubey, R. (2019). A cloud-based supply chain management system: Effects on supply chain responsiveness. Journal of Enterprise Information Management, 32(4), 585–607. https://doi.org/https://doi.org/10.1108/JEIM-05-2018-0106
- Guo, Z., Fang, F., & Whinston, A.B. (2006). Supply chain information sharing in a macro prediction market. Decision Support Systems, 42(3), 1944–1958. https://doi.org/https://doi.org/10.1016/j.dss.2006.05.003
- Hahn, G.J. (2020). Industry 4.0: A supply chain innovation perspective. International Journal of Production Research, 58(5), 1425-1441. https://doi.org/https://doi.org/10.1080/00207543.2019.1641642.
- Hair, F.J., Jr, Sarstedt, M., Hopkins, L., & Kuppelwieser, G. (2014). Partial least squares structural equation modeling (PLS-SEM) An emerging tool in business research. European Business Review, 26(2), 106–121. https://doi.org/https://doi.org/10.1108/EBR-10-2013-0128
- Hair, J.F., Jr, Hult, G.T.M., Ringle, C., & Sarstedt, M. (2016). A primer on partial least squares structural equation modeling (PLS-SEM). Sage publications.
- Hair, J.F., Risher, J.J., Sarstedt, M., & Ringle, C.M. (2019a). When to use and how to report the results of PLS-SEM. European Business Review.
- Hair, J.F., Sarstedt, M., & Ringle, C.M. (2019). Rethinking some of the rethinking of partial least squares. European Journal of Marketing, Forthcoming, 53(4), 566–584. https://doi.org/https://doi.org/10.1108/EJM-10-2018-0665
- Haseeb, M., Hussain, H.I., Ślusarczyk, B., & Jermsittiparsert, K. (2019). Industry 4.0: A solution towards technology challenges of sustainable business performance. Social Sciences, 8 (5),154. https://doi.org/https://doi.org/10.3390/socsci8050154
- Heavin, C., & Power, D.J. (2018). Challenges for digital transformation–towards a conceptual decision support guide for managers. Journal of Decision Systems, 27(sup1), 38–45. https://doi.org/https://doi.org/10.1080/12460125.2018.1468697
- Henseler, J., Ringle, C.M., & Sinkovics, R.R. (2009). The use of partial least squares path modeling in international marketing. In Sinkovics, R.R. and Ghauri, P.N. (eds.), New challenges to international marketing (Advances in International Marketing, 20, Emerald Group Publishing Limited, Bingley, 277-319. https://doi.org/https://doi.org/10.1108/S1474-7979(2009)0000020014
- Huo, B., Gu, M., & Wang, Z. (2018). Supply chain flexibility concepts, dimensions and outcomes: An organisational capability perspective. International Journal of Production Research, 56(17), 5883–5903. https://doi.org/https://doi.org/10.1080/00207543.2018.1456694
- Irfan, M., Wang, M., & Akhtar, N. (2019). Impact of IT capabilities on supply chain capabilities and organizational agility: A dynamic capability view. Operations Management Research, 12(3–4), 113–128. https://doi.org/https://doi.org/10.1007/s12063-019-00142-y
- Ivanov, D., Das, A., & Choi, T.M. (2018). New flexibility drivers for manufacturing, supply chain and service operations. International Journal of Production Research, 56(10), 3359–3368. https://doi.org/https://doi.org/10.1080/00207543.2018.1457813
- Jharkaria, S., & Shankar, R. (2005). Supply chain management: Some sectoral dissimilarities in the Indian manufacturing industry. Supply Chain Management: An International Journal, 11(4), 345–352. https://doi.org/https://doi.org/10.1108/13598540610671798
- Jimenez-Jimenez, D., Martínez-Costa, M., & Sanchez Rodriguez, C. (2019). The mediating role of supply chain collaboration on the relationship between information technology and innovation. Journal of Knowledge Management, 23(3), 548–567. https://doi.org/https://doi.org/10.1108/JKM-01-2018-0019
- Jin, Y., Hopkins, M.M., & Wittmer, J.L. (2010). Linking human capital to competitive advantages: Flexibility in a manufacturing firm's supply chain. Human Resource Management, 49(5), 939–963. https://doi.org/https://doi.org/10.1002/hrm.20385
- Jin, Y., Vonderembse, M., Ragu-Nathan, T.S., & Smith, J.T. (2014). Exploring relationships among IT-enabled sharing capability, supply chain flexibility, and competitive performance. International Journal of Production Economics, 153, 24–34. https://doi.org/https://doi.org/10.1016/j.ijpe.2014.03.016
- Kamble, S., Gunasekaran, A., & Arha, H. (2019). Understanding the Blockchain technology adoption in supply chains-Indian context. International Journal of Production Research, 57(7), 2009–2033. https://doi.org/https://doi.org/10.1080/00207543.2018.1518610
- Kerin, M., & Pham, D.T. (2019). A review of emerging industry 4.0 technologies in remanufacturing. Journal of Cleaner Production, 237, 117805. https://doi.org/https://doi.org/10.1016/j.jclepro.2019.117805
- Kline, P. (2015). Personality (Psychology Revivals): Measurement and Theory. Routledge.
- Kock, N., & Hadaya, P. (2018). Minimum sample size estimation in PLS‐SEM: The inverse square root and gamma‐exponential methods. Information Systems Journal, 28(1), 227–261. https://doi.org/https://doi.org/10.1111/isj.12131
- Kou, T.C., Chiang, C.T., & Chiang, A.H. (2018). Effects of IT-based supply chains on new product development activities and the performance of computer and communication electronics manufacturers. Journal of Business & Industrial Marketing, 33(7), 869–882. https://doi.org/https://doi.org/10.1108/JBIM-11-2016-0269
- Kumar, N., & Ganguly, K.K. (2020). External diffusion of B2B e-procurement and firm financial performance: Role of information transparency and supply chain coordination. Journal of Enterprise Information Management. https://doi.org/https://doi.org/10.1108/JEIM-02-2020-0060
- Kume, K., & Fujiwara, T. (2016). Production flexibility of real options in daily supply chain. Global Journal of Flexible Systems Management, 17(3), 249–264. https://doi.org/https://doi.org/10.1007/s40171-015-0103-3
- Lai, F., Zhang, M., Lee, D.M., & Zhao, X. (2012). The impact of supply chain integration on mass customization capability: An extended resource-based view. IEEE Transactions on Engineering Management, 59(3), 443–456. https://doi.org/https://doi.org/10.1109/TEM.2012.2189009
- Lee, N.C.A., Wang, E.T., & Grover, V. (2020). IOS drivers of manufacturer-supplier flexibility and manufacturer agility. The Journal of Strategic Information Systems, 29(1), 101594. https://doi.org/https://doi.org/10.1016/j.jsis.2020.101594
- Li, G., Fan, H., Lee, P.K., & Cheng, T.C.E. (2015). Joint supply chain risk management: An agency and collaboration perspective. International Journal of Production Economics, 164, 83–94. https://doi.org/https://doi.org/10.1016/j.ijpe.2015.02.021
- Li, L. (2012). Effects of enterprise technology on supply chain collaboration: Analysis of China-linked supply chain. Enterprise Information Systems, 6(1), 55–77. https://doi.org/https://doi.org/10.1080/17517575.2011.639904
- Liang, H., Wang, N., Xue, Y., & Ge, S. (2017). Unraveling the alignment paradox: How does business—IT alignment shape organizational agility? Information Systems Research, 28(4), 863–879. https://doi.org/https://doi.org/10.1287/isre.2017.0711
- Liu, H., Ke, W., Wei, K.K., & Hua, Z. (2013). The impact of IT capabilities on firm performance: The mediating roles of absorptive capacity and supply chain agility. Decision Support Systems, 54(3), 1452–1462. https://doi.org/https://doi.org/10.1016/j.dss.2012.12.016
- Liu, H., Wei, S., Ke, W., Wei, K.K., & Hua, Z. (2016). The configuration between supply chain integration and information technology competency: A resource orchestration perspective. Journal of Operations Management, 44(1), 13–29. https://doi.org/https://doi.org/10.1016/j.jom.2016.03.009
- Mabrouk, N., Omri, A., & Jarraya, B. (2020). Factors influencing the performance of supply chain management in Saudi SMEs. Uncertain Supply Chain Management, 8(3), 569–578. https://doi.org/https://doi.org/10.5267/j.uscm.2020.2.006
- Mandal, S. (2015). Supply and demand effects on supply chain flexibility: An empirical exploration. Knowledge and Process Management, 22(3), 206–219. https://doi.org/https://doi.org/10.1002/kpm.1475
- Manders, J.H., Caniëls, M.C., & Paul, W.T. (2016). Exploring supply chain flexibility in a FMCG food supply chain. Journal of Purchasing and Supply Management, 22(3), 181–195. https://doi.org/https://doi.org/10.1016/j.pursup.2016.06.001
- Manders, J.H., Caniëls, M.C., & Paul, W.T. (2017). Supply chain flexibility. The International Journal of Logistics Management, 28(4), 964–1026. https://doi.org/https://doi.org/10.1108/IJLM-07-2016-0176
- Martínez, M.E.C., Aranda, D.A., & Gutiérrez, L.G. (2016). IT integration, operations flexibility and performance: An empirical study. Journal of Industrial Engineering and Management, 9(3), 684–707. https://doi.org/https://doi.org/10.3926/jiem.1869
- Miemczyk, J., & Luzzini, D. (2019). Achieving triple bottom line sustainability in supply chains. International Journal of Operations & Production Management, 39(2), 238–259. https://doi.org/https://doi.org/10.1108/IJOPM-06-2017-0334
- Mishra, R., Pundir, A.K., & Ganapathy, L. (2018). Empirical assessment of factors influencing potential of manufacturing flexibility in organization. Business Process Management Journal, 24(1), 158–182. https://doi.org/https://doi.org/10.1108/BPMJ-07-2016-0157
- Moliner-Velázquez, B., Fuentes-Blasco, M., & Gil-Saura, I. (2019). The role of ICT, eWOM and guest characteristics in loyalty. Journal of Hospitality and Tourism Technology, 10(2), 153-168. https://doi.org/https://doi.org/10.1108/JHTT-11-2017-0120
- Mu, E., Kirsch, L.J., & Butler, B.S. (2015). The assimilation of enterprise information system: An interpretation systems perspective. Information & Management, 52(3), 359–370. https://doi.org/https://doi.org/10.1016/j.im.2015.01.004
- Niranjan, S., Spulick, S.R., & Savitskie, K. (2018). Mediating and moderating influencers of firm performance. Journal of Enterprise Information Management, 31(1), 38–63. https://doi.org/https://doi.org/10.1108/JEIM-08-2016-0141
- Nugraha, A.T., & Hakimah, Y. (2019). Role of relational capabilities on the supply chain performance of Indonesian textile sector with moderating effect of technology adoption. International Journal of Supply Chain Management, 8(5), 509–522.
- Oyebamiji, F. (2018). Information technology and its effect on performance of logistics firms in Nigeria. Asian Research Journal of Arts & Social Sciences, 6(1),1–11. https://doi.org/https://doi.org/10.9734/ARJASS/2018/39813
- Pavlis, N.E., Moschuris, S.J., & Laios, L.G. (2018). Supply management performance and cash conversion cycle. International Journal of Supply and Operations Management, 5(2), 107–121. https://doi.org/https://doi.org/10.22034/2018.2.1
- Podsakoff, P.M., MacKenzie, S.B., & Podsakoff, N.P. (2012). Sources of method bias in social science research and recommendations on how to control it. Annual Review of Psychology, 63(1), 539–569. https://doi.org/https://doi.org/10.1146/annurev-psych-120710-100452
- Pu, X., Chong, A.Y.L., Cai, Z., Lim, M.K., & Tan, K.H. (2019). Leveraging open-standard interorganizational information systems for process adaptability and alignment. International Journal of Operations & Production Management, 39(6/7/8), 962–992. https://doi.org/https://doi.org/10.1108/IJOPM-12-2018-0747
- Qrunfleh, S., & Tarafdar, M. (2014). Supply chain information systems strategy: Impacts on supply chain performance and firm performance. International Journal of Production Economics, 147, 340–350. https://doi.org/https://doi.org/10.1016/j.ijpe.2012.09.018
- Quach, S., Thaichon, P., Lee, J.Y., Weaven, S., & Palmatier, R.W. (2019). Toward a theory of outside-in marketing: Past, present, and future. Industrial Marketing Management, 89(August 2020), 107-128. https://doi.org/https://doi.org/10.1016/j.indmarman.2019.10.016
- Ravichandran, T., Han, S., & Mithas, S. (2017). Mitigating diminishing returns to R&D: The role of information technology in innovation. Information Systems Research, 28(4), 812–827. https://doi.org/https://doi.org/10.1287/isre.2017.0717
- Raymond, L., & St-Pierre, J. (2005). Antecedents and performance outcomes of advanced manufacturing systems sophistication in SMEs. International Journal of Operations & Production Management, 25(6), 514–533. https://doi.org/https://doi.org/10.1108/01443570510599692
- Rhee, M., & Stephens, A.R. (2020). Innovation-orientated technology assimilation strategy and Korean SMEs’enhancing innovation capability, competitive advantage and firm performance. International Journal Of Innovation Management, 2050081.
- Ringle, C.M., Wende, S., & Becker, J.M. (2015). SmartPLS 3. SmartPLS. Retrieved July, 15, 2016.
- Sahay, B.S., Gupta, J.N.D., & Mohan, R. (2006). Managing supply chains for competitiveness: The Indian scenario. Supply Chain Management: An International Journal, 11(1), 15–24. https://doi.org/https://doi.org/10.1108/13598540610642439
- Samadi, E., & Kassou, I. (2016). The relationship between IT and supply chain performance: A systematic review and future research. American Journal of Industrial and Business Management, 6(4), 480. https://doi.org/https://doi.org/10.4236/ajibm.2016.64044
- Sánchez, Á.M., Pérez-Pérez, M., & Vicente-Oliva, S. (2019). Agile production, innovation and technological cooperation. Baltic Journal of Management, 14(4), 597–615. https://doi.org/https://doi.org/10.1108/BJM-12-2018-0410
- Sarstedt, M., Ringle, C.M., & Hair, J.F. (2017). Partial least squares structural equation modeling. In C. Homburg, M. Klarmann, & A. Vomberg (Eds.), Handbook of market research. Springer.
- Shukla, R.K., Garg, D., & Agarwal, A. (2018). Modelling supply chain coordination for performance improvement using analytical network process-based approach. International Journal of Business Excellence, 14(1), 18–48. https://doi.org/https://doi.org/10.1504/IJBEX.2018.088313
- Singh, A., & Teng, J.T. (2016). Enhancing supply chain outcomes through Information Technology and Trust. Computers in Human Behavior, 54, 290–300. https://doi.org/https://doi.org/10.1016/j.chb.2015.07.051
- Singh, R.K., & Acharya, P. (2013). Supply chain flexibility: A frame work of research dimensions. Global Journal of Flexible Systems Management, 14(3), 157–166. https://doi.org/https://doi.org/10.1007/s40171-013-0039-4
- Stefanou, C.J. (2001). Organizational key success factors for implementing SCM/ERP systems to support decision making. Journal of Decision Systems, 10(1), 49–64. https://doi.org/https://doi.org/10.3166/jds.10.49-64
- Stoel, M.D., & Muhanna, W.A. (2009). IT capabilities and firm performance: A contingency analysis of the role of industry and IT capability type. Information & Management, 46(3), 181–189. https://doi.org/https://doi.org/10.1016/j.im.2008.10.002
- Subiah, A.R. (2019) Managing demand variability through information sharing: A case study of imperial cold logistics (Thesis dissertation). https://hdl.handle.net/10539/27080
- Sundar, S., Kannabiran, G., & Tigga, G.A. (2018). IT leveraged downstream supply chain capabilities on competitive marketing performance-a study of Indian manufacturing firms. International Journal of Business Performance and Supply Chain Modelling, 10(2), 165–194. https://doi.org/https://doi.org/10.1504/IJBPSCM.2018.098309
- Swafford, P.M., Ghosh, S., & Murthy, N. (2006). The antecedents of supply chain agility of a firm: Scale development and model testing. Journal of Operations Management, 24(2), 170–188. https://doi.org/https://doi.org/10.1016/j.jom.2005.05.002
- Szalavetz, A. (2019). Industry 4.0 and capability development in manufacturing subsidiaries. Technological Forecasting and Social Change, 145, 384–395. https://doi.org/https://doi.org/10.1016/j.techfore.2018.06.027
- Tiwari, A.K., Tiwari, A., & Samuel, C. (2015). Supply chain flexibility: A comprehensive review. Management Research Review, 38(7), 767–792. https://doi.org/https://doi.org/10.1108/MRR-08-2013-0194
- Üstündağ, A., & Ungan, M.C. (2020). Supplier flexibility and performance: An empirical research. Business Process Management Journal, 26(7), 1851–1870. https://doi.org/https://doi.org/10.1108/BPMJ-01-2019-0027
- Vanpoucke, E., Vereecke, A., & Muylle, S. (2017). Leveraging the impact of supply chain integration through information technology. International Journal of Operations & Production Management, 37(4), 510–530. https://doi.org/https://doi.org/10.1108/IJOPM-07-2015-0441
- Wagner, S.M., Grosse-Ruyken, P.T., & Erhun, F. (2018). Determinants of sourcing flexibility and its impact on performance. International Journal of Production Economics, 205, 329–341. https://doi.org/https://doi.org/10.1016/j.ijpe.2018.08.006
- Wu, F., Yeniyurt, S., Kim, D., & Cavusgil, S.T. (2006). The impact of information technology on supply chain capabilities and firm performance: A resource-based view. Industrial Marketing Management, 35(4), 493–504. https://doi.org/https://doi.org/10.1016/j.indmarman.2005.05.003
- Wu, Y., & Wang, Y. (2019). Achieving market agility through organizational mindfulness towards IT innovation and information processing capacities.
- Xu, D., Huo, B., & Sun, L. (2014). Relationships between intra-organizational resources, supply chain integration and business performance. Industrial Management & Data Systems, 114(8), 1186–1206. https://doi.org/https://doi.org/10.1108/IMDS-05-2014-0156.
- Yang, J-J., Li, J., Mulder, J., Wang, Y., Chen, S., Wu, H., Wang, Q., & Pan, H. (2015). Emerging information technologies for enhanced healthcare. Computers in industry, 69, 3-11. doi:https://doi.org/10.1016/j.compind.2015.01.012
- Yang, Y., Jia, F., & Xu, Z. (2019). Towards an integrated conceptual model of supply chain learning: An extended resource-based view. Supply Chain Management: An International Journal, 24(2), 189–214.
- Yeniyurt, S., Wu, F., Kim, D., & Cavusgil, S.T. (2019). Information technology resources, innovativeness, and supply chain capabilities as drivers of business performance: A retrospective and future research directions. Industrial Marketing Management, 79, 46–52. https://doi.org/https://doi.org/10.1016/j.indmarman.2019.03.008
- Yu, W., Chavez, R., Jacobs, M.A., & Feng, M. (2018). Data-driven supply chain capabilities and performance: A resource-based view. Transportation research part E. Logistics and Transportation Review, 114, 371–385. https://doi.org/https://doi.org/10.1016/j.tre.2017.04.002
- Yu, Y., Zhou, S., & Shi, Y. (2020). Information sharing or not across the supply chain: The role of carbon emission reduction. Transportation Research Part E: Logistics and Transportation Review, 137, 101915. https://doi.org/https://doi.org/10.1016/j.tre.2020.101915.
- Zhang, M., Zhao, X., & Lyles, M. (2018). Effects of absorptive capacity, trust and information systems on product innovation. International Journal of Operations & Production Management, 38(2), 493–512. https://doi.org/https://doi.org/10.1108/IJOPM-11-2015-0687