Dynamic Capabilities and Technological Innovation for Firm Resilience: A Configurational Analysis
Downloads
Firm resilience is essential to manage response and rapid recovery from disruptive events for a firm. Moreover, there is limited literature that investigates the combined effects of dynamic capability and technological innovation that are interrelated with firm resilience. This study used the dimensions of firm resilience, which were investigated with both necessary condition analysis (NCA) and fuzzy-set Qualitative Comparative Analysis (fsQCA) methods using survey questionnaires from 308 respondents operating in Bangladeshi corporate industries that are currently facing uncertainties due to unforeseen crises. NCA results showed that visibility, market position, and digitalization achieved firm resilience as these antecedents reached the full percentile to achieve an optimal level of outcome. On the contrary, the influence of reserve capacity and big data analytics was not empirically significant for achieving firm resilience. Moreover, fsQCA results appreciated NCA results and showed four solutions that are sufficient for achieving a high level of firm resilience. The study reveals the configurational effects of dynamic capabilities and technological innovation to achieve firm resilience. The results show the necessary effects of configurational relationships that lead to outcomes. The configurational method is applied to identify the combined effects of antecedents that help managers predict high levels of firm resilience in a turbulent environment.
Downloads
[1] Aristei, D., & Gallo, M. (2024). Green management, access to credit, and firms’ vulnerability to the COVID-19 crisis. Small Business Economics, 62(1), 179–211. doi:10.1007/s11187-023-00759-1.
[2] Li, N., Li, G., & Xue, J. (2025). Does ESG protect firms equally during crises? The role of supply chain concentration. Omega (United Kingdom), 130. doi:10.1016/j.omega.2024.103171.
[3] Jin, S., Xiong, R., Peng, H., & Tang, S. (2025). ESG performance and private enterprise resilience: Evidence from Chinese financial markets. International Review of Financial Analysis, 98. doi:10.1016/j.irfa.2024.103884.
[4] Ralston, P., & Blackhurst, J. (2020). Industry 4.0 and resilience in the supply chain: a driver of capability enhancement or capability loss? International Journal of Production Research, 58(16), 5006–5019. doi:10.1080/00207543.2020.1736724.
[5] Chen, Y., Li, B., & Huo, B. (2025). Building operational resilience through digitalization: The roles of supply chain network position. Technological Forecasting and Social Change, 211. doi:10.1016/j.techfore.2024.123918.
[6] Ambulkar, S., Blackhurst, J., & Grawe, S. (2015). Firm’s resilience to supply chain disruptions: Scale development and empirical examination. Journal of Operations Management, 33–34, 111–122. doi:10.1016/j.jom.2014.11.002.
[7] Lengnick-Hall, C. A., Beck, T. E., & Lengnick-Hall, M. L. (2011). Developing a capacity for organizational resilience through strategic human resource management. Human Resource Management Review, 21(3), 243–255. doi:10.1016/j.hrmr.2010.07.001.
[8] Xu, J., Cai, D., & Zhu, J. (2025). Navigating the green wave: Urban climate adaptation and firms’ investment decisions-evidence from China. Energy Economics, 141. doi:10.1016/j.eneco.2024.108087.
[9] Swink, M., Sant’Ana Gallo, I., Defee, C., & da Silva, A. L. (2024). Supply chain visibility types and contextual characteristics: A literature-based synthesis. Journal of Business Logistics, 45(1), 12366. doi:10.1111/jbl.12366.
[10] Hohenstein, N. O., Feise, E., Hartmann, E., & Giunipero, L. (2015). Research on the phenomenon of supply chain resilience: A systematic review and paths for further investigation. International Journal of Physical Distribution & Logistics Management, 45, 90–117. doi:10.1108/IJPDLM-05-2013-0128.
[11] Kundu, A., Anderson, S. J., & Ramdas, K. (2024). Disruptions, Redundancy Strategies, and Performance of Small Firms: Evidence from Uganda. Management Science, 70(12), 8265–8283. doi:10.1287/mnsc.2023.4978.
[12] Ali, I., Arslan, A., Chowdhury, M., Khan, Z., & Tarba, S. Y. (2022). Reimagining global food value chains through effective resilience to COVID-19 shocks and similar future events: A dynamic capability perspective. Journal of Business Research, 141, 1–12. doi:10.1016/j.jbusres.2021.12.006.
[13] Kochan, C. G., & Nowicki, D. R. (2018). Supply chain resilience: a systematic literature review and typological framework. International Journal of Physical Distribution & Logistics Management, 48(8), 842–865. doi:10.1108/IJPDLM-02-2017-0099.
[14] Chowdhury, M. M. H., & Quaddus, M. (2017). Supply chain resilience: Conceptualization and scale development using dynamic capability theory. International Journal of Production Economics, 188, 185–204. doi:10.1016/j.ijpe.2017.03.020.
[15] Opazo-Basáez, M., Monroy-Osorio, J. C., & Marić, J. (2024). Evaluating the effect of green technological innovations on organizational and environmental performance: A treble innovation approach. Technovation, 129. doi:10.1016/j.technovation.2023.102885.
[16] Ciasullo, M. V., Chiarini, A., & Palumbo, R. (2024). Mastering the interplay of organizational resilience and sustainability: Insights from a hybrid literature review. Business Strategy and the Environment, 33(2), 1418–1446. doi:10.1002/bse.3530.
[17] Colombari, R., Neirotti, P., & Berbegal-Mirabent, J. (2024). Disentangling the socio-technical impacts of digitalization: What changes for shop-floor decision-makers? International Journal of Production Economics, 276. doi:10.1016/j.ijpe.2024.109377.
[18] Caputo, A., Pizzi, S., Pellegrini, M. M., & Dabić, M. (2021). Digitalization and business models: Where are we going? A science map of the field. Journal of Business Research, 123, 489–501. doi:10.1016/j.jbusres.2020.09.053.
[19] Gradillas, M., & Thomas, L. D. W. (2025). Distinguishing digitization and digitalization: A systematic review and conceptual framework. Journal of Product Innovation Management, 42(1), 112–143. doi:10.1111/jpim.12690.
[20] Chatterjee, S., Chaudhuri, R., Gupta, S., Sivarajah, U., & Bag, S. (2023). Assessing the impact of big data analytics on decision-making processes, forecasting, and performance of a firm. Technological Forecasting and Social Change, 196. doi:10.1016/j.techfore.2023.122824.
[21] Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124–143. doi:10.1108/09574090910954873.
[22] Yu, W., Jacobs, M. A., Chavez, R., & Yang, J. (2019). Dynamism, disruption orientation, and resilience in the supply chain and the impacts on financial performance: A dynamic capabilities perspective. International Journal of Production Economics, 218, 352–362. doi:10.1016/j.ijpe.2019.07.013.
[23] Vanany, I., Ali, M. H., Tan, K. H., Kumar, A., & Siswanto, N. (2024). A Supply Chain Resilience Capability Framework and Process for Mitigating the COVID-19 Pandemic Disruption. IEEE Transactions on Engineering Management, 71, 10358–10372. doi:10.1109/TEM.2021.3116068.
[24] Vali-Siar, M. M., & Roghanian, E. (2022). Sustainable, resilient and responsive mixed supply chain network design under hybrid uncertainty with considering COVID-19 pandemic disruption. Sustainable Production and Consumption, 30, 278–300. doi:10.1016/j.spc.2021.12.003.
[25] Brandon-Jones, E., Squire, B., Autry, C. W., & Petersen, K. J. (2014). A Contingent Resource-Based Perspective of Supply Chain Resilience and Robustness. Journal of Supply Chain Management, 50(3), 55–73. doi:10.1111/jscm.12050.
[26] Scholten, K., Sharkey Scott, P., & Fynes, B. (2019). Building routines for non-routine events: supply chain resilience learning mechanisms and their antecedents. Supply Chain Management, 24(3), 430–442. doi:10.1108/SCM-05-2018-0186.
[27] Jüttner, U., & Maklan, S. (2011). Supply chain resilience in the global financial crisis: An empirical study. Supply Chain Management, 16(4), 246–259. doi:10.1108/13598541111139062.
[28] Afraz, M. F., Bhatti, S. H., Ferraris, A., & Couturier, J. (2021). The impact of supply chain innovation on competitive advantage in the construction industry: Evidence from a moderated multi-mediation model. Technological Forecasting and Social Change, 162. doi:10.1016/j.techfore.2020.120370.
[29] Laguir, I., Gupta, S., Bose, I., Stekelorum, R., & Laguir, L. (2022). Analytics capabilities and organizational competitiveness: Unveiling the impact of management control systems and environmental uncertainty. Decision Support Systems, 156. doi:10.1016/j.dss.2022.113744.
[30] Mishra, P., & Yadav, M. (2021). Environmental capabilities, proactive environmental strategy and competitive advantage: A natural-resource-based view of firms operating in India. Journal of Cleaner Production, 291. doi:10.1016/j.jclepro.2020.125249.
[31] Wong, L. W., Lee, V. H., Tan, G. W. H., Ooi, K. B., & Sohal, A. (2022). The role of cybersecurity and policy awareness in shifting employee compliance attitudes: Building supply chain capabilities. International Journal of Information Management, 66. doi:10.1016/j.ijinfomgt.2022.102520.
[32] Duchek, S. (2020). Organizational resilience: a capability-based conceptualization. Business Research, 13(1), 215–246. doi:10.1007/s40685-019-0085-7.
[33] Hillmann, J., & Guenther, E. (2021). Organizational Resilience: A Valuable Construct for Management Research? International Journal of Management Reviews, 23(1), 7–44. doi:10.1111/ijmr.12239.
[34] Pitelis, C. N., Teece, D. J., & Yang, H. (2024). Dynamic Capabilities and MNE Global Strategy: A Systematic Literature Review-Based Novel Conceptual Framework. Journal of Management Studies, 61(7), 3295–3326. doi:10.1111/joms.13021.
[35] Zhou, X., Cai, Z., Tan, K. H., Zhang, L., Du, J., & Song, M. (2021). Technological innovation and structural change for economic development in China as an emerging market. Technological Forecasting and Social Change, 167. doi:10.1016/j.techfore.2021.120671.
[36] Chatterjee, S., Chaudhuri, R., Vrontis, D., Dana, L. P., & Kabbara, D. (2024). Developing resilience of MNEs: From global value chain (GVC) capability and performance perspectives. Journal of Business Research, 172. doi:10.1016/j.jbusres.2023.114447.
[37] Barney, J. (1991). Firm Resources and Sustained Competitive Advantage. Journal of Management, 17(1), 99–120. doi:10.1177/014920639101700108.
[38] Teece, D. J. (2007). Explicating dynamic capabilities: The nature and micro foundations of (sustainable) enterprise performance. Strategic Management Journal, 28(13), 1319–1350. doi:10.1002/smj.640.
[39] Gupta, S., Modgil, S., Meissonier, R., & Dwivedi, Y. K. (2024). Artificial Intelligence and Information System Resilience to Cope with Supply Chain Disruption. IEEE Transactions on Engineering Management, 71, 10496–10506. doi:10.1109/TEM.2021.3116770.
[40] Teece, D. J. (2018). Dynamic capabilities as (workable) management systems theory. Journal of Management & Organization, 24(3), 359–368. doi:10.1017/jmo.2017.75.
[41] Turner, N., Swart, J., & Maylor, H. (2013). Mechanisms for managing ambidexterity: A review and research agenda. International Journal of Management Reviews, 15(3), 317–332. doi:10.1111/j.1468-2370.2012.00343.x.
[42] Williamson, O. E. (1999). Strategy research: governance and competence perspectives. Strategic Management Journal, 20(12), 1087–1108. doi:10.1002/(sici)1097-0266(199912)20:12<1087::aid-smj71>3.0.co;2-z.
[43] Easterby‐Smith, M., Lyles, M. A., & Peteraf, M. A. (2009). Dynamic Capabilities: Current Debates and Future Directions. British Journal of Management, 20(s1). doi:10.1111/j.1467-8551.2008.00609.x.
[44] Pavlou, P. A., & El Sawy, O. A. (2011). Understanding the Elusive Black Box of Dynamic Capabilities. Decision Sciences, 42(1), 239–273. doi:10.1111/j.1540-5915.2010.00287.x.
[45] Wang, C. L., & Ahmed, P. K. (2007). Dynamic capabilities: A review and research agenda. International Journal of Management Reviews, 9(1), 31–51. doi:10.1111/j.1468-2370.2007.00201.x.
[46] Barreto, I. (2010). Dynamic Capabilities: A review of past research and an agenda for the future. Journal of Management, 36(1), 256–280. doi:10.1177/0149206309350776.
[47] Helfat, C. E., & Peteraf, M. A. (2003). The dynamic resource-based view: capability lifecycles. Strategic Management Journal, 24(10), 997-1010. doi:10.1002/smj.332.
[48] Zhao, N., Hong, J., & Lau, K. H. (2023). Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model. International Journal of Production Economics, 259, 108817. doi:10.1016/j.ijpe.2023.108817.
[49] Bondeli, J. V., & Havenvid, M. I. (2022). Bouncing back in turbulent business environments: Exploring resilience in business networks. Industrial Marketing Management, 107, 383–395. doi:10.1016/j.indmarman.2022.10.022.
[50] Dubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C., Roubaud, D., & Hazen, B. T. (2020). Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organisations. International Journal of Production Economics, 226. doi:10.1016/j.ijpe.2019.107599.
[51] Sharma, V., Vijayaraghavan, T. A. S., Tata, R. R., & Raj, A. (2024). Strengthening organizational resilience: role of sustainable supply chain, digitalization and business model adaptation. Journal of Business & Industrial Marketing, 39(11), 2420–2437. doi:10.1108/JBIM-06-2023-0332.
[52] Kantur, D., & Arzu, Í. S. (2012). Organizational resilience: A conceptual integrative framework. Journal of Management & Organization, 18(6), 762–773. doi:10.5172/jmo.2012.18.6.762.
[53] Burnard, K., & Bhamra, R. (2011). Organisational resilience: Development of a conceptual framework for organisational responses. International Journal of Production Research, 49(18), 5581–5599. doi:10.1080/00207543.2011.563827.
[54] Gutiérrez, M. D. L., Rojas López, F., & Ochoa, G. R. (2024). Adaptive Strategies: Algorithmic Analysis of Pre- and Post-Pandemic Manager-Frontline Employee Communication Model in Restaurants. Emerging Science Journal, 8(5), 2023–2046. doi:10.28991/ESJ-2024-08-05-021.
[55] Holgado, M., & Niess, A. (2023). Resilience in global supply chains: analysis of responses, recovery actions and strategic changes triggered by major disruptions. Supply Chain Management, 28(6), 1040–1059. doi:10.1108/SCM-01-2023-0020.
[56] Ye, F., Ke, M., Ouyang, Y., Li, Y., Li, L., Zhan, Y., & Zhang, M. (2023). Impact of digital technology usage on firm resilience: a dynamic capability perspective. Supply Chain Management: An International Journal, 29(1), 162–175. doi:10.1108/scm-12-2022-0480.
[57] Do, H., Budhwar, P., Shipton, H., Nguyen, H. D., & Nguyen, B. (2022). Building organizational resilience, innovation through resource-based management initiatives, organizational learning and environmental dynamism. Journal of Business Research, 141, 808–821. doi:10.1016/j.jbusres.2021.11.090.
[58] Forliano, C., Bullini Orlandi, L., Zardini, A., & Rossignoli, C. (2023). Technological orientation and organizational resilience to Covid-19: The mediating role of strategy’s digital maturity. Technological Forecasting and Social Change, 188, 122288. doi:10.1016/j.techfore.2022.122288.
[59] Alexander, L., & Van Knippenberg, D. (2014). Teams in pursuit of radical innovation: A goal orientation perspective. Academy of Management Review, 39(4), 423–438. doi:10.5465/amr.2012.0044.
[60] Kamalahmadi, M., & Parast, M. M. (2016). A review of the literature on the principles of enterprise and supply chain resilience: Major findings and directions for future research. International Journal of Production Economics, 171, 116–133. doi:10.1016/j.ijpe.2015.10.023.
[61] Di Vaio, A., Palladino, R., Pezzi, A., & Kalisz, D. E. (2021). The role of digital innovation in knowledge management systems: A systematic literature review. Journal of Business Research, 123, 220–231. doi:10.1016/j.jbusres.2020.09.042.
[62] Zhao, S., Jiang, Y., Peng, X., & Hong, J. (2020). Knowledge sharing direction and innovation performance in organizations: Do absorptive capacity and individual creativity matter? European Journal of Innovation Management, 24(2), 371–394. doi:10.1108/EJIM-09-2019-0244.
[63] A.S, B., & Ramanathan, U. (2021). The role of digital technologies in supply chain resilience for emerging markets’ automotive sector. Supply Chain Management, 26(6), 654–671. doi:10.1108/SCM-07-2020-0342.
[64] Gu, M., Yang, L., & Huo, B. (2021). The impact of information technology usage on supply chain resilience and performance: An ambidexterous view. International Journal of Production Economics, 232. doi:10.1016/j.ijpe.2020.107956.
[65] Leemann, N., & Kanbach, D. K. (2022). Toward a taxonomy of dynamic capabilities – a systematic literature review. Management Research Review, 45(4), 486–501. doi:10.1108/MRR-01-2021-0066.
[66] Al-Talib, M., Melhem, W. Y., Anosike, A. I., Garza Reyes, J. A., Nadeem, S. P., & Kumar, A. (2020). Achieving resilience in the supply chain by applying IoT technology. Procedia CIRP, 91, 752–757. doi:10.1016/j.procir.2020.02.231.
[67] Schoemaker, P. J. H., Day, G. S., & Snyder, S. A. (2013). Integrating organizational networks, weak signals, strategic radars and scenario planning. Technological Forecasting and Social Change, 80(4), 815–824. doi:10.1016/j.techfore.2012.10.020.
[68] Faruquee, M., Paulraj, A., & Irawan, C. A. (2024). The dual effect of environmental dynamism on proactive resilience: can governance mechanisms negate the dark side? Production Planning & Control, 35(15), 2113–2130. doi:10.1080/09537287.2023.2291378.
[69] Li, Y., Ye, F., & Sheu, C. (2014). Social capital, Information sharing and performance evidence from china. International Journal of Operations & Production Management, 34(11), 1440–1462. doi:10.1108/IJOPM-03-2013-0132.
[70] Wang, Z., Ye, F., & Tan, K. H. (2014). Effects of managerial ties and trust on supply chain information sharing and supplier opportunism. International Journal of Production Research, 52(23), 7046–7061. doi:10.1080/00207543.2014.932931.
[71] Adobor, H., & McMullen, R. S. (2018). Supply chain resilience: a dynamic and multidimensional approach. International Journal of Logistics Management, 29(4), 1451–1471. doi:10.1108/IJLM-04-2017-0093.
[72] Tipper, D., Babay, A., Palanisamy, B., & Krishnamurthy, P. (2024). Network Connectivity Resilience in Next Generation Backhaul Networks: Challenges and Future Opportunities. IEEE Transactions on Network and Service Management, 21(5), 5321–5334. doi:10.1109/TNSM.2024.3392857.
[73] Nair, A. J., Manohar, S., & Mittal, A. (2024). Reconfiguration and transformation for resilience: Building service organizations towards sustainability. Journal of Services Marketing, 38(4), 404-425. doi:10.1108/JSM-04-2023-0144.
[74] Ivanov, D. (2024). Two views of supply chain resilience. International Journal of Production Research, 62(11), 4031–4045. doi:10.1080/00207543.2023.2253328.
[75] Namdar, J., Torabi, S. A., Sahebjamnia, N., & Nilkanth Pradhan, N. (2021). Business continuity-inspired resilient supply chain network design. International Journal of Production Research, 59(5), 1331–1367. doi:10.1080/00207543.2020.1798033.
[76] Zokaee, M., Tavakkoli-Moghaddam, R., & Rahimi, Y. (2021). Post-disaster reconstruction supply chain: Empirical optimization study. Automation in Construction, 129. doi:10.1016/j.autcon.2021.103811.
[77] Singh, A., Dwivedi, A., Agrawal, D., & Chauhan, A. (2024). A framework to model the performance indicators of resilient construction supply chain: An effort toward attaining sustainability and circular practices. Business Strategy and the Environment, 33(3), 1688–1720. doi:10.1002/bse.3563.
[78] Dolgui, A., & Ivanov, D. (2022). 5G in digital supply chain and operations management: fostering flexibility, end-to-end connectivity and real-time visibility through internet-of-everything. International Journal of Production Research, 60(2), 442–451. doi:10.1080/00207543.2021.2002969.
[79] Ardolino, M., Bacchetti, A., & Ivanov, D. (2022). Analysis of the COVID-19 pandemic’s impacts on manufacturing: a systematic literature review and future research agenda. Operations Management Research, 15(1–2), 551–566. doi:10.1007/s12063-021-00225-9.
[80] Chakraborty, S., Bhatt, V., Chakravorty, T., & Chakraborty, K. (2021). Analysis of digital technologies as antecedent to care service transparency and orchestration. Technology in Society, 65. doi:10.1016/j.techsoc.2021.101568.
[81] Gürdür, D., El-khoury, J., & Törngren, M. (2019). Digitalizing Swedish industry: What is next?: Data analytics readiness assessment of Swedish industry, according to survey results. Computers in Industry, 105, 153–163. doi:10.1016/j.compind.2018.12.011.
[82] Li, G., Xue, J., Li, N., & Ivanov, D. (2022). Blockchain-supported business model design, supply chain resilience, and firm performance. Transportation Research Part E: Logistics and Transportation Review, 163. doi:10.1016/j.tre.2022.102773.
[83] Eller, R., Alford, P., Kallmünzer, A., & Peters, M. (2020). Antecedents, consequences, and challenges of small and medium-sized enterprise digitalization. Journal of Business Research, 112, 119–127. doi:10.1016/j.jbusres.2020.03.004.
[84] Büyüközkan, G., & Göçer, F. (2018). Digital Supply Chain: Literature review and a proposed framework for future research. Computers in Industry, 97, 157–177. doi:10.1016/j.compind.2018.02.010.
[85] Stank, T., Esper, T., Goldsby, T. J., Zinn, W., & Autry, C. (2019). Toward a Digitally Dominant Paradigm for twenty-first century supply chain scholarship. International Journal of Physical Distribution & Logistics Management, 49(10), 956–971. doi:10.1108/IJPDLM-03-2019-0076.
[86] Hennelly, P. A., Srai, J. S., Graham, G., & Fosso Wamba, S. (2020). Rethinking supply chains in the age of digitalization. Production Planning & Control, 31(2–3), 93–95. doi:10.1080/09537287.2019.1631469.
[87] Fayyaz, A., Liu, C. G., Xu, Y., Khan, F., & Ahmed, S. (2025). Untangling the cumulative impact of big data analytics, green lean six sigma and sustainable supply chain management on the economic performance of manufacturing organisations. Production Planning & Control, 36(8), 1137–1154. doi:10.1080/09537287.2024.2348517.
[88] Ashrafi, A., Zare Ravasan, A., 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. doi:10.1016/j.ijinfomgt.2018.12.005.
[89] Bouncken, R. B., Kraus, S., & Roig-Tierno, N. (2021). Knowledge- and innovation-based business models for future growth: digitalized business models and portfolio considerations. Review of Managerial Science, 15(1), 1–14. doi:10.1007/s11846-019-00366-z.
[90] MacKenzie, S. B., & Podsakoff, P. M. (2012). Common Method Bias in Marketing: Causes, Mechanisms, and Procedural Remedies. Journal of Retailing, 88(4), 542–555. doi:10.1016/j.jretai.2012.08.001.
[91] Baruch, Y., & Holtom, B. C. (2008). Survey response rate levels and trends in organizational research. Human Relations, 61(8), 1139–1160. doi:10.1177/0018726708094863.
[92] Lindebaum, D., & Ashraf, M. (2024). The Ghost in the Machine, or the Ghost in Organizational Theory? A Complementary View on the Use of Machine Learning. Academy of Management Review, 49(2), 445–448. doi:10.5465/amr.2021.0036.
[93] Lee, G., Chang, T., & Chi, S. (2024). Data-Driven Bridge Maintenance Cost Estimation Framework for Annual Expenditure Planning. Journal of Management in Engineering, 40(2). doi:10.1061/jmenea.meeng-5706.
[94] Barbosa, B., Saura, J. R., Zekan, S. B., & Ribeiro-Soriano, D. (2023). Defining content marketing and its influence on online user behavior: a data-driven prescriptive analytics method. Annals of Operations Research, 337(S1), 17. doi:10.1007/s10479-023-05261-1.
[95] Chen, I. J., Paulraj, A., & Lado, A. A. (2004). Strategic purchasing, supply management, and firm performance. Journal of Operations Management, 22(5), 505–523. doi:10.1016/j.jom.2004.06.002.
[96] 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. doi:10.1016/j.jom.2009.06.001.
[97] Dillman, D. A. (2011). Mail and Internet surveys: The tailored design method-2007 Update with new Internet, visual, and mixed-mode guide. John Wiley & Sons, Hoboken, United States.
[98] Papadas, K. K., Avlonitis, G. J., & Carrigan, M. (2017). Green marketing orientation: Conceptualization, scale development and validation. Journal of Business Research, 80, 236–246. doi:10.1016/j.jbusres.2017.05.024.
[99] Dul, J. (2015). Necessary Condition Analysis (NCA). Organizational Research Methods, 19(1), 10–52. doi:10.1177/1094428115584005.
[100] Schneider, C. Q., & Wagemann, C. (2012). Set-theoretic methods for the social sciences: A guide to qualitative comparative analysis. Cambridge University Press, Cambridge, United Kingdom. doi:10.1017/cbo9781139004244.
[101] Dul, J., Hauff, S., & Bouncken, R. B. (2023). Necessary condition analysis (NCA): review of research topics and guidelines for good practice. Review of Managerial Science, 17(2), 683–714. doi:10.1007/s11846-023-00628-x.
[102] Vis, B., & Dul, J. (2016). Analyzing Relationships of Necessity Not Just in Kind but Also in Degree. Sociological Methods & Research, 47(4), 872–899. doi:10.1177/0049124115626179.
[103] Dul, J., van der Laan, E., & Kuik, R. (2020). A Statistical Significance Test for Necessary Condition Analysis. Organizational Research Methods, 23(2), 385–395. doi:10.1177/1094428118795272.
[104] Leppänen, P. T., McKenny, A. F., & Short, J. C. (2019). Qualitative Comparative Analysis in Entrepreneurship: Exploring the Approach and Noting Opportunities for the Future. Standing on the Shoulders of Giants, 155–177, Emerald Publishing Limited, Leeds, United Kingdom. doi:10.1108/s1479-838720190000011010.
[105] Misangyi, V. F., Greckhamer, T., Furnari, S., Fiss, P. C., Crilly, D., & Aguilera, R. (2016). Embracing Causal Complexity. Journal of Management, 43(1), 255–282. doi:10.1177/0149206316679252.
[106] Fiss, P. C. (2011). Building better causal theories: A fuzzy set approach to typologies in organization research. Academy of Management Journal, 54(2), 393–420. doi:10.5465/AMJ.2011.60263120.
[107] Ragin, C. C. (2000). Fuzzy-set social science. University of Chicago Press, Chicago, United States.
[108] Douglas, E. J., Shepherd, D. A., & Prentice, C. (2020). Using fuzzy-set qualitative comparative analysis for a finer-grained understanding of entrepreneurship. Journal of Business Venturing, 35(1), 105970. doi:10.1016/j.jbusvent.2019.105970.
[109] Pappas, I. O., & Woodside, A. G. (2021). Fuzzy-set Qualitative Comparative Analysis (fsQCA): Guidelines for research practice in Information Systems and marketing. International Journal of Information Management, 58. doi:10.1016/j.ijinfomgt.2021.102310.
[110] Hair, J. F., Risher, J. J., Sarstedt, M., & Ringle, C. M. (2019). When to use and how to report the results of PLS-SEM. European Business Review, 31(1), 2–24. doi:10.1108/EBR-11-2018-0203.
[111] Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. doi:10.1177/002224378101800104.
[112] Jr., J. F. H., Matthews, L. M., Matthews, R. L., & Sarstedt, M. (2017). PLS-SEM or CB-SEM: updated guidelines on which method to use. International Journal of Multivariate Data Analysis, 1(2), 107. doi:10.1504/ijmda.2017.087624.
[113] Du, Y., & Kim, P. H. (2021). One size does not fit all: Strategy configurations, complex environments, and new venture performance in emerging economies. Journal of Business Research, 124, 272–285. doi:10.1016/j.jbusres.2020.11.059.
[114] Ragin, C. C. (2009). Redesigning social inquiry: Fuzzy sets and beyond. University of Chicago press, Chicago, United States.
[115] Crespo, N. F., Rodrigues, R., Samagaio, A., & Silva, G. M. (2019). The adoption of management control systems by start-ups: Internal factors and context as determinants. Journal of Business Research, 101, 875–884. doi:10.1016/j.jbusres.2018.11.020.
[116] Ragin, C. C. (2008). What is qualitative comparative analysis? Paper presented at the NCRM Research Methods Festival, Oxford, United Kingdom.
[117] Rihoux, B., & Ragin, C. (2009). Configurational Comparative Methods: Qualitative Comparative Analysis (QCA) and Related Techniques. Sage Publications, Thousand Oaks, United States. doi:10.4135/9781452226569.
[118] Garrido-Moreno, A., Martín-Rojas, R., & García-Morales, V. J. (2024). The key role of innovation and organizational resilience in improving business performance: A mixed-methods approach. International Journal of Information Management, 77. doi:10.1016/j.ijinfomgt.2024.102777.
[119] Rathnayaka, B., Robert, D., Siriwardana, C., Adikariwattage, V. V., Pasindu, H. R., Setunge, S., & Amaratunga, D. (2023). Identifying and prioritizing climate change adaptation measures in the context of electricity, transportation and water infrastructure: A case study. International Journal of Disaster Risk Reduction, 99. doi:10.1016/j.ijdrr.2023.104093.
[120] Bocchini, P., Frangopol, D. M., Ummenhofer, T., & Zinke, T. (2014). Resilience and Sustainability of Civil Infrastructure: Toward a Unified Approach. Journal of Infrastructure Systems, 20(2), 04014004. doi:10.1061/(asce)is.1943-555x.0000177.
[121] Argyroudis, S. A., Mitoulis, S. A., Hofer, L., Zanini, M. A., Tubaldi, E., & Frangopol, D. M. (2020). Resilience assessment framework for critical infrastructure in a multi-hazard environment: Case study on transport assets. Science of the Total Environment, 714. doi:10.1016/j.scitotenv.2020.136854.
[122] Liang, L., & Li, Y. (2024). How does organizational resilience promote firm growth? The mediating role of strategic change and managerial myopia. Journal of Business Research, 177. doi:10.1016/j.jbusres.2024.114636.
[123] Xi, M., Liu, Y., Fang, W., & Feng, T. (2024). Intelligent manufacturing for strengthening operational resilience during the COVID-19 pandemic: A dynamic capability theory perspective. International Journal of Production Economics, 267. doi:10.1016/j.ijpe.2023.109078.
[124] Xue, C., & Wang, J. (2024). Proactive boundary-spanning search, organizational resilience, and radical green innovation. Business Strategy and the Environment, 33(3), 1834–1852. doi:10.1002/bse.3576.
[125] Jiang, Z., Shi, J., & Liu, Z. (2025). Digitalization and productivity in the Chinese wind power industry: the serial mediating role of reconfiguration capability and technological innovation. Business Process Management Journal, 31(1), 26–53. doi:10.1108/BPMJ-12-2023-0943.
[126] Ivanov, D., Dolgui, A., & Sokolov, B. (2022). Cloud supply chain: Integrating Industry 4.0 and digital platforms in the “Supply Chain-as-a-Service.” Transportation Research Part E: Logistics and Transportation Review, 160, 102676. doi:10.1016/j.tre.2022.102676.
[127] Liu, F., & Zhang, L. (2025). The role of digital resilient agility: how digital capability incompatibility affects knowledge cooperation performance in project network organizations. Journal of Knowledge Management, 29(1), 25–48. doi:10.1108/JKM-11-2023-1067.
[128] Guo, H., Shen, Z., Chen, Y., & Dong, M. (2025). Analyzing the impact of government R&D subsidy and digital transformation on supply chain risk dynamics management and firm performance in the China’s chip industry. International Journal of Production Economics, 281. doi:10.1016/j.ijpe.2025.109524.
[129] Bach, T. N., Hoang, K., & Le, T. (2024). Biodiversity risk and firm performance. Business Strategy and the Environment 34(1), 1113-1132. doi:10.2139/ssrn.4735012.
[130] Kareem, S., Fehrer, J. A., Shalpegin, T., & Stringer, C. (2025). Navigating tensions of sustainable supply chains in times of multiple crises: A systematic literature review. Business Strategy and the Environment, 34(1), 316–337. doi:10.1002/bse.3990.
[131] Napier, E., Liu, S. Y. H., & Liu, J. (2024). Adaptive strength: Unveiling a multilevel dynamic process model for organizational resilience. Journal of Business Research, 171. doi:10.1016/j.jbusres.2023.114334.
[132] Wu, H., Li, G., & Zheng, H. (2024). How Does Digital Intelligence Technology Enhance Supply Chain Resilience? Sustainable Framework and Agenda. Annals of Operations Research, 1-23. doi:10.1007/s10479-024-06104-3.
[133] El Baz, J., & Ruel, S. (2024). Achieving social performance through digitalization and supply chain resilience in the COVID-19 disruption era: An empirical examination based on a stakeholder dynamic capabilities view. Technological Forecasting and Social Change, 201. doi:10.1016/j.techfore.2024.123209.
[134] Shao, Z. (2024). From human to virtual: Unmasking consumer switching intentions to virtual influencers by an integrated fsQCA and NCA method. Journal of Retailing and Consumer Services, 78. doi:10.1016/j.jretconser.2024.103715.
[135] Dul, J. (2024). A different causal perspective with Necessary Condition Analysis. Journal of Business Research, 177. doi:10.1016/j.jbusres.2024.114618.
- This work (including HTML and PDF Files) is licensed under a Creative Commons Attribution 4.0 International License.



















