Factors affecting the supply chain resilience and supply chain performance: an empirical investigation
Keywords:
Adaptive capability, Artificial intelligence, Supply chain collaboration, Supply chain performance, Supply chain resilienceAbstract
The key objective of this research study is to delve into the factors affecting supply chain resilience to enhance supply chain performance through the mediation of supply chain resilience. A quantitative method of research was applied to perform this particular research. Data collection was performed using the questionnaire technique. As it was impossible to collect data from every member of the targeted population, a sample of data was calculated using G*power software and a sample size of 129 respondents. It was concluded that supply chain artificial intelligence, adaptive capability, and collaboration positively and significantly influence supply chain resilience and performance. At the same time, supply chain resilience also positively impacts supply chain performance. Thus, adopting resilience and other dynamic capacities can enhance organizational and supply chain performance. This research study provides insight to the manufacturing firms' practitioners and managers for improving their resilience level in the supply chain. This specific research study plays a significant role in literature by highlighting the concept of supply chain resilience and the supply chain performance of organizations.
References
Adhikari, A., & Bisi, A. (2020). Collaboration, bargaining, and fairness concern for a green apparel supply chain: An emerging economy perspective. Transportation Research Part E: Logistics and Transportation Review, 135, 101863. https://doi.org/10.1016/j.tre.2020.101863
Adobor, H. (2020). Supply chain resilience: an adaptive cycle approach. The International Journal of Logistics Management, 31(3), 443–463. https://doi.org/10.1108/ijlm-01-2020-0019
Agyabeng-Mensah, Y., Ahenkorah, E., Afum, E., Nana Agyemang, A., Agnikpe, C., & Rogers, F. (2020). Examining the influence of internal green supply chain practices, green human resource management and supply chain environmental cooperation on firm performance. Supply Chain Management: An International Journal, 25(5), 585-599. https://doi.org/10.1108/scm-11-2019-0405
Akter, S., Michael, K., Uddin, M. R., McCarthy, G., & Rahman, M. (2020). Transforming business using digital innovations: the application of AI, blockchain, cloud and data analytics. Annals of Operations Research, 308(1). https://doi.org/10.1007/s10479-020-03620-w
Al-Doori, J. A. (2019). The impact of supply chain collaboration on performance in automotive industry: Empirical evidence. Journal of Industrial Engineering and Management, 12(2), 241. https://doi.org/10.3926/jiem.2835
Ali, A., & Haseeb, M. (2019). Radio frequency identification (RFID) technology as a strategic tool towards higher performance of supply chain operations in textile and apparel industry of Malaysia. Uncertain Supply Chain Management, 7(2), 215–226. https://doi.org/10.5267/j.uscm.2018.10.004
Alrazehi, H. A. A. W., Amirah, N. A., Emam, A. S., & Hashmi, A. R. (2021). Proposed model for entrepreneurship, organizational culture and job satisfaction towards organizational performance in International Bank of Yemen. International Journal of Management and Human Science, 5(1), 1-9. https://ejournal.lucp.net/index.php/ijmhs/article/view/1330/1399
Alzoubi, H. M., Ahmed, G., Al-Gasaymeh, A., & Al Kurdi, B. (2020). Empirical study on sustainable supply chain strategies and its impact on competitive priorities: The mediating role of supply chain collaboration. Management Science Letters, 10(3), 703–708. https://doi.org/10.5267/j.msl.2019.9.008
Appelbaum, S. H., Calla, R., Desautels, D., & Hasan, L. (2017). The challenges of organizational agility (part 1). Industrial and Commercial Training, 49(1), 6–14. https://doi.org/10.1108/ict-05-2016-0027
Asiamah, N., Mensah, H., & Oteng-Abayie, E. F. (2017). General, Target, and Accessible Population: Demystifying the Concepts for Effective Sampling. The Qualitative Report, 22(6), 1607–1621. https://doi.org/10.46743/2160-3715/2017.2674
Baloch, N. & Rashid, A. (2022). Supply Chain Networks, Complexity, and Optimization in Developing Economies: A Systematic Literature Review and Meta-Analysis. South Asian Journal of Operations and Logistics, 1(1), 1-13. https://doi.org/10.57044/SAJOL.2022.1.1.2202
Baryannis, G., Validi, S., Dani, S., & Antoniou, G. (2018). Supply Chain Risk Management and Artificial intelligence: State of the Art and Future Research Directions. International Journal of Production Research, 57(7), 1–24. https://doi.org/10.1080/00207543.2018.1530476
Basheer, M. F., Siam, M. R. A., Awn, A. M., & Hussan, S. G. (2019). Exploring the role of TQM and supply chain practices for firm supply performance in the presence of information technology capabilities and supply chain technology adoption: A case of textile firms in Pakistan. Uncertain Supply Chain Management, 7(2), 275–288. https://doi.org/10.5267/j.uscm.2018.9.001
Belhadi, A., Kamble, S. S., Zkik, K., Cherrafi, A., & El fezazi, S. (2019). The integrated effect of big data analytics, lean six sigma, and green manufacturing on the environmental performance of manufacturing companies: The case of North Africa. Journal of Cleaner Production, 119903. https://doi.org/10.1016/j.jclepro.2019.119903
Belhadi, A., Mani, V., Kamble, S. S., Khan, S. A. R., & Verma, S. (2021). Artificial intelligence-driven innovation for enhancing supply chain resilience and performance under the effect of supply chain dynamism: an empirical investigation. Annals of Operations Research. Springer. https://doi.org/10.1007/s10479-021-03956-x
Bottani, E., Centobelli, P., Gallo, M., Kaviani, M. A., Jain, V., & Murino, T. (2019). Modelling wholesale distribution operations: an artificial intelligence framework. Industrial Management & Data Systems, 119(4), 698–718. https://doi.org/10.1108/imds-04-2018-0164
Busse, C., Schleper, M. C., Niu, M., & Wagner, S. M. (2016). Supplier development for sustainability: contextual barriers in global supply chains. International Journal of Physical Distribution & Logistics Management, 46(5), 442–468. https://doi.org/10.1108/ijpdlm-12-2015-0300
Chaudhuri, A., Boer, H., & Taran, Y. (2018). Supply chain integration, risk management and manufacturing flexibility. International Journal of Operations & Production Management, 38(3), 690–712. https://doi.org/10.1108/ijopm-08-2015-0508
Cheng, J.-H., & Lu, K.-L. (2017). Enhancing effects of supply chain resilience: insights from trajectory and resource-based perspectives. Supply Chain Management: An International Journal, 22(4), 329–340. https://doi.org/10.1108/scm-06-2016-0190
Choi, T.-M. (2020). Innovative “Bring-Service-Near-Your-Home” operations under Corona-Virus (COVID-19/SARS-CoV-2) outbreak: Can logistics become the Messiah?. Transportation Research Part E: Logistics and Transportation Review, 140, 101961. https://doi.org/10.1016/j.tre.2020.101961
Chowdhury, M. M. H., Quaddus, M., & Agarwal, R. (2019). Supply chain resilience for performance: role of relational practices and network complexities. Supply Chain Management: An International Journal, 24(5), 659–676. https://doi.org/10.1108/scm-09-2018-0332
Christopher, M., Lowson, R., & Peck, H. (2004). Creating agile supply chains in the fashion industry. International Journal of Retail & Distribution Management, 32(8), 367–376. https://doi.org/10.1108/09590550410546188
Das, S., Ghani, M., Rashid, A., Rasheed, R., Manthar, S., & Ahmed, S. (2021). How customer satisfaction and loyalty can be affected by employee’s perceived emotional competence: The mediating role of rapport. International Journal of Management, 12(3), 1268-1277. https://doi.org/10.34218/IJM.12.3.2021.119
Dhamija, P., & Bag, S. (2020). Role of artificial intelligence in operations environment: a review and bibliometric analysis. The TQM Journal, 32(4), 869–896. https://doi.org/10.1108/tqm-10-2019-0243
Dolgui, A., & Ivanov, D. (2021). Ripple effect and supply chain disruption management: new trends and research directions. International Journal of Production Research, 59(1), 102–109. https://doi.org/10.1080/00207543.2021.1840148
Dovers, S. R., & Handmer, J. W. (1992). Uncertainty, sustainability and change. Global Environmental Change, 2(4), 262–276. https://doi.org/10.1016/0959-3780(92)90044-8
Dubey, R., Gunasekaran, A., Childe, S. J., & Papadopoulos, T. (2018). Skills needed in supply chain-human agency and social capital analysis in third party logistics. Management Decision, 56(1), 143–159. https://doi.org/10.1108/md-04-2017-0428
Dubey, R., Gunasekaran, A., Childe, S. J., Bryde, D. J., Giannakis, M., Foropon, C., Roubaud, D., & Hazen, B. T. (2019). Big data analytics and artificial intelligence pathway to operational performance under the effects of entrepreneurial orientation and environmental dynamism: A study of manufacturing organizations. International Journal of Production Economics, 226, 107599. https://doi.org/10.1016/j.ijpe.2019.107599
Duong, L. N. K., & Chong, J. (2020). Supply chain collaboration in the presence of disruptions: a literature review. International Journal of Production Research, 58(11), 1–20. https://doi.org/10.1080/00207543.2020.1712491
Dwivedi, Y. K., Hughes, L., Ismagilova, E., Aarts, G., Coombs, C., Crick, T., Duan, Y., Dwivedi, R., Edwards, J., Eirug, A., Galanos, V., Ilavarasan, P. V., Janssen, M., Jones, P., Kar, A. K., Kizgin, H., Kronemann, B., Lal, B., Lucini, B., & Medaglia, R. (2019). Artificial Intelligence (AI): Multidisciplinary Perspectives on Emerging challenges, opportunities, and Agenda for research, Practice and Policy. International Journal of Information Management, 57(101994). https://doi.org/10.1016/j.ijinfomgt.2019.08.002
Eisenhardt, K. M., & Martin, J. A. (2000). Dynamic capabilities: what are they? Strategic Management Journal, 21(10-11), 1105–1121. https://doi.org/10.1002/1097-0266(200010/11)21:10/11<1105::AID-SMJ133>3.0.CO;2-E
Eshima, Y., & Anderson, B. S. (2016). Firm growth, adaptive capability, and entrepreneurial orientation. Strategic Management Journal, 38(3), 770–779. https://doi.org/10.1002/smj.2532
Fattahi, M., Govindan, K., & Maihami, R. (2020). Stochastic optimization of disruption-driven supply chain network design with a new resilience metric. International Journal of Production Economics, 230, 107755. https://doi.org/10.1016/j.ijpe.2020.107755
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/brm.41.4.1149
Fornell, C., & Larcker, D. F. (1981). Evaluating Structural Equation Models with Unobservable Variables and Measurement Error. Journal of Marketing Research, 18(1), 39–50. https://doi.org/10.1177/002224378101800104
Forza, C., & Salvador, F. (2001). Information flows for high-performance manufacturing. International Journal of Production Economics, 70(1), 21–36. https://doi.org/10.1016/s0925-5273(00)00038-4
Gligor, D., Gligor, N., Holcomb, M., & Bozkurt, S. (2019). Distinguishing between the concepts of supply chain agility and resilience. The International Journal of Logistics Management, 30(2), 467–487. https://doi.org/10.1108/ijlm-10-2017-0259
Gölgeci, I., & Kuivalainen, O. (2019). Does social capital matter for supply chain resilience? The role of absorptive capacity and marketing-supply chain management alignment. Industrial Marketing Management, 84. https://doi.org/10.1016/j.indmarman.2019.05.006
Govindan, K., Azevedo, S. G., Carvalho, H., & Cruz-Machado, V. (2013). Lean, green and resilient practices influence on supply chain performance: interpretive structural modeling approach. International Journal of Environmental Science and Technology, 12(1), 15–34. https://doi.org/10.1007/s13762-013-0409-7
Green, K. W., Inman, R. A., Brown, G., & Hillman Willis, T. (2005). Market orientation: relation to structure and performance. Journal of Business & Industrial Marketing, 20(6), 276–284. https://doi.org/10.1108/08858620510618110
Grover, P., Kar, A. K., & Dwivedi, Y. K. (2020). Understanding artificial intelligence adoption in operations management: insights from the review of academic literature and social media discussions. Annals of Operations Research, 308. https://doi.org/10.1007/s10479-020-03683-9
Hair, J. F., Black, W. C., & Babin, B. J. (2019). Multivariate data analysis. Cengage Learning Emea.
Hair, J., Anderson, R., Black, B., & Babin, B. (2016). Multivariate Data Analysis. Pearson Higher Ed.
Ham, Y.-G., Kim, J.-H., & Luo, J.-J. (2019). Deep learning for multi-year ENSO forecasts. Nature, 573(7775), 568–572. https://doi.org/10.1038/s41586-019-1559-7
Haque, I., Rashid, A., & Ahmed, S. Z. (2021). The Role of Automobile Sector in Global Business: Case of Pakistan. Pakistan Journal of International Affairs, 4(2), 363-383. https://doi.org/10.52337/pjia.v4i2.195
Hashmi, A. (2022). Factors affecting the supply chain resilience and supply chain performance. South Asian Journal of Operations and Logistics, 1(2), 65-85. https://doi.org/10.57044/SAJOL.2022.1.2.2212
Hashmi, A. R., & Mohd, A. T. (2020). The effect of disruptive factors on inventory control as a mediator and organizational performance in health department of Punjab, Pakistan. International Journal of Sustainable Development & World Policy, 9(2), 122-134. https://doi.org/10.18488/journal.26.2020.92.122.134
Hashmi, A. R., Amirah, N. A., & Yusof, Y. (2020a). Mediating effect of integrated systems on the relationship between supply chain management practices and public healthcare performance: Structural Equation Modeling. International Journal of Management and Sustainability, 9(3), 148-160. https://doi.org/10.18488/journal.11.2020.93.148.160
Hashmi, A. R., Amirah, N. A., & Yusof, Y. (2021b). Organizational performance with disruptive factors and inventory control as a mediator in public healthcare of Punjab, Pakistan. Management Science Letters, 11(1), 77-86. https://doi.org/10.5267/j.msl.2020.8.028
Hashmi, A. R., Amirah, N. A., Yusof, Y., & Zaliha, T. N. (2020b). Exploring the dimensions using exploratory factor analysis of disruptive factors and inventory control. The Economics and Finance Letters, 7(2), 247-254. https://doi.org/10.18488/journal.29.2020.72.247.254
Hashmi, A. R., Amirah, N. A., Yusof, Y., & Zaliha, T. N. (2021a). Mediation of inventory control practices in proficiency and organizational performance: State-funded hospital perspective. Uncertain Supply Chain Management, 9(1), 89-98. https://doi.org/10.5267/j.uscm.2020.11.006
Hashmi, R. (2023). Business Performance Through Government Policies, Green Purchasing, and Reverse Logistics: Business Performance and Green Supply Chain Practices. South Asian Journal of Operations and Logistics, 2(1), 1–10. https://doi.org/10.57044/SAJOL.2023.2.1.2301
Hendry, L. C., Stevenson, M., MacBryde, J., Ball, P., Sayed, M., & Liu, L. (2019). Local food supply chain resilience to constitutional change: the Brexit effect. International Journal of Operations & Production Management, 39(3), 429–453. https://doi.org/10.1108/IJOPM-03-2018-0184
Huang, M.-H., & Rust, R. T. (2020). Engaged to a Robot? The Role of AI in Service. Journal of Service Research, 24(1), 109467052090226. https://doi.org/10.1177/1094670520902266
Huin, S. F., Luong, L. H. S., & Abhary, K. (2003). Knowledge-based tool for planning of enterprise resources in ASEAN SMEs. Robotics and Computer-Integrated Manufacturing, 19(5), 409–414. https://doi.org/10.1016/s0736-5845(02)00033-9
Jadhav, A., Orr, S., & Malik, M. (2018). The role of supply chain orientation in achieving supply chain sustainability. International Journal of Production Economics, 217. https://doi.org/10.1016/j.ijpe.2018.07.031
Jain, V., Kumar, S., Soni, U., & Chandra, C. (2017). Supply chain resilience: model development and empirical analysis. International Journal of Production Research, 55(22), 6779–6800. https://doi.org/10.1080/00207543.2017.1349947
Jüttner, U., & Maklan, S. (2011). Supply chain resilience in the global financial crisis: an empirical study. Supply Chain Management: An International Journal, 16(4), 246–259. https://doi.org/10.1108/13598541111139062
Khan, S. K., Ahmed, S., & Rashid, A. (2021). Influence of social media on purchase intention and customer loyalty of generation Y with the mediating effect of conviction: a case of Pakistan. Pakistan Journal of International Affairs, 4(2), 526-548. https://doi.org/10.52337/pjia.v4i2.207
Khan, S. K., Rashid. A., Benhamed, A., Rasheed, R., & Huma, Z. (2023). Effect of leadership styles on employee performance by considering psychological capital as mediator: evidence from airlines industry in emerging economy. World Journal of Entrepreneurship, Management and Sustainable Development, 18(6), 799-818. https://doi.org/10.47556/J.WJEMSD.18.6.2022.7
Khan, S., Rasheed., R., Rashid, A., Abbas, Q., & Mahboob, F. (2022b). The Effect of Demographic Characteristics on Job Performance: An Empirical Study from Pakistan. Journal of Asian Finance, Economics and Business, 9(2), 283-294. https://doi.org/10.13106/JAFEB.2022.VOL9.NO2.0283
Khan, S., Rashid, A., Rasheed, R., & Amirah, N. A. (2022a). Designing a knowledge-based system (KBS) to study consumer purchase intention: the impact of digital influencers in Pakistan. Kybernetes, 52(5), 1720-1744. https://doi.org/10.1108/K-06-2021-0497
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. https://doi.org/10.1108/ijpdlm-02-2017-0099
Koçyiğit, Y., & Akkaya, B. (2020). The Role of Organizational Flexibility in Organizational Agility: A Research on SMEs. Business Management and Strategy, 11(1), 110. https://doi.org/10.5296/bms.v11i1.16867
Kraus, S., Azaria, A., Fiosina, J., Greve, M., Hazon, N., Kolbe, L., Lembcke, T.-B., Muller, J. P., Schleibaum, S., & Vollrath, M. (2020). AI for Explaining Decisions in Multi-Agent Environments. Proceedings of the AAAI Conference on Artificial Intelligence, 34(09), 13534–13538. https://doi.org/10.1609/aaai.v34i09.7077
Kwak, D.-W., Seo, Y.-J., & Mason, R. (2018). Investigating the relationship between supply chain innovation, risk management capabilities and competitive advantage in global supply chains. International Journal of Operations & Production Management, 38(1), 2–21. https://doi.org/10.1108/ijopm-06-2015-0390
Lai, C.-C., Shih, T.-P., Ko, W.-C., Tang, H.-J., & Hsueh, P.-R. (2020). Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) and coronavirus disease-2019 (COVID-19): The epidemic and the challenges. International Journal of Antimicrobial Agents, 55(3), 105924. https://doi.org/10.1016/j.ijantimicag.2020.105924
Lee, S. M., & Rha, J. S. (2016). Ambidextrous supply chain as a dynamic capability: building a resilient supply chain. Management Decision, 54(1), 2–23. https://doi.org/10.1108/md-12-2014-0674
Leitão, P. (2009). Agent-based distributed manufacturing control: A state-of-the-art survey. Engineering Applications of Artificial Intelligence, 22(7), 979–991. https://doi.org/10.1016/j.engappai.2008.09.005
Li, P., Xiao, X., & Seekamp, E. (2022). Climate adaptation planning for cultural heritages in coastal tourism destinations: A multi-objective optimization approach. Tourism Management, 88, 104380. https://doi.org/10.1016/j.tourman.2021.104380
Lopes de Sousa Jabbour, A. B., Chiappetta Jabbour, C. J., Hingley, M., Vilalta-Perdomo, E. L., Ramsden, G., & Twigg, D. (2020). Sustainability of supply chains in the wake of the coronavirus (COVID-19/SARS-CoV-2) pandemic: lessons and trends. Modern Supply Chain Research and Applications, 2(3). https://doi.org/10.1108/mscra-05-2020-0011
Macías-Escrivá, F. D., Haber, R., del Toro, R., & Hernandez, V. (2013). Self-adaptive systems: A survey of current approaches, research challenges and applications. Expert Systems with Applications, 40(18), 7267–7279. https://doi.org/10.1016/j.eswa.2013.07.033
Moore, G. C., & Benbasat, I. (1991). Development of an Instrument to Measure the Perceptions of Adopting an Information Technology Innovation. Information Systems Research, 2(3), 192–222. https://doi.org/10.1287/isre.2.3.192
Ojha, D., Struckell, E., Acharya, C., & Patel, P. C. (2018). Supply chain organizational learning, exploration, exploitation, and firm performance: A creation-dispersion perspective. International Journal of Production Economics, 204, 70–82. https://doi.org/10.1016/j.ijpe.2018.07.025
Olivares-Aguila, J., & ElMaraghy, W. (2020). System dynamics modelling for supply chain disruptions. International Journal of Production Research, 1–19. https://doi.org/10.1080/00207543.2020.1725171
Park, S., & Park, S. (2020). How Can Employees Adapt to change? Clarifying the Adaptive Performance Concepts. Human Resource Development Quarterly, 32(1). https://doi.org/10.1002/hrdq.21411
Paschen, U., Pitt, C., & Kietzmann, J. (2019). Artificial intelligence: Building blocks and an innovation typology. Business Horizons, 63(2). https://doi.org/10.1016/j.bushor.2019.10.004
Patel, S., Srivastava, S., Singh, M. R., & Singh, D. (2018). Preparation and optimization of chitosan-gelatin films for sustained delivery of lupeol for wound healing. International Journal of Biological Macromolecules, 107, 1888–1897. https://doi.org/10.1016/j.ijbiomac.2017.10.056
Pettit, T. J., Croxton, K. L., & Fiksel, J. (2019). The Evolution of Resilience in Supply Chain Management: A Retrospective on Ensuring Supply Chain Resilience. Journal of Business Logistics, 40(1), 56–65. https://doi.org/10.1111/jbl.12202
Ponomarov, S. Y., & Holcomb, M. C. (2009). Understanding the concept of supply chain resilience. The International Journal of Logistics Management, 20(1), 124–143. https://doi.org/10.1108/09574090910954873
Queiroz, M. M., Ivanov, D., Dolgui, A., & Fosso Wamba, S. (2020). Impacts of Epidemic Outbreaks on Supply chains: Mapping a Research Agenda amid the COVID-19 Pandemic through a Structured Literature Review. Annals of Operations Research, 319. https://doi.org/10.1007/s10479-020-03685-7
Rasheed, R., & Rashid, R. (2023). Role of service quality factors in word of mouth through student satisfaction. Kybernetes, In press. http://dx.doi.org/10.1108/k-01-2023-0119
Rasheed, R., Rashid, A., Amirah, N. A., & Afthanorhan, A. (2023). Quantifying the moderating effect of servant leadership between occupational stress and employee in-role and extra-role performance. Calitatea, 24(195), 60-68. https://doi.org/10.47750/QAS/24.195.08
Rashid, A. & Rasheed, R. (2022). A Paradigm for Measuring Sustainable Performance Through Big Data Analytics–Artificial Intelligence in Manufacturing Firms. Available at SSRN 4087758. https://doi.org/10.2139/ssrn.4087758
Rashid, A. (2016). Impact of inventory management in downstream chains on customer satisfaction at manufacturing firms. International Journal of Management, IT and Engineering, 6(6), 1-19.
Rashid, A., & Amirah, N. A. (2017). Relationship between poor documentation and efficient inventory control at Provincial Ministry of Health, Lahore. American Journal of Innovative Research and Applied Sciences, 5(6), 420-423.
Rashid, A., & Rasheed, R. (2023). Mediation of inventory management in the relationship between knowledge and firm performance. SAGE Open, 13(2), 1-11. https://doi.org/10.1177/21582440231164593
Rashid, A., Ali, S. B., Rasheed, R., Amirah, N. A. & Ngah, A. H. (2022a). A paradigm of blockchain and supply chain performance: a mediated model using structural equation modeling. Kybernetes, 52(12), 6163-6178. https://doi.org/10.1108/K-04-2022-0543
Rashid, A., Amirah, N. A., & Yusof, Y. (2019). Statistical approach in exploring factors of documentation process and hospital performance: a preliminary study. American Journal of Innovative Research and Applied Sciences, 9(4), 306-310.
Rashid, A., Amirah, N. A., Yusof, Y., & Mohd, A. T. (2020). Analysis of demographic factors on perceptions of inventory managers towards healthcare performance. The Economics and Finance Letters, 7(2), 289-294. https://doi.org/10.18488/journal.29.2020.72.289.294
Rashid, A., Rasheed, R., & Amirah, N. A. (2023b). Information technology and people involvement in organizational performance through supply chain collaboration. Journal of Science and Technology Policy Management, In press. https://doi.org/10.1108/JSTPM-12-2022-0217
Rashid, A., Rasheed, R., & Amirah, N. A., & Afthanorhan, A. (2022b). Disruptive factors and customer satisfaction at chain stores in Karachi, Pakistan. Journal of Distribution Science, 20(10), 93-103. https://doi.org/10.15722/jds.20.10.202210.93
Rashid, A., Rasheed, R., & Ngah, A. H. (2023a). Achieving Sustainability through Multifaceted Green Functions in Manufacturing. Journal of Global Operations and Strategic Sourcing, In press. https://doi.org/10.1108/JGOSS-06-2023-0054
Rashid, A., Rasheed, R., Amirah, N. A., Yusof, Y., Khan, S., & Agha, A., A. (2021). A Quantitative Perspective of Systematic Research: Easy and Step-by-Step Initial Guidelines. Turkish Online Journal of Qualitative Inquiry, 12(9), 2874-2883. https://www.tojqi.net/index.php/journal/article/view/6159/4387
Sá, M. M. de, Miguel, P. L. de S., Brito, R. P. de, & Pereira, S. C. F. (2019). Supply chain resilience: the whole is not the sum of the parts. International Journal of Operations & Production Management, 40(1), 92–115. https://doi.org/10.1108/ijopm-09-2017-0510
Salvador, F., Forza, C., & Rungtusanatham, M. (2002). Modularity, product variety, production volume, and component sourcing: theorizing beyond generic prescriptions. Journal of Operations Management, 20(5), 549–575. https://doi.org/10.1016/s0272-6963(02)00027-x
Schaltegger, S., & Burritt, R. (2014). Measuring and managing sustainability performance of supply chains. Supply Chain Management: An International Journal, 19(3), 232–241. https://doi.org/10.1108/scm-02-2014-0061
Schniederjans, D. G., Curado, C., & Khalajhedayati, M. (2019). Supply chain digitization trends: An integration of knowledge management. International Journal of Production Economics, 220, 107439. Sciencedirect. https://doi.org/10.1016/j.ijpe.2019.07.012
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: An International Journal, 24(3), 430–442. https://doi.org/10.1108/scm-05-2018-0186
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. https://doi.org/10.1016/j.emj.2011.02.004
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. https://doi.org/10.1111/poms.12746
Tarafdar, M., & Qrunfleh, S. (2016). Agile supply chain strategy and supply chain performance: complementary roles of supply chain practices and information systems capability for agility. International Journal of Production Research, 55(4), 925–938. https://doi.org/10.1080/00207543.2016.1203079
Tarigan, Z. J. H., Siagian, H., & Jie, F. (2021). Impact of Internal Integration, Supply Chain Partnership, Supply Chain Agility, and Supply Chain Resilience on Sustainable Advantage. Sustainability, 13(10), 5460. https://doi.org/10.3390/su13105460
Teece, D. J., Pisano, G., & Shuen, A. (1997). Dynamic Capabilities and Strategic Management. Strategic Management Journal, 18(7), 509–533. https://www.jstor.org/stable/3088148
Toorajipour, R., Sohrabpour, V., Nazarpour, A., Oghazi, P., & Fischl, M. (2021). Artificial intelligence in supply chain management: A systematic literature review. Journal of Business Research, 122(1), 502–517. Sciencedirect. https://doi.org/10.1016/j.jbusres.2020.09.009
Treleaven, P., & Bogdan Batrinca. (2017). Algorithmic Regulation: Automating Financial Compliance Monitoring and Regulation Using AI and Blockchain. Journal of Financial Transformation, 45, 14–21.
Um, J., Lyons, A., Lam, H. K. S., Cheng, T. C. E., & Dominguez-Pery, C. (2017). Product variety management and supply chain performance: A capability perspective on their relationships and competitiveness implications. International Journal of Production Economics, 187, 15–26. https://doi.org/10.1016/j.ijpe.2017.02.005
Um, K.-H., & Oh, J.-Y. (2020). The interplay of governance mechanisms in supply chain collaboration and performance in buyer–supplier dyads: substitutes or complements. International Journal of Operations & Production Management, 40(4), 415–438. https://doi.org/10.1108/ijopm-07-2019-0507
Wang, C., & Hu, Q. (2017). Knowledge sharing in supply chain networks: Effects of collaborative innovation activities and capability on innovation performance. Technovation, 94-95, 102010. https://doi.org/10.1016/j.technovation.2017.12.002
Wen, J., He, L., & Zhu, F. (2018). Swarm Robotics Control and Communications: Imminent Challenges for Next Generation Smart Logistics. IEEE Communications Magazine, 56(7), 102–107. https://doi.org/10.1109/mcom.2018.1700544
Wollschlaeger, M., Sauter, T., & Jasperneite, J. (2017). The Future of Industrial Communication: Automation Networks in the Era of the Internet of Things and Industry 4.0. IEEE Industrial Electronics Magazine, 11(1), 17–27. https://doi.org/10.1109/mie.2017.2649104
Wong, C. W. Y., Lirn, T.-C., Yang, C.-C., & Shang, K.-C. (2020). Supply chain and external conditions under which supply chain resilience pays: An organizational information processing theorization. International Journal of Production Economics, 226, 107610. https://doi.org/10.1016/j.ijpe.2019.107610
Yang, B., & Burns, N. (2003). Implications of postponement for the supply chain. International Journal of Production Research, 41(9), 2075–2090. https://doi.org/10.1080/00207544031000077284
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. https://doi.org/10.1016/j.ijpe.2019.07.013
Published
How to Cite
Issue
Section
Copyright (c) 2023 South Asian Journal of Operations and Logistics
This work is licensed under a Creative Commons Attribution 4.0 International License.