How to cite this paper
APA: Javed, K., Qiao, Z & Wanga, J. (2027). Blockchain adoption and agri-food supply chain performance in Pakistan: The mediating role of transparency and the moderating effect of IoT. Uncertain Supply Chain Management, 15(1), 1-14.
Chicago/Turabian: Javed, K., Qiao, Z & Wanga, J. 2027. "Blockchain adoption and agri-food supply chain performance in Pakistan: The mediating role of transparency and the moderating effect of IoT." Uncertain Supply Chain Management 15, no. 1 (2027): 1-14.
AMA: Javed, K., Qiao, Z & Wanga, J. Blockchain adoption and agri-food supply chain performance in Pakistan: The mediating role of transparency and the moderating effect of IoT. Uncertain Supply Chain Management. 2027;15(1):1-14.
References
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Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002
Ali, M. H., Chung, L., Kumar, Zailani, S., Tan, & K. H. (2021). A sustainable Blockchain framework for the halal food supply chain: Lessons from Malaysia . Technological Forecasting and Social Change, 170.
Ali, S. S., Jalil, S. A., Kamal, M., & Rameshwar, R. (2024). Amplifying swift-trust, collaboration, and teamwork in warehouse management through blockchain-enabled technology. Supply Chain Analytics, 8. https://doi.org/10.1016/j.sca.2024.100089
Armstrong, J. S. , & O. T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 3–14.
Aslam, J., Saleem, A., Khan, N. T., & Kim, Y. B. (2021). Factors influencing blockchain adoption in supply chain management practices: A study based on the oil industry. Journal of Innovation and Knowledge, 6(2), 124–134. https://doi.org/10.1016/j.jik.2021.01.002
Azizi, N., Malekzadeh, H., Akhavan, P., Haass, O., Saremi, S., & Mirjalili, S. (2021). IoT–blockchain: Harnessing the power of internet of thing and blockchain for smart supply chain. Sensors, 21(18). https://doi.org/10.3390/s21186048
Bagozzi, R. P., Fornell, C., & Larcker, D. F. (1981). Canonical correlation-analysis as a special case of a structural relations model. Multivariate Behav. Res., 16(4), 437–457.
Ball, C. (2009). What Is Transparency? Public Integrity, 11(4), 293–308. https://doi.org/10.2753/PIN1099-9922110400
Baralla, G., Ibba, S., Marchesi, M., Tonelli, R., & Missineo, S. (2019). A blockchain based system to ensure transparency and reliability in food supply chain. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11339 LNCS, 379–391. https://doi.org/10.1007/978-3-030-10549-5_30
Basana, S. R., Malelak, M. I., Suprapto, W., Siagian, H., & Tarigan, Z. J. H. (2024). The impact of SCM integration on business performance through information sharing, quality integration and innovation system. Uncertain Supply Chain Management, 12(1), 435–448. https://doi.org/10.5267/j.uscm.2023.9.008
Buell, R. W., Kim, T., & Tsay, C. J. (2016). Creating Reciprocal Value Through Operational Transparency. Https://Doi.Org/10.1287/Mnsc.2015.2411, 63(6), 1673–1695. https://doi.org/10.1287/MNSC.2015.2411
Clark, D. H. , and W. Reed. (2005). The Strategic Sources of Foreign Policy Substitution. American Journal of Political Science, 609–624.
Crosby Nachiappan Pradan Pattanayak Sanjeev Verma, M., & Kalyanaraman, V. (2016). BlockChain Technology: Beyond Bitcoin.
De Vass, T., Shee, H., & Miah, S. (2018). The effect of “Internet of Things” on supply chain integration and performance: An organisational capability perspective. In Research Article IoT and Supply Chain Integration and Performance (Vol. 22).
Etikan, I. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1. https://doi.org/10.11648/j.ajtas.20160501.11
Gertrude Chavez-Dreyfuss, & Reuters. (2018). Coca-Cola, U.S. State Dept to use blockchain to combat forced labor.
Hair, J. J. F., Hult, G. T. M., Ringle, & C., et al. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications.
Hasan, I., & Habib, M. M. (2024). Enhancing Transparency in Agri-Food Supply Chain by Securing IoT-Generated Data with Blockchain. https://doi.org/10.21203/rs.3.rs-4486156/v1
Hosseini Bamakan, S. M., Ghasemzadeh Moghaddam, S., & Dehghan Manshadi, S. (2021). Blockchain-enabled pharmaceutical cold chain: Applications, key challenges, and future trends. In Journal of Cleaner Production (Vol. 302). Elsevier Ltd. https://doi.org/10.1016/j.jclepro.2021.127021
Jaradat, Z., Al-Hawamleh, A., Al Shbail, M. O., & Hamdan, A. (2024). Does the adoption of blockchain technology add intangible benefits to the industrial sector? Evidence from Jordan. Journal of Financial Reporting and Accounting, 22(2), 327–349. https://doi.org/10.1108/JFRA-03-2023-0164
Khan, S., Singh, R., Haleem, A., Dsilva, J., & Ali, S. (2022). Exploration of Critical Success Factors of Logistics 4.0: A DEMATEL Approach. Logistics, 6–13.
Kromes, R., Li, T., Bouillon, M., Güler, T. E., van der Hulst, V., & Erkin, Z. (2024). Fear of Missing Out: Constrained Trial of Blockchain in Supply Chain. Sensors, 24(3). https://doi.org/10.3390/s24030986
Kshetri, N. (2021). (2021). Blockchain and sustainable supply chain management in developing countries. International Journal of Information Management, 60.
Kumar Bhardwaj, A., Garg, A., & Gajpal, Y. (2021a). Determinants of Blockchain Technology Adoption in Supply Chains by Small and Medium Enterprises (SMEs) in India. Mathematical Problems in Engineering, 2021. https://doi.org/10.1155/2021/5537395
Kumar Bhardwaj, A., Garg, A., & Gajpal, Y. (2021b). Determinants of Blockchain Technology Adoption in Supply Chains by Small and Medium Enterprises (SMEs) in India. Mathematical Problems in Engineering, 2021. https://doi.org/10.1155/2021/5537395
Lai, Y., Sun, H., & Ren, J. (2018). Understanding the determinants of big data analytics (BDA) adoption in logistics and supply chain management: An empirical investigation. International Journal of Logistics Management, 29(2), 676–703. https://doi.org/10.1108/IJLM-06-2017-0153
Lim, M. K., Li, Y., Wang, C., & Tseng, M. L. (2021). A literature review of blockchain technology applications in supply chains: A comprehensive analysis of themes, methodologies and industries. Computers and Industrial Engineering, 154. https://doi.org/10.1016/j.cie.2021.107133
Mohammed, A., Potdar, V., & Quaddus, M. (2023). Exploring Factors and Impact of Blockchain Technology in the Food Supply Chains: An Exploratory Study. Foods, 12(10). https://doi.org/10.3390/foods12102052
Morgan, T. R., Richey, R. G., & Ellinger, A. E. (n.d.). Supplier transparency: scale development and validation. https://doi.org/10.1108/IJLM-01-2017-0018
Nayal, K., Raut, R. D., Narkhede, B. E., Priyadarshinee, P., Panchal, G. B., & Gedam, V. V. (2023). Antecedents for blockchain technology-enabled sustainable agriculture supply chain. Annals of Operations Research, 327(1), 293–337. https://doi.org/10.1007/s10479-021-04423-3
Nisha, K. D., Navaneethan, M., Dhanalakshmi, B., Saravana Murali, K., Hayakawa, Y., Ponnusamy, S., Muthamizhchelvan, C., & Gunasekaran, P. (2015). Effect of organic-ligands on the toxicity profiles of CdS nanoparticles and functional properties. Colloids and Surfaces B: Biointerfaces, 126, 407–413. https://doi.org/10.1016/j.colsurfb.2014.12.044
Podsakoff, P. , M. S. , L. J.-Y. , P. N. ,. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol.
Raoufi, K., Tajasob, P., Al-e-Hashem, S. M. J. M., & Jokar, M. A. (2025). Challenges, opportunities, and future research directions of aggregate production planning: A State-of-the-Art analysis of sustainability, uncertainty, and case studies. In Journal of Cleaner Production (Vol. 489). Elsevier Ltd. https://doi.org/10.1016/j.jclepro.2025.144686
Ringle, C.M., Wende, , Sven, Becker, & Jan-Michael. (2022). SmartPLS 4. SmartPLS, Boenningstedt from. .
Roozkhosh, P., Pooya, A., & Agarwal, R. (2023). Blockchain acceptance rate prediction in the resilient supply chain with hybrid system dynamics and machine learning approach. Operations Management Research, 16(2), 705–725. https://doi.org/10.1007/s12063-022-00336-x
Sabahi, S., & Parast, M. M. (2020). Firm innovation and supply chain resilience: a dynamic capability perspective. International Journal of Logistics Research and Applications, 23(3), 254–269. https://doi.org/10.1080/13675567.2019.1683522
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117–2135. https://doi.org/10.1080/00207543.2018.1533261
Sarstedt, M., R., C.M., Hair, & J.F. (2017). Treating Unobserved Heterogeneity in PLS-SEM: A Multi-Method Approach. Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications. . In: Latan, H., Noonan, R. (Eds.),.
Sharma, A., Bhatia, T., Singh, R. K., & Sharma, A. (2024). Developing the framework of blockchain-enabled agri-food supply chain. Business Process Management Journal, 30(1), 291–316. https://doi.org/10.1108/BPMJ-01-2023-0035
Taylor, P. J., Dargahi, T., Dehghantanha, A., Parizi, R. M., & Choo, K. K. R. (2020). A systematic literature review of blockchain cyber security. In Digital Communications and Networks (Vol. 6, Number 2, pp. 147–156). Chongqing University of Posts and Telecommunications. https://doi.org/10.1016/j.dcan.2019.01.005
Tripoli, M., & Schmidhuber, J. (2018). Issue Paper Emerging Opportunities for the Application of Blockchain in the Agri-food Industry Agriculture.
Tsou, H. T. , & H. S. H. Y. (2015). Performance effects of technology-organization-en vironment openness, service co-production, and digital-resource readiness: The case of the IT industry. . International Journal of Information Management, 1–14.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. In Source: MIS Quarterly (Vol. 27, Number 3).
Wang, Y. Y., Wang, Y. S., & Lin, T. C. (2018). Developing and validating a technology upgrade model. International Journal of Information Management, 38(1), 7–26. https://doi.org/10.1016/j.ijinfomgt.2017.07.003
Weerabahu, S. K., Samaranayake, P., Dasanayaka, S. W. S., & Wickramasinghe, C. N. (2022). Challenges of agri-food supply in city region food systems: an emerging economy perspective. Journal of Agribusiness in Developing and Emerging Economies, 12(2), 161–182. https://doi.org/10.1108/JADEE-01-2021-0004
Yu, S., Liu, S., Gong, X., Liu, C. e., & Cai, W. (2025). Online platform algorithmic control and gig workers’ turnover intention in China: The mediating role of relative deprivation. Journal of Management Science and Engineering, 10(1), 37–53. https://doi.org/10.1016/j.jmse.2024.08.004
Alalwan, A. A., Dwivedi, Y. K., & Rana, N. P. (2017). Factors influencing adoption of mobile banking by Jordanian bank customers: Extending UTAUT2 with trust. International Journal of Information Management, 37(3), 99–110. https://doi.org/10.1016/j.ijinfomgt.2017.01.002
Ali, M. H., Chung, L., Kumar, Zailani, S., Tan, & K. H. (2021). A sustainable Blockchain framework for the halal food supply chain: Lessons from Malaysia . Technological Forecasting and Social Change, 170.
Ali, S. S., Jalil, S. A., Kamal, M., & Rameshwar, R. (2024). Amplifying swift-trust, collaboration, and teamwork in warehouse management through blockchain-enabled technology. Supply Chain Analytics, 8. https://doi.org/10.1016/j.sca.2024.100089
Armstrong, J. S. , & O. T. S. (1977). Estimating nonresponse bias in mail surveys. Journal of Marketing Research, 3–14.
Aslam, J., Saleem, A., Khan, N. T., & Kim, Y. B. (2021). Factors influencing blockchain adoption in supply chain management practices: A study based on the oil industry. Journal of Innovation and Knowledge, 6(2), 124–134. https://doi.org/10.1016/j.jik.2021.01.002
Azizi, N., Malekzadeh, H., Akhavan, P., Haass, O., Saremi, S., & Mirjalili, S. (2021). IoT–blockchain: Harnessing the power of internet of thing and blockchain for smart supply chain. Sensors, 21(18). https://doi.org/10.3390/s21186048
Bagozzi, R. P., Fornell, C., & Larcker, D. F. (1981). Canonical correlation-analysis as a special case of a structural relations model. Multivariate Behav. Res., 16(4), 437–457.
Ball, C. (2009). What Is Transparency? Public Integrity, 11(4), 293–308. https://doi.org/10.2753/PIN1099-9922110400
Baralla, G., Ibba, S., Marchesi, M., Tonelli, R., & Missineo, S. (2019). A blockchain based system to ensure transparency and reliability in food supply chain. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 11339 LNCS, 379–391. https://doi.org/10.1007/978-3-030-10549-5_30
Basana, S. R., Malelak, M. I., Suprapto, W., Siagian, H., & Tarigan, Z. J. H. (2024). The impact of SCM integration on business performance through information sharing, quality integration and innovation system. Uncertain Supply Chain Management, 12(1), 435–448. https://doi.org/10.5267/j.uscm.2023.9.008
Buell, R. W., Kim, T., & Tsay, C. J. (2016). Creating Reciprocal Value Through Operational Transparency. Https://Doi.Org/10.1287/Mnsc.2015.2411, 63(6), 1673–1695. https://doi.org/10.1287/MNSC.2015.2411
Clark, D. H. , and W. Reed. (2005). The Strategic Sources of Foreign Policy Substitution. American Journal of Political Science, 609–624.
Crosby Nachiappan Pradan Pattanayak Sanjeev Verma, M., & Kalyanaraman, V. (2016). BlockChain Technology: Beyond Bitcoin.
De Vass, T., Shee, H., & Miah, S. (2018). The effect of “Internet of Things” on supply chain integration and performance: An organisational capability perspective. In Research Article IoT and Supply Chain Integration and Performance (Vol. 22).
Etikan, I. (2016). Comparison of Convenience Sampling and Purposive Sampling. American Journal of Theoretical and Applied Statistics, 5(1), 1. https://doi.org/10.11648/j.ajtas.20160501.11
Gertrude Chavez-Dreyfuss, & Reuters. (2018). Coca-Cola, U.S. State Dept to use blockchain to combat forced labor.
Hair, J. J. F., Hult, G. T. M., Ringle, & C., et al. (2014). A Primer on Partial Least Squares Structural Equation Modeling (PLS-SEM). Sage Publications.
Hasan, I., & Habib, M. M. (2024). Enhancing Transparency in Agri-Food Supply Chain by Securing IoT-Generated Data with Blockchain. https://doi.org/10.21203/rs.3.rs-4486156/v1
Hosseini Bamakan, S. M., Ghasemzadeh Moghaddam, S., & Dehghan Manshadi, S. (2021). Blockchain-enabled pharmaceutical cold chain: Applications, key challenges, and future trends. In Journal of Cleaner Production (Vol. 302). Elsevier Ltd. https://doi.org/10.1016/j.jclepro.2021.127021
Jaradat, Z., Al-Hawamleh, A., Al Shbail, M. O., & Hamdan, A. (2024). Does the adoption of blockchain technology add intangible benefits to the industrial sector? Evidence from Jordan. Journal of Financial Reporting and Accounting, 22(2), 327–349. https://doi.org/10.1108/JFRA-03-2023-0164
Khan, S., Singh, R., Haleem, A., Dsilva, J., & Ali, S. (2022). Exploration of Critical Success Factors of Logistics 4.0: A DEMATEL Approach. Logistics, 6–13.
Kromes, R., Li, T., Bouillon, M., Güler, T. E., van der Hulst, V., & Erkin, Z. (2024). Fear of Missing Out: Constrained Trial of Blockchain in Supply Chain. Sensors, 24(3). https://doi.org/10.3390/s24030986
Kshetri, N. (2021). (2021). Blockchain and sustainable supply chain management in developing countries. International Journal of Information Management, 60.
Kumar Bhardwaj, A., Garg, A., & Gajpal, Y. (2021a). Determinants of Blockchain Technology Adoption in Supply Chains by Small and Medium Enterprises (SMEs) in India. Mathematical Problems in Engineering, 2021. https://doi.org/10.1155/2021/5537395
Kumar Bhardwaj, A., Garg, A., & Gajpal, Y. (2021b). Determinants of Blockchain Technology Adoption in Supply Chains by Small and Medium Enterprises (SMEs) in India. Mathematical Problems in Engineering, 2021. https://doi.org/10.1155/2021/5537395
Lai, Y., Sun, H., & Ren, J. (2018). Understanding the determinants of big data analytics (BDA) adoption in logistics and supply chain management: An empirical investigation. International Journal of Logistics Management, 29(2), 676–703. https://doi.org/10.1108/IJLM-06-2017-0153
Lim, M. K., Li, Y., Wang, C., & Tseng, M. L. (2021). A literature review of blockchain technology applications in supply chains: A comprehensive analysis of themes, methodologies and industries. Computers and Industrial Engineering, 154. https://doi.org/10.1016/j.cie.2021.107133
Mohammed, A., Potdar, V., & Quaddus, M. (2023). Exploring Factors and Impact of Blockchain Technology in the Food Supply Chains: An Exploratory Study. Foods, 12(10). https://doi.org/10.3390/foods12102052
Morgan, T. R., Richey, R. G., & Ellinger, A. E. (n.d.). Supplier transparency: scale development and validation. https://doi.org/10.1108/IJLM-01-2017-0018
Nayal, K., Raut, R. D., Narkhede, B. E., Priyadarshinee, P., Panchal, G. B., & Gedam, V. V. (2023). Antecedents for blockchain technology-enabled sustainable agriculture supply chain. Annals of Operations Research, 327(1), 293–337. https://doi.org/10.1007/s10479-021-04423-3
Nisha, K. D., Navaneethan, M., Dhanalakshmi, B., Saravana Murali, K., Hayakawa, Y., Ponnusamy, S., Muthamizhchelvan, C., & Gunasekaran, P. (2015). Effect of organic-ligands on the toxicity profiles of CdS nanoparticles and functional properties. Colloids and Surfaces B: Biointerfaces, 126, 407–413. https://doi.org/10.1016/j.colsurfb.2014.12.044
Podsakoff, P. , M. S. , L. J.-Y. , P. N. ,. (2003). Common method biases in behavioral research: a critical review of the literature and recommended remedies. J. Appl. Psychol.
Raoufi, K., Tajasob, P., Al-e-Hashem, S. M. J. M., & Jokar, M. A. (2025). Challenges, opportunities, and future research directions of aggregate production planning: A State-of-the-Art analysis of sustainability, uncertainty, and case studies. In Journal of Cleaner Production (Vol. 489). Elsevier Ltd. https://doi.org/10.1016/j.jclepro.2025.144686
Ringle, C.M., Wende, , Sven, Becker, & Jan-Michael. (2022). SmartPLS 4. SmartPLS, Boenningstedt from. .
Roozkhosh, P., Pooya, A., & Agarwal, R. (2023). Blockchain acceptance rate prediction in the resilient supply chain with hybrid system dynamics and machine learning approach. Operations Management Research, 16(2), 705–725. https://doi.org/10.1007/s12063-022-00336-x
Sabahi, S., & Parast, M. M. (2020). Firm innovation and supply chain resilience: a dynamic capability perspective. International Journal of Logistics Research and Applications, 23(3), 254–269. https://doi.org/10.1080/13675567.2019.1683522
Saberi, S., Kouhizadeh, M., Sarkis, J., & Shen, L. (2019). Blockchain technology and its relationships to sustainable supply chain management. International Journal of Production Research, 57(7), 2117–2135. https://doi.org/10.1080/00207543.2018.1533261
Sarstedt, M., R., C.M., Hair, & J.F. (2017). Treating Unobserved Heterogeneity in PLS-SEM: A Multi-Method Approach. Partial Least Squares Path Modeling: Basic Concepts, Methodological Issues and Applications. . In: Latan, H., Noonan, R. (Eds.),.
Sharma, A., Bhatia, T., Singh, R. K., & Sharma, A. (2024). Developing the framework of blockchain-enabled agri-food supply chain. Business Process Management Journal, 30(1), 291–316. https://doi.org/10.1108/BPMJ-01-2023-0035
Taylor, P. J., Dargahi, T., Dehghantanha, A., Parizi, R. M., & Choo, K. K. R. (2020). A systematic literature review of blockchain cyber security. In Digital Communications and Networks (Vol. 6, Number 2, pp. 147–156). Chongqing University of Posts and Telecommunications. https://doi.org/10.1016/j.dcan.2019.01.005
Tripoli, M., & Schmidhuber, J. (2018). Issue Paper Emerging Opportunities for the Application of Blockchain in the Agri-food Industry Agriculture.
Tsou, H. T. , & H. S. H. Y. (2015). Performance effects of technology-organization-en vironment openness, service co-production, and digital-resource readiness: The case of the IT industry. . International Journal of Information Management, 1–14.
Venkatesh, V., Morris, M. G., Davis, G. B., & Davis, F. D. (2003). User Acceptance of Information Technology: Toward a Unified View. In Source: MIS Quarterly (Vol. 27, Number 3).
Wang, Y. Y., Wang, Y. S., & Lin, T. C. (2018). Developing and validating a technology upgrade model. International Journal of Information Management, 38(1), 7–26. https://doi.org/10.1016/j.ijinfomgt.2017.07.003
Weerabahu, S. K., Samaranayake, P., Dasanayaka, S. W. S., & Wickramasinghe, C. N. (2022). Challenges of agri-food supply in city region food systems: an emerging economy perspective. Journal of Agribusiness in Developing and Emerging Economies, 12(2), 161–182. https://doi.org/10.1108/JADEE-01-2021-0004
Yu, S., Liu, S., Gong, X., Liu, C. e., & Cai, W. (2025). Online platform algorithmic control and gig workers’ turnover intention in China: The mediating role of relative deprivation. Journal of Management Science and Engineering, 10(1), 37–53. https://doi.org/10.1016/j.jmse.2024.08.004