The Effect of Digital Transformation on the Pharmaceutical Sustainable Supply Chain Performance: The Mediating Role of Information Sharing and Traceability Using Structural Equation Modeling
Abstract
:1. Introduction
2. Literature Review
2.1. Digital Transformation
2.2. Information Sharing
2.3. Traceability
2.4. Sustainable Supply Chain Performance
3. Hypotheses Development
3.1. Research Hypothesis
3.1.1. Digital Transformation and Sustainable Supply Chain Performance
3.1.2. Digital Transformation and Information Sharing
3.1.3. Digital Transformation and Traceability
3.1.4. Information Sharing and Sustainable Supply Chain Performance
3.1.5. Traceability and Sustainable Supply Chain Performance
3.1.6. Information Sharing and Traceability
3.1.7. Mediating Role of Information Sharing
3.1.8. Mediating Role of Traceability
3.1.9. Mediating Role of Information Sharing and Traceability
3.2. Measurement
3.3. Demographics
4. Data Analysis and Results
4.1. Exploratory Factor Analysis
4.2. Confirmatory Factor Analysis
4.3. Correlation Analysis
4.4. Path Analysis
4.5. Test of Mediating Effect
5. Discussion and Conclusions
5.1. Discussion
5.2. Conclusions
5.2.1. Theoretical Implications
5.2.2. Practical Implications
5.2.3. Limitations
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Conflicts of Interest
References
- Rudnicka, E.; Napierała, P.; Podfigurna, A.; Męczekalski, B.; Smolarczyk, R.; Grymowicz, M. The World Health Organization (WHO) approach to healthy ageing. Maturitas 2020, 139, 6–11. [Google Scholar] [CrossRef] [PubMed]
- Shacham, M.; Greenblatt-Kimron, L.; Hamama-Raz, Y.; Martin, L.R.; Peleg, O.; Ben-Ezra, M.; Mijiritsky, E. Increased COVID-19 vaccination hesitancy and health awareness amid COVID-19 vaccinations programs in Israel. Int. J. Environ. Res. Public Health 2021, 18, 3804. [Google Scholar] [CrossRef] [PubMed]
- Jung, H.; Jeon, J.; Choi, H. Important factors in the development of biopharmaceutical logistics centers. Asian J. Shipp. Logist. 2021, 37, 301–306. [Google Scholar] [CrossRef]
- Healthcare in 2022: The Aftermath of Coronavirus. Available online: https://www.eiu.com/n/healthcare-in-2022-the-aftermath-of-coronavirus/ (accessed on 28 October 2022).
- Zavala-Alcívar, A.; Verdecho, M.J.; Alfaro-Saiz, J.J. A conceptual framework to manage resilience and increase sustainability in the supply chain. Sustainability 2020, 12, 6300. [Google Scholar] [CrossRef]
- Khanfar, A.A.; Iranmanesh, M.; Ghobakhloo, M.; Senali, M.G.; Fathi, M. Applications of blockchain technology in sustainable manufacturing and supply chain management: A systematic review. Sustainability 2021, 13, 7870. [Google Scholar] [CrossRef]
- Taboada, I.; Shee, H. Understanding 5G technology for future supply chain management. Int. J. Logist. Res. Appl. 2021, 24, 392–406. [Google Scholar] [CrossRef]
- Wan, P.K.; Huang, L.; Holtskog, H. Blockchain-enabled information sharing within a supply chain: A systematic literature review. IEEE Access 2020, 8, 49645–49656. [Google Scholar] [CrossRef]
- Liang, X.; Li, G.; Zhang, H.; Nolan, E.; Chen, F. Firm performance and marketing analytics in the Chinese context: A contingency model. J. Bus. Res. 2022, 141, 589–599. [Google Scholar] [CrossRef]
- Haji, M.; Kerbache, L.; Sheriff, K.M.; Al-Ansari, T. Critical success factors and traceability technologies for establishing a safe pharmaceutical supply chain. Methods Protoc. 2021, 4, 85. [Google Scholar] [CrossRef]
- Silva, R.B.D.; Mattos, C.A.D. Critical success factors of a drug traceability system for creating value in a pharmaceutical supply chain (PSC). Int. J. Environ. Res. Public Health 2019, 16, 1972. [Google Scholar] [CrossRef]
- Salamai, A.A. A review of collaboration and secure information-sharing for supply chain management. J. Inf. Knowl. Manag. 2022, 21, 2250047. [Google Scholar] [CrossRef]
- Meo, S.A.; Bukhari, I.A.; Akram, J.; Meo, A.S.; Klonoff, D.C. COVID-19 vaccines: Comparison of biological, pharmacological characteristics and adverse effects of Pfizer/BioNTech and Moderna Vaccines. Eur. Rev. Med. Pharmacol. Sci. 2021, 25, 1663–1669. [Google Scholar]
- Vishwakarma, A.; Dangayach, G.S.; Meena, M.L.; Gupta, S.; Luthra, S. Adoption of blockchain technology enabled healthcare sustainable supply chain to improve healthcare supply chain performance. Manag. Environ. Qual. Int. J. 2022. ahead-of-print. [Google Scholar] [CrossRef]
- Ding, B. Pharma Industry 4.0: Literature review and research opportunities in sustainable pharmaceutical supply chains. Process Saf. Environ. Prot. 2018, 119, 115–130. [Google Scholar] [CrossRef]
- Burin, A.R.G.; Perez-Arostegui, M.N.; Llorens-Montes, J. Ambidexterity and IT competence can improve supply chain flexibility? A resource orchestration approach. J. Purch. Supply Manag. 2020, 26, 100610. [Google Scholar] [CrossRef]
- Kavita, K.; Vaishali, P. Implementation of ICT for supply chain management by the large and MSME indian pharmaceutical manufacturing firms. Ann. Univ. Dunarea De Jos Galati Fascicle I Econ. Appl. Inform. 2019, 25, 37–42. [Google Scholar] [CrossRef]
- Alharthi, S.; Cerotti, P.R.; Far, S.M. An exploration of the role of blockchain in the sustainability and effectiveness of the pharmaceutical supply chain. J. Supply Chain. Cust. Relatsh. Manag. 2020, 2020, 562376. [Google Scholar] [CrossRef]
- Saha, E.; Rathore, P.; Parida, R.; Rana, N.P. The interplay of emerging technologies in pharmaceutical supply chain performance: An empirical investigation for the rise of Pharma 4.0. Technol. Forecast. Soc. Change 2022, 181, 121768. [Google Scholar] [CrossRef]
- Salehi, V.; Salehi, R.; Mirzayi, M.; Akhavizadegan, F. Performance optimization of pharmaceutical supply chain by a unique resilience engineering and fuzzy mathematical framework. Hum. Factors Ergon. Manuf. Serv. Ind. 2020, 30, 336–348. [Google Scholar] [CrossRef]
- Hendy, T.; Resdiansyah, R.; Johanes, F.A.; Rustono, F.M. Exploring the role of ICT readiness and information sharing on supply chain performance in coronavirus disruptions. Technol. Rep. Kansai Univ. 2020, 62, 2581–2588. [Google Scholar]
- Shao, X.F.; Liu, W.; Li, Y.; Chaudhry, H.R.; Yue, X.G. Multistage implementation framework for smart supply chain management under industry 4.0. Technol. Forecast. Soc. Change 2021, 162, 120354. [Google Scholar] [CrossRef] [PubMed]
- Sombultawee, K.; Lenuwat, P.; Aleenajitpong, N.; Boon-itt, S. COVID-19 and supply chain management: A review with bibliometric. Sustainability 2022, 14, 3538. [Google Scholar] [CrossRef]
- Kiers, J.; Seinhorst, J.; Zwanenburg, M.; Stek, K. Which strategies and corresponding competences are needed to improve supply chain resilience: A COVID-19 based review. Logistics 2022, 6, 12. [Google Scholar] [CrossRef]
- Mangla, S.K.; Kusi-Sarpong, S.; Luthra, S.; Bai, C.; Jakhar, S.K.; Khan, S.A. Operational excellence for improving sustainable supply chain performance. Resour. Conserv. Recycl. 2020, 162, 105025. [Google Scholar] [CrossRef]
- Kraus, S.; Jones, P.; Kailer, N.; Weinmann, A.; Chaparro-Banegas, N.; Roig-Tierno, N. Digital transformation: An overview of the current state of the art of research. Sage Open 2021, 11, 21582440211047576. [Google Scholar] [CrossRef]
- Kraus, S.; Durst, S.; Ferreira, J.J.; Veiga, P.; Kailer, N.; Weinmann, A. Digital transformation in business and management research: An overview of the current status quo. Int. J. Inf. Manag. 2022, 63, 102466. [Google Scholar] [CrossRef]
- Stroumpoulis, A.; Kopanaki, E. Theoretical perspectives on sustainable supply chain management and digital transformation: A literature review and a conceptual framework. Sustainability 2022, 14, 4862. [Google Scholar] [CrossRef]
- Kim, Y.; Atukeren, E.; Lee, Y. A new digital value chain model with PLC in biopharmaceutical industry: The implication for open innovation. J. Open Innov. Technol. Mark. Complex. 2022, 8, 63. [Google Scholar] [CrossRef]
- Hartley, J.L.; Sawaya, W.J. Tortoise, Not the hare: Digital transformation of supply chain business processes. Bus. Horiz. 2019, 62, 707–715. [Google Scholar] [CrossRef]
- Ma, J.Y.; Song, P.T.; Kang, T.W. A study on the influence of telemedicine service characteristics on intention to use in China-The moderating effect of on-line word-of-mouth. China Area Stud. Assoc. Korea 2022, 9, 173–197. [Google Scholar] [CrossRef]
- Ma, J.Y.; Kang, T.W. A study on the effects of service quality of pharmaceutical e-commerce on customer satisfaction -Mediating effect of perceived value. Korean-Chin. Assoc. Soc. Sci. Stud. 2021, 19, 185–205. [Google Scholar] [CrossRef]
- Khan, A.A.; Abonyi, J. Information sharing in supply chains-Interoperability in an era of circular economy. Clean. Logist. Supply Chain 2022, 5, 100074. [Google Scholar] [CrossRef]
- Xu, M.; Ma, S.; Wang, G. Differential game model of information sharing among supply chain finance based on blockchain technology. Sustainability 2022, 14, 7139. [Google Scholar] [CrossRef]
- Saberi, S.; Kouhizadeh, M.; Sarkis, J.; Shen, L. Blockchain technology and its relationships to sustainable supply chain management. Int. J. Prod. Res. 2019, 57, 2117–2135. [Google Scholar] [CrossRef] [Green Version]
- Rejeb, A.; Keogh, J.G.; Zailani, S.; Treiblmaier, H.; Rejeb, K. Blockchain technology in the food industry: A review of potentials, challenges and future research directions. Logistics 2020, 4, 27. [Google Scholar] [CrossRef]
- Hayrutdinov, S.; Saeed, M.S.; Rajapov, A. Coordination of supply chain under blockchain system-based product lifecycle information sharing effort. J. Adv. Transp. 2020, 2020, 1–10. [Google Scholar] [CrossRef]
- Jäger-Roschko, M.; Petersen, M. Advancing the circular economy through information sharing: A systematic literature review. J. Clean. Prod. 2022, 369, 133210. [Google Scholar] [CrossRef]
- Al-Ghetaa, R.K.; Daniel, I.; Shaw, J.; Klein, D.; Brown, A. The determinants of effective inter-organization information sharing in the health capital planning process. Healthc. Manag. Forum 2022, 35, 236. [Google Scholar] [CrossRef]
- Betcheva, L.; Erhun, F.; Jiang, H. OM Forum—Supply chain thinking in healthcare: Lessons and outlooks. Manuf. Serv. Oper. Manag. 2021, 23, 1333–1353. [Google Scholar] [CrossRef]
- Wilson, T.P.; Clarke, W.R. Food safety and traceability in the agricultural supply chain: Using the Internet to deliver traceability. Supply Chain Manag. 1998, 3, 127–133. [Google Scholar] [CrossRef]
- Khan, S.; Haleem, A.; Khan, M.I.; Abidi, M.H.; Al-Ahmari, A. Implementing traceability systems in specific supply chain management (SCM) through critical success factors (CSFs). Sustainability 2018, 10, 204. [Google Scholar] [CrossRef] [Green Version]
- Theyel, G. Biomedical value chain traceability for innovation. In Proceedings of the 2017 IEEE Technology & Engineering Management Conference (TEMSCON), Santa Clara, CA, USA, 8–10 June 2017; pp. 295–300. [Google Scholar]
- Bamakan, S.M.H.; Moghaddam, S.G.; Manshadi, S.D. Blockchain-enabled pharmaceutical cold chain: Applications, key challenges, and future trends. J. Clean. Prod. 2021, 302, 127021. [Google Scholar] [CrossRef]
- Dasaklis, T.K.; Voutsinas, T.G.; Tsoulfas, G.T.; Casino, F. A systematic literature review of blockchain-enabled supply chain traceability implementations. Sustainability 2022, 14, 2439. [Google Scholar] [CrossRef]
- Rejeb, A.; Treiblmaier, H.; Rejeb, K.; Zailani, S. Blockchain research in healthcare: A bibliometric review and current research trends. J. Data Inf. Manag. 2021, 3, 109–124. [Google Scholar] [CrossRef]
- Sunny, J.; Undralla, N.; Pillai, V.M. Supply chain transparency through blockchain-based traceability: An overview with demonstration. Comput. Ind. Eng. 2020, 150, 106895. [Google Scholar] [CrossRef]
- Musamih, A.; Salah, K.; Jayaraman, R.; Arshad, J.; Debe, M.; Al-Hammadi, Y.; Ellahham, S. A blockchain-based approach for drug traceability in healthcare supply chain. IEEE Access 2021, 9, 9728–9743. [Google Scholar] [CrossRef]
- Lebas, M.J. Performance measurement and performance management. Int. J. Prod. Econ. 1995, 41, 23–35. [Google Scholar] [CrossRef]
- Govindan, K.; Khodaverdi, R.; Jafarian, A.A. fuzzy multi criteria approach for measuring sustainability performance of a supplier based on triple bottom line approach. J. Clean. Prod. 2013, 47, 345–354. [Google Scholar] [CrossRef]
- Slaper, T.F.; Hall, T.J. The triple bottom line: What is it and how does it work. Indiana Bus. Rev. 2011, 86, 4–8. [Google Scholar]
- Raza, J.; Liu, Y.; Zhang, J.; Zhu, N.; Hassan, Z.; Gul, H.; Hussain, S. Sustainable supply management practices and sustainability performance: The dynamic capability perspective. Sage Open 2021, 11, 21582440211. [Google Scholar] [CrossRef]
- Zamiela, C.; Hossain, N.U.I.; Jaradat, R. Enablers of resilience in the healthcare supply chain: A case study of US healthcare industry during COVID-19 pandemic. Res. Transp. Econ. 2022, 93, 101174. [Google Scholar] [CrossRef]
- Hosseini, S.; Ivanov, D.; Dolgui, A. Review of quantitative methods for supply chain resilience analysis. Transp. Res. Part E Logist. Transp. Rev. 2019, 125, 285–307. [Google Scholar] [CrossRef]
- Hossain, N.U.I.; Fazio, S.A.; Lawrence, J.M.; Gonzalez, E.D.S.; Jaradat, R.; Alvarado, M.S. Role of systems engineering attributes in enhancing supply chain resilience: Context of COVID-19 pandemic. Heliyon 2022, 8, e09592. [Google Scholar] [CrossRef] [PubMed]
- Ahmadi, V.; Benjelloun, S.; El Kik, M.; Sharma, T.; Chi, H.; Zhou, W. Drug governance: IoT-based blockchain implementation in the pharmaceutical supply chain. In Proceedings of the 2020 Sixth International Conference on Mobile and Secure Services, Miami Beach, FL, USA, 22–23 February 2020; pp. 1–8. [Google Scholar]
- Piprani, A.Z.; Jaafar, N.I.; Ali, S.M.; Mubarik, M.S.; Shahbaz, M. Multi-dimensional supply chain flexibility and supply chain resilience: The role of supply chain risks exposure. Oper. Manag. Res. 2022, 15, 307–325. [Google Scholar] [CrossRef]
- Safkhani, M.; Rostampour, S.; Bendavid, Y.; Bagheri, N. IoT in medical & pharmaceutical: Designing lightweight RFID security protocols for ensuring supply chain integrity. Comput. Netw. 2020, 181, 107558. [Google Scholar]
- Agrawal, D.; Minocha, S.; Namasudra, S.; Gandomi, A.H. A robust drug recall supply chain management system using hyperledger blockchain ecosystem. Comput. Biol. Med. 2022, 140, 105100. [Google Scholar] [CrossRef]
- Mak, K.K.; Pichika, M.R. Artificial intelligence in drug development: Present status and future prospects. Drug Discov. Today 2019, 24, 773–780. [Google Scholar] [CrossRef]
- Alabdali, M.A.; Salam, M.A. The impact of digital transformation on supply chain procurement for creating competitive advantage: An empirical study. Sustainability 2022, 14, 12269. [Google Scholar] [CrossRef]
- Lerman, L.V.; Benitez, G.B.; Müller, J.M.; de Sousa, P.R.; Frank, A.G. Smart green supply chain management: A configurational approach to enhance green performance through digital transformation. Supply Chain Manag. Int. J. 2022, 27, 147–176. [Google Scholar] [CrossRef]
- Yoo, I.; Yi, C.G. Economic innovation caused by digital transformation and impact on social systems. Sustainability 2022, 14, 2600. [Google Scholar] [CrossRef]
- Li, H.; Wu, Y.; Cao, D.; Wang, Y. Organizational mindfulness towards digital transformation as a prerequisite of information processing capability to achieve market agility. J. Bus. Res. 2021, 122, 700–712. [Google Scholar] [CrossRef]
- Napoleone, A.; Macchi, M.; Pozzetti, A. A review on the characteristics of cyber-physical systems for the future smart factories. J. Manuf. Syst. 2020, 54, 305–335. [Google Scholar] [CrossRef]
- Abburu, S.; Berre, A.J.; Jacoby, M.; Roman, D.; Stojanovic, L.; Stojanovic, N. COGNITWIN–Hybrid and cognitive digital twins for the process industry. In Proceedings of the 2020 IEEE International Conference on Engineering, Technology and Innovation, Cardiff, UK, 15–7 June 2020; pp. 1–8. [Google Scholar]
- Appio, F.P.; Frattini, F.; Petruzzelli, A.M.; Neirotti, P. Digital transformation and innovation management: A synthesis of existing research and an agenda for future studies. J. Prod. Innov. Manag. 2021, 38, 4–20. [Google Scholar] [CrossRef]
- Apilioğulları, L. Digital transformation in project-based manufacturing: Developing the ISA-95 model for vertical integration. Int. J. Prod. Econ. 2022, 245, 108413. [Google Scholar] [CrossRef]
- Massaro, M. Digital transformation in the healthcare sector through blockchain technology. Insights from academic research and business developments. Technovation 2021, 102386, in press. [Google Scholar] [CrossRef]
- Kraus, S.; Schiavone, F.; Pluzhnikova, A.; Invernizzi, A.C. Digital transformation in healthcare: Analyzing the current state-of-research. J. Bus. Res. 2021, 123, 557–567. [Google Scholar] [CrossRef]
- Uddin, M. Blockchain Medledger: Hyperledger fabric enabled drug traceability system for counterfeit drugs in pharmaceutical industry. Int. J. Pharm. 2021, 597, 120235. [Google Scholar] [CrossRef]
- Omar, I.A.; Debe, M.; Jayaraman, R.; Salah, K.; Omar, M.; Arshad, J. Blockchain-based Supply Chain Traceability for COVID-19 personal protective equipment. Comput. Ind. Eng. 2022, 167, 107995. [Google Scholar] [CrossRef]
- Guan, Z.; Zhang, X.; Zhou, M.; Dan, Y. Demand information sharing in competing supply chains with manufacturer-provided service. Int. J. Prod. Econ. 2020, 220, 107450. [Google Scholar] [CrossRef]
- Yatuwa, S. Assessment of Factors Influencing Demand and Supply Management on Pharmaceutical Supply Chain Performance in Tanzania: A Case of Medical Store Department in Dar es Salaam Region; Mzumbe University: Morogoro, Tanzania, 2020. [Google Scholar]
- Yin, W.; Ran, W. Utilizing blockchain technology to manage the dark and bright sides of supply network complexity to enhance supply chain sustainability. Complexity 2022, 2022, 1–14. [Google Scholar] [CrossRef]
- Lee, C.; Ha, B.C. Interactional justice, informational quality, and sustainable supply chain management: A comparison of domestic and multinational pharmaceutical companies. Sustainability 2021, 13, 998. [Google Scholar] [CrossRef]
- Lu, G.; Koufteros, X.; Talluri, S.; Hult, G.T.M. Deployment of supply chain security practices: Antecedents and consequences. Decis. Sci. 2019, 50, 459–497. [Google Scholar] [CrossRef]
- Roy, V. Contrasting supply chain traceability and supply chain visibility: Are they interchangeable? Int. J. Logist. Manag. 2021, 32, 942–972. [Google Scholar] [CrossRef]
- Shekarian, M.; Mellat, P.M. An integrative approach to supply chain disruption risk and resilience management: A literature review. Int. J. Logist. Res. Appl. 2020, 24, 1–29. [Google Scholar] [CrossRef]
- Wang, Y.; Han, J.H.; Beynon-Davies, P. Understanding blockchain technology for future supply chains: A systematic literature review and research agenda. Supply Chain. Manag. 2019, 24, 62–84. [Google Scholar] [CrossRef] [Green Version]
- Hader, M.; Tchoffa, D.; El Mhamedi, A.; Ghodous, P.; Dolgui, A.; Abouabdellah, A. Applying integrated blockchain and big data technologies to improve supply chain traceability and information sharing in the textile sector. J. Ind. Inf. Integr. 2022, 28, 100345. [Google Scholar] [CrossRef]
- Sarkar, S. Supply chain security act 2023: Interoperable data exchange for drug traceability. Int. J. Sci. Res. Comput. Sci. Eng. Inf. Technol. 2022, 8, 471–476. [Google Scholar]
- Marion, T.J.; Fixson, S.K. The transformation of the innovation process: How digital tools are changing work, collaboration, and organizations in new product development. J. Prod. Innov. Manag. 2021, 38, 192–215. [Google Scholar] [CrossRef]
- Nestle, V.; Täube, F.A.; Heidenreich, S.; Bogers, M. Establishing open innovation culture in cluster initiatives: The role of trust and information asymmetry. Technol. Forecast. Soc. Change 2019, 146, 563–572. [Google Scholar] [CrossRef]
- Owago, K.O.; Ngacho, C.; Wafula, J. The role of Procurement Act 2015 in the buyer-supplier relationships and the performance of milk processing firms: A case of Nairobi County, Kenya. Int. Acad. J. Procure. Supply Chain Manag. 2021, 3, 104–144. [Google Scholar]
- Kim, S.; Park, S.; Noh, H.; Kim, S.C. Impact of ICT capability on real time enterprise capability and supply chain performance. J. Soc. Korea Ind. Syst. Eng. 2020, 43, 110–122. [Google Scholar] [CrossRef]
- Kim, H.K.; Lee, C.W. Relationships among healthcare digitalization, social capital, and supply chain performance in the healthcare manufacturing industry. Int. J. Environ. Res. Public Health 2021, 18, 1417. [Google Scholar] [CrossRef] [PubMed]
- Aldawood, H.; Alabadi, M.; Alharbi, O.; Skinner, G. A Contemporary review of raising health awareness using ICT for application in the cyber security domain. In Proceedings of the 2019 International Conference in Engineering Applications (ICEA), Sao Miguel, Portugal, 8–11 July 2019; pp. 1–8. [Google Scholar]
- Al-Farsi, S.; Rathore, M.M.; Bakiras, S. Security of blockchain-based supply chain management systems: Challenges and opportunities. Appl. Sci. 2021, 11, 5585. [Google Scholar] [CrossRef]
- Centobelli, P.; Cerchione, R.; Del Vecchio, P.; Oropallo, E.; Secundo, G. Blockchain technology for bridging trust, traceability and transparency in circular supply chain. Inf. Manag. 2022, 59, 103508. [Google Scholar] [CrossRef]
- Fletcher, T.D. Methods and approaches to assessing distal mediation. In Proceedings of the 66th Annual Meeting of the Academy of Management, Atlanta, GA, USA, 11–16 August 2006. [Google Scholar]
- Hayes, A.F.; Preacher, K.J.; Myers, T.A. Mediation and the estimation of indirect effects in political communication research. Sourceb. Political Commun. Res. Methods Meas. Anal. Tech. 2011, 23, 434–465. [Google Scholar]
- Nasiri, M.; Ukko, J.; Saunila, M.; Rantala, T. Managing the digital supply chain: The role of smart technologies. Technovation 2020, 96, 102121. [Google Scholar] [CrossRef]
- Singhdong, P.; Suthiwartnarueput, K.; Pornchaiwiseskul, P. Factors influencing digital transformation of logistics service providers: A case study in thailand. J. Asian Financ. Econ. Bus. 2021, 8, 241–251. [Google Scholar]
- Kiswili, N.E.; Shale, I.N.; Osoro, A. Influence of supply chain leagility on performance of humanitarian aid organizations in Kenya. J. Bus. Econ. Dev. 2021, 6, 37. [Google Scholar] [CrossRef]
- Zhang, M.; Hu, H.; Zhao, X. Developing product recall capability through supply chain quality management. Int. J. Prod. Econ. 2020, 229, 107795. [Google Scholar] [CrossRef]
- Notice of Public Consultation on the Standard Regulations for the Classification of Small and Medium-Sized Enterprises (Revised Draft for Comments). Available online: https://www.miit.gov.cn/gzcy/yjzj/art/2021/art_4952142da8aa407aab85ac87bf74a1b9.html (accessed on 28 October 2022).
- Babbie, E.; Wagner III, W.E.; Zaino, J. Adventures in Social Research: Data Analysis Using IBM SPSS Statistics; Sage Publications: Thousand Oaks, CA, USA, 2022. [Google Scholar]
- Henry, F.K.; John, R. Little Jiffy, Mark Iv. Educ. Psychol. Meas. 1974, 34, 111–117. [Google Scholar]
- Fornell, C.; Larcker, D.F. Structural equation models with unobservable variables and measurement error: Algebra and statistics. J. Mark. Res. 1981, 18, 382–388. [Google Scholar] [CrossRef]
- Schober, P.; Boer, C.; Schwarte, L.A. Correlation coefficients: Appropriate use and interpretation. Anesth. Analg. 2018, 126, 1763–1768. [Google Scholar] [CrossRef] [PubMed]
- MacKinnon, D.P. Introduction to Statistical Mediation Analysis; Routledge: London, UK, 2012. [Google Scholar]
- Baron, R.M.; Kenny, D.A. The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations. J. Personal. Soc. Psychol. 1986, 51, 1173–1182. [Google Scholar] [CrossRef] [PubMed]
- Kamble, S.S.; Gunasekaran, A.; Subramanian, N.; Ghadge, A.; Belhadi, A.; Venkatesh, M. Blockchain technology’s impact on supply chain integration and sustainable supply chain performance: Evidence from the automotive industry. Ann. Oper. Res. 2021, in press. [CrossRef]
Variables | Items | Sources | |
---|---|---|---|
Digital Transformation | DT1 | Digital transformation enhance information systems capabilities. | Nasiri et al., (2020) [93] Singhdong et al., (2021) [94] |
DT2 | Digital transformation create networks between different businesses. | ||
DT3 | Digital transformation allows for the collection of large amounts of data from different sources. | ||
DT4 | Digital transformation aligns business and information systems. | ||
DT5 | Digital transformation enhance efficient customer interfaces. | ||
Information Sharing | IS1 | Supply chain uses information sharing to share information with partners in a timely manner | Yatuwa, (2020) [74] Kim et al., (2021) [87] |
IS2 | Supply chains use information sharing to respond to the mutual needs of supply chain members timely. | ||
IS3 | Supply chain uses information sharing to minimize distortion of communication information. | ||
IS4 | Supply chain can grasp market demand by using information sharing. | ||
IS5 | Supply chains use information sharing to share strategic direction with partners. | ||
Traceability | T1 | Supply chain traceability facilitates identification of drug location information. | Kim et al., (2020) [86] Kiswili et al., (2021) [95] Zhang et al., (2020) [96] |
T2 | Supply chain traceability for tracking the status of drug shipments. | ||
T3 | Supply chain traceability facilitates the tracking of drugs from raw material to endpoint. | ||
T4 | Supply chain traceability facilitates tracking the source of drug quality problems. | ||
T5 | Supply chain traceability facilitates recall of drugs with safety concerns. | ||
Sustainable Supply Chain Performance | SSCP1 | Sustainable supply performance maximizes profits. | Kim et al., (2020) [86] Lee et al., (2021) [76] Owago et al., (2021) [85] Lu et al., (2019) [77] |
SSCP2 | Sustainable supply performance rationalizes total product cost. | ||
SSCP3 | Sustainable supply performance leads to sustained improvement in financial performance. | ||
SSCP4 | Sustainable supply performance leads to increased production profitability. | ||
SSCP5 | Sustainable supply performance can improve supply chain vulnerability. |
Variables | Category | Frequency | Ratio (%) |
---|---|---|---|
Gender | Male | 152 | 51.0 |
Female | 146 | 49.0 | |
Age | <30 | 132 | 44.3 |
30–40 | 149 | 50.0 | |
41–50 | 14 | 4.7 | |
>50 | 3 | 1.0 | |
Education Background | Bachelor | 245 | 82.2 |
Master | 46 | 15.5 | |
Doctor | 7 | 2.3 | |
work seniority | 1–5 | 213 | 71.5 |
5–10 | 64 | 21.5 | |
>10 | 21 | 7.0 | |
Annual Company Turnover (million RMB) | <200 | 162 | 54.4 |
200–2000 | 94 | 31.5 | |
>2000 | 42 | 14.1 | |
Major Service District (Multiple selection) | First-tier cities | 158 | 33.5 |
Second-tier cities | 122 | 25.8 | |
Third-tier cities | 96 | 20.3 | |
Fourth-tier cities | 69 | 14.6 | |
Fifth-tier cities | 27 | 5.7 |
Variables | Codes | Factor Loading | Cronbach’s α | |||
---|---|---|---|---|---|---|
1 | 2 | 3 | 4 | |||
Digital Transformation | DT1 | 0.293 | 0.168 | 0.323 | 0.815 | 0.937 |
DT2 | 0.318 | 0.222 | 0.285 | 0.804 | ||
DT3 | 0.308 | 0.296 | 0.290 | 0.705 | ||
DT4 | 0.360 | 0.335 | 0.245 | 0.683 | ||
DT5 | 0.462 | 0.381 | 0.161 | 0.627 | ||
Information Sharing | IS1 | 0.213 | 0.263 | 0.796 | 0.249 | 0.923 |
IS2 | 0.279 | 0.333 | 0.667 | 0.328 | ||
IS3 | 0.261 | 0.403 | 0.655 | 0.299 | ||
IS4 | 0.277 | 0.401 | 0.686 | 0.271 | ||
IS5 | 0.291 | 0.300 | 0.742 | 0.206 | ||
Traceability | T1 | 0.314 | 0.707 | 0.346 | 0.279 | 0.936 |
T2 | 0.341 | 0.634 | 0.435 | 0.263 | ||
T3 | 0.272 | 0.771 | 0.319 | 0.194 | ||
T4 | 0.266 | 0.709 | 0.414 | 0.275 | ||
T5 | 0.261 | 0.748 | 0.295 | 0.307 | ||
Sustainable Supply Chain Performance | SSCP1 | 0.826 | 0.268 | 0.272 | 0.322 | 0.976 |
SSCP2 | 0.809 | 0.255 | 0.301 | 0.280 | ||
SSCP3 | 0.818 | 0.255 | 0.263 | 0.328 | ||
SSCP4 | 0.822 | 0.272 | 0.247 | 0.288 | ||
SSCP5 | 0.842 | 0.283 | 0.237 | 0.316 | ||
Eigen Value (Rotated) | 4.796 | 3.930 | 3.903 | 3.869 | ||
Explained Variance (%) | 23.981 | 19.648 | 19.516 | 19.343 | ||
Cumulative Variance (%) | 23.981 | 43.629 | 63.145 | 82.488 | ||
KMO = 0.955, Bartlett = 7051.682, Sig = 0.000, df = 190 |
Variables | Codes | Unstd. | S.E. | T-Value | p | Std. | C.R. | AVE |
---|---|---|---|---|---|---|---|---|
Digital Transformation | DT1 | 1 | 0.906 | 0.938 | 0.752 | |||
DT2 | 1.014 | 0.039 | 25.688 | *** | 0.918 | |||
DT3 | 0.981 | 0.048 | 20.621 | *** | 0.837 | |||
DT4 | 0.983 | 0.048 | 20.679 | *** | 0.838 | |||
DT5 | 0.953 | 0.047 | 20.443 | *** | 0.833 | |||
Information Sharing | IS1 | 1 | 0.827 | 0.923 | 0.705 | |||
IS2 | 0.948 | 0.054 | 17.523 | *** | 0.837 | |||
IS3 | 0.945 | 0.053 | 17.951 | *** | 0.850 | |||
IS4 | 0.993 | 0.053 | 18.606 | *** | 0.869 | |||
IS5 | 0.998 | 0.059 | 16.825 | *** | 0.815 | |||
Traceability | T1 | 1 | 0.869 | 0.937 | 0.747 | |||
T2 | 0.968 | 0.047 | 20.658 | *** | 0.870 | |||
T3 | 1.076 | 0.056 | 19.273 | *** | 0.839 | |||
T4 | 1.015 | 0.047 | 21.598 | *** | 0.890 | |||
T5 | 0.983 | 0.049 | 19.905 | *** | 0.854 | |||
Sustainable Supply Chain Performance | SSCP1 | 1 | 0.965 | 0.976 | 0.892 | |||
SSCP2 | 0.96 | 0.029 | 33.139 | *** | 0.917 | |||
SSCP3 | 0.988 | 0.024 | 40.365 | *** | 0.952 | |||
SSCP4 | 0.972 | 0.029 | 33.684 | *** | 0.920 | |||
SSCP5 | 1.013 | 0.023 | 44.705 | *** | 0.967 | |||
CMIN = 528.178, DF = 164, CMIN/DF = 3.221, GFI = 0.848, AGFI = 0.806,TLI = 0.940, CFI = 0.948, RMSEA = 0.086, SRMR = 0.0343 |
Variables | M | SD | 1 | 2 | 3 | 4 |
---|---|---|---|---|---|---|
Digital Transformation | 4.476 | 0.557 | 1 | |||
Information Sharing | 4.396 | 0.593 | 0.728 ** | 1 | ||
Traceability | 4.443 | 0.601 | 0.733 ** | 0.822 ** | 1 | |
Sustainable Supply Chain Performance | 4.462 | 0.602 | 0.763 ** | 0.690 ** | 0.709 ** | 1 |
Hypothesis | Path | Standardized Estimate | SE | CR | p | Results |
---|---|---|---|---|---|---|
H1 | DT→SSCP | 0.546 | 0.073 | 7.439 | *** | Supported |
H2 | DT→IS | 0.825 | 0.059 | 14.036 | *** | Supported |
H3 | DT→T | 0.195 | 0.061 | 3.180 | 0.001 | Supported |
H4 | IS→SSCP | 0.082 | 0.111 | 0.744 | 0.457 | Not Supported |
H5 | T→SSCP | 0.305 | 0.108 | 2.809 | 0.005 | Supported |
H6 | IS→T | 0.739 | 0.068 | 10.856 | *** | Supported |
CMIN = 528.178, DF = 164, CMIN/DF = 3.221, GFI = 0.848, AGFI = 0.806, TLI = 0.940, CFI = 0.948, RMSEA = 0.086, SRMR = 0.0343 |
Mediating | Hypothesis | Point Estimation | SE | Bootstrapping | Results | ||
---|---|---|---|---|---|---|---|
Bias-Corrected 95% CI | |||||||
Lower | Upper | p | |||||
DT→SSCP | Total effect | ||||||
- | 0.859 | 0.070 | 0.742 | 1.023 | 0.003 | - | |
Direct effect | |||||||
- | 0.546 | 0.147 | 0.263 | 0.847 | 0.000 | - | |
Indirect effect | |||||||
- | 0.313 | 0.122 | 0.106 | 0.580 | 0.003 | - | |
DT→IS→SSCP | H7 | 0.068 | 0.153 | −0.257 | 0.358 | 0.706 | Not Supported |
DT→T→SSCP | H8 | 0.059 | 0.049 | 0.001 | 0.219 | 0.045 | Supported |
DT→IS→T→SSCP | H9 | 0.181 | 0.108 | −0.004 | 0.436 | 0.054 | Not Supported |
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Ma, J.-Y.; Shi, L.; Kang, T.-W. The Effect of Digital Transformation on the Pharmaceutical Sustainable Supply Chain Performance: The Mediating Role of Information Sharing and Traceability Using Structural Equation Modeling. Sustainability 2023, 15, 649. https://doi.org/10.3390/su15010649
Ma J-Y, Shi L, Kang T-W. The Effect of Digital Transformation on the Pharmaceutical Sustainable Supply Chain Performance: The Mediating Role of Information Sharing and Traceability Using Structural Equation Modeling. Sustainability. 2023; 15(1):649. https://doi.org/10.3390/su15010649
Chicago/Turabian StyleMa, Jing-Yan, Lei Shi, and Tae-Won Kang. 2023. "The Effect of Digital Transformation on the Pharmaceutical Sustainable Supply Chain Performance: The Mediating Role of Information Sharing and Traceability Using Structural Equation Modeling" Sustainability 15, no. 1: 649. https://doi.org/10.3390/su15010649
APA StyleMa, J. -Y., Shi, L., & Kang, T. -W. (2023). The Effect of Digital Transformation on the Pharmaceutical Sustainable Supply Chain Performance: The Mediating Role of Information Sharing and Traceability Using Structural Equation Modeling. Sustainability, 15(1), 649. https://doi.org/10.3390/su15010649