Search results

Manufacturing capability is a crucial component of every nation’s economy and pharmaceuticals are frequently a significant part of the manufacturing sector. Pharmaceutical supply chains are essential to health-care systems, contributing to living quality and shorter hospital stays. This study aims to examine the role of multiple integrations on business performance (BP) through supply chain flexibility (SCF) and supply chain agility (SCA).

Data was collected from 198 supply chain professionals in the pharmaceutical sector of the developing economy of Pakistan. The sample was collected based on a nonprobability purposive sampling approach. A five-point Likert-scale survey was used and analyzed with the PLS-SEM technique using SmartPLS 4.

This study found that process integration (PI) does not affect SCA, whereas relationship integration and measurement integration positively affect SCA. SCA positively impacts BP. In contrast, all integrations significantly influenced supply flexibility and BP except for PI. Finally, SCF significantly mediates the relationship between all integrations and BP.

This study examined the relationships of multiple integrations on BP, directly and indirectly, through SCF and agility. The theory of dynamic capabilities has been applied and extended to increase the comprehensiveness of the findings. A developing economy’s pharmaceutical industry supply chain was examined, producing empirical evidence of the results.

Supply chain collaboration (SCC) benefits organizational performance (OP). Although it is complex, it is also hard to implement and measure collaborative initiatives in the field of the supply chain. This study aims to examine the role of information technology (IT) and people’s involvement in OP through the mediation of supply chain collaboration.

This study used a deductive and quantitative approach to test the research hypotheses. Data was collected from 249 supply chain professionals working at various manufacturing firms.

This research found a significant effect of IT on supply chain collaboration. Similarly, people involvement (PI) also significantly influenced the supply chain collaboration. For the mediation hypotheses, SCC significantly mediates the relationships between two independent variables (IT and PI) and OP. Furthermore, the full mediation of SCC occurred.

This study provides a framework emphasizing manufacturing firms’ practices, SCC and OP. The “people involvement” was found as a novel variable in the tested model using the resource-based view as a supporting theory. The research findings can benefit the professionals working on supply chain business processes to improve OP.

Environmental concerns, government action and activism have increased the bar for how businesses operate. The United Nations also suggested sustainable performance in their SDG-12 and SDG-13 to achieve sustainability by 2030. Therefore, this research aimed to examine environmental and operational performance in the manufacturing context and how institutional pressure and manufacturing supply chain collaboration affect performance.

Data were collected from 207 manufacturing firms using purposive sampling. The hypotheses were tested through a Covariance-Based Structural Equation Modeling approach with the help of IBM SPSS AMOS version 22.0. The study conducted an explanatory factor analysis and found two sub-constructs (higher-order) for “institutional pressure.”

The findings illustrated that environmental performance significantly mediates the relationship between manufacturing supply chain collaboration and operational performance. The manufacturing supply chain collaboration significantly directly and indirectly affected operational performance. Likewise, institutional pressure was a crucial construct for manufacturing supply chain collaboration.

In earlier studies, the relationships of study variables were examined individually. However, this study validated all the relationships in an integrated model with one variable (institutional pressure) in higher order. The study is grounded in institutional and stakeholder theory and contributes to the literature on green measures. At the operational level, the research can assist managers in comprehending the function of various manufacturing supply chain players to assist the eco-friendly practices that help to achieve SDG-12 (Responsible Consumption and Production) and SDG-13 (Climate Action) by 2030.

This study aims to investigate how the management of supply chain information impacts the performance of the supply chain. This relationship is explored by considering the mediating influence of internal and external integration, which is underpinned by the principles of resource-based theory.

Data was collected from 144 supply chain professionals across different manufacturing companies. The proposed hypotheses were subjected to quantitative analysis using partial least squares structural equation modeling, and the validity of the measurement model was assessed with the assistance of SmartPLS software.

This study identified that information management (IM) significantly and positively affects internal integration (II), customer integration (CI) and supply chain performance (SCP). Similarly, the results showed that II significantly and positively affects SCP. Likewise, CI positively and significantly affected SCP. At the same time, II found a positive yet significant mediating role in the relationship between IM and SCP. CI was found to play a positive but insignificant mediating role in the relationship between IM and SCP.

This research evaluated a second-order model and tested the SCP in conjunction with the resource-based view in the manufacturing industry. This research could be beneficial for researchers, manufacturers and policymakers to attain organizational objectives by implementing an efficient IM system for better integration and SCP.

Supply chain (SC) management is more challenging than ever. Significantly, the pandemic has provoked global and economic destruction that appeared in the manufacturing industry as a “black swan.” Therefore, the purpose of this study was to examine the role of information processing and digital supply chain in supply chain resilience through supply chain risk management.

This study examines SC risk management and resilience from an information processing theory perspective. The authors used data collected from 251 SC professionals in the manufacturing industry, and the authors used a quantitative method to analyze the data. The data was analyzed using partial least squares-structural equation modeling. To confirm the higher-order measurement model, the authors used SmartPLS version 4 software.

This study found that information processing capability (disruptive orientation and visibility in high-order) and digital SC significantly and positively affect SC risk management and resilience. Similarly, SC risk management positively mediates the relationship between information processing capability and digital SC. However, information processing capability was found to have a more substantial effect on SC risk management than the digital SC.

This study has both academic and practical contributions. It contributed to existing information processing theory, and manufacturing firms can improve their performance by proactively responding to SC disruptions by recognizing the pivotal role of study variables in risk management for a resilient SC.

The conceptual model of this study is based on information processing theory, which asserts that synchronizing information processing capabilities and digital SCs allows a firm to deal with unplanned events. SC disruption orientation and visibility are considered risk controllers as they allow the firms to be more proactive. An integrated model of conceptualizing the disruption orientation, visibility (higher-order) and digital SC with information processing theory makes this research novel.

Due to the environmental concerns in our society, governments are moving towards green purchasing. However, public sector organizations have substantial internal problems. By using a theory of natural resource-based view, this study aimed to analyse the influence of leadership styles and innovation capabilities on green purchasing in the public sector organizations of a developing economy.

Data was collected from 199 purchasing professionals of public sector organizations, and hypotheses were tested through a quantitative method using partial least square-structural equation modelling with the help of SmartPLS version 4 to validate the measurement model.

This study identified that transformational leadership and delegation style of leadership have a significant and positive effect on innovation capability and green purchasing. Similarly, innovation capability mediates the relationship between leadership styles and green purchasing. However, transformational leadership found a more substantial effect on innovation capability and green purchasing than the delegation leadership style.

Results provide insight into the role of leadership styles in green purchasing and innovation capabilities in public sector organizations. Thus, addressing the important issues of how leadership styles and innovative capabilities (IC) can improve green culture, specifically green purchasing, to enhance ecological sustainability.

Results provide insight into the role of leadership styles in green purchasing and innovation capabilities in public sector organizations. Thus, it addresses how leadership styles and IC can improve green culture, specifically green purchasing, to enhance ecological sustainability.

This study aims to examine the role of big data analytics (BDA) powered by artificial intelligence (AI) in improving sustainable performance (SP) through green supply chain collaboration (GSCC), sustainable manufacturing (SM) and environmental process integration (EPI).

Data was collected from 249 supply chain professionals working at various manufacturing firms, and hypotheses were tested through a quantitative method using PLS-SEM with the help of SmartPLS version 4 to validate the measurement model.

This study identified that BDA-AI significantly and positively affects GSCC, SM and EPI. Similarly, the results showed that GSCC significantly and positively affects SP. At the same time, SM and EPI have an insignificant effect on SP. The GSCC found a significant relationship between BDA-AI and SP for mediation. However, SM and environmental performance integration did not mediate the relationship between BDA and AI and SP.

This research evaluated a second-order model and tested SP in conjunction with the dynamic capability theory in the manufacturing industry of Pakistan. Therefore, this research could be beneficial for researchers, manufacturers and policymakers to attain sustainable goals by implementing the BDA-AI in the supply chain.

Green practices are essential for sustainability. However, it is challenging due to the socioeconomic and environmental concerns. Similarly, after the induced SDG-12 and SDG-13 by United Nations, the pressure groups forced manufacturers to consider sustainability. Therefore, this research aims to examine the sustainability through multifaceted green functions in manufacturing is examined.

Data were collected from 293 supply chain professionals of manufacturers from a developing economy. Hypotheses were tested through a quantitative method using partial least squares-structural equation modeling with the help of SmartPLS version 4 to validate the measurement model.

The findings revealed that all six direct hypotheses were supported. However, out of four hypotheses of mediation, one was not supported. Besides, a sequential mediation of green supply chain environmental cooperation and green human resource management was supported. The findings illustrated that green supply chain practices positively influence all used variables.

This research provides practical insight to practitioners to implement green practices in their supply chain networks for social, economic and environmental sustainability and compliance with SDG-12 and SDG-13. The sustainability was validated in a higher-order construct (HOC) (formative), including sequential mediation in the model with the support of resource dependency theory. Therefore, this study adds substantial literature to the existing body of knowledge.

This research provides an interdisciplinary framework by adding knowledge to the Resource Dependency Theory to address Sustainable Development Goals-12 (SDGs) and SDG-13. Likewise, this research provides an extension towards the body of knowledge on the issue, which can be used in future research and critical examinations for cleaner and sustainable production. So far, in Pakistan, no research has looked at the function of these integrated variables in the manufacturing industry with a diligent focus on sustainability as it was validated in a higher-order construct (formative) with one sequential mediation, which makes this research unique.

The purpose of this study is to present a complete framework that defines the link between choices and decision criteria based on existing research on digital influencers (DIs) connected to consumer purchase intentions. The primary goal of this article is to assess the effect of DIs on customer purchase intentions via the creation of an integrated knowledge-based system (KBS).

The suggested KBS is based on the fuzzy analytic hierarchy process (AHP), which creates a link between DI elements and their overall effect on consumer purchase intentions.

With the help of a KBS, the performance of DIs may be evaluated. It demonstrates the link between choices connected to factors and decision criteria of various variables, demonstrating the beneficial effect of DIs in molding customer purchase intentions in the organic skincare industry.

The proposed KBS would aid marketing managers and decision makers in assessing the effect of DIs on customer purchase intentions. This research would also give decision makers with extensive information on influencer marketing and crucial elements that have a significant effect on customer purchase intentions.

This is the first research to employ the fuzzy AHP methodology and KBS in relation to influencers' effect. No prior research has targeted the organic skincare industry to assess the effect of Internet influencers on consumer purchase intentions. Furthermore, the KBS offers a holistic and complete way to studying influencers' effect on cost per impression (CPI) by establishing a linkage between choices and decision criteria.

This paper aims to find the impact of blockchain supply chain on supply chain performance with a mediating role of supplier trust, traceability and transparency.

Data was collected using the purposive sampling technique on a five-point Likert scale from 150 respondents. For data analysis, IBM SPSS and Smart PLS 3.3.7 were used to test the hypotheses by evaluating the structural equation modeling.

The blockchain supply chain found a significant effect on supply chain performance. Moreover, there is a substantial effect of the blockchain supply chain on supply chain performance via mediators, including supplier trust, supply chain traceability and supply chain transparency. Further, the mediation type of all mediators was full mediation in the relationships between blockchain supply chain and supply chain performance.

The research findings are helpful for industrialists, supply chain practitioners and policymakers. The practitioners can adopt blockchain technology to enhance inter-organizational collaboration, develop trust, data visibility and traceability, and critical decisions, ultimately bringing sustainable growth for the firm.

The outcomes of this research enrich the literature and share the impact of one of the most trending technologies in the supply chain perspective. Future research can empirically test the relationship between blockchain and supply chain sustainability.