Simonov Kusi-Sarpong

The pharmaceutical industry faces unprecedented challenges in ensuring uninterrupted access to life-saving medications while navigating complex regulatory landscapes, global supply chain disruptions, and evolving patient expectations. This chapter presents a comprehensive framework for architecting patient-centric pharmaceutical supply chain control towers that integrate three critical imperatives: visibility, resilience, and compliance. Drawing on recent literature from 2020 to 2026, we synthesise theoretical foundations from supply chain management, information systems, and healthcare operations to propose a three-pillar framework supported by enabling technologies, including the Internet of Things (IoT), blockchain, artificial intelligence, and digital twins. The chapter provides practical guidance on implementation journeys, governance structures, change management strategies, and patient-centric performance measurement through balanced scorecards.

This study examines and evaluates renewable energy (RE) supply chain sources to guide practitioners in selecting and investing in viable RE supply chains that drive the transition to RE, sustainability, and value creation for stakeholders. The relative influence of the various sustainability factors on key RE sources was empirically evaluated using multi-criteria decision-making analysis. Supplementary data were also analysed using the same techniques to assess the tacit factors affecting the transition to RE. Interviews with experts were evaluated using template analysis to explore latent factors further to support the transition to RE. The results revealed solar energy as the most economical, environmentally, and socially preferred cleaner energy with fewer barriers to overcome, followed by wind energy, Biomass, geothermal, and hydropower energy, respectively. The AHP and TOPSIS models provide novel rankings for RE sources to guide stakeholders. Energy supply chain participants may embrace the results to make strategic decisions. The study contributed to the literature by proposing original empirical models that facilitate understanding the viability of various RE supply chain sources and how the transition to RE will contribute positively to sustainability performance and assist supply chain practitioners in making strategic decisions.

Purpose: It is important to understand the factors that are significant in supply chain (SC) collaboration decision making and whether supply chain collaborative factors that are considered in the literature are still valid. To date, SC collaboration has not been extensively studied in the literature with supply chain finance (SCF) factors to evaluate SCF performance. Therefore, in this paper, the authors investigate the interrelationships between SCF and supply chain collaborative (SCC) factors for achieving SCF performance. The authors identified the most important factors from the literature on SCF and SCC and with inputs from experts in the textile industry in Pakistan.Design/methodology/approach: The authors employed the Gray-Decision Making Trial and Evaluation Laboratory approach to help examine the cause-and-effect relationship between the factors and identify the influence of each factor on the others.Findings: The findings showed that the most prominent factors of the study are “level of digitalization”, “information sharing”, and “collaborative communication”, and “most effect factors of this study are incentive alignment” and “information quality”. Furthermore, the “Level of digitalization” was identified as the factor with the central role and most significant correlation with other factors.Research limitations/implications: The major implication of the study is that textile industries should effectively develop their supply chain decisions after analyzing their internal and external factors, which will help in developing strategies that will facilitate better management of SCF relationships. The limitations of the study are that only 15 SCF and supply chain collaborative factors were considered, and time and scope are also limited. This study is only applied in the textile industry, so generalization may be limited.Originality/value: To date, this study is the only one that has taken into consideration SCC with SCF factors to evaluate supply chain performance. This paper therefore makes this initial attempt and original contribution to this discussion, which can be helpful for those working to enhance supply chain performance, such as practitioners and policymakers.

This study aims to evaluate the relative importance of critical performing supply chain (SC) processes instrumental in reducing the Time to Market (TTM) of a firm by taking the case of an apparel company. An integrated decision support system based on the Fuzzy Inference System (FIS) and Analytic Hierarchy Process (AHP) has been employed to prioritize the critical strategic factors and their relevant sub-factors essential for TTM. This approach also allows determining the degree of impact of each factor on the company’s TTM. The results show the instrumental role of Plan and Deliver in SC processes in reducing the TTM. Within Plan and Deliver, the role of demand forecasting error and service quality was found to be substantial in controlling TTM. The findings of this study can be helpful for the managers and decision-makers to identify the key areas at the operational level that need to be improved and have an impact on strategic level performance, i.e. TTM. The use of a decision support system to identify the critical supply chain processes and sub-processes is a major contribution of this study.