Revolutionizing Pharmaceutical Data Transformation with Microservices Architecture

Title: Optimization of Chemical Supply Chains for Regulatory Compliance and Sustainability: An SME-Focused Framework for India and the EU Abstract: Chemical supply chains are increasingly challenged by strict regulatory requirements—such as the European Union’s REACH and the Globally Harmonized System (GHS)—alongside growing expectations for sustainability and cost efficiency. For small and medium-sized enterprises (SMEs), these dual pressures are particularly acute due to resource constraints and exposure to multi-jurisdictional markets in India and the EU. Existing supply chain research often treats regulatory compliance and sustainability as separate domains: compliance studies emphasize legal and documentation requirements, while sustainability studies focus on environmental and operational efficiency. This separation limits the development of integrated, practical decision-support approaches for SMEs. This paper proposes a conceptual framework for optimizing chemical supply chains by integrating regulatory compliance and sustainability objectives. The framework highlights four key dimensions: compliance drivers (REACH, GHS, hazard communication), sustainability drivers (circular economy, carbon reduction), SME constraints (limited resources, expertise), and supply chain decision areas (supplier selection, logistics planning, inventory management). By analyzing trade-offs and synergies between compliance, sustainability, and efficiency, the framework offers pathways for SMEs to align operations with both regulatory obligations and sustainability goals. This study bridges two fragmented research areas and proposes an integrated agenda for developing scalable, SME-focused tools. The outcomes are intended to guide both academics and practitioners in designing compliant, resilient, and sustainable chemical supply chains. Keywords: Supply Chain Optimization, Regulatory Compliance, Sustainability, SMEs, REACH, GHS

This paper proposes a groundbreaking theoretical model specifically designed for the FMCG sector, focusing on optimizing supply chain dynamics to balance operational efficiency with customer satisfaction. Drawing on hands-on strategies and problem-solving abilities, the framework aims to offer practical solutions for common challenges faced by FMCG operations managers, such as inventory management, demand forecasting, and efficient resource allocation. The fast-moving consumer goods (FMCG) industry is characterized by intense competition, short product life cycles, and rapidly changing consumer preferences. In this challenging environment, optimizing supply chain dynamics is crucial for FMCG companies to achieve operational efficiency and enhance customer satisfaction. This concept paper presents a novel framework for integrating operational efficiency and customer satisfaction in FMCG supply chains, aiming to provide insights and strategies for FMCG companies to improve their supply chain performance. The framework emphasizes the importance of aligning supply chain strategies with customer needs and preferences. By focusing on key areas such as inventory management, distribution network efficiency, and technology integration, FMCG companies can improve their supply chain agility and responsiveness. Additionally, the framework highlights the importance of leveraging data analytics and technology to enhance supply chain visibility and decision-making. Implementing the framework requires collaboration among stakeholders, including suppliers, manufacturers, distributors, and retailers. By working together to optimize supply chain processes and enhance customer service, FMCG companies can gain a competitive advantage in the marketplace. Overall, the framework offers a comprehensive approach to optimizing FMCG supply chain dynamics, with the ultimate goal of improving operational efficiency, reducing costs, and enhancing customer satisfaction.
 Keywords: FMCG, Supply Chain, Customers, Framework.

In recent years, with the emergence of new technologies, big data, artificial intelligence, and other technologies have had a greater impact on supply chain management. Among them, big data analysis capability, as one of the important capabilities that supply chain enterprises should have, has a particularly significant impact on supply chain resilience management. From the perspective of performance management, based on supply chain resilience theory, the relationship between the supply chain performance management level, supply chain collaboration, and other supply chain resilience elements, as well as big data analysis capability and supply chain performance can be analyzed to study the impact of big data analysis capability on supply chain performance of enterprises of different scales. The impact on the level of supply chain performance is being studied. This paper investigates the problem of supply chain performance evaluation and optimization based on the LMBP algorithm and provides some references for supply chain performance evaluation and optimization.

Purpose The purpose of this paper is to investigate the complex interrelationships among the key constructs, supply chain orientation (SCO), supply chain integration (SCI) and supply chain performance (SCP) in Indian manufacturing industries. These relationships have been studied using the relational view (RV) and the knowledge-based view (KBV) theoretical perspectives. Design/methodology/approach The conceptual model was derived from the existing body of knowledge in the supply chain domain. The study is based on a sample size of 122 data collected via face-to-face meetings with the Indian manufacturers using well-established scales. The covariance-based structural equation modeling was used to test the proposed hypotheses. Findings In Indian manufacturing and supply chains, SCO has a positive relationship with SCI and SCP. Moreover, the direct impact of SCO on SCP diminishes when SCI is used as a mediating variable. This study also observes positive impact of: i) SCO on SCP, ii) SCI on SCP and iii) discovery of mediating role of SCI on SCP under the theoretical lenses of RV and KBV. Research limitations/implications Cross-sectional survey of manufacturing firms of one country (using one response per firm) calls for validation covering other parts of the world and demands a longitudinal survey. This research will trigger more scholarly, practice and policy debate among researchers studying Indian and emerging economies context. Practical implications The notion of a holistic view of the SC with a focus on improving the customer value can enhance strategic partnerships among the SC partners (i.e. SCI) and overall SCP. Firms should make efforts to include SCI in SC designs to successfully transform SCO into SCP. Originality/value The originality of the research lies in studying the complex interrelationships among key concepts of SC in a unique Indian manufacturing context. The Indian supply chains operate in a set of unique characteristics, which have been detailed out in this paper. This paper not only establishes the mediating role of SCI for overall SCP in emerging economies but also enhances the scholarly knowledge in the SC domain. Most studies report SCO as a single-order construct, measured by scales comprising of only few items. The second-order SCO measures in this study bring credibility to the findings. Additionally, it contributes to both academicians and practitioners alike in the context of an integrated SC in emerging economies.

The article discusses supply chain optimization based on blockchain supply chain technology and genetic algorithm in the context of IoT to improve the availability of goods and the security of logistics information, improve supply chain efficiency and reduce transportation costs. First, the basic theories of supply chain technology, supply chain optimization and genetic algorithm are introduced, and supply chain optimization with collaborative logistics information management is analyzed. Then, a supply chain network optimization model based on genetic algorithm is established and the optimization results are analyzed. The optimization results show that applying blockchain technology to collaborative logistics information management system improves the overall efficiency of supply chain logistics; using genetic algorithm, the logistics distribution cost is reduced. The study is innovative in optimizing the collaborative logistics information management system in the logistics supply chain and the logistics distribution channel by using blockchain technology and genetic algorithm to improve the security and availability of logistics information. The case study shows that the optimization of supply chain logistics using blockchain technology and genetic algorithm improves efficiency, reduces costs, improves corporate governance and economic efficiency, and increases the competitiveness of the company.

Impact of supply chain digitalization on supply chain resilience and performance: A multi-mediation model

Purpose The purpose of this paper is to illustrate how blockchain technology can improve supply chain adaptability, alignment and agility which collectively enhance competitive advantage which in turn influences firm performance. Design/methodology/approach The conceptual framework of the present study is developed by conducting an extensive literature review on blockchain technology, supply chain adaptability, alignment, agility and competitive advantage. The sample data were collected from 397 supply chain practitioners in India to validate the conceptual model. Confirmatory factor analysis was conducted to ascertain the validity of the measures used and a structural model was analyzed for testing the proposed conceptual framework. Findings The results of the present study show that blockchain technology can improve supply chain adaptability, alignment, agility which lead to competitive advantage, which leads to better firm performance. Besides, trust generated through blockchain use also increases firm performance. Research limitations/implications Currently, the respondents do not have practical experience of using blockchain technology. They have responded based on their knowledge about supply chain and blockchain which they acquired from published sources. Different supply chains require different strategic choices and different information needs. But the present study assumes that all supply chain needs are identical. The present study assumes that government regulations regarding blockchain technology are favorable; however, currently, there is no legal framework to address blockchain technology. The findings of the current study indicate that companies not only should create more awareness regarding blockchain but also should actively work with IT companies that are engaged in developing blockchain-based supply chain solution. Managers, as well as IT companies and academicians, should join hands to study and develop a framework for regulating blockchain technology and suggest these to the policy actors. Practical implications The present study shows that supply chain practitioners are confident that blockchain technology will help improve supply chain parameters. These findings can help IT companies and their marketers for developing and promoting blockchain-based IT applications. In addition, the important implication for supply chain practitioners is that blockchain helps in creating a competitive advantage and increases firm performance. Originality/value The effect of IT on important supply chain variables has been studied in the past; however, there is not a single study which sheds light on how disruptive technologies such as blockchain will affect supply chain adaptability, alignment, agility and firm performance.

Microservices architecture has emerged as a transformative paradigm in modern software development, enabling organizations to build resilient and scalable distributed systems. This comprehensive exploration delves into the fundamental principles, implementation strategies, and real-world applications of microservices architecture. The architectural framework facilitates independent service deployment, enhanced fault isolation, and streamlined maintenance processes while promoting technology stack flexibility. Through the implementation of sophisticated monitoring patterns, testing strategies, and data consistency mechanisms, organizations can effectively address common challenges in distributed systems. The integration of enterprise architecture principles with microservices has demonstrated significant improvements in resource utilization, system reliability, and operational efficiency. The adoption of API gateway patterns, security frameworks, and containerization technologies further enhances system performance and scalability. Real-world applications, particularly in e-commerce platforms, showcase the practical benefits of microservices architecture in managing complex business operations while maintaining high availability and performance standards.

Background This systematic assessment of 408 research publications from 2004 to 2024 examines how talent management (TM) improves supply chain optimization (SCO). Objective The main goal is to find and study TM CSFs that affect SCO. The research distinguishes internal elements (consumer expectations, flexibility, and cost reduction) from external aspects (human capital and sustainability) and provides insights into successful TM techniques that enhance supply chain performance. Methods This research examines talent management (TM) and supply chain optimization (SCO) using a systematic literature review and bibliometric analysis. The study maps co-occurrence networks and significant themes using VOSviewer and RStudio on 408 Web of Science articles. TM’s influence on SCO is assessed by categorizing key success factors (CSFs) and showing trends, topic clusters, and literature gaps. Results show that strategic TM practices including personnel planning and performance management improve operational efficiency, innovation, and market response. The paper also emphasizes TM integration into supply chain strategy by highlighting TM and SCO developments. Implications This study highlights the relevance of TM in SCO and lays the groundwork for future research on TM and SCO.

Aim: Recent innovations in artificial intelligence (AI) transform the supply chain management system and allow organizations to predict demand, regulate the stock, reduce risk, and optimize the logistics process, becoming more specific and quicker. The purpose of this study is to examine how end-to-end supply chain optimization through artificial intelligence (AI)-based predictive analytics can improve the accuracy of the forecast, inventory management, and logistics effectiveness. Methods: Based on modern-day case evidence and measurements, the analysis will be directed towards quantifiable goals: 10 30% reductions in MAPE; 5-15% reductions in days-in-inventory; 10-20% reductions in logistics cost per order; and 4-8% reduction percentage payback in on-time-in-very-full and ROI of over 20%. The study adopted a comparative analytical design using secondary data from multiple industries to assess the effectiveness of AI-driven predictive models (gradient boosting, random forests, and LSTM) against classical time-series forecasting approaches. Results: The findings show that companies with unified AI platforms, feature stores, MLOps pipelines, and balanced data models are binding significantly more adoption and return compared to the competitors, which use individual instruments, since the mutual data resource, lineage, and governance decelerate friction and aid learning speed. Conclusion: The study concludes that predictive analytics, when integrated into unified AI platforms, enhances supply chain resilience and sustainability by converting real-time data into actionable insights for cost and service optimization. Recommendation: The study proposes that organizations should embrace unified AI structures that have controlled data models to achieve optimal predictive analytics performance and scale across supply chain operations.

Drawing on the Transaction Cost Economics (TCE) and taking the perspective of a developing economy, the study examined the impacts of governance mechanisms (GM-formal control and social control) on supply chain (SC) performance (operational efficiency and service & market performance). Data were collected using questionnaires from 152 firms operating in the most industrialized regions of Ghana. Structural equation modelling technique (using LISREL 8.5) was employed in estimating the study’s model. The study finds significant positive associations between formal control and operational efficiency; and between social control and service & market performance. The study also finds that within the research context, social control is antecedent of (adherence to) formal control; and that the effect of social control on operational efficiency is fully channelled via formal control. These findings imply that firms’ ability to institute and implement GMs would present them opportunities to enhance the performance of their SCs. Theoretically, the results suggest the potential mediating role of formal control in the link between social control and SC performance; which means that having in place formal controls is necessary for firms in this part of the world (who mostly rely on social control) to better experience benefits arising out of social relationships.

This article examines the implementation of blockchain technology in pharmaceutical supply chain management through SAP's integrated enterprise solutions. The article analyzes how the combination of SAP Blockchain and SAP Integrated Business Planning addresses critical challenges in pharmaceutical supply chains, including product authenticity verification, regulatory compliance, and supply chain transparency. Through comprehensive analysis of implementation data from multiple pharmaceutical organizations, the article demonstrates the effectiveness of blockchain integration in reducing counterfeit drugs, enhancing traceability, and streamlining compliance processes. The article highlights significant improvements in supply chain visibility, operational efficiency, and regulatory adherence through strategic industry partnerships with major pharmaceutical companies. The article reveals how blockchain technology, when coupled with enterprise systems, transforms traditional pharmaceutical supply chains into transparent, secure, and efficient digital ecosystems.

Background: Blockchain technology (BCT) is widely recognised for its potential to transform supply chain (SC) operations by enhancing SC transparency, hence fostering trust among SC partners. However, most empirical research has explored its direct impact through conceptual and causal models, while limited studies have explored how SC professionals themselves perceive the role of BCT in strengthening SC transparency and trust among SC partners, especially within emerging economies.Objectives: This study explores the perceptions of SC professionals regarding BCT technology, SC transparency and trust. The focus is on understanding how practitioners interpret the relational value of BCT in the context of emerging economies, with Egypt serving as a representative case.Method: This study employs an exploratory quantitative research approach through a quantitative method that utilises surveys to collect data from 63 SC professionals working in organisations operating in Egypt.Results: Findings confirm that professionals perceive BCT as a tool that positively influences both SC trust and SC transparency, with SC transparency partially mediating the relationship between BCT and trust. However, SC transparency alone does not fully explain trust-building, highlighting the importance of other BCT features such as immutability, traceability and smart contracts.Conclusion: This study reveals that SC professionals in emerging economies perceive BCT as a multifaceted trust-enabling mechanism, operating through SC transparency and other technological affordances.Contribution: By capturing practitioners’ perceptions, this study offers exploratory observations about the perceived relationship among BCT, SC transparency and trust, offering evidence-based understanding from an emerging economy perspective. The findings inform both academics and managers on how BCT’s perceived benefits can shape future trust-oriented SC practices.

Measuring the influence of digital twins on the sustainability of manufacturing supply chain: A mediating role of supply chain resilience and performance

This study aims at investigating the roles of supply chain integration and innovation on supply chain performance through a mediation mechanism of supply chain. This study develops a theoretical framework based on resource-based view and dynamic capability theory. Based on a quantitative study of 214 Saudi hospitals, an empirical analysis was made using a structural equation modelling with AMOS. Results revealed that supply chain integration and innovation positively affect supply chain resilience and performance. In addition, supply chain resilience has a positive and significant relationship with supply chain performance. Most significantly, the relationships of supply chain integration and of innovation to supply chain performance were found to be partially mediated by supply chain resilience. These results showed that integration and innovation have direct effects to improve supply chain performance and indirect ones when hospitals make efforts in developing their resilience. This study is important for top managers of Saudi hospitals to integrate their supply chains and innovate them to improve their resilience and performance.