Optimization Analysis of Supply Chain Based on E-commerce

Amidst the swift expansion of the global trade economy, enterprises are confronted with escalating competition within their industries. Enhancing market competitiveness to boost economic efficiency emerges as a pivotal strategy for ensuring corporate viability. This study employs applied mathematics to refine the optimization of supply chain management, thereby offering a novel approach to augmenting management efficacy in enterprise supply chains. Initially, the research adopts mathematical models tuned to the traditional structure of enterprise supply chains, addressing prevalent profiling issues. Subsequently, it introduces a two-tier planning model to facilitate multi-objective decision-making in supply chain management. This model is rigorously applied to resolve various decision-making scenarios. An empirical analysis is conducted using Company M as a case study. Post-optimization, Company M's inventory exhibited only one instance of material shortfall, involving 132 items. The capital tied up in inventory was significantly reduced to 214,092 yuan—a decrease of 36,319 yuan compared to the capital occupied under traditional supply chain management methods. Furthermore, the optimized supply chain management system demonstrated a notable increase in the average inventory turnover rate to 12.3507%, marking an improvement of 3.6923% over the traditional model. The findings underscore the efficacy of the proposed optimization in enhancing the economic efficiency of enterprise supply chain management. This optimization not only streamlines operations but also provides robust support for the ongoing development of enterprise supply chains.

Prove the effectiveness and efficiency of supply chain management through the application of a StartUp product. The methodology used in this research is a qualitative approach, namely through participatory observation, depending on experience, case studies and other literature related to measuring the effectiveness and efficiency of Supply Chain Management through the application of a StartUp product. It seeks to integrate work in supply chain management, by implementing a StartUp product into one partnership. Cooperation that results in effectiveness and efficiency in the scope of work. The findings obtained are effective ProductStartUp and efficiency of Supply Chain Management, namely by facilitating information, logistics, making references, strategies and reducing risks as well as reducing costs and reducing the risk of reducing complaints, and increasing satisfaction. This research provides many fields, where researchers can complete additional research and develop further research agendas. Originality value - This paper provides some insight into the effectiveness and efficiency of Supply Chain Management, focusing on facilitating information, logistics, making references, strategies and reducing risks while also reducing the cost of reducing complaints, and increasing satisfaction. towards supply chain management.

This study explores the enhancement of Supply Chain Management (SCM) efficiency in the Philippines' modular construction sector through Integrated Project Delivery (IPD). It highlights the critical alignment of SCM success factors with IPD principles, emphasizing the importance of collaboration in modular construction projects. Quantitative analysis via surveys among modular construction professionals assesses IPD's impact on SCM efficiency, uncovering a positive correlation between IPD adoption and compliance with SCM success factors, particularly in larger organizations. This reveals the benefits of early collaboration and shared management practices. The research proposes a comprehensive framework tailored to the Philippine construction industry to optimize SCM efficiency by integrating modular construction with IPD principles. This strategy aims to tackle unique organizational and individual challenges, offering insights for improving SCM practices through IPD. The study paves the way for superior project delivery in developing economies and calls for future research into IPD and SCM risks, the influence of organizational structures, and the role of emerging technologies and cultural factors in modular construction.

The development of globalization has made digital technology play an important role in increasing the efficiency of supply chain management to ensure that its products are truly halal at the point of purchase for consumers. The technology that plays an active role in supply chain management is artificial intelligence (AI). This study aims to determine the effectiveness of implementing AI in halal product supply chain management. The object of this study is a scientific article that implements AI technology in halal product supply chain management with a qualitative approach through the Systematic Literature Review (SLR) method. Literature studies were conducted using Google Scholar and Science Direct to obtain detailed and up-to-date information on the topics to be studied. This study found 12 AI models that can be used in supply chain management. However, its implementation in the field of halal supply chains has not been widely implemented. This study also found that the implementation of AI in the halal product supply chain can improve operational efficiency and improve supply chain performance. However, successful adoption depends on technological readiness, good collaboration between technology and human expertise, and consumer trust. Investing in AI-based systems can significantly improve supply chain integrity and consumer trust.

Inventory optimization is pivotal in mitigating economic losses and enhancing efficiency in supply chain management. This paper examines the challenges associated with traditional inventory practices, including inefficiencies, demand variability, and supply chain disruptions, which lead to substantial financial and operational setbacks. Building on theoretical foundations and insights from existing research, a comprehensive inventory optimization framework is proposed, integrating advanced technologies such as Artificial Intelligence (AI), the Internet of Things (IoT), and cloud-based systems. The framework emphasizes data-driven decision-making, real-time tracking, lean inventory management, and sustainability, offering scalable solutions for diverse industries. Practical recommendations for implementation include investments in advanced technologies, collaborative supply chain practices, and continuous performance monitoring. The proposed framework aims to reduce costs, improve operational resilience, and align inventory management with broader economic and environmental goals. By adopting this innovative approach, organizations can navigate the complexities of modern supply chains and achieve long-term success.. Keywords: Inventory Optimization, Supply Chain Management, Economic Losses, Advanced Technologies, Lean Inventory, Sustainability.

Blockchain technology and smart contracts are emerging as transformative tools for enhancing transparency and efficiency in supply chain management and vendor relations. Traditional supply chains often face challenges such as inefficiencies, lack of transparency, and susceptibility to fraud (Kouhizadeh & Sarkis, 2018). Blockchain, a decentralized ledger technology, coupled with smart contracts, which are self-executing contracts with the terms directly written into code, offers promising solutions to these challenges (Wang, Han, & Beynon-Davies, 2019). This paper explores the application of blockchain and smart contracts in these domains, examining their potential to provide immutable records, streamline processes, and mitigate risks (Casado-Vara et al., 2018). Through a comprehensive analysis of current literature and case studies, we identify key benefits including improved transparency, enhanced efficiency, and better risk management (Christidis & Devetsikiotis, 2016; Tian, 2016). Our findings suggest that blockchain and smart contracts can significantly improve supply chain transparency and vendor management, though their implementation requires careful consideration of technical, regulatory, and organizational factors (Saberi et al., 2019). Notable case studies, such as Walmart’s blockchain pilot for food safety and De Beers' diamond tracking initiative, illustrate the practical benefits and challenges of adopting these technologies in real-world scenarios (Casino, Dasaklis, & Patsakis, 2019; Kshetri, 2018). Despite the promising outlook, further research is needed to address scalability, interoperability, and regulatory compliance issues to fully realize the potential of blockchain and smart contracts in supply chain management (Hughes et al., 2019).

Purpose This study aims to explore the interplay between supply chain collaboration and disruption and their joint impact on supply chain resilience. It also aims to identify the configurational conditions under which supply chain resilience is achieved, providing a holistic framework for enhancing supply chain management practices amidst disruptions. Design/methodology/approach This study uses a fuzzy-set qualitative comparative analysis (fsQCA) to investigate the complex causal mechanisms linking supply chain collaboration and disruption with supply chain resilience. The research integrates three dimensions of collaboration with three dimensions of disruption, offering a comprehensive understanding of supply chain resilience factors. Findings This study reveals that supply chain resilience is not solely dependent on individual elements but is shaped by unique configurations of collaboration and disruption factors. Information sharing emerges as a core factor in high resilience, while the absence of supply and facility disruptions significantly influences resilience outcomes. The research highlights the importance of multiple paths leading to supply chain resilience and the asymmetrical impact of collaboration and disruption. Research limitations/implications The study acknowledges limitations due to data sourced exclusively from China and the use of static data, suggesting the need for cross-temporal and international samples to enhance broader applicability. Future research should consider dynamic temporal changes and diverse theoretical perspectives to comprehensively examine the factors influencing supply chain resilience. Practical implications The research underscores the critical role of information sharing in bolstering supply chain resilience and advises firms to prioritize it in their strategies. It also highlights the importance of mitigating supply and facility disruptions through supplier diversification and robust contingency planning, offering actionable insights for enhancing operational efficiency and risk management in supply chain management. Social implications This research has significant social implications, particularly in the context of global supply chain disruptions. By identifying key factors that enhance supply chain resilience, it can help businesses better prepare for and respond to crises, thereby reducing economic instability and social disruption. Improved resilience can lead to more stable employment, maintain the flow of essential goods and services and contribute to overall societal well-being during times of supply chain stress. Originality/value This study offers original insights by applying fsQCA to explore the multifaceted relationship between supply chain collaboration, disruption and resilience. Its value lies in revealing the complex causal configurations that lead to high or low levels of supply chain resilience, challenging traditional linear perspectives and providing a nuanced understanding that can guide both academic research and practical supply chain management strategies.

Today successful business success relies on efficient supply chain management (SCM) in the ever-changing global marketplace. Traditional SCM processes are subject to inefficiency, manual intervention, destruction, etc. This paper evaluates the contribution of Pega’s Robotic Process Automation (RPA) in effecting transformation in SCM efficiency. Powered by AI and Machine Learning, Pega’s RPA streamlines processes like order management, inventory tracking, demand forecasting and so much more, moving supply chains from reactive to predictive. This was a mixed methods approach combining case studies, surveys, and interviews with industry professionals. Results indicate significant operational improvements: This resulted in a 40 percent reduction in processing times, an 85 percent decrease in manual errors, and a 30 percent reduction in operational costs. Another case example illustrates how Pega’s RPA improves scalability, decreases errors and is cost-efficient. While the technology is beneficial, the initial costs are high, there is workforce adaptation, and enough makes the integration challenging. The findings underscore the need for strategic planning and workforce readiness for implementation success. Finally, the study concludes that Pega’s RPA is not just another tool for automation, but an investment in supply chain modernization that provides actionable insights to organizations and serves as a foundation for future RPA research on scalability and integration with new technology. Keywords: Supply Chain Management (SCM), Robotic Process Automation (RPA), Pega, Operational Efficiency, AI and Machine Learning, Cost Reduction, Scalability

This study explores the pivotal role of HR analytics in enhancing supply chain management (SCM) efficiency, marking a significant shift from traditional HR practices to data-driven decision-making. The main objective was to bridge the gap between HR analytics and SCM performance, highlighting the transformative potential of integrating advanced data analysis in workforce management to optimize supply chain operations. Employing a systematic literature review and content analysis methodology, this research meticulously analyzed peer-reviewed articles, conference papers, and scholarly books from prominent databases. The search strategy was comprehensive, incorporating a broad spectrum of relevant keywords to ensure the inclusion of significant studies that address the integration of HR analytics into SCM. Key findings underscore the transformative power of HR analytics in SCM, revealing that data-driven HR practices significantly contribute to operational efficiency, strategic decision-making, and enhanced competitive advantage. Advanced analytical tools, such as AI, machine learning, and predictive analytics, have been identified as critical in optimizing workforce performance and aligning human capital with supply chain objectives. The study concludes with actionable recommendations for practitioners, leaders, and policymakers, emphasizing the importance of robust data governance, cross-functional collaboration, and the development of analytics competencies. It also outlines emerging challenges and opportunities in leveraging workforce analytics, suggesting directions for future research, particularly in exploring the strategic impacts of HR analytics on supply chain resilience and sustainability. This research contributes to the growing body of knowledge on the strategic integration of HR analytics in supply chain management, offering a roadmap for organizations seeking to enhance supply chain efficiency through data-driven HR practices. Keywords: HR Analytics, Supply Chain Management, Data-Driven Decision-Making, Workforce Optimization.

In today’s dynamic business environment, delays and inefficiencies which are inherent across supply chains have continued to weaken the responsiveness of organizations and tend to reduce customer satisfaction. Many of these challenges stem from fragmented workflows, undocumented procedures, and a lack of coordination between departments, factors that often result in longer lead times, missed deliveries, and higher operational costs. One promising solution is process mapping, a strategic tool that enables managers to visualize workflows, detect bottlenecks, and optimize operations. Despite its growing adoption, there is limited empirical evidence on its direct effect on time efficiency, especially within the Nigerian context. This study explores how process mapping influences time efficiency in supply chain management (SCM), with a focus on Nigerian firms operating in the manufacturing, retail, and logistics sectors. A quantitative correlational design was employed, and data were collected from 120 SCM professionals through structured questionnaires. The responses were analyzed using SPSS Version 26, applying descriptive statistics, independent samples t-tests, and multiple linear regression. Results show a significant positive relationship between process mapping and time efficiency (R² = 0.67, p < 0.001). Among the tools evaluated, flowcharts and swim lane diagrams proved most effective in reducing lead time and cycle time. Additionally, employee training and the use of digital mapping platforms such as Lucidchart and Bizagi emerged as strong predictors of improved performance. Organizations that consistently applied these practices reported quicker deliveries, better internal coordination, and fewer operational delays. These findings offer valuable insights for supply chain managers and policymakers seeking to improve operational agility in resource-constrained environments. The study emphasizes the need to institutionalize process mapping as a routine practice within supply chains to achieve sustainable, measurable improvements in time-based performance.

The efficiency of the supply chain of pig breeding in China is low due to the structure of scattering raising-households and the competition among the enterprises within the supply chain is also fierce. Faced with the uncertainty of the market environment and the complexity of the decision-making environment, how to choose the competitive strategy and competition mode for pig breeding enterprises and determine the optimal sales price and sales volume is the key problem to be solved by enterprises in the supply chain management. Based on this, this paper constructs a model of competition between two manufacturers (large farmers) and two retailers (pork wholesalers) in the pig breeding industry under fuzzy environment. Under the three modes of Cournot competition, Collusion competition and Stackelberg competition, the competition model between two retailers is constructed in turn, and the optimal strategy of each manufacturer and retailer is obtained. Finally, the mental state index is introduced to describe the decision maker’s attitude or preference to the risk, which can make the model more reasonable. The result shows that the change of the mental state index will not only influence the optimal solution, but also affect the final decision result.

The advent of blockchain technology substantially transformed chain of supplies management procedures. This article describes how blockchain technology optimizes supply chain management by increasing its efficiency and transparency. Most supply chain system problems, including inefficiencies and a lack of openness coupled with fraud vulnerabilities, have the potential to be resolved by leveraging blockchain technology, which creates an immutable, transparent ledger. Blockchains and the chain of supply management association alongside decentralized ledger key features and logistics are also outlined throughout this research. The paper handles both the disadvantages and difficulties in deploying blockchain systems for supply chains while recommending strategies for current use and further research initiatives.

Contributors

This study aims to analyze the effect of the effectiveness of the implementation of supply chain management and operational cost efficiency on the company's performance with competitive advantage as a moderating variable. The research population is the decision maker on the CV. Eight Eight as many as 36 people. The results showed that the effect of the effectiveness of the implementation of supply chain management and operational cost efficiency had a positive effect on company performance. Meanwhile, competitive advantage weakens the effect of the effectiveness of implementing supply chain management and operational cost efficiency on company performance.
 Keywords: Supply Chain Management Effectiveness; Operational Cost Efficiency; Company Performance; Competitive Advantage.

Here is its sentence format:Blockchain in supply chain Blockchain technology can provide traceability, reduce counterfeiting, and improve overall process efficiency in your supply chain management. Yet obstacles, including but not limited to scalability, complex integration, cost implications, energy consumption, and regulatory hurdles, have prevented widespread adoption. These factors create numerous obstacles due to the significant resources required for implementation while also ensuring a minimized environmental impact. To mitigate the complexity related to the integration of blockchain technology, the proposed framework ensures seamless integration with existing legacy systems. Additionally, the study articulates real-world case studies that highlight the practical use of blockchain technology in increasing product traceability and reducing instances of counterfeiting across world supply chains. This framework ensures that blockchain solutions comply with global regulatory requirements, enabling simple and uniform adoption within various industries and geographical areas. This work develops a paradigm-transforming approach for modern supply chains that vindicates critical supply chain challenges such as data security, efficiency, and sustainability and further advances the global deployment of blockchain technology to enable transparent supply chain processes and prevent counterfeiting.