Developing inventory optimization frameworks to minimize economic loss in supply chain management

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.

Inventory planning and optimization are crucial components of effective supply chain management, playing a pivotal role in providing a balance between customer demand and operational efficiency. This research article investigates the current landscape of inventory optimization processes, their implementation, and their considerable impact on business performance in the context of recent global supply-chain disruptions and technological advancements. The study also proceeds to examine various characteristics of inventory management, including but not limited to demand forecasting, inventory strategy formulation, and stock replenishment methodologies. By analysis of data from multiple sources and case studies, the effectiveness of different optimization approaches, such as machine learning-based demand forecasting, multi-objective optimization, and advanced inventory models are investigated. The research also delves into the aspects of integration of artificial intelligence and machine learning in developing inventory optimization processes, especially in the face of stochastic demand and supply chain disruptions. Our findings indicate that successful inventory optimization strategies contribute significantly reducing costs, improving customer satisfaction, and increasing overall supply chain resilience. The study reveals that companies implementing data-driven inventory optimization techniques experience a 15-20% reduction in inventory holding costs and a 10-15% improvement in service levels. Additionally, the research highlights the importance technology and human handshake of real-time data analysis, cross-functional collaboration, and adaptive strategies in achieving optimal inventory levels to avoid opportunity cost. The impact of recent global disruptive events, such as the COVID-19 pandemic that was unprecedented, on supply chain management practices is also examined, providing insights into the development of more resilient and flexible inventory systems. This comprehensive examination and evaluation of inventory planning and optimization provides valuable insights for supply chain professionals and researchers, offering a foundation for future advancements in this critical area of business operations in an increasingly volatile and interconnected global market.

Contributors

Implementation and adoption of new technologies are gaining the result of smooth supply chain and logistics operations. Internet of things (IoT) artificial intelligence, including data mining, intensified in all fields of life, particularly in supply chain management and operations. Blockchain technology has the capability to reform the supply chain and logistics operations management. Blockchain provides digital database solutions for all transactions across supply chain and operations management. Radio frequency identification device (RFID) is also helping technology transmit electromagnetic waves to radio-compatible integrated circuits to look after and manage the entire supply chain and logistics operations management. The Fourth Industry Revolution 4.0 refers to the automation, interconnectivity, machine learning, and real-time data that help supply chain and logistics operations management in the 21st century.

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.

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.

A public health emergency of international concern, such as a pandemic, disrupts the normal operation of the global supply chain, which necessitates in-depth research on supply chain management. In this paper, we used bibliometric and content analysis to provide a systematic analysis of the supply chain industry from this background. The descriptive analysis provides insights into the publication growth trajectory, in terms of the contributing authors, countries, and subject categories, which presents an intuitive display of previous research. In addition, the existing research mainly covers three dimensions of supply chain disruption, strategies, and sustainability, which can be clustered into supply chain disruption, disruption recovery, reconfiguration, digital intelligence, optimization, and sustainability. By revisiting the supply chain industry, we explored the transformation of its characteristics in the pandemic, covering themes ranging from expansion to contraction, from traditional to digital intelligence, and from fragile to sustainability, which suggests potential research directions for future studies. This contributes to the further research of supply chain management during the pandemic and provides supply chain managers with a practical approach for dealing with supply chain disruption risks and improving supply chain sustainability in this context.

Purpose– Developing ambidexterity as a dynamic capability is important for firms to sustain their competitive advantage. Moreover, this capability allows firms to build the resiliency to mitigate enterprise risks. The purpose of this paper is to apply two main theoretical frames from the strategy literature, dynamic capabilities, and organizational ambidexterity, to supply chain management (SCM) to examine mitigation strategies for supply chain (SC) disruptions. The authors empirically investigated how the firm’s SC ambidexterity is developed through a dynamic capability-building process and how this, in turn, can mitigate the negative impact of SC disruptions and improve business performance.Design/methodology/approach– This study conducted a field survey to answer the research questions as there exists no archival database with detailed information on ambidextrous SC strategies and dynamic capability. A total of 316 usable responses were received from managers working in the SC area. Confirmatory factor analysis and structural equation modeling were run on SPSS (version 16.0) and AMOS (version 18.0) to test the hypotheses to answer research questions.Findings– Overall, the results of the study confirmed that a dynamic SC capability-building process is an antecedent of SC ambidexterity, and that SC ambidexterity is important to firms as it mitigate the negative impact of SC disruptions and enhance business performance. To take advantage of an ambidextrous SC, through minimizing the negative impact of SC disruptions and maximizing firm performance, firms should continually search for creative ways to satisfy new market needs and adapt to the fast changing business environment.Originality/value– This study applied a dynamic capability-building process and ambidexterity to SCM. From the resilient SC perspective, the study found that the ability to effectively utilize existing resources and create novel strategies for problem solving plays a critical role in addressing SC disruptions.

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.

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).

Modern companies face numerous challenges in supply chain management, particularly due to globalization, increasing competition, and the need for quick adaptation to market changes. Inefficient supply chain management can lead to higher costs, supply delays, and reduced customer satisfaction, which directly impacts financial performance and competitiveness. The study aims to identify methods for improving supply chain management efficiency, taking into account current economic and technological conditions. Given the volatility of global markets, it is crucial to develop adaptive and resilient supply chain strategies that align with both short-term objectives and long-term sustainability goals. The study uses methods of analysis, synthesis, comparative analysis, as well as a systems approach to assess modern supply chain management strategies. The impact of cutting-edge technologies such as Big Data, artificial intelligence, the Internet of Things, and blockchain on optimizing supply chain processes was analyzed. The effectiveness of ERP systems in the context of business process integration and risk management was evaluated. The study identified key issues in supply chain management: insufficient integration between systems, low supply chain transparency, inefficient inventory management, and high logistics costs. To address these issues, the following solutions were proposed: Implementing ERP systems and enhancing their functionality for business process integration; Using Big Data analytics for demand forecasting; Developing risk management strategies, particularly through supplier and transport route diversification; Optimizing inventory and reducing logistics costs by automating and applying flexible supply models. Improving supply chain management efficiency requires active use of modern technologies and innovative optimization methods. Integration of Big Data, artificial intelligence, and the Internet of Things helps reduce costs, shorten delivery times, increase process transparency, and ensure stability in order fulfillment. The proposed solutions will contribute to enhancing the competitiveness of enterprises in dynamic economic conditions.

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.

PurposeThe purpose of this study is to provide insights into the way in which understanding and implementation of disruptive technology, specifically big data analytics and the Internet of Things (IoT), have changed over time. The study also examines the ways in which research in supply chain and related fields differ when responding to and managing disruptive change.Design/methodology/approachThis study follows a four-step systematic review process, consisting of literature collection, descriptive analysis, category selection and material evaluation. For the last stage of evaluating relevant issues and trends in the literature, the latent semantic analysis method was adopted using Leximancer, which allows more rapid, reliable and consistent content analysis.FindingsThe empirical analysis identified key research trends in big data analytics and IoT divided over two time-periods, in which research demonstrated steady growth by 2015 and the rapid growth was shown afterwards. The key finding of this review is that the main interest in recent big data is toward overlapping customer service, support and supply chain network, systems and performance. Major research themes in IoT moved from general supply chain and business information management to more specific context including supply chain design, model and performance.Originality/valueIn addition to providing more awareness of this research approach, the authors seek to identify important trends in disruptive technologies research over time.

The paper presents possible solutions to small farmers in the agricultural sector in a small island setting grappling with challenges of enhancing their local industry and import substitution through a supply-demand chain framework. In 2005, Hawaiian farms produced approximately 363,200 kg of avocados. However, Hawaiian demand for these fruits required an additional 908,000 kg of avocados that were supplied through imports. At the same time, it is worth noting; almost 49% of locally produced avocados did not reach the market. These facts clearly suggest inefficiencies in the local avocado supply chain. Review of the literature on supply chain management suggests a sustainable avocado industry requires an integrated supply and demand chain management system. Hence, a modified conceptual model of supply-chain management called the Supply Demand Integrated Management (SDIM) model is proposed in this paper. Traditional supply chains contain three functional components: supply coordination, physical production and logistic management. In the new model, we propose adding R4D (Research for Development), a public good provided by the government to agricultural industries as an integral part of the supply-demand chain system. It articulates the significance of research and supply chain partnerships between small growers, industry groups, and public agencies. A well-integrated demand/supply chain in the avocado industry allows sharing of vital market information which can contribute to long-term strategic decisions that help local avocado growers increase their competitiveness against foreign imports. It also provides metrics in terms of consumer satisfaction, profitability, competitiveness, self-sufficiency, import substitution and sustainability. The SDIM model as applied to the avocado industry suggests two hypotheses relevant to the current situation. The hypotheses are: (1) There is a lack of coordination between what the farmers are growing and the chefs' (a high-end customer/buyer) preferences; (2) Forming an avocado farmer cooperative will enhance the profitability of local farmers. Survey data was collected from Hawaiian chefs and avocado farmers. Data was analysed using a Duncan multi-range test and a mathematical model, respectively, to test the hypotheses. The test revealed a lack of coordination between what the farmers are growing and buyer preferences. The results from the mathematical model suggested that formation of an avocado marketing cooperative would enhance the profitability of local farmers. Thus, the SDIM framework expands existing body of knowledge about supply chain management and provides useful information to local avocado growers that can help strengthen their supply and demand chain management.