Efficiency Of Supply Chain Operations Research Articles

The Effect of ERP System Utilization, Inventory Management, and Interdivisional Collaboration on Supply Chain Operational Efficiency in the Automotive Industry

This study examines the impact of ERP system utilization, inventory management practices, and interdivisional collaboration on supply chain operational efficiency in Indonesia’s automotive industry. Using a quantitative approach, data were collected from 120 respondents and analyzed using Structural Equation Modeling–Partial Least Squares (SEM-PLS 3). The results indicate that ERP system utilization, inventory management, and interdivisional collaboration contribute to supply chain efficiency, with a combined effect explaining 67% of the variance in operational efficiency. Findings highlight ERP systems’ role in enhancing real-time data sharing, inventory management’s impact on stock optimization, and collaboration’s ability to streamline cross-functional processes. This study provides insights for industry practitioners seeking to optimize supply chain performance through technology adoption, robust inventory practices, and cohesive interdepartmental collaboration.

Enhancing Supply Chain Management Through Artificial Intelligence: A Case Study of JD Logistics

With the intensification of global economic competition, enterprises face the challenge of improving the supply chain management efficiency, and AI technology, as an emerging field in computer science, can provide effective solutions. As a leading e-commerce logistics service provider in China, JD Logistics has accumulated a wealth of logistics technology capabilities and digital transformation experience within and outside the JD Group. Using JD Logistics as a case study, this paper discusses the application of AI technology in supply chain management and its impact on enterprise responsiveness and operational efficiency. AI technology has significantly improved the supply chain operational efficiency and responsiveness of JD Logistics by applying intelligent supply chain planning, predictive analysis and intelligent decision-making. The study systematically summarizes the key role of AI technology in optimizing supply chain management through a literature review and specific case studies, providing an important reference and practical experience for enterprises to achieve digital transformation.

Financing and operational strategies for supply chains with yield uncertainty and capital constraints

Facing yield uncertainty is a common phenomenon that corporations encounter in their production and operations processes, especially small and medium-sized enterprises (SMEs). It is a challenge for SMEs that also have capital constraints, and thus financing from supply chain members or commercial banks is the normal way to improve the efficiency of supply chain operations. We consider a supply chain finance system consisting of an SME, a core enterprise (CE), and a bank, in which the SME is capital-constrained and faces productivity yield uncertainty. Therefore, the SME may use two financing sources to support his production: financing or advance payment from the CE. In the presence of bankruptcy risks for the SME, we model their strategic interaction as a Stackelberg game with the CE as the leader. We design the framework for the order penalty contract and derive the optimal strategies that include the planned production quantity decision of the SME and the pricing decisions of the CE under the two financing sources. We find that from the SME’s perspective, he will always prefer advance payments from the CE to bank financing. Furthermore, we propose a framework for partial credit guarantees. When it is difficult for banks to evaluate the credit history of SMEs, CEs provide guarantees to banks for financing SMEs. The analytical methods and numerical results provide decision-making methods and suggestions for production planning of the SME and wholesale prices formulated by CE.

Resilient Supply Chains in Industry 5.0: Leveraging AI for Predictive Maintenance and Risk Mitigation

This integrative literature review investigates the transformative impact of artificial intelligence (AI) on supply chain management, addressing the pressing need for efficiency and robustness through AI-driven predictive maintenance, machine learning (ML), and decision support systems. By examining current literature, the study highlights AI's potential to automate and revolutionize supply chain operations, enhancing speed, accuracy, and risk management capabilities while identifying significant challenges such as bias mitigation, algorithmic transparency, and data privacy. The methodology involves a comprehensive review of scholarly articles, reports, and academic publications, focusing on AI applications in predictive maintenance, risk mitigation, and decision-making processes. The analysis reveals significant improvements in operational efficiency and accuracy due to AI, alongside concerns about biases, transparency, and implementation issues. The findings confirm AI's transformative potential in supply chain management but emphasize the necessity for ongoing supervision, regular audits, and the development of AI models capable of detecting and rectifying operational anomalies. The study proposes creating roles such as AI Supply Chain Oversight Officer (AISCO), AI Supply Chain Compliance Officer (AISCCO), and AI Supply Chain Quality Assurance Officer (AISQAO) to ensure responsible AI utilization, maintaining the integrity and efficiency of supply chain operations while addressing implementation challenges. The review concludes that AI is promising for transforming supply chains; however, careful implementation is crucial to uphold operational integrity and resilience. Future research should prioritize longitudinal studies to evaluate AI's long-term impact, focus on addressing implementation concerns, and ensure fair and transparent integration of AI technologies. These findings have significant implications for practice and policy, underscoring the need for robust frameworks and regulatory measures to guide the effective use of AI in supply chains.

Manufacturer’s Channel Strategy and Demand Information Sharing in a Retailer-Led Green Supply Chain

In the rapidly evolving landscape of e-commerce, companies are increasingly focusing on their channel strategies to gain sustainable development. However, asymmetric demand information poses challenges to these decisions. This paper explores the interplay between a retailer’s information sharing strategy and a manufacturer’s channel strategy in a retailer-led green supply chain, where the manufacturer may establish an online channel to sell its green products directly. The dominant retailer has private demand information about the market and decides whether to share private information with the manufacturer. By establishing a game model, we analyze the impacts of information sharing and the manufacturer’s channel strategy on the payoffs for all the supply chain members, considering sustainability aspects such as the environmental benefits of green products and the efficiency of supply chain operations. The results show that information sharing benefits both the retailer and the manufacturer, irrespective of the establishment of an online channel. When the retailer shares demand information, opening an online channel benefits the manufacturer but benefits the retailer under certain conditions. Furthermore, through a numerical approach, we examine the strategic preferences of the firms and derive the equilibrium strategy. Interestingly, the manufacturer consistently prefers the scenario involving both an online channel and information sharing. The retailer’s preference, however, depends on the direct selling cost; it favors information sharing with or without an online channel based on this cost. Ultimately, our findings suggest that the equilibrium strategy can either be sharing information with an online channel or not sharing information without an online channel, which is contingent upon the direct selling cost and the forecast signal precision. These insights provide actionable strategies for enhancing the sustainability of supply chain operations.

Research on dynamic pricing and coordination model of fresh produce supply chain based on differential game considering traceability goodwill

This study aims to solve the current pricing and coordination problems in the fresh produce supply chain by proposing a dynamic pricing and coordination differential game model based on traceability goodwill to optimize the operational efficiency and profitability of the supply chain. Freshness and traceability are critical consumer trust and brand value factors incorporated into the dynamic pricing and coordination model in the agricultural supply chain. The research methodology of this paper integrates critical factors such as supply chain cost and market demand to construct a comprehensive differential game model. It also highlights the motivation of dynamic pricing strategy and coordination mechanism based on traceability goodwill. Through traceability goodwill, operating companies can better assess and manage product quality and improve consumer trust in agricultural products, thus enhancing brand value. The dynamic pricing strategy based on traceability goodwill can flexibly adjust prices according to changes in the quality characteristics of agricultural products and market demand, realizing a dynamic balance between supply and demand. On the other hand, the mutual cost-sharing and coordination mechanism promotes the synergy between the various links of the supply chain. It improves overall efficiency through cooperation coo, coordination, and other means. The validity and reliability of the model are verified through numerical simulation experiments. The numerical simulation results show that the dynamic pricing and coordination model based on traceability will significantly improve supply chain efficiency and profitability compared with the traditional model. Specifically, the interests of supply chain participants are balanced, and the overall supply chain operational efficiency is improved. The main contribution of this study is to propose a dynamic pricing and coordination model based on traceability goodwill and verify its superiority through numerical simulation experiments. This study provides a valuable reference for fresh agricultural products supply chain management and offers new ideas for improving supply chain efficiency and profitability.

Investigating the impact of smart manufacturing and interconnected emerging technologies in building smarter supply chains

PurposeIndustry 4.0 has put forward a smart perspective on managing supply chain networks and their operations. The current manufacturing system is primarily data-driven. Industries are deploying new emerging technologies in their operations to build a competitive edge in the business environment; however, the true potential of smart manufacturing has not yet been fully unveiled. This research aims to extensively analyse emerging technologies and their interconnection with smart manufacturing in developing smarter supply chains.Design/methodology/approachThis research endeavours to establish a conceptual framework for a smart supply chain. A real case study on a smart factory is conducted to demonstrate the validity of this framework for building smarter supply chains. A comparative analysis is carried out between conventional and smart supply chains to ascertain the advantages of smart supply chains. In addition, a thorough investigation of the several factors needed to transition from smart to smarter supply chains is undertaken.FindingsThe integration of smart technology exemplifies the ability to improve the efficiency of supply chain operations. Research findings indicate that transitioning to a smart factory radically enhances productivity, quality assurance, data privacy and labour efficiency. The outcomes of this research will help academic and industrial sectors critically comprehend technological breakthroughs and their applications in smart supply chains.Originality/valueThis study highlights the implications of incorporating smart technologies into supply chain operations, specifically in smart purchasing, smart factory operations, smart warehousing and smart customer performance. A paradigm transition from conventional, smart to smarter supply chains offers a comprehensive perspective on the evolving dynamics in automation, optimisation and manufacturing technology domains, ultimately leading to the emergence of Industry 5.0.

Quantitative Research on “Blockchain+Supply Chain” Financing Based on Game Theory Modeling

In the 21st century, with globalization and the “Belt and Road” economic activities. As an important financial means, supply chain financing plays a key role in trade transactions between enterprises. Supply chain financing refers to providing financial support and services to different participants in the entire supply chain through financial instruments to meet the financial needs of their production and trade activities. To address the issue of “blockchain+supply chain” financing, specifically in the traditional supply chain, the downstream of the SMEs financing difficulties has been one of the factors plaguing its development. Still, also one of the constraints on the overall supply chain operational efficiency, we use the principles of game theory to establish a game theory model between financial institutions and SMEs and use Matlab software to solve the simulation data. We use the principle of game theory to establish a game theory model between financial institutions and MSMEs, use Matlab software to solve the simulation data and analyze the financial institutions to adopt the “blockchain+supply chain” financing strategy, and MSMEs to adopt the trustworthy strategy so that the two sides can maximize the benefits, and also maximize the benefits for the whole supply side. In addition, the research process and results can provide references for relevant state departments and various social enterprises and organizations.

Challenges in the Integration of E-Procurement Procedures into Construction Supply Chains

The growing interest in digitalization signals a need for technology-oriented supply chain operations in the construction industry. Electronic procurement (e-procurement) aims to convert traditional procurement approaches into web-based/online platforms. Even though e-procurement is an effective tool that may improve supply chain management, the extent of e-procurement implementation has been slow to date. This study investigates the barriers that hinder e-procurement implementation in construction supply chains with the aim of prioritizing solutions to the identified barriers relative to time, cost, quality, and construction owner satisfaction. A comprehensive literature survey was performed, and a focus group discussion was organized for the purpose of the study, which resulted in the identification of 28 barriers. Then, a total of 131 construction practitioners were contacted to evaluate the barriers through a questionnaire survey. The responses were analyzed using the fuzzy Technique for Order Preference by Similarities to Ideal Solution (fuzzy TOPSIS) for prioritization. Finally, 15 semi-structured interviews were conducted to gain a deeper insight into the transformation process from the conventional procurement route to the e-procurement solution. Findings highlight that issues related to unexpected order cancellations, large variations in material costs, and the uncertain nature of the industry that requires a large number of changes are ranked as the most significant barriers. Given the highly competitive environment and the high demand for advanced technologies in the construction industry, a new paradigm can enhance the efficiency of supply chain operations. Exploring and eliminating the potential difficulties of adopting e-procurement in the procurement process may be a good start. Overall, this research is expected to facilitate the transformation of the procurement process by addressing the critical barriers identified by practitioners.

Research on Supply Chain Demand Prediction Model Based on LSTM

The supply chain regards suppliers, producers, and consumers as an organic whole, unifying and coordinating the information flow, logistics, and capital flow of all members, and achieving the goal of win-win for all members in the overall operation of cross organization. Demand forecasting is an important factor driving the entire supply chain, and low error rates in forecasting are a common goal pursued by the industry. In order to improve the quality of demand forecasting, enhance the efficiency of supply chain operations, and leverage the important role of machine learning in the era of artificial intelligence, this paper conducts research based on LSTM. Firstly, this paper determines the objective function and constraints for supply chain demand forecasting; Then, this paper constructs a supply chain demand prediction model, based on the LSTM network structure, determine the network training method and model construction process; Finally, this paper conducts simulation experiments and result analysis, configure LSTM parameters, determine model performance evaluation indicators, and compare and analyze actual values with predicted values. The results indicate that the supply chain demand prediction model constructed in this article has very good performance and has promotional value in practice.

Analysis of the Impact of Human Resource Optimization on Supply Chain Efficiency Based on Performance Management

With the increasingly fierce competition in the global market, the demand of enterprises to improve supply chain efficiency is becoming more and more urgent. As one of the valuable resources of enterprises, human resources play an important role in optimizing supply chain efficiency. Based on this, this paper will analyze the impact of human resource optimization on supply chain efficiency based on performance management from the aspects of employee performance, teamwork, talent training, and process design to provide useful reference and guidance for enterprises to improve supply chain operational efficiency.

Applicability of blockchain technology in improving efficiency in supply chain operations in public procurement in Tanzania

The primary aim of this study was to assess the suitability of blockchain technology for improving the efficiency of supply chain operations in the public sector in Tanzania. Blockchain technology (BT) is a contemporary and rapidly growing technology that has gained widespread popularity globally due to its capacity to connect several stakeholders (blocks) worldwide with the aim of enhancing efficiency in business transactions. With this perspective in mind, the researcher was driven to evaluate the capabilities of blockchain technology in the field of supply chain in Tanzania. This evaluation concentrated on three distinct areas: the degree of public awareness of blockchain technology, the strategies used by public bodies to use blockchain technology, and the significant issues that obstruct the implementation of blockchain technology. The study utilized network theory as a framework to analyze the findings. It employed a descriptive survey approach, with a sample size of 192 respondents who were engaged as registered procurement experts in public institutions. In collecting data from respondents, structured questionnaires were prepared using Google Forms and submitted to respondents through their e-mails. A total of 154 questionnaires were properly filled out and submitted, for a response rate of 80.2%. The data was analyzed using descriptive statistics and correlation analysis. The results show that 74.7% of the respondents are unaware of the application of blockchain technology in supply chain operations. In terms of practice, the majority of public entities (67%) use e-payment as the main application of blockchain technology. Additionally, 64% of the respondents identified technical issues and a lack of understanding as the main challenges affecting the application of blockchain technology. Moreover, the study demonstrates a robust correlation between the utilization of blockchain technology and the enhancement of efficiency in supply chain operations. Ultimately, the study suggests implementing an extensive awareness campaign targeted at practitioners in order to enhance the rate of adoption and fully use the capabilities of blockchain technology in Tanzania.

Cloud Computing a key to Supply Chain Management: Embracing the Cloud Advantage

Cloud-based Supply Chain Management (SCM) is a rapidly evolving approach which uses cloud computing to improve the efficacy and efficiency of supply chain operations. There are numerous methods for managing supply chains, including employing Excel spreadsheets and web-based programmes.

Research on Evolutionary Game and Simulation of Information Sharing in Prefabricated Building Supply Chain

Enterprises in the prefabricated building supply chain (PBSC) only share information according to their interests, which is bound to cause conflicts of interest and reduce the efficiency of supply chain operations. To promote information sharing (IS) in PBSC, it is necessary to construct an evolutionary game model that fits the realistic network. In this paper, based on the integration of existing research, 13 influencing factors of IS in PBSC are analyzed comprehensively from the perspective of information ecology theory. In addition, due to the complexity and uncertainty of the PBSC, enterprise interaction and supply chain network structure affect the IS decision. Therefore, this paper builds an evolutionary game model of IS in PBSC under a scale-free network, and conducts numerical simulation analysis with MATLAB 2017 software to analyze the evolution law of enterprise IS under different situations. The results show that (1) when the network scale is large, the density of information sharers generally increases, and the speed of network evolution to a steady state generally slows down; (2) eight factors can promote the increase in information sharers’ density, and five factors can inhibit it, but factors have no significant effect on the speed of network evolution to reach the steady state. Based on the simulation results, this paper proposes countermeasures and suggestions such as strengthening the support of the policy environment and social environment, setting up the demonstration benchmark of leading construction enterprises, establishing a directional information resource database, and improving information technologies and risk management systems to provide the scientific basis for government supervision and enterprise decision making.

Hongxingerke Leveraging Marketing Strategy Research

This paper deeply analyzes the case of Hongxing Erke's trend marketing, firstly, it summarizes its trend marketing techniques, and analyzes the techniques used by Hongxing Erke in carrying out trend marketing, i.e., choosing the trend precisely, following the trend and taking advantage of the trend. Secondly, it innovatively proposed the rules that enterprises should follow in the process of applying the trend marketing, including the law of opportunity, the law of relevance, the law of emotional utility, the law of innovation, and the law of long-term. Again, the problems of Hongxing Erke's marketing are analyzed, including short influence cycle, lack of brand loyalty, and lagging development of supply chain system. Finally, the optimization plan is proposed for the marketing strategy of Hongxing Erke Industry Co., Ltd.: In the era of content is king, increasing R&D efforts and improving brand quality is the way to go; there should be a systematic planning and long-term marketing strategy for borrowing, and insist on long-term borrowing, so that the public's favorable feeling towards the brand can be transformed into purchasing actions and customer loyalty can be won; in the era of big data, the construction of supply chain management talents should be strengthened, and the supply chain should be seamlessly integrated. In the era of big data, we should strengthen the construction of supply chain management talents and strive for seamless integration of supply chain, so as to improve the operation efficiency of supply chain..

Analyzing the Effectiveness of Finance in Supply Chain in Solving the Financing Difficulties of SMEs Based on Grey Theory Model.

Small and medium-sized enterprises (SMEs) play an indispensable role in China's national economic system, and they can play a critical role in promoting economic growth and full employment. The main reason for the disruption and impediment to the development of SME clusters is that the enterprises in the clusters are experiencing a “capital shortage,” as a result of the double contradiction between the clusters' financial benefits and the difficulties in financing. Grey theory is a relatively new concept in the field of information processing. It proposes theories and methods for processing and analyzing incomplete information systems using mathematical methods. This study uses finance in supply chain as a new research perspective to investigate the effectiveness of finance in supply chain in resolving SMEs' financing problems using the Grey theory model, with the goal of resolving SMEs' financing problems. When comparing the results of the Grey theory model and the regression analysis model, the relative error of the Grey theory model is on average 12.2% lower than that of the regression analysis model, indicating that the Grey theory model greatly improves accuracy. As a result, using the Grey theory model to solve supply chain financing and SMEs' difficulties can share risks, share credit, reduce transaction costs, weaken information asymmetry, and achieve mutual benefits and a win-win situation. It is expected to promote the development of the finance in supply chain model, mobilise enterprise enthusiasm for using finance in supply chain, improve finance in supply chain operational efficiency, and promote finance in supply chain development.

Critical analysis of the impact of big data analytics on supply chain operations

Undoubtedly, due to the increasingly competitive pressures and the stride of varying demands, volatility and disturbance have become the standard in today’s global markets. The spread of Covid-19 is a prime example of that. Supply chain managers are urged to rethink their competitive strategies to make use of Big Data Analytics (BDA), due to the increasing uncertainty in both demand and supply side, the competition among the supply chain partners and the need to identify ways to offer personalised products and services. With many supply chain executives recognising the need of ‘improving with data’, supply chain businesses need to equip themselves with sophisticated BDA methods/techniques to create valuable insights from big data, thus, enhancing the decision-making process and optimising the efficiency of Supply Chain Operations (SCO). This paper proposes the building blocks of a theoretical framework for understanding the impact of BDA on SCO. The framework is based on a Systematic Literature Review (SLR) on BDA and SCO, underpinned by Task-Technology-Fit theory and Institutional Theory. The paper contributes to the literature by building a platform for future work on investigating factors driving and inhibiting BDA impact on SCO.

An intelligent stochastic optimization approach for stochastic order allocation problems with high-dimensional order uncertainties

Effective order allocation has a great impact on improving the efficiency of supply chain operations. This paper investigates a high-dimensional stochastic order allocation problem that assigns uncertain customer orders to heterogeneous parallel machines. Considering the arrival uncertainty of customer orders in the real-world production environment, a mathematical model of the investigated problem is established with the objective of maximizing the expected profit of order processing. A novel intelligent stochastic optimization approach is proposed by combining a modified adaptive large neighborhood search algorithm with a scenario generation technique. In this approach, the modified adaptive large neighborhood search algorithm suitable for the generalized allocation problem is proposed to seek the best solutions, while the scenario generation technique is used to generate the scenarios needed to evaluate the solutions of the high-dimensional stochastic optimization problem. Experimental results demonstrate that the proposed approach outperforms the compared stochastic optimization method in terms of optimization efficiency and optimization ability.

The impact of horizontal R&D cooperation on the climbing of the industrial cluster supply chain: from the perspective of the evolutionary game theory

Supply chain upgrade is a transformation process of supply chain operation efficiency and value realisation. The upgrading of an industrial cluster supply chain is of great practical significance to the development of China's cluster enterprises. As a kind of spatial economic organisation with geographical proximity and industrial relevance, supply chain network and industrial cluster create a favourable platform for enterprise cooperation. This paper studies the R&D cooperation of industrial clusters based on the perspective of the supply chain, constructs the evolutionary game model of R&D cooperation of horizontal enterprises in the cluster, and conducts numerical simulation analysis. The results show that: the impact mechanism of R&D investment, R&D cooperation risk, mutual trust level, R&D cooperation knowledge spillover, enterprise knowledge absorption capacity and R&D cooperation cost respectively to horizontal enterprise R&D cooperation in industrial cluster supply chain network. Finally, combined with the impact mechanism, it puts forward suggestions for realising the strategy and path of the supply chain climbing of China's industrial clusters.

Shifting trust in construction supply chains through blockchain technology

PurposeBlockchain technology is booming in many industries. Its application in supply chain management is also gradually increasing. Supply chain management (SCM) has long been committed to reducing costs and increasing efficiency and is trying to optimise resources and reduce the sector's fragmentation. Trust has always been an important factor in managing supply chain relationships, and it also affects the efficiency of supply chain operations. To this end, this study aims to examine how trust is affected by the introduction of blockchain technology in construction supply chain management.Design/methodology/approachThis study is based on semi-structured interviews and publicly available information from experts in blockchain and construction supply chain management. Through content analysis, the data are analysed thematically to explore how various types of trust, such as system-based, cognition-based and relation-based, are affected by blockchain technology.FindingsBlockchain technology provides solutions for data tracking, contracting and transferring resources in supply chain management. These applications help enhance the various sources of trust in SCM and provide supply chain partners with protection mechanisms to avoid the risks and costs of opportunistic behaviour in collaboration, shifting trust from relational to system-based and cognition-based.Research limitations/implicationsThis study focuses only on inter-organisational rather than interpersonal trust and empirical data from experts whose knowledge and cognition could be subjective.Practical implicationsLeveraging the potential of digitalisation to manage trust requires that leaders and managers actively try to improve contractual arrangements, information sharing and being open to new innovative technologies like blockchain.Social implicationsFrom a relational view of supply chain management, the extent to which blockchain technology can develop and spread depends on the readiness of the social capital to accept decentralised governance structures.Originality/valueThis study builds upon an original data set and discusses features and applications of blockchain technology, explores the sources and dimensions of trust in supply chain management and explains the impact of blockchain technology on trust.