Supply Chain Management Model Research Articles

Dropshipping Strategies in Luxury and Fashion Retail - Unveiling the Potential

Purpose: Dropshipping, a supply chain management model where the retailer does not keep goods in stock but instead transfers customer orders and shipment details to either the manufacturer, another retailer, or a wholesaler who then ships the goods directly to the customer, has gained significant traction in various industries. However, its application in luxury and fashion retail remains unexplored. This study aims to investigate the potential of dropshipping strategies within the context of luxury and fashion retail, analyzing its benefits, challenges, and implications for businesses operating in this sector. Methodology: This research employs a comprehensive review of existing literature, case studies, and industry trends to gather insights into dropshipping practices in luxury and fashion retail. Findings: Our analysis reveals that dropshipping offers promising opportunities for luxury and fashion retailers to enhance operational efficiency, expand market reach, and provide exceptional customer experiences. Challenges such as maintaining brand reputation and managing supplier relationships are identified and discussed. Unique contribution to theory policy and practice: This paper contributes to the existing literature by shedding light on the application of dropshipping in the luxury and fashion retail sector. It provides practical recommendations for retailers to leverage dropshipping effectively, thereby advancing both theoretical understanding and practical implications for industry stakeholders and policymakers.

Evolutionary Game Analysis of Green Supply Chain Management Diffusion under Environmental Regulation

The continuous deterioration of the ecological environment and the increasing scarcity of resources have posed a serious challenge to the survival and development of human beings, and the implementation of green supply chain management (GSCM) in this context is an effective means to ensure the sustainable development of society and the economy. In order to seek the optimal strategy of evolutionary game in the implementation of green supply chain management and explore the influence of environmental regulation intensity and public preference degree on the evolution process of green supply chain management diffusion development, this paper takes the study of green supply chain management diffusion as the core innovation point, and under the premise of environmental regulation, selects the government, the core enterprise, and the public as the participating bodies of green supply chain management diffusion, and uses the theory of evolutionary game to construct a diffusion model of green supply chain management. Using evolutionary game theory to construct a diffusion model, and with the help of MATLAB and other mathematical tools for numerical simulation analysis, we discuss the diffusion of the green supply chain and derive the optimal combination strategy. The results of the study show that: (1) there are four evolutionary stable states in the process of green supply chain management diffusion: preliminary diffusion, extinction, semi-diffusion, and full diffusion; (2) it will be beneficial for the government to promote the evolutionary diffusion of green supply chain management by implementing a higher intensity of pollution tax policy while implementing green supply chain incentive strategies; (3) the government, while implementing environmental regulation policies, should also pay attention to the guidance of the public’s awareness of environmental friendliness and greenness, and focus on the role of the comprehensive strategy selection of the three parties of the game in reaching the optimal state. The conclusions of the study provide theoretical guidance and decision support for the implementation and diffusion of green supply chain management under environmental regulation.

Research on the International Supply Chain Management of Chinese Bamboo Weaving and Cultural and Creative Products

With the increasing of China's international status and the acceleration of the process of global economic integration, the internationalization strategy of Chinese enterprises is getting deeper and deeper. This paper analyzes the problems and challenges faced by the international supply chain management of Chinese bamboo weaving and creative products, and puts forward a set of supply chain management model that ADAPTS to the international development. Firstly, the concept, connotation and types of supply chain management are sorted out through literature review. Secondly, this paper analyzes the current situation of international supply chain management of bamboo editing and creative products, and points out the existing problems. Thirdly, based on the theory and practice of international supply chain management, this paper puts forward a set of supply chain management model suitable for the international development of bamboo editing and creative products. Finally, taking a bamboo weaving and creative products enterprise as an example, the application effect of the supply chain management model is empirically analyzed. The results show that the supply chain management model can effectively reduce the cost and improve the efficiency, and is conducive to the international development of bamboo editing and creative products

The Potential Application of Large Language Models in Pharmaceutical Supply Chain Management.

The Potential Application of Large Language Models in Pharmaceutical Supply Chain Management.

Enterprise Marketing Risk Control Based on Information Technology and Supply Chain Management

The overall economic development of today’s society is showing a downward trend. In the process of operating and marketing, enterprises are affected by various factors. After the marketing risk reaches a certain level, enterprises would encounter various risks such as blocked marketing plans and failure to meet the estimated marketing goals. Enterprise marketing is affected by economic and market risks such as lack of information, decision-making errors, natural disasters, human factors, and other natural and social risks. This article combined information technology with supply chain management, applied radio frequency identification (RFID) technology to supply chain management, and controlled enterprise marketing risks through reasonable management of the supply chain. It also compared the effectiveness of enterprise marketing risk control between an information technology intelligent supply chain combined with RFID and a supply chain managed by ordinary artificial structures. The experimental results showed that the highest value of goods loss rate in the supply chain based on RFID technology and using traditional technology was 5% and 15%, respectively, according to the sample of goods loss experiments. For the information verification process of goods in supply chain management, the information identification accuracy rates of barcode and RFID technology were 89.98% and 97.7%, respectively. Therefore, applying the information technology intelligent supply chain management model combined with RFID technology to enterprise marketing risk control can save money for enterprises, ensure product quality, and effectively reduce the risks encountered in enterprise marketing by reducing information gaps, and reducing transportation and storage costs.

A comparative study of machine learning-based regression models for supply chain management

The rise of machine learning technology has opened up unprecedented opportunities for the retail industry. Machine learning, as an essential branch of artificial intelligence, enables computers to improve their performance through continuous learning and experience. It has demonstrated its ability to handle large-scale data and complex problems effectively. In retail, machine learning predictions and methods can also lead to significant breakthroughs in supply chain management, helping businesses identify better ways to maintain economic stability and growth, which are crucial for improving people's living standards, eliminating poverty, promoting social stability, driving technological progress, and reducing inequality. This is achieved through different algorithmic regression methods, which can predict future trends and consumer behavior with high accuracy. Machine learning algorithms can analyze vast amounts of data to identify patterns and trends and make accurate predictions about future demand, product inventory levels, and other important factors that drive business success in the retail industry.

Modeling of nonlinear supply chain management with lead-times based on Takagi-Sugeno fuzzy control model

In this study, we present a novel fuzzy control strategy that considers the influence of lead times on nonlinear supply chain management (SCM) systems. The authors have constructed a fuzzy control model for an SCM model based on nonlinear phenomena with lead times, drawing inspiration from Takagi-Sugeno's (T-S) fuzzy control system. Additionally, the authors have designed a fuzzy H∞ control approach to mitigate the effects of lead times, switch between sub-models, and address customers' stochastic requests, all while considering the concept of maximal overlapped rules groups. The control of nonlinear supply chain management is implemented in a manner that ensures asymptotic stability and facilitates smooth transitions from one subsystem to another. The introduction of the membership function into the fuzzy system results in reduced fluctuations in the system's variables. The key contributions of the research include the design of a fuzzyH∞ control approach, leveraging maximal overlapping-rules group (MRRG) to ensure stability through localized definite positive matrices identification. This strategy achieves two primary objectives: asymptotic stability of the supply chain system and smooth switching between nonlinear SCM elements. The authors demonstrate the effectiveness of their proposed method through comprehensive comparisons with the fuzzyH∞ control technique. The study provides a valuable insight into managing lead times in SCM through dynamic and stable control methodologies. Finally, a comprehensive comparison is provided between the suggested H∞ management approach and the fuzzyH∞ control strategy. This comparison is demonstrated through two-stage nonlinear numerical simulations, keeping SCM lead times in mind. Movement results are presented to illustrate the effectiveness of our suggested algorithm.

Automobile Transportation Logistics Supply Chain Management Strategy

To enhance the management level and quality of the automobile transportation logistics supply chain and promote innovation and development in automobile transportation logistics enterprises, it is essential to strengthen the construction of the automobile transportation logistics supply chain management model. This can be achieved through the gradual improvement of the automobile transportation logistics management process, ensuring that the management of the automobile transportation logistics supply chain proceeds in an orderly manner. The aim is to improve automobile transportation and logistics service levels while meeting the changing market supply needs. This will enable automobile transportation and logistics enterprises to maintain steady economic benefits and enhance their core competitiveness in the market. Therefore, this paper has conducted a comprehensive exploration and research on managing the automobile transportation logistics supply chain. Corresponding management strategies are proposed as a starting point to achieve the aforementioned goals.

The Application of Blockchain Technology in Enterprise Value Chain Cost Management

This paper examines the application of blockchain technology in managing costs across the enterprise value chain. A literature review analyzes current research on blockchain-based supply chain management and cost optimization models. The methodology employs a case study approach to evaluate the implementation of blockchain platforms in reducing transaction fees, enhancing transparency, and streamlining operations. Results demonstrate measurable improvements in cost-efficiency, reporting accuracy, and partner collaboration. Tables illustrate quantitative impacts in areas including inventory holding reductions, contract enforcement savings, and lowered IT expenses. Findings suggest blockchain solutions enable robust tracking and coordination of end-to-end workflows, although further integration work is needed. In conclusion, blockchain technology shows promise in transforming enterprise value chains to be more responsive and economical.

Tree Seed Algorithm-based Feature Selection with Optimal Deep Learning Model for Supply Chain Management

In recent days, supply chain and logistic industries have been going through a transformational wave of automation and digitization. Supply chain management (SCM) can involve machine learning (ML) abilities and prediction models to ensure that the demands are satisfied at a minimum cost. Intelligent models can be developed to determine whether adequate inventory is accessible to encounter the predictable rise in demands, and if not, the system spontaneously begins to adjust the orders with suppliers to source the raw materials for resolving the predicted future high demand. The conventional ways of SCM can be replaced by the design of recent artificial intelligence (AI) and deep learning (DL) techniques. By this motivation, this research presents a tree seed algorithm-based feature selection with optimum DL technique for supply chain management (TSA-ODLSCM). The proposed TSA-ODLSCM model involves the design of a feature subset selection approach using a tree search algorithm (TSA) algorithm. Besides, a new convolutional neural network with fuzzy cognitive maps (CNN-FCM) technique is designed for the classification process. Moreover, optimal parameter tuning of the CNN-FCM model was performed using the Henry gas solubility optimization (HGSO) technique. To exhibit the improved performance of the TSA-ODLSCM approach, a huge range of simulations were executed and outcomes were examined below several aspects. The experimental validation reported an enhanced 96.52% outcome of the TSA-ODLSCM approach over other methods.

Unregulated Cap-and-Trade Model for Sustainable Supply Chain Management

Cap-and-trade models have been largely studied in the literature when it comes to reducing emissions in a supply chain. In this paper, further pursuing the goal of analyzing the effectiveness of cap-and-trade strategies in reducing emissions in supply chains, we propose a mathematical model for sustainable supply chain management. This optimization program aims at reducing emissions and supply chain costs in an unregulated scenario w.r.t. the cap definition, i.e., trading CO2 is allowed but no formal limit on the CO2 emissions is imposed. Also, we considered an initial budget for technological investments by the facilities in the considered supply chain, allowing plants to reduce their unit production emissions at a different unit production cost. For this model, differently from what exists in the literature, we derive some theoretical conditions guaranteeing that, if obeyed, the emissions over time have a non-increasing trend meaning that decreasing caps over time can be attained with a self-regulated scenario. Computational results show the effectiveness of our approach.

IoT-BIM and blockchain integration for enhanced data traceability in offsite manufacturing

The transformation of dynamic supply chains within the realm of offsite manufacturing presents a unique and compelling opportunity to effectively respond to shifts in market demand. However, this paradigm shift also entails novel challenges and prospects for streamlining processes, augmenting efficiency, and ultimately driving success across production workflows and logistical operations. Dynamic supply chains necessitate unimpeded access to high-quality, dependable data to facilitate real-time, data-driven decision-making. Furthermore, owing to their inherently intricate nature, these supply chains are subject to a heightened vulnerability to disruptions and delays, surpassing those encountered in traditional supply chains. Against this backdrop, this paper proposes a framework that synthesises the convergence of the Internet of Things (IoT), Building Information Modelling (BIM), and blockchain technology (BCT) into a cohesive and integrated system, thereby optimising the efficiency and transparency of supply chain management operations. The proposed framework takes cognisance of the challenges inherent in ensuring information traceability, mitigating fragmented information, enhancing interoperability, and fortifying reliability throughout the design, production, and implementation phases of assets within dynamic supply chains operating in the offsite manufacturing domain. To illustrate the efficacy of our proposition, we present a framework that exemplifies the seamless integration of a permissioned, open-source distributed ledger, which forms the bedrock of our support infrastructure for IoT and BIM integration.Through rigorous analysis, we showcase the effectiveness of the developed framework in the form of a designed Supply Chain Management Model (SCMM-PDO), which harmonises the physical, digital, and operational layers within a robust system architecture (BCT.IoT-BIM). The integration of these technologies provides a decentralised solution, reinforcing supply chains with improved security, reliability, and quality control mechanisms, thus enhancing the efficiency of the supply chain network. It is anticipated that this transformative integration will yield substantial improvements in key performance indicators (KPIs) such as operational efficiency, cost reduction, and the cultivation of trust and accountability across supply chain activities.The research proposes an IoT and BIM conceptual framework that simulates the dynamic supply chain operations, facilitating real-time analysis and prediction of supply chain participants' behaviours from resources, processes, and assets. Furthermore, the integration of IoT-BIM (digital twinning) with a blockchain-based system, such as Hyperledger Fabric, engenders a secure and transparent framework for the diligent tracking of assets and information throughout the supply chain. The findings of this study offer an all-encompassing conceptual framework for the secure and transparent tracking of asset information by integrating Blockchain-based technologies with IoT and BIM. This research endeavour thus expands the existing body of knowledge, establishing a foundation for future investigations within this proliferating field.

Exploring the Potential of Large Language Models in Supply Chain Management

This study aims to identify emerging topics, themes, and potential areas for applying large language models (LLMs) in supply chain management through data triangulation. This study involved the synthesis of 33 published articles and a total of 3421 social media documents, including tweets, posts, expert opinions, and industry reports on utilizing LLMs in supply chain management. By employing BERT models, four core themes were derived: Supply chain optimization, supply chain risk and security management, supply chain knowledge management, and automated contract intelligence, which provides the present status of LLM in the supply chain. The results of this study will empower managers to identify prospective applications and areas for improvement, affording them a comprehensive understanding of the antecedents, decisions, and outcomes detailed in the framework. The insights garnered from this study are highly valuable to both researchers and managers, equipping them to harness the latest advancements in LLM technology and its role within supply chain management.

Análise de uma cadeia de abastecimento do setor cerâmico: um olhar sobre os processos de negócios

Abstract Given the importance of structuring organizations in supply chains as a mechanism for competitiveness, as well as process management for the good operational performance of these chains, this article aims to map and analyze the business processes of a supply chain of the ceramic sector located in northeastern Brazil. To achieve the proposed objective, Lambert, Cooper, and Pagh’s (LCP) model of supply chain management is adopted, which comprises, within its analysis dimensions, the mapping of the dimensional structure of the chain, its processes, and management components. As a result, it was possible to characterize the configuration of the chain under analysis, highlighting the company's proximity focused on the upstream direction of the chain and, consequently, the complexity of the supply operations. Furthermore, based on the problems and inefficiencies identified during the mapping of the supply processes, this study proposes suggestions for changes and improvements to the ceramic sector's supply chain analyzed. By providing a detailed analysis of the dimensional structure of the chain, its processes, and managerial components, this article contributes to the continuous improvement of organizations by providing a practical discussion on the structuring of supply processes and emphasizing the importance of overcoming the identified inefficiencies.

The response of the Irish pharmaceutical manufacturing sector to the COVID-19 pandemic with a focus on Lean and JIT.

Just in Time (JIT) and Lean manufacturing are concepts that originated in the automotive industry and were then adopted by pharmaceutical and biopharmaceutical companies during the 1990s. However, the Covid-19 pandemic and the urgent demand for pharmaceutical treatment challenged JIT and Lean manufacturing processes. Production of Covid-19-related medicines increased, putting pressure on global supply chains and operations. This also hindered the production of medicines using the same or similar materials. Thus, questions are raised concerning JIT and Lean supply chains in the pharmaceutical industry. The present study aimed to explore (1) if material and supply constraints occurred due to the Covid-19 pandemic, (2) how companies were impacted and managed and (3) if changes are required to future proof the JIT supply chain approach for future global events. A mixed-method cross-sectional survey design was used and focused on material supply, qualification and validation in Irish pharmaceutical manufacturing sites. Employees working in the Irish pharmaceutical manufacturing industry were recruited using convenience sampling through online advertisement using the social media platform 'LinkedIn'. Quantitative data was analysed using percentages and qualitative data from free-text responses were used to add context to the quantitative survey questions. A total of 41 participants were recruited. The results suggested that the pandemic had a negative effect on material availability according to 81% of participants. This translated to delays or stoppage of production activity and was mainly handled by sourcing new materials (70%). To cope with future global crises, 60% of participants recommended more flexibility in future validation processes while 78% of participants acknowledged the importance of validating additional suppliers. A hybrid model of manufacturing and supply chain management was also a preferred approach to exclusive Lean and JIT (42%). The production of non-Covid-19 medicines was adversely affected by the Covid-19 pandemic, but the pharmaceutical industry in Ireland demonstrated resilience and collaboration in response to these challenges. This study suggests that the JIT and Lean manufacturing model should be adjusted to ensure medicine supply chains are not disrupted during future global events.

Innovation of Marketing Supply Chain Management Model Based on SICAS Modeling

Abstract The marketing service system is not perfect enough to highlight the competitive advantages of enterprises, and improving the marketing supply chain management mode is an inevitable trend under the change of the market economic environment. The marketing supply chain management model proposed in this paper is based on the SICAS model to respond quickly to market and customer demand. A collaborative optimization model of the supply chain based on virtual inventory management is constructed to ensure the normal operation of the whole supply chain by deploying flexible inventory in the hands of customers, and the constructed model is solved by using an evolutionary algorithm based on indexes and an optimal solution sorting method based on regret theory. The feasibility and scientificity of the proposed management model are verified by analyzing the effect of applying the management model to J and S e-commerce companies and analyzing consumer evaluation. The results show that from 2014 to 2022, the purchasing cost of J e-commerce enterprises decreased by 0.0307 as a proportion of operating income, the inventory turnover ratio increased by 0.0869, the marketing cost and logistics cost increased by 189 million yuan and 3,878 million yuan, respectively, and the supply chain cost was effectively managed. At the same time, the consumer evaluation score of the marketing supply chain management model based on SICAS model is 3.608±0.043 points; the user experience is good, to a certain extent, to enhance the competitive advantage of the enterprise.

Digital Transformation of Supply Chain Management in the Fast Fashion Industry: A Case Study of Zara

With continuous innovation and evolution in the clothing industry, fast fashion brands have gained significant popularity due to their ability to quickly respond to changing fashion trends, offer affordable and stylish clothing, and cater to the preferences of fashion-conscious consumers worldwide. This research analyzes the supply chain of the renowned fast fashion brand Zara, known for its unique supply chain management model. It is one of the most valuable apparel brands globally. The study explores the impact of supply chain management and digitalization on the entire fast fashion supply chain, encompassing upstream suppliers and manufacturers, middle-channel retailers and distributors, and consumers. Through a comprehensive examination of Zara’s success story, this study serves as an inspiring example for domestic apparel enterprises, showcasing the potential benefits that can arise from adopting a unique supply chain model, and offers valuable insights for Chinese apparel companies seeking to enhance their supply chain management and adapt to the digital era.

LEVERAGING COMPETITIVE STRATEGIES ON BUSINESS OUTCOMES POST-COVID-19 PANDEMIC: EMPIRICAL INVESTIGATION FROM AFRICA

Background: The novel coronavirus has damaged the global economy, and business outcomes such as low profitability, poor sales, and weak market share, including intense competition, are widespread within the business ecosystem; however, competitive strategies have been some of the business decisions in recent times. Aim: The study, therefore, examined the effects of competitive strategies on business outcomes of selected consumer goods companies listed in Nigeria, the most populous and largest economy in Africa. Methods and Sample: The study adopted a survey research design, with a population of 22,466 staff members, comprising regular employees and top- and middle-level managers of twenty consumer goods companies listed on the Nigeria Exchange Group (NGX). The study used a proportionate stratified sampling technique to draw a convenient sample for the analysis. 491 copies of the questionnaire were administered to the respondents, with a response rate of 97.76%. Results: Findings showed that competitive strategies significantly and positively affected business outcomes (Adj. R2 = 0.563; F5/1306 = 337.061, p<0.05). Conclusion: The study recommended that the consumer goods companies often refer to Fast Moving Consumer Goods (FMCG) listed in Nigeria must have a market-development mindset, invest in consumer education, and integrate an efficient supply chain management model.

Design of Supply Chain Management in Kasongan Pottery MSMEs

Post-COVID 19 pandemic raises new challenges for Kasongan Bantul Pottery Micro, Small and Medium Enterprises (MSMEs), in addition to significantly changing the economic landscape, MSMEs experience challenges in marketing systems that are not yet optimal and increasingly fierce product competition is a serious obstacle. This is one of the challenges for Kasongan Pottery MSMEs so that the businesses built can succeed and be able to survive, one of which is to use a system that integrates the needs of business actors, consumers (costumers), capital owners, raw material suppliers (suppliers) and collectors without space limits. The purpose of this research focuses on the Supply Chain Management (SCM) model to improve efficiency in the supply chain of Kasongan Pottery MSMEs. The research method used is qualitative with a descriptive analysis approach. The population in this study was 303 Kasongan Pottery MSMEs, while the sample taken was 25% of the population, namely 76 MSMEs.

An Integrated Cloud-based Blockchain Model for Supply Chain Management

An Integrated Cloud-based Blockchain Model for Supply Chain Management