Collaborative Supply Chain Management Research Articles

Supply Chain Management (SCM) Breakdowns and SCM Strategy Selection during the COVID-19 Pandemic Using the Novel Rough MCDM Model

Supply chain management (SCM) is deeply affected by the COVID-19 pandemic besides breakdowns occurred in all sectors. Nowadays, managers need techniques for protecting supply chains from serious and costly disruptions, establishing permanent relationships with the customers and partners and preventing breakdowns throughout the process. Each firm needs to determine SCM strategies to be prepared for breakdowns in an intense competitive environment. With COVID-19, the change in business and trade environments has taken a different dimension, and it has revealed a new relationship between the efforts to perpetuate supply chains and strategies for supply chain management and enabled new models. In this study, it is aimed to prioritize the factors that lead to SCM breaks needed in project management and the realization of projects, and to choose the most successful SCM strategy considering COVID-19. For this purpose, rough SWARA was used for weighting factors and rough MARCOS was used for the alternative selection. According to the findings, the transportation capacity factor was found to be the most important factor leading to SCM breakdowns. The most ideal supply chain management strategy has been the “collaborative supply chain management strategy.” In the food manufacturing sector, the study can be considered as a roadmap in terms of preventing supply chain management breaks during the COVID-19 process and helping to ensure a sustainable production. As another theoretical and practical importance of the study, it is aimed to propose a robust, powerful, and practical decision-making model that can cope with the current uncertainties.

Preventing waste in food supply networks - a platform architecture for AI-driven forecasting based on heterogeneous big data

Waste is a major challenge in today´s food supply networks. It induces economic, ecologic, and social implications. Current advanced supply and demand planning frameworks consider waste as an expected lost value in a profit-seeking trade-off. Consequently, existing initiatives for food re-distribution tackle the problem at the end of the supply chain, i.e., at the retailer stage. Advanced forecasting is foreseen as a facilitator of planning towards food waste prevention. However, companies in food production and retail seldomly utilize advanced forecasting methods, i.e., artificial intelligence. Deterrents for inadaptability rank from the differentiation between the role of pure data driven reliance and the human factor. Furthermore, no remarkable endeavor has so far combined heterogeneous external data integration with advanced forecasting techniques for food waste reduction. This paper proposes an architecture for a collaborative digital demand and supply matching platform for perishable food supply chains. Focus lies in the integration of heterogeneous big data (i.e., mobile transaction data and weather data) with AI-based forecasting methods. Building on the Design Science Research methodology, problems and requirements from the perishable food industry form the base for the platform architecture as the core artifact. The validation of the proposed architecture is undertaken by a panel of selected business experts from food retail and wholesale. The designed platform architecture consists of the core modules “data layer”, “logic layer”, “interaction layer”, and “data visualization”, and includes governance rules for sensible knowledge protection and data security. The present work contributes to the research area of food waste prevention by combining collaborative supply chain management approaches with advanced data-driven technologies including artificial intelligence and heterogeneous big data integration. Further research will extend this study by a use-case implementation.

The mediating effect of operational capabilities on operational performance

PurposeCollaboration and operational capabilities are two strengths for managing supply chains to achieve operational performance. In this context, this study aims to analyze the mediating effect of operational capabilities on the relationship between collaborative supply chain management and operational performance.Design/methodology/approachThe study design consisted of a theoretical framework to estimate the mediation paths by latent variable structural modeling methods. A survey of 138 respondents from Brazilian capital goods companies was conducted.FindingsThe study revealed that operational capabilities partially mediate the relationship between collaborative supply chain management and operational performance. The findings provide important guidance for managers to strengthen the relationship with suppliers to continuously improve operational capability.Research limitations/implicationsAs the sample size was made up of 138 respondents, it was impossible to revalidate the theoretical–empirical model. New data need to be collected to re-evaluate the structural model and expand them to other economic segments.Practical implicationsBy examining the theoretical insights and empirical findings, the study expanded knowledge about collaborative management and the understanding of the importance of operational capabilities in the relationship between collaborative management and operational performance for management practices.Originality/valueThe study developed a theoretical–empirical measurement model, reliable and statistically validated, to test the mediating effect of operational capabilities in the relationship between collaborative management and operational performance.

The role of 3S in big data quality: a perspective on operational performance indicators using an integrated approach

PurposeThis study aims to provide insight into the operational factors of big data. The operational indicators/factors are categorized into three functional parts, namely synthesis, speed and significance. Based on these factors, the organization enhances its big data analytics (BDA) performance followed by the selection of data quality dimensions to any organization's success.Design/methodology/approachA fuzzy analytic hierarchy process (AHP) based research methodology has been proposed and utilized to assign the criterion weights and to prioritize the identified speed, synthesis and significance (3S) indicators. Further, the PROMETHEE (Preference Ranking Organization METHod for Enrichment of Evaluations) technique has been used to measure the data quality dimensions considering 3S as criteria.FindingsThe effective indicators are identified from the past literature and the model confirmed with industry experts to measure these indicators. The results of this fuzzy AHP model show that the synthesis is recognized as the top positioned and most significant indicator followed by speed and significance are developed as the next level. These operational indicators contribute toward BDA and explore with their sub-categories' priority.Research limitations/implicationsThe outcomes of this study will facilitate the businesses that are contemplating this technology as a breakthrough, but it is both a challenge and opportunity for developers and experts. Big data has many risks and challenges related to economic, social, operational and political performance. The understanding of data quality dimensions provides insightful guidance to forecast accurate demand, solve a complex problem and make collaboration in supply chain management performance.Originality/valueBig data is one of the most popular technology concepts in the market today. People live in a world where every facet of life increasingly depends on big data and data science. This study creates awareness about the role of 3S encountered during big data quality by prioritizing using fuzzy AHP and PROMETHEE.

Improving sustainable supplier evaluation by an integrated MCDM method under pythagorean fuzzy environment

Sustainability plays a significant role in promoting competence and collaboration in supply chain management due to increased environmental awareness, tightened regulations, and government policies. The evaluation of sustainable suppliers and selecting the best one is indispensable for companies to promote sustainability. Due to multi-criteria nature of the supplier selection process, it has been considered as a multi-criteria decision making (MCDM) problem in many studies. In this study, a state-of-the-art MCDM method for sustainable supplier selection is developed by integrating AHP and TOPSIS techniques within the Pythagorean Fuzzy Sets (PFSs) linguistic setting. A Group Decision Making (GDM) environment is utilized due to superiority of group consensus over individual decisions. Finally, an apparel industry example is used to illustrate the effectiveness and feasibility of the proposed sustainable supplier selection method. A comparison with existing techniques and sensitivity analysis are done to verify and validate the given outcome.

Supply Chain Inventory Collaborative Management and Information Sharing Mechanism Based on Cloud Computing and 5G Internet of Things

With the development of economic globalization, the competition among enterprises is increasingly fierce. Therefore, companies need close information sharing to realize the integration of supply chain. This article aims to study the collaborative management and information sharing mechanism of supply chain inventory based on cloud computing and 5G Internet of Things. This article first introduces the theory and methods of collaborative supply chain management and the information exchange mechanism and then discusses the problem of information sharing in the supply chain, that is, the bullwhip phenomenon, and then from the demand forecast, supply chain structure, time lag, and shortage game, six aspects are analyzed. The cause of the bullwhip phenomenon is analyzed. Secondly, this article proposes a quantitative analysis of the bullwhip effect, establishes a mathematical model of the bullwhip effect in the supply chain, and uses quantitative analysis to analyze the value of information sharing in the supply chain. Finally, this article uses cloud computing technology to build a supply chain information collaboration system architecture and uses EPC Internet of Things to build a supply chain information sharing model and describes the entire operation process of the supply chain. The experimental results of this paper show that the application of cloud computing technology to supply chain management establishes a system platform for supply chain information sharing, improves the overall operational efficiency of supply chain management, and realizes supply chain information sharing and business collaboration. In addition, the operating costs and risks of each node enterprise in the supply chain are reduced by 12% compared with the nonsharing situation, which also shows that the overall benefits of the supply chain have been correspondingly improved and market competitiveness has been enhanced.

Information Technology Factors Affecting Supply Chain Collaboration in Automotive Component Manufacturing in Indonesia

There is a growing need for collaborative supply chain management. This collaboration has been attracting the researchers due to their critical impact to improve business value. The use of information technology (IT) which is presently widely used in almost areas of business and engineering is considered prerequisites of today’s complex supply chain. Current study shows that a broad array of references in supply chain collaboration especially in identifying influencing factors on Information Technology are partial and limited. This study was aimed at reviewing a comprehensive understanding of dominant IT factors that influence successful supply chain management. Based on thorough analysis on the state of the art literature review, a proposed construct of influencing IT factors in supply chain collaboration is offered. Multiple linear regression technique is used to model the proposed construct. The result of analysis suggests that a further research on identifying factors and determining samples is required to model accuracy.

دراسة تشخیصیة لسلسلة التورید لصناعة السجاد:دراسة حالة لشرکة سجاد رائدة

تتطلب بيئة الأعمال التنافسية اليوم ممارسات إدارة سلسلة التوريد (SC) بين شرکاء سلسلة التوريد (SC) لضمان القدرة التنافسية وتحسين الأداء التنظيمي وذلک من خلال التنسيق بين الشرکاء لتقليل الفاقد في الوقت وخفض التکاليف وتحسين الإنتاجية وزيادة الربحية. يهدف هذا البحث إلى دراسة تشخيصية لسلسلة توريد صناعة السجاد من خلال تقييم مستوى التنسيق والتکامل بين مختلف شرکاء سلسلة التوريد ووظائف سلسلة التوريد الداخلية. وتعتمد منهجية البحث علي عدة إجراءات. أولا، تم إجراء مرحلة تمهيدية لتحليل هيکل SC الحالي من حيث تحليل الموردين، وتحليل SC الداخلية، وتحليل العملاء، ووظائف SC، وتحليل ABC . بعد ذلک، تم تصميم استطلاع لتقييم مستوى التنسيق والتکامل بين مختلف شرکاء سلسلة الامداد ووظائف سلسلة الامداد الداخلية، مع توضيح نقاط الضعف ومجالات التحسين. تم إجراء دراسة حالة لإحدى الشرکات العالمية الرائدة في مجال تصنيع السجاد لإثبات إمکانية تطبيق الإجراءات المقترحة. بالنسبة لأهم النتائج، لقد وجد أنه يجب إجراء تحليل ABC بناء على الکميات المشتراة، حيث يوصى بأن تکون غالبية العناصر من الفئة C بالإضافة إلى ذلک، يجب إجراء تحليل ABC بناء على الاستهلاک السنوي للعناصر. سيحدد هذا العناصر سريعة الحرکة F والعناصر متوسطة الحرکة M والعناصر النادرة الحرکة R . النتائج الأخرى هي أن مؤشرات الأداء الرئيسية الحالية تقيس تقييم الموظفين بدلا من أهداف الشرکة، وهناک نقص في التنسيق والتکامل في سلاسل التوريد الداخلية. أيضا هناک حاجة إلى دورات تدريبية متخصصة لموظفي شرکة السجاد حتى يتمکنوا من إجراء جميع التحسينات المطلوبة. Abstract Today’s competitive business environment requires collaborative supply chain management (SCM) practices between supply chain (SC) partners to ensure competitiveness and better organizational performance. This research aims at providing procedures to conduct a diagnostic study of carpet supply chain through assessing the level of coordination and integration among different SC partners and the internal SC functions. As a methodology, first, an introductory phase was conducted to analyse the current SC structure in terms of suppliers’ analysis, internal SC analysis, customer analysis, SC functions and ABC analysis. Then, a survey was designed to assess the level of coordination and integration among different SC partners and the internal SC functions, while illustrating the weaknesses and areas of improvements. A case study of a world leading carpet manufacturer was conducted to demonstrate the applicability of the proposed procedures. It is found that the ABC analysis should be performed based on purchased quantities, where the majority of the items are recommended to be class C. In addition, the ABC analysis should take place based on items’ annual consumption. This will define the fast moving items (F), Medium moving items (M) and Rare moving items (R). Other findings are that the current KPIs measure the employees’ appraisal rather than the company’s goals, and there is a lack of coordination and integration in the internal SC. Tailored training courses are needed for the carpet company staff to be able to carry out all needed improvements.

Relationship between customer collaboration in supply chain management and operational performance of manufacturing companies

This paper presents the results of empirical analysis on the relationship between customer collaboration practices in supply chain management and operational performance of manufacturing companies. Data were collected between 2013 and 2015 from 304 manufacturing companies in 13 countries across the world in the framework of high-performance manufacturing project. The results of statistical descriptive analysis, correlation analysis and regression analysis indicate that customer collaboration practices have positive relationship with operational performance in terms of quality, cost, delivery speed, on-time delivery and flexibility. This study suggests the researchers and managers to develop and implement a set of customer collaboration practices to improve supply chain management effectiveness.

Coordination, cooperation and collaboration in relief supply chain management

In recent years, an increasing number of natural and man-made disasters has demonstrated that a working relief supply chain management (RSCM) is crucial in order to alleviate the suffering of the affected population. Coordination, cooperation and collaboration within RSCM is essential for overcoming these destructive incidents. This paper explores the research undertaken in recent years, focusing on coordination, cooperation and collaboration in the field of supply chain management (SCM) and RSCM in order to provide unique definitions of these concepts taking the disaster setting into consideration. A systematic literature review including 202 academic papers published from 1996 onwards in top journals dealing with commercial supply and relief supply chain coordination, cooperation and collaboration is applied. In order to answer the underlying research questions in a proper way, a descriptive analysis and qualitative and quantitative content analysis of the papers are conducted. Descriptive results indicate that RSCM coordination, cooperation and collaboration have increasingly shifted into the focus of scientific research since 2001/2004 (i.e., 9/11 and the Indian Ocean Tsunami). Based on the qualitative content analysis, clear definitions of the terms coordination, cooperation and collaboration in SCM and RSCM were elaborated. The research landscape, as a result of the quantitative content analysis, allowed the identification of three issues that need to be addressed in future research work.

Collocation: The Secret to Supply Chain Collaboration

A considerable literature documents the importance of collaboration in supply chain management and various means and factors that promote collaboration between suppliers and retailers such as contr...

Relationship between customer collaboration in supply chain management and operational performance of manufacturing companies

This paper presents the results of empirical analysis on the relationship between customer collaboration practices in supply chain management and operational performance of manufacturing companies. Data were collected between 2013 and 2015 from 304 manufacturing companies in 13 countries across the world in the framework of high-performance manufacturing project. The results of statistical descriptive analysis, correlation analysis and regression analysis indicate that customer collaboration practices have positive relationship with operational performance in terms of quality, cost, delivery speed, on-time delivery and flexibility. This study suggests the researchers and managers to develop and implement a set of customer collaboration practices to improve supply chain management effectiveness.

Collaboration In Supply Chain Management According To Trust Approach

Collaboration In Supply Chain Management According To Trust Approach

Use of Collaborative Plan in Supply Chain Management: A Case Study on Bangladesh Readymade Garments Industry

Collaborative plan is a major function for efficient implementation of Supply Chain Management (SCM) in the Readymade Garments (RMG) sector. Collaboration in SCM focuses on coordination, joint planning, and process integration between suppliers, customers, and other parties involved in extended supply chain. As the customers preferences are very dynamic in nature, to cope with that there is no alternative to implement collaborative SCM in the industry. This paper aims to investigate the level of practice in collaborative planning in Bangladeshi companies. A limited comparison was made with industries from developed countries. A descriptive and correlation analyses were made to find out the level of practice. The study suggests that the level of collaborative planning in Bangladesh RMG sector SCM is not satisfactory.

Supply chain collaboration in industrial symbiosis networks

A strategy supporting the development towards a circular economy is industrial symbiosis (IS). It is a form of collaborative supply chain management aiming to make industry more sustainable and achieve collective benefits based on utilization of waste, by-products, and excess utilities between economically independent industries. Based on an extensive analysis of published studies on existing IS collaborations and interviews with central stakeholders of a comprehensive IS, this paper investigates IS from a supply chain collaboration perspective. A theoretical framework is built and used to discuss how industrial symbiosis pursues sustainability and to identify the main collaboration aspects and performance impacts. This framework is then used in the analysis of selected published cases. Based on this, we derive propositions on the organizational and operational requirements for collaboration in the context of IS networks, related to the supply chain integration and coordination practices. As IS has only received little attention in the operations and supply chain management community, our propositions directly lead to future research directions. Furthermore, the analysis in this paper provides directions to increase the feasibility and resource efficiency of IS networks and can hence be used by stakeholders involved in these networks.

Electronic Data Interchange and Demand Forecasting Implications on Supply Chain Management Collaboration: A Customer Service Perspective

Customer service is a very important aspect within the supply chain. Through collaboration, the goal of each party within the supply chain is to add value to a product, in order to accelerate good customer service. Good customer service leads to customer satisfaction and most importantly it developed customer loyalty. These are the main goal of ever firm in the supply chain, starting from raw material, production, distribution and down to the final consumer. This work is developed to investigate the impact of supply chain management collaboration activities on customer service in an inter-organizational context. This is done by examining how effective collaboration in supply chain management creating confidence and trust between vendor-customer relationships that provides benefit to both organizations; one of such benefit is improved customer service. This can be obtained through the use of Electronic Data Interchange (EDI), which ensures that products are delivered to customers faster with great accuracy, and demand forecasting and inventory management, which ensures that vendors maintain optimal inventory level so that they always have what customers want in stock. The method used in this work is by gathering information from several articles, journals and text books relating to this research work. There is a total of 49 including journals, books and articles used in this work, all of which are related to this study.

Influenciadores da Gestão Colaborativa em Cadeias de Suprimentos

A gestão colaborativa em cadeia de suprimentos tem se mostrado um caminho para as organizações melhorem suas relações de forma a obter melhores resultados em seus negócios. Pesquisas demonstram ser este modelo de gestão relativamente complexo por envolver diferentes interesses das organizações, no entanto, relatam avanços, como o fato de obterem novos conhecimentos capazes de contribuir com os resultados. Nesta linha é intenção deste estudo, por meio de uma discussão literária a respeito do tema, entender quais são os influenciadores que contribuem ou não para a colaboração entre as organizações. Consequentemente, o estudo relata estes influenciadores discutindo-os como se relacionam com a gestão, sinalizando temas que podem ser melhor estudados na prática.

Collaborative Information Research on Fresh Production under Supply Chain Environment

Through the analysis of collaborative development process of supply chain and information system, this dissertation analyses how to achieve the collaboration between fresh supply chain and efficient information system. Meanwhile, it puts forward the concept of collaborative management information system of supply chain. The paper introduces the construction scheme of the collaborative agricultural supply chain management information system. In the end, the paper makes five reasonable suggestions about material procurement, transportation, warehousing, and distribution and information system construction, which with respect to integrated supply information, supplier management and produce-marketing integration.

Collaborative academic–industry SCM research and knowledge building

This empirical study represents the first attempt to explore how academics and practitioners engage each other in the Supply Chain Management (SCM) discipline, and provides a better understanding of collaborative SCM research between both parties. A two-pronged approach, involving a content analysis and an e-mail survey, is employed to explore the issues on collaborative SCM research. We examine 131 articles co-authored by both scholars and practitioners of 6 SCM journals from 2003 to 2013. Specifically, we analyse the motivations, expectations, and communication involved in the process of collaborative research. Our findings suggest that academics and practitioners can partner as co-investigators in research collaboration to better explore an array of SCM phenomena embedded in SCM practice. Further, building collaborative SCM knowledge relationships expedites collaboration and benefits SCM knowledge learning, transfer, and co-production. The development of practice-based scientific SCM knowledge is useful for SCM theory building and serves to bridge the gap between rigour and relevance.

Impacts of adaptive collaboration on demand forecasting accuracy of different product categories throughout the product life cycle

Purpose – This paper aims to empirically analyze how adaptive collaboration in supply chain management impacts demand forecast accuracy in short life-cycle products, depending on collaboration intensity, product life-cycle stage, retailer type and product category. Design/methodology/approach – The authors assembled a data set of forecasts and sales of 169 still-camera models, made by the same manufacturer and sold by three different retailers in France over five years. Collaboration intensity, coded by collaborative planning forecasting and replenishment level, was used to analyze the main effects and specific interaction effects of all variables using ANOVA and ordered feature evaluation analysis (OFEA). Findings – The findings lend empirical support to the long-standing assumption that supply chain collaboration intensity increases demand forecast accuracy and that product maturation also increases forecast accuracy even in short life-cycle products. Furthermore, the findings show that it is particularly the lack of collaboration that causes negative effects on forecast accuracy, while positive interaction effects are only found for life cycle stage and product category. Practical implications – Investment in adaptive supply chain collaboration is shown to increase demand forecast accuracy. However, the choice of collaboration intensity should account for life cycle stage, retailer type and product category. Originality/value – This paper provides empirical support for the adaptive collaboration concept, exploring not only the actual benefits but also the way it is achieved in the context of innovative products with short life cycles. The authors used a real-world data set and pushed its statistical analysis to a new level of detail using OFEA.