Improve Supply Chain Management Research Articles

Big data driven innovation for sustaining SME supply chain operation in post COVID-19 scenario: Moderating role of SME technology leadership

Due to the COVID-19 pandemic, there is an unprecedented crisis for businesses. The small and medium enterprises (SMEs) have been impacted even more, due to their limited resources. Extant literature has prescribed many treatments on how SMEs could survive in post COVID-19 situation, but studies did not analyse how big data driven innovation could improve supply chain management (SCM) process in the post COVID-19 pandemic under the moderating influence of SME technology leadership support. Thus, there is a research gap in this important domain. The aim of this study is to examine the impact of big data driven innovation and technology capability of the SME on its supply chain system. The study also investigates the moderating role of SME technology leadership support on SME performance in the post COVID-19 scenario. With the help of literature and resource-based view (RBV) and dynamic capability view (DCV) theory, a theoretical model has been developed conceptually. Later the model is validated using structural equation modelling (SEM) technique with 327 usable respondents from SMEs from India. The study found that both big data driven innovation and the techno-functional capability of SME impacts supply chain capability which in turn impacts the SME performance in the post COVID-19 scenario. The study also finds that there will be a moderating impact of SME technology leadership support on SME performance.

A Proposed Framework for Improving Supply Chain Management using Block Chain

A Proposed Framework for Improving Supply Chain Management using Block Chain

An analytical approach for evaluating the impact of blockchain technology on sustainable supply chain performance

Nowadays, distributed ledger technologies (e.g., blockchain technology) can play significant roles in improving supply chain management and sustainability. Blockchain technology can support responsible sourcing and ensure compliance with environmental standards by boosting traceability and transparency in sustainable supply chains. Nevertheless, blockchain technology has not been widely applied in this field due to the lack of familiarity of managers with its intrinsic characteristics. This study investigates the performance improvement, arising from the blockchain implementation, to address the problem of managerial conservatism and this technology adoption. Accordingly, an analytical approach is proposed to identify blockchain technology adoption enablers and analyze their impact on supply chain performance. At first, the main enablers, derived from the literature review, are explored using network theory. The existing causal relationships between enablers are extracted based on a multi-expertise team members’ agreement. Then, the fuzzy inference system is employed to determine the weights of relationships between the identified enablers and supply chain performance-related targets. After modeling the extracted causal relationships using the fuzzy cognitive map model, a scenario is defined for each enabler, and its impact on improving supply chain performance is estimated by implementing the hybrid learning algorithm. Finally, the obtained outputs are used to prioritize the blockchain technology adoption enablers using the fuzzy data envelopment analysis model. The result of this study implies that the blockchain technology can have a significant impact on mineral supply chain performance by creating smart contracts and enhancing environmental sustainability, traceability, and transparency.

A roadmap for sustainable development through responsible sourcing in construction

Responsible sourcing and green supply chains are becoming dominant tools towards procuring materials in a sustainable manner across the architecture, engineering and construction sector to achieve the UN’s sustainable development goals. The aim of this study was to provide a structured review of responsible sourcing literature to identify the potential opportunities and obstacles towards the accomplishment of a roadmap for the sector to support the delivery of the goals. The main opportunities included competitive advantage, stakeholder value and improved supply chain management. The main obstacles included cost, deficiencies in structured frameworks and an array of industry specific constraints. These were aligned with the goals to produce a roadmap, validated by industry experts. For fruition, it is surmised that refocusing the industry in recent years combined with achievement of the goals will stimulate innovative technical solutions to produce truly sustainable development.

Logistics and Agri-Food: Digitization to Increase Competitive Advantage and Sustainability. Literature Review and the Case of Italy

This paper examines the current challenges faced by logistics with a focus on the agri-food sector. After outlining the context, a review of the literature on the relationship between logistics and strategic management in gaining and increasing competitiveness in the agri-food sector is conducted. In particular, the flow of the paper is as follows: after examining the aforementioned managerial problem and its broader repercussions, the paper proceeds to address two main research questions. First, how and by which tools can digitization contribute to improving supply chain management and sustainability in logistics? Second, what are the main managerial and strategic implications and consequences of this for the agri-food sector in terms of efficiency, effectiveness, cost reduction, and supply chain optimization? Finally, the paper presents Italy as a case study, chosen both for its peculiar internal differences in logistical infrastructures and entrepreneurial management between Northern and Southern regions (which could be at least partially overcome with the use of new technologies and frameworks) and for the importance of the agri-food sector for the domestic economy (accounting about 25% of the country’s GDP), on which digitization should have positive effects in terms of value creation and sustainability.

Application of Value Stream Mapping in E-Commerce: A Case Study on an Amazon Retailer

In recent years, the e-commerce market has grown significantly, and the online retail market has become very competitive. Online retailers strive to improve their supply chain operations to reduce costs and to improve customer satisfaction. Value stream mapping (VSM), a tool created by the lean production movement to identify and reduce errors, losses, and lead time and to improve value-added activities, has been proven to be effective in many manufacturing processes. In this study, we investigate the application of value stream mapping (VSM) in the supply chain of an e-commerce retailer on Amazon. By visualizing the entire supply chain with VSM, the waste that is produced during the delivery process from the retailer to the customer was identified. The five whys method was then applied to find the root cause of the waste. Furthermore, a scoring method was developed to evaluate and compare two different supply chain logistic models to identify a strategy for improvement. This study provides a systematic methodology to understand, evaluate, and improve the entire e-commerce supply chain process utilizing VSM. It was demonstrated that the methodology could improve supply chain management efficiency, customer satisfaction, and cost reduction.

The role of internal audit in improving supply chain management in shipping companies

In the backdrop of several recent accounting crises, internal auditing has emerged as a major force in supporting effective controls and risk management. Therefore, internal auditing of the supply chain management performance is one of the strongest and quickest ways to reduce operational costs and provide the company competitive advantages in the global market in times of economic crisis. The purpose of this study was to examine the role of internal audit in improving supply chain management in shipping companies, the questionnaire was used to suit the nature of this study. Also, the survey included 167 participants of these companies. The results indicated a statistically significant relationship between the internal audit (independence and objectivity of internal audit, efficiency of internal audit and internal audit quality) and supply chain management in shipping companies.

Exploiting Discrete Event Simulation to Improve a Chicken Supply Chain

This article focuses on improving supply chain management (SCM) at a poultry processing plant. The strategies applied in SCM are dependent on understanding customers’ demand, the ability to forecast accurately, and maintaining smart inventory management to achieve the full advantages of SCM. This study exploits the integration of SCM concepts with business simulation, along with exploring strategies to improve the whole operation of a chicken supply chain. Witness Horizon software is utilized to model the supply chain of Company X, and information gathered on the demand and sales of poultry (chicken) is applied and computed in the simulation. The study investigates several ordering strategies, which are based on the previous week’s demand (PWD), weighted (forward) 3-point average demand (WAFD), weighted (backward) 3-point average demand (WABD), and moving average demand (MAD). Each simulation result obtained from different ordering strategies indicates the effectiveness and potential of the proposed methodology. These strategies are successfully developed and simulated, in which the results obtained demonstrate a desirable level of inventory, and profitability can be achieved by implementing these strategies in real time. The study concludes with MAD as being a suitable forecasting method for the given scenario.

Exploiting Discrete Event Simulation to Improve a Chicken Supply Chain

This article focuses on improving supply chain management (SCM) at a poultry processing plant. The strategies applied in SCM are dependent on understanding customers’ demand, the ability to forecast accurately, and maintaining smart inventory management to achieve the full advantages of SCM. This study exploits the integration of SCM concepts with business simulation, along with exploring strategies to improve the whole operation of a chicken supply chain. Witness Horizon software is utilized to model the supply chain of Company X, and information gathered on the demand and sales of poultry (chicken) is applied and computed in the simulation. The study investigates several ordering strategies, which are based on the previous week’s demand (PWD), weighted (forward) 3-point average demand (WAFD), weighted (backward) 3-point average demand (WABD), and moving average demand (MAD). Each simulation result obtained from different ordering strategies indicates the effectiveness and potential of the proposed methodology. These strategies are successfully developed and simulated, in which the results obtained demonstrate a desirable level of inventory, and profitability can be achieved by implementing these strategies in real time. The study concludes with MAD as being a suitable forecasting method for the given scenario.

Use of Big Data in Supply Chain Management

Abstract: The rapidly expanding interest in the application of big data analytics (BDA) in supply chain management (SCM) among academics and practitioners has prompted an assessment of current research progress in order to define a new agenda. the use of sophisticated analytics tools to improve supply chain management The apps are divided into three categories: descriptive, predictive, and prescriptive analytics, as well as the supply chain operations reference (SCOR) model domains of plan, source, make, deliver, and return. This review answers to the demand by offering a new classification scheme that provides a comprehensive picture of current literature on where and how BDA has been used in SCM. The classification system is based on Mayring's (2008) content analysis method and addresses four research questions: (1) In which aspects of SCM is BDA used? (2) To what extent is BDA employed in these SCM domains in terms of analytics? (3) What are the different types of BDA models utilised in SCM? (4) How are these models developed using BDA techniques? The consideration of these four topics reveals several research gaps, pointing to future study directions. Purpose - Rapid innovation and globalisation have created a plethora of opportunities and choices for businesses and consumers in the marketplace. Due to competitive pressures, sourcing and manufacturing are now done on a global basis, resulting in a huge increase in product availability. The purpose of this article is to determine whether real-time business intelligence (BI) is required in supply chain analytics. Design/methodology/approach – The paper argues for and analyses the benefits and drawbacks of BI. Findings – The article focuses on the need to review the classic BI notion of integrating and consolidating information in an organisation in order to help service-oriented businesses that want to keep their customers. Using a BI methodology to improve the effectiveness and efficiency of supply chain analytics is a vital component of a company's ability to establish a competitive edge. Originality/value – This study contributes to a better understanding of the difficulties surrounding the usage of business intelligence tools in supply chains. Keywords: Supply chain management, Business analytics, Information systems, Big Data, Big data analysis

Resilient manufacturing: case studies in Thai automotive industries during the COVID-19 pandemic

AbstractThe coronavirus pandemic is a crisis that disrupts the global supply chain and slows down the world economy. A significant challenge for the companies in the manufacturing sector is to mitigate risks related to the COVID-19 outbreak. Grounded in the resilience theory, resilience (i.e., prepare, prevent, protect, respond, and recover processes) aims to manage risks and ensure business continuity. This research aims to identify the key factors for the resilient manufacturing management of Thai automotive industries during the COVID-19 outbreak. Three outstanding companies of tier 1 automotive suppliers have been selected as case studies in this work. This qualitative research was completed by using a semi-structured interview. The target interviewers were CEOs or general managers. The data analysis was divided into two phases. Phase one summarised the interview data of each company. Phase two used thematic analysis and cross-case analysis to identify resilience practices’ patterns, themes, and multi-factors. The findings indicate three key factors to enhance resilience: leadership, technology, and the firm’s experience in handling emerging events. Together, these factors help enterprises to prepare for Business Continuity Planning (BCP), improve supply chain management, and increase the firm’s ability to recover from disruption situations. This paper contributes to the literature on the supply chain resilience in the automotive industry by providing a guideline for firms to implement resilience practices, improve business operations, and increase firm’s capabilities, both as human skills and technologies, to deal with a novel crisis. Resilience practices response to the COVID-19 outbreak not only helps the companies minimise business disruption in the short-term but also includes the long-term response strategies for unknown events. For this purpose, the case study research was conducted to investigate the resilience strategies during the COVID-19 pandemic and determine the critical success factors of resilience implementation in the Thai automotive industry.

Time for action towards a sustainable future: a policy brief for “Green Supermarkets”

Context: Climate change is considered to be the greatest threat to global public health. It affects our food and water sources, the air we breathe and the weather we experience. Climate change is equally harmful to supermarkets: 95% of the current food supply is at risk from climate change. As fewer products become available, costs will increase not only for consumers but also for purchasers. The European Green Deal functions as a secure foundation to create a business that is focused on the protection of the environment. The aim of this policy brief is to guide industry leaders on how to transform supermarkets to function in a more sustainable way and mitigate negative environmental impacts. Policy Options: Three policy options are presented for discussion: reduction of food waste, reduce energy efficiency, reduce plastic packaging. Supermarkets are a major factor in climate change contributing to food waste, high energy use and plastic pollution, each with negative effects. We see an urgent need and opportunity for supermarket chains to act. These policy options are presented in conjunction to allow for maximum effect of action. Recommendations: Supermarkets should reduce fossil fuel use in transport, storage, and delivery, incorporating sustainable design into practice. Landfill and food waste should be minimised by an improved supply chain management. Harmful packaging should be diminished or replaced by alternative materials providing customers with more sustainable options. Acknowledgments: The authors would like to acknowledge and thank John Middleton (ASPHER) for his help and support in the development of this policy brief and his insight into the field of public health during this process. Special thanks to Katarzyna (Kasia) Czabanowska for her guidance and assistance throughout all the stages of the policy brief development. Authors’ contributions: All authors contributed equally to this work. Conflicts of interest: None declared Funding: None declared

Reimagining China's Transportation Funding Investments in Africa in the Context of COVID-19.

Africa has not invested enough in its healthcare system, and China has been investing in and financing much of Africa's transportation system. Many African countries' fragile health and transportation systems have been further weakened by the COVID-19 pandemic. This literature review confirms the interdependence of the key functional areas of comprehensive development planning and the importance of building and maintaining a sound transportation infrastructure. With respect to partnerships with China, African nations need to strengthen government functional areas more comprehensively, considering all of the areas of development planning including trade as well as transportation and aid issues. It is all the more apparent given the COVID-19 pandemic that these trade deals need to include simultaneous heavy investments in healthcare, education, housing, public utilities (water and electricity), and economic development through improved supply chain management and the use of advanced digital technology. In addition to the deal structures for China's investments in Africa's transportation infrastructure, there are also opportunities to reimagine the African nations' internal transportation spending. For example, there are models in the United States for using transportation funds to invest in health clinics in transit stations. The COVID-19 pandemic has brought this issue to bear, and it is a problem that can be rectified with "comprehensive" development planning that takes into account all of the key functional areas of planning: healthcare, environmental protection, safety, education, housing, economic development, and transportation. Five recommendations follow the literature review and discussion.

Data-driven quality improvement approach to reducing waste in manufacturing

PurposeData-driven quality management systems, brought about by the implementation of digitisation and digital technologies, is an integral part of improving supply chain management performance. The purpose of this study is to determine a methodology to aid the implementation of digital technologies and digitisation of the supply chain to enable data-driven quality management and the reduction of waste from manufacturing processes.Design/methodology/approachMethodologies from both the quality management and data science disciplines were implemented together to test their effectiveness in digitalising a manufacturing process to improve supply chain management performance. The hybrid digitisation approach to process improvement (HyDAPI) methodology was developed using findings from the industrial use case.FindingsUpon assessment of the existing methodologies, Six Sigma and CRISP-DM were found to be the most suitable process improvement and data mining methodologies, respectively. The case study revealed gaps in the implementation of both the Six Sigma and CRISP-DM methodologies in relation to digitisation of the manufacturing process.Practical implicationsValuable practical learnings borne out of the implementation of these methodologies were used to develop the HyDAPI methodology. This methodology offers a pragmatic step by step approach for industrial practitioners to digitally transform their traditional manufacturing processes to enable data-driven quality management and improved supply chain management performance.Originality/valueThis study proposes the HyDAPI methodology that utilises key elements of the Six Sigma DMAIC and the CRISP-DM methodologies along with additions proposed by the author, to aid with the digitisation of manufacturing processes leading to data-driven quality management of operations within the supply chain.

Analysis and Evaluation of Barriers Influencing Blockchain Implementation in Moroccan Sustainable Supply Chain Management: An Integrated IFAHP-DEMATEL Framework

Blockchain technology has received wide attention during recent years, and has huge potential to transform and improve supply chain management. However, its implementation in the SSCM (Sustainable Supply Chain Management) strategy is sophisticated, and the challenges are not explored very well, especially in the Moroccan context. To this end, the chief objective of the current endeavor is to investigate the barriers that hinder the adoption of blockchain technology in SSCM from the Moroccan industry and service sectors’ perspective. Based on a comprehensive literature search and the use of experts’ viewpoints, the barriers affecting the successful implementation of blockchain are classified into three categories called TEO: technological and system, environmental, and intra-organizational dimensions. In this context, a fuzzy group decision-making framework is organized by combining DEMATEL (Decision-Making Trial and Evaluation Laboratory) and IFAHP (Intuitionistic Fuzzy Analytic Hierarchy Process). The IFAHP technique helps to determine the importance/priorities of barriers affecting blockchain adoption, while the DEMATEL technique forms the cause–effect interconnections between these barriers and classifies them concerning the degree of importance and relationships. The results reveal that ‘government policy and support’ and ‘challenges in integrating sustainable practices and blockchain technology through SCM’ are significant adoption barriers of blockchain in Moroccan SSCM. The proposed solution can support industrial decision makers to form flexible short- and long-term decision-making strategies to efficiently manage a sustainable supply chain.

Integration Dematel and ANP for The Supplier Selection in The Textile Industry: A Case Study

Currently, companies are required to improve supply chain performance. One of the main problems in the supply chain is the proper supplier selection. Supplier selection has an essential role in improving supply chain management performance. Supplier selection requires the proper criteria. However, the relationship between criteria is rarely considered in the selection of suppliers in the textile industry. This study tries to propose integrating the Decision Making Trial and Evaluation Laboratory (DEMATEL) and the Analytic Network Process (ANP) for supplier selection in the textile industry. Both methods are multi-criteria decision making (MCDM) tools DEMATEL is used to assess the relationship between criteria. Furthermore, ANP is used to evaluate and weigh the importance of criteria and suppliers. A case study was carried out in a textile company located in Indonesia. The results show that this procedure can identify the relationship and effect of each criterion. The results show that the product price criteria are the criteria that have the most significant weight. The criteria for conformity to specifications and consistency of quality are in second and third place. Finally, suppliers are selected based on weight assessment on each criterion by ANP.

Identification of the Critical Factors for Global Supply Chain Management under the COVID-19 Outbreak via a Fusion Intelligent Decision Support System

Under the ravages of COVID-19, global supply chains have encountered unprecedented disruptions. Past experiences cannot fully explain the situations nor provide any suitable responses to these fatal shocks on supply chain management (SCM), especially in todays’ highly intertwined/globalized business environment. This research thus revisits and rechecks the crucial components for global SCM during such special periods, and the basic essence of such management covers numerous perspectives that can be categorized into a multiple criteria decision making (MCDM) approach. To handle this complex issue appropriately, one can introduce a fusion intelligent system that involves data envelopment analysis (DEA), rough set theory (RST), and MCDM to understand the reality of the analyzed problem in a faster and better manner. Based on the empirical results, we rank the priorities in order as cash management and information (D), raw material supply (B), global management strategy (C), and productivity and logistics (A) for improvement in SCM. This finding is confirmed by companies now undergoing a downsizing strategy in order to survive in this harsh business environment.

Article 4: Impact assessment of supervision performance assessment and recognition strategy (SPARS) to improve supply chain management in health facilities in Uganda: a national pre and post study

BackgroundTo strengthen medicines management capacity, including supply chain management, at public sector health facilities in Uganda, the Ministry of Health introduced a multipronged supervision, performance assessment, and recognition strategy (SPARS). The aim of this study was to assess the impact of SPARS on improving supply chain management. A series of four papers on SPARS described the SPARS concept, its impact on overall and domain practices and appropriate medicines use, and now in the fourth paper describing the effect on supply chain management.MethodsDistrict-based health workers trained as supervisors build facility-level capacity in medicines management using an indicator-based performance assessment followed by targeted supervisory visits. From 2010 to 2013, 1222 SPARS visits were implemented, and the SPARS performance indicator scores determined. This article assesses impact on 13 indicators in three of the five SPARS domains—stock management, storage management, and ordering and reporting quality—using a pre–post design. We also explored factors that may have influenced these outcomes.ResultsBetween the first and last visit within one year of SPARS implementation, we found an average improvement of 16 percentage points (p < 0.001) in supply chain management measures across all levels of care. The improvement in scores for stock management, storage management, and ordering and reporting was 22 (ns), 16 (p < 0.001), and 11 (p = 0.032) percentage points, respectively. The study identified the key predictors of positive change as a low initial indicator score, frequent supervisory visits, and engagement of the district health officer.ConclusionsThe multipronged SPARS approach was effective in building supply chain management capacity in lower-level health care facilities with statistically significant improvements in supply chain management overall and in almost all stock and storage- management and ordering and reporting measures after one year of implementation. We recommend broad dissemination of the SPARS approach as an effective strategy to strengthen supply chain management in low-income countries.Trial registration: The study did not involve or use human participants or identifiable personal data, human tissue, or animals and thus did not require ethical approval or a waiver. It is a study implemented in collaboration with the Ministry of Health and does not require trial registration.

Bulanık DEMATEL Yöntemi ile Tedarikçi Seçim Kriterlerinin Değerlendirilmesi: Eczacılık Sektörü Üzerine Bir Uygulama

Efforts to improve supply chain management processes, which have gained importance since the '90s, have become an increasingly important phenomenon in today's competitive business life. Particularly due to recent developments, attention has turned to the health sector and improvement efforts in this sector. Supplier selection, which is the basic criterion of supply chain management, and the criteria that determine these choices are among the important issues that draw attention. In today's world where costs are reflected in prices and quality and service performance affect competition, knowing the primary criteria of pharmacies in the selection of suppliers in the health sector will guide both the actors who play a role in the sectoral dynamics and the companies. For this reason, by drawing attention to the issue of supplier selection of pharmacies, Fuzzy DEMATEL was used as a research method and supplier selection criteria of pharmacies were evaluated.

A Survey on Machine Learning Techniques for Supply Chain Management

Machine learning arose from the increasing ability of machines to handle large amounts of data over the last two decades, and some machines could also identify hidden patterns and complicated associations that humans couldn't, allowing them to make rational and precise decisions, especially for disruptive and discontinuous data. In several areas of decision-making, machines could produce more reliable outcomes than humans and have already begun to replace them. Machine learning, which is widely recognized as a breakthrough technology, has recently made significant progress in improving supply chain management processes and efficiency. From planning to delivery, machine learning may be applied at different stages of the supply chain management process. Machine learning types are supervised, unsupervised, reinforcement. Each type has many tools which are discussed below in detail. This paper presents a detailed survey on machine learning techniques for supply chain management including supply chain and supply chain management interpretation, machine learning definition, its types, and some algorithms that belong to it.