The purpose of this research is to explore phenomena within the experience of consumer packaged goods (CPG) account representatives in customer-facing roles by investigating the impact of supply chain training, experience, and skills on sales role effectiveness in CPG companies. Findings suggest that skills needed for sales include technical competency, excellent communication skills, and the knowledge to keep commitments. Supply chain understanding within their industry impacts these identified skills by removing confusion, improving identification with their company, realistically aligning customer expectations, and building confidence.

Abstract

The purpose of this research is to systematically review the state-of-the-art literature on Supply Chain Finance (SCF) and Environmental, Social, and Governance (ESG) and Value Chain within the supply chain management domain. We meticulously screened closely related themes through a systematic literature review of selected fifty-one manuscripts using the PRISMA method. Three-phase approach of planning, conducting and reporting is considered in this review. The outcomes of our review demonstrate the contributions of SCF to decision-making within the supply chain domain. This review highlights synergies, distinctions, and intersections in SCF, ESG, and value chain. Based on themes, the study led to four propositions to develop a comprehensive framework. Additionally, the literature is elucidated based on the approaches employed for SCF development, accompanied by the underlying theories. The categorization primarily separates the literature into two main groups: one focused on theory development, and the other on practical applications, revolving around SCF, ESG, and the value chain. Professionals in corporate settings and academic scholars will likely derive significant value from this review. The study thoroughly reviews, categorizes, and analyzes existing research and offers an integrated framework on SCF, ESG, and the value chain, which can be helpful for professionals. This is the first research that uses a structured approach to analyze studies on a novel topic and propose a framework for SCF, ESG, and value chain.

Introduction

In the last twenty years, a notable pattern has surfaced in the realm of corporate sustainability. This trend encompasses a range of initiatives, from mandates that encourage voluntary commitments to sustainable practices (Freeman et al., 2010; Wang et al., 2016; Aragòn-Correa et al., 2020; Fiandrino et al., 2022; Agrawal et al., 2023). Thus, along with sustainability strategies companies have also started sharing information about environmental, social, and governance (ESG) matters (Baid and Jayaraman, 2022; Asif et al., 2023; Kumar et al., 2024). Sustainability and ESG have attracted significant importance in the business landscape. Business need to incorporate these revolutionary changes to comply to emerging business environment. ESG captured the interest of various stakeholders such as scholars, governments, and enterprises through a report published by United Nations in 2006 (Atkins, 2020; Clément et al., 2023; Wang et al., 2023a,b). In 2021, ESG-focused portfolios accomplished nearly $40 trillion in assets further expecting a 30% increase by 2025 (Bloomberg Intelligence, 2021). This brought transparency in all the activities that could impact the environment. Exposure by social media and non-government firms led to an increase in global SC visibility (Clarke and Boersma, 2017; PRI, 2020; Saini et al., 2022; Fiandrino et al., 2022; Agrawal and Jain, 2022; Agrawal et al., 2024).

The global financial crisis of 2008–2009 witnessed increase in research on Supply Chain Finance (SCF) (Kaur et al., 2023). This crisis revealed that companies and their SC faced cash flow constraints and challenges in securing financing from banks. These difficulties were often attributed to a lack of understanding of liquidity and working capital management (Caniato et al., 2016; Baid and Jayaraman, 2022; Huang et al., 2022; Rijanto, 2024). Since then, SCF has progressively evolved as a crucial tool for tackling these challenges. The primary focus of SCF revolves around “planning, managing, and controlling SC cash flows,” as Wuttke et al. (2013) emphasized. According to Jia et al. (2020), aims to help companies fulfill their daily financing needs, optimising cash flow at the inter-organizational level. The concept of SCF is a recent development as compared to equity financing or mortgages and it faces numerous challenges, as emphasized (More and Basu, 2013; Joshi et al., 2024). It is evident that number of start-ups are also emerging in SCF space to facilitate businesses in their transactions. Emerging approaches in SCF include purchase order financing (Reindorp et al., 2018) and inventory financing (Yan and Sun, 2013). As SCF garners increasing attention, the volume of literature in this area is also rising (Gomm, 2010; Elliot et al., 2020; Jia et al., 2020; Medina et al., 2023). However, investigation on SCF or the convergence of finance and operations is yet in its early stages, primarily because of its innovative nature. As per the PRI (2020), adeptly managing ESG factors in SCF can yield a range of short-term and long-term financial benefits.

Conclusion

This review assesses 51 papers from 1999 to 2023 from the Scopus database. Fig. 4 illustrates the evolution of ESG, SCF and VC research over time, showing a significant upswing in activity from 2018 onwards. Fig. 2 reveals that in ESG, SCF, and VC, research predominantly occurs within decision sciences, engineering, computer science, business management, and accounting. Additionally, the analysis explores the facilitators and gaps associated with ESG, SCF and VC, as outlined in Section 2.3. The rising interest and application of ESG, SCF and VC, focused on tasks like economic values and minimizing its environmental impact, all the stakeholders are ethical and transparent, optimize the cash flow, improve efficiency and financial stability for offering practical solutions to contemporary business challenges. The exhaustive nature of this inquiry aims to provide a valuable and practical resource to all the stakeholders, particularly for future researchers in the field of production research. This investigative framework developed here can be a foundation for forthcoming research endeavors.

Abstract

In this paper, we examine which of an agency selling or a wholesale contract offered by an e-commerce platform competing suppliers with typical dual-channel supply chains should adopt, where the products are not differentiated between a direct channel and an indirect platform channel, as in the case of digital goods. Specifically, we consider the situation in which each of two competing suppliers chooses its distribution strategy regarding whether it sells via a direct channel and/or an indirect channel via the platform. In addition, a supplier also chooses an agency selling contract or a wholesale contract if selling via the platform. Constructing and solving a game-theoretic model, we derive the primary result that, in equilibrium, one supplier sells products only via the direct channel, while the other supplier sells via both the direct channel and the platform channel through adopting a wholesale contract, even given the assumption of symmetric suppliers. This finding yields the managerial implication that a supplier selling products of the same quality between direct and platform channels in a competitive environment should not adopt agency selling but instead a regular wholesale contract when selling via a platform. Moreover, this finding reverses the conventional insight from existing models in previous studies that at least one competing supplier always adopts an agency contract when the suppliers are without their own direct sales channels.

Introduction

Currently, a wide variety of products ranging from technologically advanced industrial products to daily necessities including food and groceries are sold through online e-commerce platforms worldwide. Consequently, platform companies have experienced tremendous growth over the past decade. For example, Amazon announced that its net sales for 2020 increased 37.6% to $386 billion, compared with $281 billion in 2019. Reflecting the development of these e-commerce platforms, the US Department of Commerce has documented that online retail sales in the US were $791.7 billion in 2020, accounting for 14% of all retail sales in the US.1 Likewise, in China, where the development of e-commerce has been especially rapid, online retail sales reached 11.76 trillion yuan in 2020, accounting for some 30% of total retail sales.2 Accordingly, manufacturers increasingly regard these online e-commerce platforms as one of their essential sales channels.

While online retailers have typically played the role of simple resellers in the past, the rapid adoption of online shopping by consumers has induced major platform companies, including Amazon in the US, Taobao in China, and Flipkart in India, to introduce a sales format known as marketplace in addition to their traditional reseller format. Accordingly, when selling products or services through an online platform, a supplier needs to select between a wholesale contract or an agency contract, depending on whether the supplier wishes to sell products wholesale to the platform or use its marketplace. The essential difference between the two contracts is who has the right to determine the retail price. With the wholesale contract, while a supplier determines the wholesale price of its products, the platform company determines the retail price. Conversely, the retail price decision is delegated to the supplier in the agency contract, such that the supplier directly determines the retail price of its products based on the revenue-sharing rules as determined by the royalty rates and commission fees set by the platform. A major benefit of agency selling to the supply chain is that it resolves the problem of double marginalization, unlike a wholesale contract, and thereby prevents a reduction in the transaction quantity.

Conclusions

Currently, many manufacturing companies are not only utilizing rapidly growing e-commerce platforms as important sales channels, but also they are opening their direct channels and selling directly to end-consumers using advanced IT technologies. Given that many suppliers are now using such dual-channel supply chains, this paper investigates whether a wholesale contract or an agency contract offered by an e-commerce platform is chosen by competing suppliers, in the situation where products are undifferentiated between the direct channel and the indirect platform channel, as is typically the case of digital goods.

The key result from our model is that if there is no differentiation between channels such that consumers perceive the direct and platform channels as substitutable, then neither of the competing suppliers chooses the agency contract. This result holds regardless of how much the platform increases the suppliers’ share of profits by lowering its royalty rate and thereby making the agency contract more profitable to them. This yields the managerial implication that a supplier selling products of the same quality across channels, such as digital goods in a competitive environment, should adopt a regular wholesale contract, not an agency contract when selling through a platform. Intuitively, if a supplier adopts a wholesale contract, this appears undesirable for the supplier because the problem of double marginalization is likely to occur. However, our results lie contrary to this intuition. Moreover, it is also a notable result that even though suppliers are assumed to be symmetric regarding demand and cost conditions in our model, their distribution strategies emerging in equilibrium are asymmetric. These asymmetric distribution channel strategies allow a supplier to differentiate itself from the rival supplier if the former sells through the platform. Because we have obtained all our main results and implications clearly in analytical form solely by solving our model, we do not conduct numerical analysis in this paper.

Abstract

     This paper investigates the transformation of information sharing and multi-tier supply chain management (MSCM) from the perspective of small and medium-sized enterprises (SMEs) in the context of Industry 4.0. SMEs are typically sharing less information digitally, are less active in conducting MSCM, but must be integrated in digital supplier networks to achieve supply chain transparency or traceability. For this purpose, this paper empirically analyzes SMEs from the manufacturing industry in Austria and Germany are investigated regarding information sharing and MSCM. The responses are analyzed to test three hypotheses, using 81 replies from manufacturing SMEs in Austria and Germany. The three hypotheses investigate the upstream and downstream MSCM practices of SMEs as well as which kind of information is shared with and by SMEs. The results help to understand and reveal potential barriers for information sharing besides technical possibilities to SMEs in order to be actively involved in MSCM.

Introduction and background

     Digital information sharing across supply networks represents a relevant topic since it enables data-based potentials such as in the concept of Industry 4.0 or for using Artificial Intelligence [1,2]. However, many companies do not recognize the importance of data availability and data quality yet. This is particularly true for small and medium-sized enterprises (SMEs), which are often impeded by missing trust, standardization, data exchange interfaces, or technological readiness [3-6] and do not recognize the relevance of digital technologies for their business [7]. Likewise, digital information sharing in multi-tier supply chain management (MSCM) is still in its early stages of development.

     This research investigates information sharing and subsequent data analysis in MSCM, focusing on SMEs. It aims at determining basic characteristics, e.g., size and vertical network position (up- or downstream), of early adopters of data-based MSCM. Raw material suppliers and upstream suppliers have a higher probability of being pressured by large buyer companies, which demand information sharing [2]. Hence, we argue that data based MSCM is more likely to be implemented in the upstream supply chain (H1). Moreover, five categories of information were evaluated if they are shared with SMEs or by SMEs (H1a and H1b): a) inventory level, b) state of delivery, c) expected delay, d) forecast data, and e) production plan

Discussion and Conclusion

Interpretation of Results

     From the interviews, we derived the motives of SMEs for carrying out MSCM and to share data. Mainly, SMEs aim to serve customer requests and to be able to fulfil their own production plan. This is in line with Arend and Wisner [14], who found that conducting supply chain management (SCM) is negatively related to SME performance since they do not implement SCM thoroughly enough or do it because they are forced by more powerful partners while not having benefits for themselves. Hence, before SMEs are able to conduct profitable MSCM, data exchange must be established with mutual benefits for supply chain partners [2]. In addition, we found that not all kinds of information may be relevant for partners in the supply network. For SMEs, binary notes would often suffice, e.g., whether the delivery is on time or not.

     In summary, it can be argued that SME must invest primarily in the area of data structures and availability in order to create the basis for data-based analyses. Particularly regarding network partners that are not directly connected to the company, there is a great need for data so that the entire structures can be analyzed and optimized. It is noticeable that there are differences between the companies in many areas of analysis, which result from the size of the company. Differences are particularly noticeable regarding data availability and the application of analyses in the supply chains. Larger companies are better equipped in terms of data availability and perform more analytics – presumably because they work more intensively with data and therefore also rate the potential higher than smaller ones. Likewise, larger companies have more power in the network and can therefore de facto secure better data availability from their network partners.

Abstract

1 Introduction

2 Related works

3 Methodology

4 Dataset information and predictors

5 Results

6 Discussions

7 Conclusions

Appendix A: The pseudocode of SVM-based classifier

Appendix B: The pseudocode of ANN-based classifier

Appendix C: The pseudocode of C4.5 DT

Appendix D: The pseudocode of RF

Appedix E: The pseudocode of bagging

Appendix F: The pseudocode of GB

Appendix G: Variables and definition

References

Abstract

     Exploring the value of multi-source information fusion to predict small and medium-sized enterprises’ (SMEs) credit risk in supply chain finance (SCF) is a popular yet challenging task, as two issues of key variable selection and imbalanced class must be addressed simultaneously. To this end, we develop new forecast models adopting an imbalance sampling strategy based on machine learning techniques and apply these new models to predict credit risk of SMEs in China, using financial information, operation information, innovation information, and negative events as predictors. The empirical results show that the financial-based information, such as TOC, NIR, is most useful in predicting SMEs’ credit risk in SCF, and multi-source information fusion is meaningful in better predicting the credit risk. In addition, based on the preferred CSL-RF model, which extends cost-sensitive learning to a random forest, we also present the varying mechanisms of key predictors for SMEs’ credit risk by using partial dependency analysis. The strategic insights obtained may be helpful for market participants, such as SMEs’ managers, investors, and market regulators.

Introduction

     The development of small and medium-sized enterprises (SMEs) has attracted attention from scholars and practitioners over the globe. However, because of the tightening of credit criteria for corporate loans, SMEs are facing significant challenges, mainly including capital constraints, high operational costs, and ambiguous information (Yan & He, 2020). As a major component of the economy in China, SMEs contribute almost 90% of the number of enterprises, 80% of urban employment, 70% of GDP, 60% of technological innovation, and 50% of tax revenue (see https://www.ndrc.gov.cn/ for more detail). SMEs in China also face problems mainly including high financial distress, high financing costs, high operational risks, tightening financing channels, high fraud risks, and asymmetric financing information (Weng et al., 2016; Zhu et al., 2019).

     As a popular financing channel, supply chain finance (SCF) defined by Hofmann (2005) as the inter-firms optimization of financing and the integration of financing processes with customers, suppliers, and service providers to increase the value of all participating firms, has attracted attention from both practitioners and scholars alike. The Chinese government has developed some new financial policies to ease the financing pressure on SMEs, e.g., Promoting SME Development Plan (2016–2020), which seek to “promote more supply chains to join the financing service platform of SMEs”. Similar initiatives are underway in other countries and regions, such as the United States, United Kingdom, Japan, Canada, South Korea, Europe, and Mexico. SCF is also being used to promote the development of SMEs. For example, the Office of the United States Trade Representative (USTR) is implementing a series of initiatives to address the financing problems of SMEs, including SCF.

Results and analyses

     To our best knowledge, this is the first study to consider the value of multi-source information fusion to predict the SMEs’ credit risk in SCF, and presents some managerial implications. We predict the credit risk of SMEs in SCF with an imbalance sampling strategy on machine learning techniques. Considering the value of multi-source information fusion in the big data era, we construct a broader knowledge base, including financial information, operation information, innovation information, and negative events, to predict the credit risk of SMEs in China, and develop new models to simultaneously solve for key predictor selection and imbalance classes. We then adopt six evaluation criteria to compare the prediction performances of the six machine learning techniques—SVM, NN, DT, RF, bagging, and GB—based on the data of VA and VS, respectively. We compare the results of new models via a re-sampling strategy for baseline models on VA and VS; the results indicate that the proposed CSL-RF model is optimal in terms of accuracy and robustness. The empirical results indicate that the financial-based information is the main source to predict SEMs’ credit risk in SCF, and the multi-source information fusion is meaningful. In addition, based on the preferred CSL-RF model, we also present the varying mechanisms of key predictors for SMEs’ credit risk by using partial dependency analysis. Finally, we generate strategic insights for market participants, such as regulators, investors, and managers.

Abstract

     Supply chain management refers to the logistics management between enterprises, which involves coordinating the design and operation of the entire chain, including suppliers, manufacturers, wholesalers and retailers. Implementing the system concept of integrated supply chain management is a research hotspot. The purpose of this paper is to study the application of intelligent supply chain management based on Internet of Things technology. Mainly take the drug supply chain as the research object, and apply the Internet of Things technology to drug transportation. The first is to analyze the traditional supply chain system to determine the supply chain’s demand for IoT technology and wireless technology; the second is to rationally optimize the various processes in the supply chain management system, and make its function realization practical. The experimental results show that compared with the original distribution logistics system, the optimized scheme saves 12.8% of the cost. Finally, the framework and structure of the medical supply chain system based on the Internet of Things technology are established, and the implementation and application are analyzed.

Introduction

     With the continuous development of supply chain management and the complexity of different logistics information, enterprises need logistics information, and the evolution of network technology provides technical support for logistics information [1]. The rapid development of the Internet of Things and computers has brought the whole society into the information age, and the logistics system has developed rapidly [2]. In recent years, many companies have integrated IoT technology into supply chain management platforms and achieved amazing results, making managers aware of the importance of IoT technology and beginning to pay attention to logistics management applications [3].

At present, scholars’ study and research on logistics service supply chain related knowledge is still in the stage of continuous development [4]. Kain R provides an overview of Logistics/Logistics Management in Supply Chain and its current logistics related issues in business and presents a conceptual approach to related issues. The logistics-based methodology is the input and output of the methodology. A literature review is conducted on key external and internal issues of logistics and industrial logistics issues to identify their various dimensions. Based on the insights obtained, a conceptual approach to logistics problems is proposed [5]. AGMabengmensah Y studies the relationship between information technology, supply chain quality integration, green logistics management and organizational performance. The intermediary role of supply chain quality integration and green logistics management is further investigated. It is found that supply chain quality integration and green logistics management play a mediating role between information technology and organizational performance. In addition, the findings suggest that supply chain quality integration plays a mediating role between information technology and organizational performance [6]. To provide customers with comprehensive and flexible services is the central idea of the current and future development trend of the logistics service supply chain. In order to provide high-quality services and make the supply chain operate efficiently, it is essential to conduct research on capacity coordination [7].

Conclusions

     IoT technology can track and manage all the data in the world. This feature is designed to make IoT shine in logistics management systems. How to introduce IoT technology into supply chain management has become the focus of many scholars. This paper introduces the logistics of the Internet-based pharmaceutical supply chain, mainly from supply logistics, manufacturing logistics, sales logistics and marketing logistics, and compares the original logistics methods and trade logistics methods. From the basic knowledge, system architecture, system implementation and main functions of the logistics integration platform, the Internet-based IoT automotive supply chain logistics integration platform is analyzed.

Highlights

Abstract

Keywords

1. Introduction

2. Background

3. Theoretical framework and enabling factors of blockchain technology adoption in the supply chain

4. Research method

5. Analysis and results

6. Discussion and implications

7. Limitations and conclusion

Appendix I. Description of the survey procedure and the questionnaire

Appendix II. Total Relation Matrix

References

Abstract

Blockchain technology has been growing in importance and acceptability over the past few years. Yet, there is limited empirical research on the organizational and technology specific factors that play a critical role in driving its adoption in the supply chain. The purpose of this paper is to develop a comprehensive framework for blockchain adoption in the supply chain by identifying the enablers and empirically evaluating their interdependencies and impact on adoption. 20 enablers of blockchain adoption in the supply chain are identified using an extensive literature review and theoretical lenses from the Diffusion of Innovation (DOI) theory and the business technology adoption model developed by Iacovou, Benbassat and Dexter (1995). In the confirmatory phase, we employ the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method to extract logic from data collected from 37 French experts about the impact of the enablers and their interdependencies. Our paper extends the multi-theoretic empirical studies to blockchain technology and identifies the enablers of blockchain adoption from technological, organizational, supply chain and external environment perspectives. Regarding the importance of the categories of enablers, we find that the relative advantage of the technology and the external pressure are the most prominent categories of enablers that impact blockchain adoption in the supply chain. Our analysis also shows the important causal role on adoption of the potential of blockchain to reduce transaction cost, the consumer interest in traceability data and the establishment of a regulatory framework for blockchain usage.

1. Introduction

Blockchain technology has recently gained importance as a promising technology in the area of supply chain management. For instance, Maersk used an IBM blockchain solution to efficiently track its containers around the world (Popper and Lohr, 2017). Catina Volpone vineyard (www.cantinavolpone.it) in Puglia, Italy and Ernst and Young’s EZ Lab (www.ezlab.it) developed a blockchain-based solution that enables full transparency through the wine supply chain and allows customers to access information about the harvesting, pressing, and bottling dates and conditions, among many other details for each bottle or case of wine (Montecchi et al., 2019). Similarly, Walmart and IBM have successfully implemented a blockchain-based solution for tracking pork products in China with a farm-to-table approach, providing transparency and full information about the supply chain stages every individual product went through (Yiannas, 2017). Blockchain solutions providers such as Everledger (everledger.io), Provenance (provenance.org), Bext360 (bext360.com) conducted pilot projects and offered typical use cases that demonstrate blockchain potential in verifying and certifying the origin, authenticity and integrity of products such as diamond, wine buttles, luxury fashion, coffee beans, and medicines (Kshetri, 2018; Montecchi et al., 2019; Lacity, 2018; Tönnissen and Teuteberg, 2020). Enabling traceability, enhancing transparency and establishing product provenance as shown in the above examples are not the only benefits of using blockchain technology. Indeed, blockchain is a distributed ledger (database) through which supply chain partners can interact and create, verify, validate, and securely store various kinds of records such as product information, certificates, localization data, transaction records, data acquired from sensors and other connected devices (Crosby et al., 2016; Iansiti and Lakhani, 2017). Thus, in addition to providing traceability and making the whole history of products digitally available, blockchain promises to improve supply chain coordination and process efficiency (Kshetri, 2018; Babich and Hilary, 2020; Queiroz et al., 2020; Wamba et al., 2020) and to achieve supply chain sustainability goals (Casey and Wong, 2017; Kouhizadeh and Sarkis, 2018; Kshetri, 2018; Babich and Hilary, 2020).

Highlights

Abstract

Keywords

1. Introduction

2. Methods

3. Results

4. Discussion and conclusion

5. Future of the aquaculture PFSC after the shock: the long path toward resilience

Declaration of Competing Interest

Acknowledgements

Author contributions

Competing interests

Appendix A. Supplementary material

References

Abstract

The COVID-19 global pandemic has had severe, unpredictable and synchronous impacts on all levels of perishable food supply chains (PFSC), across multiple sectors and spatial scales. Aquaculture plays a vital and rapidly expanding role in food security, in some cases overtaking wild caught fisheries in the production of high-quality animal protein in this PFSC. We performed a rapid global assessment to evaluate the effects of the COVID-19 pandemic and related emerging control measures on the aquaculture supply chain. Socio-economic effects of the pandemic were analysed by surveying the perceptions of stakeholders, who were asked to describe potential supply-side disruption, vulnerabilities and resilience patterns along the production pipeline with four main supply chain components: a) hatchery, b) production/processing, c) distribution/logistics and d) market. We also assessed different farming strategies, comparing land- vs. sea-based systems; extensive vs. intensive methods; and with and without integrated multi-trophic aquaculture, IMTA. In addition to evaluating levels and sources of economic distress, interviewees were asked to identify mitigation solutions adopted at local / internal (i.e., farm-site) scales, and to express their preference on national / external scale mitigation measures among a set of a priori options. Survey responses identified the potential causes of disruption, ripple effects, sources of food insecurity, and socio-economic conflicts. They also pointed to various levels of mitigation strategies. The collated evidence represents a first baseline useful to address future disaster-driven responses, to reinforce the resilience of the sector and to facilitate the design reconstruction plans and mitigation measures, such as financial aid strategies.

1. Introduction

In March 2020, the World Health Organization (WHO) declared the Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), COVID-19, as a pandemic. Since it was first recognized the virus spread rapidly and globally, causing millions of deaths. In a fight against time to slow the spread and to contain the severe deadly outbreak across the planet, national governments have made enormous efforts, by imposing containment and suppression measures with varying degrees of rapidity and strictness (Guan et al., 2020) with people experiencing unprecedented disruptions to their daily lives. Cumulatively, these responses, aimed at preventing the spread COVID-19, had clear direct and indirect effects on global economic productivity (FAO and CELAC, 2020).

Abstract

1 Introduction

2 Literature review

3 Research methodology

4 Discussion

5 Conclusions

References

Abstract

     This paper aims to understand the impact of big data analytics on the retail supply chain. For doing so, we set our context to select the best big data practices amongst the available alternatives based on retail supply chain performance. We have applied TODIM (an acronym in Portuguese for Interactive Multi-criteria Decision Making) for the selection of the best big data analytics tools among the identified nine practices (data science, neural networks, enterprise resource planning, cloud computing, machine learning, data mining, RFID, Blockchain and IoT and Business intelligence) based on seven supply chain performance criteria (supplier integration, customer integration, cost, capacity utilization, flexibility, demand management, and time and value). One of the intriguing understandings from this paper is that most of the retail firms are in a dilemma between customer loyalty and cost while implementing the big data practices in their organization. This study analyses the dominance of the big data practices at the retail supply chain level. This helps the newly emerging retail firms in evaluating the best big data practice based on the importance and dominance of supply chain performance measures.

Introduction

     Huge competition and fluctuating demand patterns increase the data generation in the supply chain (SC) (Arunachalam et al., 2018). This pushes the companies to adopt the supply chain analytics (SCA) so as to gain competitive advantage (Davenport and O’dwyer, 2011; Shafiq et al., 2020). Adopting the SCA practices improves the accuracy and overall performance of the SC. As firms are already using statistical methods for decision making in one way or another, some practitioners are against the implementation of SCA because of the time and cost incurred in adoption of these solutions (Kusiak, 2006; Trkman et al., 2010). Implementing SCA in businesses is a tricky task because of the uncertainty associated with the data and the changing requirements of the customer (Handfield and Nicholas 2004; Liberatore & Luo, 2010; Huner et al., 2011; LaValle et al., 2011; Manyika et al., 2011).

Conclusions

     The MCDM methods support the decisions given in the business, which contains many criteria that have to be satisfied to make any decision. The uniqueness of this study for the best big data practice to improve the overall performance of the supply chain is that, the qualitative and quantitative factors with different scales are combined in the same technique, also we need to know the risk concept in the analysis and last, TODIM method is applied to this problem. Although there are many decision-making methods that are based on complex calculations, the proposed framework can be applicable easily by the companies in various industries in order to make decisions based on many criteria. To get more accurate data and efficient decisions in the decision-making process, we can implement fuzzy logic to the TODIM method and Pythagorean Fuzzy TODIM so that we can reduce uncertainty and ambiguity in the decisions taken by the companies. The criteria chosen in this study are relevant to the Indian retail supply chain. These criteria can vary across the industries. Hence, the dominance values change with criteria which are different for different industries like for some industry cost may be the main criteria but for others demand management is the main criteria, so it varies from industry to industry. Hence, obtained priorities may not be generalized.

Abstract

     This paper aims to provide a bibliometric analysis of green supply chain management in platform economy (GSCM-PE) literature. Based on the bibliometric approach, a descriptive analysis is engaged in the literature published from 2003 to 2020 in Web of Science. There are 1404 publications in this field of GSCM-PE. The number of publications has increased steadily since 2013. China is an essential contributor to this field, with the largest number of publications (356), followed by the USA (175) and England (116). However, China’s total citation is 0.5 times that of the USA, which indicates that China needs further strengthened in quality. In addition, the cooperation between European and American countries is relatively active. Six clusters are identified from co-word network, and their main conclusions are as follows: (i) based on Internet technology, the application of SCM in business is the hottest topic and (ii) network risk and security requires further exploration.

Introduction

     Supply chain management (SCM) is a comprehensive and effective management method from purchasing to meeting the end customer of the supply chain, which aims to optimise the operation with minimum cost. With people gradually raising the awareness of environmental protection, SCM has become environmentally proactive in recent years, and then the role of the supply chain in promoting recycling, reuse, and resource reduction has increased (Paulraj 2011). Therefore, the sustainable characteristic in supply chain management has been interested in scholars all over the world (Mariadoss et al. 2016; Mardani et al. 2020; Lee et al. 2020). Within this status quo, the SCM has been recently connected with the platform economy, which has an important carrier of supply chain management innovation (Brettel et al. 2014). The platform economy is a new economic system based on digital technology, which has gained momentum as the core organisational form of informational transformation. In the recent two decades, the platform economy has been highly applied in various industries, such as commercial transactions, financial intermediation and ride sharing (You 2020). Behemoth digital platforms economy such as Tmall.com and JD.com has a continuously ignited capital market with the method of SCM, enterprise value and so on.

Conclusion and discussion

     Green supply chain management has become the most concerned issue all over the world. With the practice of platform economy in some specific field, the research of combining platform economy and green supply chain management is a novel emerging area in recent years, which pays attention to interested researchers. In the paper, a total of 1404 papers about green SCM in the platform are collected in Web of Science, and the bibliometric analysis and network analysis are carried out by R and VOSviewers, respectively.

     This research shows that, in terms of the number of publications, the study level of the application of supply chain management in the platform economy is constantly improving. Moreover, since 2003, the total citations has increased significantly. The author analysis shows that Zhong is the most influential author in this field on the basis of the DF value. Besides, China is an essential contributor to the literature of supply chain management in the platform economy, with the largest number of publications (356), followed by the USA (175) and England (116). However, China’s total citation is 0.5 times that of the USA, which indicates that the influence of China in this field may have room for further development.

Abstract

     With the advent of new technologies and globalization of business, supply chains have turned into indispensable tools for gaining competitive advantage. The application of new technologies like blockchain can benefit sustainable energy supply chains by improving chain and logistics operations in the areas of trust, transparency and accountability, cooperation, information sharing, financial exchanges, and supply chain integration. However, the efforts to adopt such technologies in supply chains tend to face many challenges and challenges, which can seriously threaten their success. Therefore, it is crucial to carefully examine the challenges to blockchain technology application. This research focuses on identifying the criteria and challenges to the application of blockchain in renewable energy supply chains and also ranks the identified challenges in terms of their capacity to disrupt the process. The applicability of the suggested structure is examined in a case study of the renewable energy supply chain of Iran. In this study, the challenges are evaluated and ranked by the hybrid developed methods by the integration of the concept of gray numbers into the gray stepwise weight assessment ratio analysis (SWARA-Gray) and the gray evaluation based on distance from average solution (EDAS-Gray). Another group of hybrid methods including the gray weighted sum method (WSM-Gray), the gray complex proportional assessment (COPRAS-Gray), and the gray technique for order of preference by similarity to ideal solution (TOPSIS-Gray) is used to validate the results. The rankings obtained from all of these techniques show high degree of correlation. Among the identified challenges, “high investment cost” is found to be the most important challenge to the application of blockchain in sustainable energy supply chains.

Introduction

     In today’s ever-changing world, supply chain networks tend to have diverse needs in terms of information assessment and risk management, which could be difcult to address (Ivanov et al., 2018). Indeed, the evolution of information and communications technologies (ICT) is constantly changing the requirements and capabilities of logistics and supply chain management (Goldsby & Zinn 2016). In recent years, blockchain has been hailed as a ground-breaking technology capable of transforming the form and size of businesses and how they conduct transactions (Behnke & Janssen 2020). Blockchain and Bitcoin were introduced by the person (or persons) using the pseudonym Nakamoto in 2008 (Nakamoto, 2008). Since its advent, this decentralized currency and transaction technology has been a major driver of change in business and is expected to play an even larger role in both the industry and service sectors (Iansiti 2017). The impetus behind the invention of blockchain was the lack of a transparent and sustainable independent decentralized fnancial system (Christidis & Devetsikiotis 2016). Blockchain prevents forgery and fake transactions by building encrypted blocks of all transaction records and storing them across the web such that they are constantly validated. Furthermore, the use of intelligent agreements in blockchain to control operations improves transaction transparency and increases trust among users (Constantinides et al. 2018). It has been argued that blockchain technology can modify numerous sectors of the economy, including supply chain management (Hofmann & Rüsch 2017), and may have far-reaching economic, social, and environmental impacts (Mathivathanan et al. 2021).

Conclusions and recommendations

     The advent of new technologies in recent decades has transformed how people do business across the world. This also applies to supply chains, and especially energy generation chains, which have undergone signifcant changes in the past decades. The application of new technologies like blockchain can beneft sustainable energy supply chains by improving chain and logistics operations in the areas of trust, transparency and accountability, cooperation, information sharing, fnancial exchanges, and supply chain integration. Blockchain technology can indeed have extensive economic, social and environmental impacts and hinder or accelerate sustainable development. Therefore, it is important to carefully consider adopting this technology in sustainable energy supply chains. However, as with all innovations, early adopters of this technology tend to face some resistance as well as unforeseen challenges. Blockchain has several features that can create challenges to its practical application. A survey of the research literature showed that the greatest studies on the application of blockchain have only provided case examples for this process in diferent contexts. Also, only a few studies have tried to systematically identify and evaluate the criteria and challenges to the application of blockchain in supply chains. To discuss this space in the literature, this research frst identifed the criteria of and practical challenges to the application of blockchain in a renewable energy supply chain and then ranked the identifed challenges. The ranking was conducted by the combined use of gray numbers and SWARA and EDAS. Also, WSM-G, COPRAS-G, and TOPSIS-G techniques were used to validate the fndings.