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Supply chain resilience assessment and strengthening has become a strategic topic in supply chain management. Extant literature on the subject of supply chain resilience assessment mainly focuses on evaluating the operational performance (e.g., inventory, capacity, lead time) while overlooking aspects of the financial performance. This article presents an event-based Bayesian approach as an effective tool for modeling the causal relationships among variables at different time intervals to evaluate resilience across operational and financial criteria. The model focuses on two key elements of resilience—reliability (the ability of the system to sustain an original state) and recoverability (the ability of a system to recover following a disruption), which allows us to investigate how different operational and financial factors affect the network reliability, recoverability, and resilience. This article contributes to the literature in three ways—first, we incorporate a financial perspective to the quantitative study of supply chain resilience; second, we evaluate both the financial and operational aspects from a longitudinal perspective; third, we show that the financial performance of individual supply chain entities has a strong influence on the overall supply chain resilience. From a practical standpoint, the article presents a model that can help managers identify the weakest nodes in their supply chain, considering operational and financial aspects over time, allowing them to design and operate more resilient supply networks.

The demand for apparel/fashion products is usually of heavy weather-related uncertainty, which can be solved by the publicly accessible weather information provided by the government. That is because weather information provides a more accurate demand signal, and the key weather indicators fashion brand, the latter determines the wholesale price but usually postpones the price decision to observe the weather information. Alternatively, the small retailer can outsource procurement to a powerful agent, who fixes the fashion brand's wholesale price. In this article, we investigate an apparel supply chain consisting of two competing small retailers (retailers 1 and 2), a powerful procurement agent, and a famous fashion brand. Given retailer 2's procurement outsourcing, retailer 1 decides whether to outsource procurement to the agent or directly procure products from the fashion brand. We identify cooperation and competition relationships in the retailers’ ordering decisions based on the weather information. The different intensities of the cooperation/competition relationships alter retailer 1's preferences of procurement outsourcing because of the mitigated/intensified quantity competition. Interestingly, we show that, when demand uncertainty is high, retailer 1's procurement outsourcing strategy will switch from Turnkey to Consignment and back to Turnkey, as its demand becomes more sensitive to the weather condition.

Fashion companies’ chance to survive the current pandemic is much dependent on their analytics skills. Despite this urge and the arising possibilities in the “data era,” analytics activities are still underestimated and scattered across different fashion supply chain functions. Therefore, this article positions itself at the important intersection of analytics and fashion supply chain management. This article analyzed analytics applications across all relevant supply chain functions within the fashion industry. We conducted our literature review with a focus on different forms of data-driven decision making applied within fashion supply chain functions. We systematically compared the findings from a structured literature review and a content analysis of corporate annual reports and detailed state-of-the-art analytics examples. We highlight deviations in the analytics level: Research papers have a strong focus on advanced analytics methods while most companies are struggling to establish descriptive analytics capabilities. Based on this, we derive and detail managerial and research implications. Having created a holistic overview, this article presents itself as a cornerstone for further analytics-focused research within the fashion industry. Also, it provides managers with insights into the current landscape of analytics applications and develops the vision of a future analytics-driven fashion supply chain.

“Retail Link” initially developed by Walmart enables the tier-1 supply chain partners to access the sales big data, and hence achieve demand information sharing. Doing so helps improve supplier relationships, but the supplier can make better wholesale price decisions based on accurate demand information, which might hurt the profit of the multinational firm (MNF) such as Walmart. Therefore, it is observed that some MNFs outsource both procurement and logistics functions to a logistics service provider (LSP) for the benefits of “one-stop-shopping,” and meanwhile, cut the information link with the supplier. This significantly changes their decision interactions and the resulted social welfare. In this article, we build a co-opetition model and study an MNF's two typical outsourcing strategies, where the MNF either outsources the logistics or the bundled functions of procurement and logistics to an LSP. We find that, when the market demand uncertainty is low, the MNF prefers bundled outsourcing given its significant brand image advantage. When the market demand uncertainty is high, the MNF prefers bundled outsourcing regardless of its brand image advantage. Interestingly, when market demand uncertainty is moderate, the MNF prefers bundled outsourcing when its brand image advantage is either not significant or very significant. We further compare the social welfare levels under two outsourcing strategies and find that win–win situations in the senses of the MNF's profit and social welfare can be identified.

Motivated by the practices of technology investment in the new energy vehicle manufacturing industry, this article investigates an outsourcing supply chain in which an original brand manufacturer (OBM) possessing the core new energy technology R&D outsources production to a competitive manufacturer (CM). To cater to market demands and increase market competitiveness, the CM may actively invest in technology with the OBM or by himself, or not, i.e., Strategies JI, OI, and NI, respectively. In particular, owing to technology spillover effect, the CM could use the technology inferior to the OBM's to produce his own-branded products in Strategy NI. Our results reveal that the OBM consistently profits the most in Strategy JI. However, the CM's preference strategy is influenced by the competition intensity, technology spillover level, consumers’ product preference, and cost-sharing ratio. In specific, when both the competition intensity and technology spillover are weak or the competition intensity is strong for arbitrary technology spillover level, the CM may prefer Strategy JI or OI depending on consumers’ product preference and cost-sharing ratio and never prefers Strategy NI. However, when the competition intensity is weak but the technology spillover level is strong, the CM may prefer Strategy NI in certain situations. Furthermore, our study extends the model to involve variable production costs, and reveals that the main results derived in the basic model still hold.

Supply-chains (SC) present performance bottlenecks that contribute to a high level of costs, infiltration of product quality, and impact productivity. Examples of such inhibitors include the bullwhip effect, new product lines, high inventory, and restrictive data flows. These bottlenecks can force manufacturers to source more raw materials and increase production significantly. Also, restrictive data flow in a complex global SC network generally slows down the movement of goods and services. The use of Distributed Ledger Technologies (DLT) in supply chain management (SCM) demonstrates the potentials to to reduce these bottlenecks through transparency, decentralization, and optimizations in data management. These technologies promise to enhance the trustworthiness of entities within the supply chain, ensure the accuracy of data-driven operations, and enable existing SCM processes to migrate from a linear to a fully circular economy. This paper presents a comprehensive review of 111 articles published in the public domain in the use and efficacy of DLT in SC. It acts as a roadmap for current and future researchers who focus on SC Security Management to better understand the integration of digital technologies such as DLT. We clustered these articles using standard descriptors linked to trustworthiness, namely, immutability, transparency, traceability, and integrity.

The food industry has been widely regarded as an effective sector due to its contribution to the national economy, job creation, and people's welfare. Malaysia as one effective country in the food industry and leading country in Halal food brand emphasized the importance of food quality in both operation and supply chain. Despite the importance of the Halal food industry to countries' economy including Malaysia, this industry is facing multiple challenges. In addition, halal food literature still in the infant stage despite the rapid growth of this important industry. Therefore, this review study aims to identify the challenges that surrounded the Halal industry worldwide generally and Malaysian firms particularly. This study also aims to identify the potential solution to overcome Halal food challenges. The finding of this study uncovers multiple challenges surrounded the Halal food industry in operation, marketing, and certification processes. This study also suggests that the application of the manufacturing execution system can bring a new insight to overcome Halal food challenges. This study contributes to the body of knowledge by providing a clear understanding of Halal food industry operation and certification and their challenges and explains how MES can improve the efficiency of this industry.

Blockchain technology has wide area of application, this article is very particular on emphasising another important field of application named Agro-products supply chain. Wherein this era, and the future needs to nurture the agriculture sector along with latest technologies, so that nation would make a revolution in the process of food supply from the farm to the plate. The main drawback in the agriculture supply chain is lack of transparency in food production and distribution, costly middleman, limited financial resources & disconnection between supplier and retailer. So this article proposes, suitable theoretical auction flow model to overcome all the issues highlighted in this agro-sector, we would like to give the solution by improving the transparency in the supply chain, by providing farmers direct access to suppliers through an appropriate auction system with an option of immediate payment on delivery & transparent transaction information to them. Further we can involve government as a central authority to overcome the technical aspects, education, policies and regulatory frame works, in turn they can generate job opportunities to the unemployed graduates.

Blockchain for supply chain use cases is quickly becoming a prevalent topic of discussion among distribution giants and smaller players. The actual and perceived benefits of blockchain have driven these discussions, as supply chain partners are well aware of the data protection, increased transparency, and end-to-end authentication of goods that blockchain technology can provide. Track and trace mandates from regulatory bodies are also driving the discussions. However, missing from the dialogue is how partners in this ecosystem manage and resolve disputes using smart contracts inherent in blockchain instead of existing dispute resolution mechanisms and processes. This gap is critical; trust will be eroded if supply chain partners do not have adequate dispute resolution mechanisms within the blockchain ecosystem. This paper highlights the areas of friction and potential disputes for supply chains arising from emerging technology such as Artificial Intelligence (AI), asset management using Internet of Things (IoT), and particularly blockchain, a type of Distributed Ledger Technology (DLT). We discuss the importance of regulation in how the use of DLT in supply chains is managed and suggest principles of resolving inevitable disputes with disparate information. We emphasize the need for portable and enforceable contractual terms and argue that standardizing how disputes are resolved may go a long way to technology adoption.

In this article, we explore the topic of supply chain resilience (SCR) in an open-system context. Systems theory and cybernetics are important methodologies in the analysis of complex networks. However, relatively little is known about their application in the supply chain (SC) operations. Using systems theory and cybernetics for SCR conceptualization, we argue that a systems-theoretical lens can help to extend the state-of-the-art research to describe SCR based on the concept of balancing vulnerability and recoverability over time. Toward this end, we define and test a new resilience measure for SCR using the Bayesian network approach with a compounding function of vulnerability and recoverability. We further propose managerial actions for implementing an open-system view of SCR. To demonstrate the applicability and usefulness of our method, we measure and analyze the resilience levels of a manufacturer. Our results provide useful decision-making support and can be valuable for SC managers seeking to balance risk mitigation and recovery capabilities. The framework and measure developed can also be used to guide firms seeking to analyze the impact of disruptions on SCs through the consideration of both performance degradation and recovery.

Many small and medium enterprises (SMEs) engage in dyadic information integration partnerships or partial integration with their direct suppliers and customers. They often utilize e-commerce or cloud computing technology platforms hosted by third-party providers to leverage such partnerships. However, information security breaches and disruptions caused by cyberattacks are commonplace in the information technology industry. The effects of said disruptions and breaches on e-commerce businesses under varied disruption conditions are still uncertain. Furthermore, the effect of security breaches on nonparticipating members of the supply chain is poorly understood, especially under various disruption profiles. Using discrete event modeling, in this article, we explore the impact of disruption caused by information security breaches on supply chain performance and the externality effect of partial integration on nonparticipants. We also examine the impact of breach disruption frequency and remediation length on supply chain performance with varying levels of information sharing. These impacts were studied under two typical inventory replenishment policies for SMEs. It was determined that remediation length should be a prioritized factor in impact management and that flexibility in the inventory replenishment policy can help mitigate the impact of information disruption on the inventory performance of businesses, especially that of nonparticipants, in information-sharing partnerships.

When multiple retailers hold inventory to satisfy random demand, retailer inventory-sharing strategies can potentially reduce the supply-demand mismatch and increase overall supply chain performance. In this paper, we experimentally investigate alternative inventory-sharing strategies in a two-tier supply chain with an upstream manufacturer and two downstream retailers. In one setting, retailers act as if they are centralized and use a single quantity to fulfill joint demand. In the other, retailers are decentralized and face separate demands, but they can transfer inventory after demands are realized. In this latter decentralized scenario, we also consider whether the manufacturer or retailers have decision authority over the inventory transfer price. One key result is that when the retailers are decentralized and the manufacturer sets the transfer price, both retailers and the manufacturer earn higher profits than in the centralized retailer strategy, which runs counter to theory. We also find that when retailers are decentralized and set their own transfer price, the most equitable distribution of profits is achieved. In an effort to account for these results, we find that a model of fairness captures decisions well. Overall, by investigating how different inventory-sharing strategies affect the distribution of profits in a two-tier supply chain, our results provide guidance to firms considering how, if at all, they should enter such arrangements. This paper was accepted by Jay Swaminathan, operations management. Funding: The authors acknowledge financial support from Cornell University and the University of Virginia. Supplemental Material: The data files and electronic companion are available at https://doi.org/10.1287/mnsc.2022.4323 .

Problem definition: This paper investigates and compares two types of food safety auditing structures: decentralized and centralized audits. Academic/practical relevance: Decentralized food safety auditing systems are common among developing economies, that is, different tiers of a food supply chain are audited by separate government agencies. Such an auditing structure has been widely criticized as ineffective at mitigating food safety risks. Some developing countries began implementing centralized auditing systems as a remedy for the mis-coordination across local auditing agencies. We compare food safety outcomes and economical payoffs of the two auditing systems. Methodology: We study a parsimonious game-theoretic model of a one-supplier, one-buyer supply chain and two agencies auditing each tier of the supply chain, respectively. Under decentralized audits, each of the two agencies minimizes its individual cost, and their decisions are sequential; under centralized audits, the agencies minimize total agency cost and make auditing commitment up front. Results: We identify forces that drive equilibrium decisions under decentralized audits. The penalty-shield effect of an agency’s auditing capability may lead to risky behavior by the supplier. The free-riding effect between the two agencies may lead to less auditing. A centralized commitment makes the agencies the leader in the game at the expense of them losing the flexibility to respond to the actions of supply chain members. The common objective under centralization strengthens the incentives for at least one agency to conduct an audit, but it may also induce the lower-cost, less-capable agency to audit. Hence, centralized audits can be detrimental to performance regarding both food safety outcomes and system payoff. Managerial implications: Changing the auditing structure from decentralization to centralization may fail to improve food safety and system payoff insofar as it may replace one form of inefficiency with another. Addressing the new inefficiencies should be part of the ongoing effort to enhance the efficacy of centralized audits. History: This paper has been accepted for the Manufacturing & Service Operations Management Special Section on Responsible Research in Operations Management. Funding: The work of D. Shi was supported by the National Natural Science Foundation of China [Grant 72102205]. Supplemental Material: The online supplement is available at https://doi.org/10.1287/msom.2021.1058 .

Closed-loop supply chain (CLSC) implementation has become imperative for organizations owing to resource scarcity and generation of toxic waste. However, CLSC implementation can be very challenging due to several barriers, especially in an emerging manufacturing hub such as India. This article identifies and analyzes the prominent barriers to CLSC implementation in the Indian automotive sector. Further, this article also examines causal relationships between the barriers. A total of 22 barriers to CLSC implementation are identified from the literature and subsequently, validated by industry experts. The finalized barriers are then evaluated by analytical hierarchy process and grey–decision making trial and evaluation laboratory techniques. This article provides managers and policy makers with insights on the most prominent and causal barriers, and recommends strategies to overcome these barriers. The findings will help managers to frame short-term and long-term strategies to mitigate barriers to CLSC and contribute toward successful implementation of CLSC.

With the increasing popularity of third-party platforms, some retailers have used them to sell their products in addition to their own online and offline channels, while other retailers have not. An important pair of questions thus arise: should a retailer that has its own online and offline channels sell through a third-party platform? If so, which selling format should it adopt? This study considers the interaction between offline channel and internet channels (including online channel and third-party platform channel) and establishes a model with a spillover effect that can act in two directions: from offline channel to internet channels (O2I) or from internet channels to offline channel (I2O). We explore three different supply chain structures/scenarios: a dual-channel structure (D); a triple-channel structure: reselling format (MR); and a triple-channel structure: agency selling format (MA). Using a game-theoretic model, we investigate whether the retailer should use a third-party platform and its selling format preference, and further explore the impact of the direction of the spillover effect. Our theoretical analysis shows that when the channel competition is moderate, the region in which the retailer uses the third-party platform first increases and then decreases as the spillover effect increases. Given a reasonable agency fee, when the channel competition is medium, the retailer is more likely to prefer MR as the O2I spillover effect increases, but to prefer MA as the I2O spillover effect increases. We also find that two Pareto zones exist, that is, the retailer and third-party platform prefer the same selling format in some cases, either MR or MA.

In supply chain (SC) systems, channel coordination can be achieved by incentive alignment contracts. The contracting mechanisms reported in the literature are usually “short-term-based” and the respective decisions are assumed to be static. However, real world supply chains (SCs) operate in the long term and decisions may evolve when time passes. As a result, this paper analytically explores the instability of the short-term coordination strategies and examines the evolutionary behaviors of SC members towards SC coordination. Moreover, it incorporates the effects of SC members’ evolutionary strategy adoption into profit surplus distribution among them. To be specific, an evolutionary game theory-based model, namely the “profit surplus distribution (PSD) mechanism for supply chain coordination”, is proposed to investigate how long-term behaviors of SC members will affect the coordination decisions (i.e., choosing to collaborate) and their share of coordination profit surplus. Based on a real case in consumer electronics, we analytically investigate a two-level SC consisting of a retailer investing in sales-effort and a population of manufacturers investing in innovation effort. Using the evolutionary game theory, we examine the relationship between the evolutionary strategies of SC members towards channel coordination and the profit surplus distribution among them. The results reveal that the coordination strategy is preferred by a great percentage of manufacturers in the long term and their share of coordination profit surplus plays a critical role in affecting their evolutionary preference (and vice versa).

We live in an age of massive global disruption. Technological advancements threaten century-old business models, globalization is reordering supply chains, and people need to work with colleagues and customers who have vastly different backgrounds. On top of that, we have been in the midst of a global pandemic, and customers, employers, and investors are demanding more than just a Black Lives Matter social media post from organizations that purport to take social justice seriously. Organizations with high cultural intelligence (CQ) are able to navigate this volatility and complexity effectively. Over the last two decades, scholars from across the world have published hundreds of articles on CQ, the capability to relate and work effectively in complex, culturally diverse situations. Most of the work has examined CQ at the individual level. But what about organizations? Can organizations be culturally intelligent? The emerging research on CQ at the organizational level offers leaders and organizations critical insights for navigating today's diverse, digital world. Organizational CQ is a firm's capability to function effectively in a complex and unpredictable multicultural world. This article stresses the importance of the culturally intelligent organization and explains how to develop organizational CQ.

With the advent of responsible business, ensuring social responsibility in sourcing is of interest to both academics and practitioners. In this study, we examine one way of achieving this goal: ethical sourcing initiatives (ESIs). ESIs refer to a firm’s formal and informal actions to manage sourcing processes in an ethical and socially responsible manner. While ESIs have been established as an important part of corporate social responsibility, it is unclear whether, how, and when this corporate effort is economically beneficial. We conduct an event study estimating the shareholder value effect of 159 publicly traded firms’ ESIs and find that the stock market reacts positively to ESIs in general. We also compare market reactions under different conditions including reactive versus proactive ESIs, and their interactions with initiative timing, firm size, and financial risk. Additionally, we find that ESIs are associated with long-term stock price and operating performance. Overall, our findings clarify the potential economic benefits of corporate ESIs and encourage buying firms to take these initiatives selectively according to business contexts.

The recent COVID-19 pandemic pandemic has highlighted the importance of food safety and supply chain governance. In other words, we need to ensure traceability along the supply chain, support high-frequency transactions and effective data collections, etc. Thus, we posit the potential of using lightning network, which is a decentralized traceable paradigm for achieving high-frequency transactions in blockchain-based systems. In addition, we also utilize edge computing to help facilitate data collection. However, a key challenge in securing food supplies is determining the optimal global transaction path in lightning network, while achieving efficiency and meeting the dynamic nature of food supply management. Thus, we propose a blockchain-edge scheme that utilizes our proposed dynamic programming to produce optimal solutions to selecting global transaction paths. Specifically, our scheme optimizes routing fees under existing constraints (e.g., transmission cost, computing resource consumption, and lightning network balance). Findings from our evaluations demonstrate that the utility of our proposed approach in facilitating food safety management.

To reinforce competitiveness, companies must focus on competitive priorities including cost, quality, delivery, and flexibility. The competitiveness also depends on the adherence to environmental requirements and the ability of companies to survive unforeseen disruptions. Lean, agile, resilient, and green (LARG) paradigm is a hybrid supply chain paradigm, which can enhance competitiveness in today's complex markets. In this article, we propose a new conceptual decision-making model to evaluate LARG supply chain performance in medical equipment companies. In this regard, supply chain operations reference model attributes were utilized as performance evaluation criteria. Furthermore, the appropriate practices of LARG supply chain are selected through fuzzy Delphi method. Also, an extension of decision making trial and evaluation laboratory-based analytic network process method is proposed to uncover network relationships and obtain the weights for dimensions and elements. According to the results, the agile paradigm, responsiveness, and quick introduction of new products are determined as the most prioritized elements in their corresponding dimensions, which emphasize the importance of the customer satisfaction. Finally, the extended hesitant fuzzy linguistic VIKOR (Vlsekriterijumska Optimizacija I Kompromisno Resenje) is applied to rank LARG performance of Iranian needles and syringes companies via qualitative group decision-making process. The results of this study are conformed to conventional selection results of needles and syringes suppliers conducted by Iran's Ministry of Health.

Project management is used to coordinate effort during tasks, such as new product design, software engineering, and supply chain improvement. An essential component of project management is the communication plan that directs team members in their use of communication channels for information sharing during the project. Yet, few decision-making tools exist that can help project managers understand the tradeoffs of different communication plans. Herein we connect theory and practice to advance a computational model that provides objective-based assessments of communication plans and helps managers weigh tradeoffs of cost, time, and quality in the use of communication channels across the project. We draw on adaptive structuration theory to understand the impetus to utilize technology in group settings and media richness to explain the capabilities of channels that offer rich synchronous platforms (for e.g., phone, face-to-face, and web conference) and asynchronous lean approaches (for e.g., email, message board, and archive). We describe the tool based on a multiple-criteria decision making model. This model contributes a theoretically based decision support tool for project communication plans.

We quantify the criticality of the world’s 1300 most important ports for global supply chains by predicting the allocation of trade flows on the global maritime transport network, which we link to a global supply-chain database to evaluate the importance of ports for the economy. We find that 50% of global trade in value terms is maritime, with low-income countries and small islands being 1.5 and 2.0 times more reliant on their ports compared to the global average. The five largest ports globally handle goods that embody >1.4% of global output, while 40 ports add >10% of domestic output of the economies they serve, predominantly small islands. We identify critical cross-border infrastructure dependencies for some landlocked and island countries that rely on specific ports outside their jurisdiction. Our results pave the way for developing new strategies to enhance the resilience and sustainability of port infrastructure and maritime trade.

The modern day food industries are part of a complex agri-food supply chain, where food production has become efficient, yet potentially vulnerable to supply chain risks. The COVID-19 pandemic is a testament to that end. This article measures and identifies the U.S. food manufacturing industries' vulnerability to upstream industries and labor occupations by (i) calculating a food industry's diversification of intermediate input purchases across upstream industries, (ii) quantifying the relative exposure of food manufacturing in a given industry and location to upstream input suppliers and labor occupations, and (iii) estimating each food industry's gross output elasticity of inputs. Among our results, we find the evidence that the animal processing industry's output is relatively vulnerable to production labor which is consistent with the observed disruptions to the meat packing sector during COVID19, which were largely caused by labor issues. Our results may help academics and practitioners to understand food industries' vulnerabilities to upstream industries and labor occupations.

In the early onset of the COVID-19 pandemic in the U.S., consumers experienced surprising shortages of essential goods such as toilet paper, yeast and flour, and some of their favorite meat cuts that appeared to be unrelated to the pandemic at first look. The “usual” explanations attributing these shortages to “demand spikes” (e.g., foreign suppliers, trade wars and tariffs, and “hoarding behavior” of panicked consumers) often failed to explain them, and in the best of cases, predicted only temporary shortages. However, shortages in these supply chains ended up being in many cases real “supply chain struggles,” with their true causes going beyond the “usual” ones, and revealing a set of deeper and “unusual causes.” Our detailed analysis of the affected supply chains identifies these overlooked failure factors and hidden causes. Our underestimated causes include demand shifts among market segments, siloed demand planning, bottlenecks in shared resources such as transportation and distribution, and supply chain structures driven by the economics of an efficiency era that failed in a risk-fraught environment. We conclude on the profound lessons learned from the pandemic crisis on supply chains, and the implied challenges to address for building resilient supply chains for the future. The resilient supply chains of the future require rethinking the relevant “systems” we plan and optimize (e.g., firm, industry, region, global factor resources, etc.). The usual answer of building firm-specific redundancy of assets and operational flexibility might be prohibitive in the level of investment required for any one firm, or their financial stakeholders, to pursue and accept.

During the past decade, the demand for biofuel has rapidly increased because of fossil fuel scarcity and pollution, which has resulted in the accelerating commercialization of the global biofuel markets with a potential 500 exajoules per year by 2050. This paper evaluates the economic benefits of five biomass types and proposes a stochastic programming model for the optimal design of the global biodiesel supply chain under the demand and price uncertainty. The biomass is produced in Southeast Asia and oil is extracted. Then, the vegetable oil is shipped to Europe and North America for biodiesel conversion and fulfilling the local demand. The results show that palm tree is a cost-effective clean energy with high benefits and low-carbon emissions. Based on the economic evaluation of biomass, the optimal capital investment, allocation of cultivated area, and transportation paths are identified to maximize the expected global profit in this supply chain in 2008–2012 by the proposed supply chain optimization model.

This study investigated the effects of applications of international quality assurance certification at farm level on the implementation of traceability along the shrimp supply chain with evidence from Vietnam. Descriptive statistics was explored to compare products, information flows, financial efficiency, and willingness to implement traceability between certified and noncertified quality assurance shrimp farms. A binary logistics model was applied to examine the effects of applications of international quality assurance certification and other factors on the willingness to implement traceability of shrimp farmers. Found results showed that the applications of international quality assurance certification of shrimp farmers supported traceability of shrimp products among stakeholders in the supply chain. The certified farmers indicated a higher willingness to implement traceability. However, the profitability of those applications for shrimp farmers was not statistically found. The economics incentives, including farm-gate price differentiation and minimization of production costs, should be carefully considered.

The authors propose that the current trends and developments in the international marketplace call for a new theoretical concept-based approach to inform and guide cross-border marketing strategy. Specifically, the authors label this approach marketing ecosystem orchestration (MEO). The marketing ecosystem is defined as connected, interdependent, and co-evolving sets of actors, activities, and institutions enabling the marketing of an offering that has value for customers, clients, partners, and society at large. MEO is a new strategic approach for an internationalizing firm to achieve sustained value creation, value appropriation, and growth in a host market. Orchestration involves developing and/or coordinating the ecosystem’s interdependent – but independent actors, resources, information, processes, and services to create, co-create, and appropriate value from firms’ market-based assets. The authors theorize three components of MEO – the orchestration of supply chains and fulfillment networks, marketing communications, and transactions and payments sub-ecosystems – and develop a conceptual framework and propositions influencing the determinants of MEO adoption by the focal firm. This paper concludes with managerial implications and offers several new directions for international marketing research.

Internet of things (IoT) results in massive amount of streaming data, often referred to as “big data”, which brings new opportunities to monitor agricultural and food processes. Besides sensors, big data from social media is also becoming important for the food industry. In this review we present an overview of IoT, big data, and artificial intelligence (AI) and their disruptive role in shaping the future of agri-food systems. Following an introduction to the fields of IoT, big data, and AI, we discuss the role of IoT and big data analysis in agriculture (including greenhouse monitoring, intelligent farm machines, and drone-based crop imaging), supplychain modernization, social media (for open innovation and sentiment analysis) in food industry, food quality assessment (using spectral methods and sensor fusion), and finally, food safety (using gene sequencing and blockchain based digital traceability). A special emphasis is laid on the commercial status of applications and translational research outcomes.

Metrics that assess farmer sustainability performance have emerged as a leading approach to fostering continuous improvement in the sustainability of agriculture. As multi-stakeholder initiatives (MSIs) have developed sustainability metrics for US agriculture, these initiatives are entering a new phase focused on the adoption of metrics. This paper examines the approaches being used by two MSIs, Field to Market and the Stewardship Index for Specialty Crops (SISC), to promote their respective metrics to farmers. Drawing on assemblage theory, we analyze the processes that MSIs are using to get their metrics implemented, and how the actual adoption of metrics takes place in agrifood supply chains. Specifically, we identify five processes that both Field to Market and SISC are using to facilitate the implementation of their metrics: (1) leveraging members, (2) utilizing supply chains, (3) providing technical assistance, (4) building technological platforms, and (5) creating partnerships. In identifying these processes, our analysis shifts understanding of metrics adoption beyond just consumer and market forces, and focuses attention on the specific actors and processes through which sustainability metrics are put into practice. In concluding, we highlight ongoing challenges facing Field to Market and SISC's efforts to construct assemblages around their metrics.

This paper considers the digitalisation of food infrastructure as a wider context within which smart farming and big data applications in agriculture are being introduced. It examines the use of digital devices aimed providing traceability and transparency across different sites of food supply chains, from farm to fork. The infrastructural perspective problematises ideas of digitalisation as a technological fix to the uncertainness of food supply chains, and highlights the relational nature of food. Digital devices aimed at ensuring food integrity and the control of supply chains are shown to reconstitute infrastructures of qualification by which the qualities of foodstuffs are established as they move through the processes of the supply chain, from production to consumption. The paper identifies question of power around the ongoing process of infrastructuring that generate a requirement for more labour by some actors; the possibility of new politics and relationships built around increased circulation of quality information; and questions of who controls access to information that are obscured by different understandings of transparency.

As a novel retail model in the age of Internet Plus, community group buying (CGB) has received a growing attention from the public. This paper introduces promotion effort (PE) and service level (SL) into system decision-making, and tries to coordinate the CGB supply chain comprising of a supplier, a group buying platform, and a group leader. Firstly, the authors constructed a decentralized decision-making model and a centralized decision-making model for the CGB supply chain, and solved the optimal decisions and profits of each model. On this basis, a coordination mechanism was designed for the CGB supply chain. After that, the model results were verified through numerical simulation. The results show that: Under the decentralized decision-making model, the wholesale price, retail price, platform SL, and leader’s PE are positively correlated with the elastic coefficient of PE, and negatively with the effort cost; under the centralized decision-making model, the retail price, platform SL, and leader’s PE are positively correlated with the elastic coefficient of SL, and negatively with the service cost; using the group leader’s commission as a coordination tool and combining with the traditional revenue sharing contract, the revenue sharing-commission coordination (RS-CC) contract is designed to realize the coordinated operation of the CGB supply chain. The research findings further enrich and improve the theoretical basis of the CGB supply chain, and provide a reference for the decision-making by relevant enterprises.

Transportation and movement of goods is one of the most important human needs, the operation of transportation determines the efficiency of moving products. The progress in techniques and information technology (IT) and management principles improves the moving load, delivery speed, service quality, operation costs, the usage of facilities and energy saving. This study deals with the logistics processes in supply chain management, information technology in management and prospects for the use of information technology in the transportation logistics segment, with particular attention paid to the key factors in information technology that affects the efficiency of transport, allows information to be collected on such as traffic volume, flow, average traffic speed, and actual journey time. Such innovative means of gathering data on automobile traffic open up new perspectives for assessing transport accessibility in terms of automobile traffic by providing high-quality data that meet the requirements for use in company. The main purpose of this study is to give a comprehensive review of information technology (IT) and relationship with transport leading to increased competition and improvement of the level of Algerian companies.

Motivated by the commonly observed commercial used apparel collection (UAC) programs in fashion retail supply chain operations, this paper analytically explores the associated operational challenges that firms face. First, in the basic model, we consider the case when a fashion retail brand promotes its UAC program and collects the used apparel from consumers. Depending on the conditions of the collected apparel products, the fashion retail brand will classify and either donate them for charity or send them to remanufacturing. For either case, the fashion retail brand gains a benefit. We analytically derive in closed-form the optimal promotion effort and study the mechanism for “profit” coordination. Our results indicate that many traditional supply chain contracts fail to achieve “profit” coordination. Thus, the effort cost sharing (ECS) contract is proposed and proven to be effective for “profit” coordination. Finally, to check the robustness of findings from the basic model, we examine various UAC practice related extended models, such as i) consumer coupon offering, ii) “no remanufacturing” model, iii) consumer heterogeneity in environmental consciousness, iv) own-brand collection vs any-brand collection. Our findings show that the qualitative insights continue to hold in the extended scenarios. Some novel scenario-dependent findings are also obtained. Insights derived in this paper not only contribute to the literature but also provide scientifically sound managerial guidance and insights to practitioners on how UAC programs can be best operated.

Despite efforts to maintain supply chains unaltered as a result of the Covid-19 pandemic, statistics published after the second quarter (Q2) of 2020 have confirmed a drop in maritime traffic in European ports. Furthermore, the evolution of the pandemic indicates that stabilisation of traffic at levels prior to the Q1 of 2020 may take years. Port authorities in Europe, in an overall context of landlord port governance, are already being challenged, due to the need to ensure the provision of port technical services (mooring, pilotage and towage). In addition, the cost adaptability of these services to the current situation could be confronted by the European legal framework that demands transparency and proportionality in port rates in order to provide an effective cost of services. This paper analyses the impacts of Covid-19 on European ports, first by quantifying traffic drop after Q2 of 2020 and then calculating its effects on the cost of port technical services, in a general context of lack of flexibility in the cost structures of private providers. Due to this ongoing situation, a rise in rates, allowed by the port authorities, could mean that the prices of port services are not aligned with effective costs, along with loss of competitiveness.

Problem definition: We study the coordination of an E-commerce supply chain between online sellers and third party shippers to meet random demand surges, induced by, for instance, online shopping holidays. Academic/practical relevance: Motivated by the challenge of meeting the unpredictable demand surges in E-commerce, we study shipping contracts and supply chain coordination between online sellers and third party shippers in a novel model taking into account the unique features of the shipping industry. Methodology: We compare two shipping contracts: the risk penalty (proposed by UPS) and the flat rate (used by FedEx), and analyze their impact on the seller, the shipper, and the supply chain. Results: Under information symmetry, the sophisticated risk penalty contract is no better than the simple flat rate contract for the shipper, against common belief. Although both the risk penalty and the flat rate can coordinate the supply chain, the risk penalty does so only if the shipper makes zero profit, but the flat rate can provide a positive profit for both. These results represent a new form of double marginalization and risk-sharing, in sharp contrast to the well-known literature on the classic supplier-retailer supply chain, where risk-sharing contracts (similar to the risk penalty) can bring benefits to all parties, but the single wholesale price contract (similar to the flat rate) can achieve supply chain coordination only when the supplier makes zero profit. We also find that only the online seller, but not the shipper, has the motivation to vertically integrate the seller-shipper supply chain. Under information asymmetry, however, the risk penalty brings more benefit to the shipper than the flat rate, but hurts the seller and the supply chain. Managerial implications: Our results imply that information plays an important role in the shipper’s choices of shipping contracts. Under information symmetry, the risk penalty is unnecessarily complex because the simple flat rate is as good as the risk penalty for the shipper; moreover, it is better for the seller-shipper coordination. However, under information asymmetry, the shipper faces additional shipping risk that can be offset by the extra flexibility of the risk penalty. Our study also explains and supports the recent practice of online sellers (e.g., Amazon.com and JD.com), but not shippers, to vertically integrate the supply chain by consistently expanding their shipping capabilities.

This paper investigates the impact of business strategy on firms’ trade credit policies. We find that firms following an innovation-oriented strategy (prospectors) offer significantly more trade credit to their customers than those following an efficiency-oriented strategy (defenders). Furthermore, by exploiting two exogenous shocks to the supplies of high-skill employees and bank credit, we find that prospectors curtail trade credit in response to the reduction of talent mobility following the adoption of Inevitable Disclosure Doctrine, whereas defenders significantly increase provisions of trade credit following the increase in bank credit supply due to the relaxation in interstate branching regulations. Additional evidence substantiates that prospectors increasing trade credit provisions enjoy higher sales generation efficiency and superior performance. Finally, our supply chain analysis documents that prospectors also receive significantly more trade credit from their suppliers. Collectively, our findings highlight that business strategy is an important yet intrinsic determinant of supply chain financing.

Problem definition: Price surge of essential commodities despite inventory availability, due to artificial shortage, presents a serious threat to food security in many countries. To protect consumers’ welfare, governments intervene reactively with either (i) cash subsidy, to increase consumers’ purchasing power by directly transferring cash; or (ii) supply allocation, to increase product availability by importing the commodity from foreign markets and selling it at subsidized rates. Academic/practical relevance: This paper develops a new behavioral game-theoretic model to examine the supply chain and market dynamics that engender artificial shortage as well as to analyze the effectiveness of various government interventions in improving consumer welfare. Methodology: We analyze a three-stage dynamic game between the government and the trader. We fully characterize the market equilibrium and the resulting consumer welfare under the base scenario of no government intervention as well as under each of the interventions being studied. Results: The analysis demonstrates the disparate effects of different interventions on artificial shortage; whereas supply allocation schemes often mitigate shortage, cash subsidy can inadvertently aggravate shortage in the market. Furthermore, empirical analysis with actual data on onion prices in India shows that the proposed model explains the data well and provides specific estimates on the implied artificial shortage. A counterfactual analysis quantifies the potential impacts of government interventions on market outcomes. Managerial implications: The analysis shows that reactive government interventions with supply allocation schemes can have a preemptive effect to reduce the trader’s incentive to create artificial shortage. Although cash subsidy schemes have recently gained wide popularity in many countries, we caution governments to carefully consider the strategic responses of different stakeholders in the supply chain when implementing cash subsidy schemes.

The traditional paradigm for pharmaceutical manufacturing is focused primarily upon centralized facilities that enable mass production and distribution. While this system reliably maintains high product quality and reproducibility, its rigidity imposes limitations upon new manufacturing innovations that could improve efficiency and support supply chain resiliency. Agile manufacturing methodologies, which leverage flexibility through portability and decentralization, allow manufacturers to respond to patient needs on demand and present a potential solution to enable timely access to critical medicines. Agile approaches are particularly applicable to the production of small-batch, personalized therapies, which must be customized for each individual patient close to the point-of-care. However, despite significant progress in the advancement of agile-enabling technologies across several different industries, there are substantial global regulatory challenges that encumber the adoption of agile manufacturing techniques in the pharmaceutical industry. This review provides an overview of regulatory barriers as well as emerging opportunities to facilitate the use of agile manufacturing for the production of pharmaceutical products. Future-oriented approaches for incorporating agile methodologies within the global regulatory framework are also proposed. Collaboration between regulators and manufacturers to cohesively navigate the regulatory waters is ultimately needed to best serve patients in the rapidly-changing healthcare environment.

Background aims The novelty of cell and gene therapies (CGTs) has introduced unique supply chain challenges and considerations not seen by chemically synthesized (small-molecule) drugs. These complexities increase during the clinical phases, where drug safety and efficacy milestones are still underdeveloped. For example, for autologous therapies such as chimeric antigen receptor T-cell therapies, in which the treatment is developed from the patient's own cells, supply chain management plays an integral role in chemistry, manufacturing and control processes. Supply chain management requires proactive planning because of the strict cold chain requirements and time sensitivity of CGTs. This research examines strategies and responses to challenges experienced by industry stakeholders (e.g., sponsors and manufacturers) during the implementation phases of clinical supply chain management. This research further evaluates the adequacy of the current regulatory framework for distribution and supply chain management of CGTs in the US. Methods A survey methodology was used to query subject matter experts from the biopharmaceutical industry who were familiar with the clinical supply management of CGTs in the US. The survey instrument was developed using an implementation framework and disseminated electronically to mid- and senior-level subject matter experts who had experience with clinical trials, supply chain management and CGTs. Results A total of 128 respondents accessed the survey, and 105 respondents answered at least one question. Seventy-five respondents completed the survey. Results showed that a lack of harmonization in regulations across the supply chain, limited resources, challenges with vendor management, high costs and complexities in the supply chain due to product specificity and customization proved to be impediments for the industry. In addition, the coronavirus disease 2019 pandemic had a significant impact on supply chain implementation. The results revealed that less than half of the respondents had business continuity plans in place. These challenges increased for smaller and mid-size organizations. Thirty percent of small and mid-size organizations were less prepared to scale up than larger companies. Conclusions Suggestions from industry stakeholders were to adopt and enforce Good Distribution Practices in the US (81%), pre-plan distribution strategies with internal and external stakeholders along the supply chain and develop agile systems and robust processes end to end. Hurdles in scaling up and scaling out from the clinical to commercial phases for time- and temperature-sensitive CGT products make it difficult to predict the supply chain's long-term feasibility. Although there are initiatives to improve these impediments, such as improving industry partnerships and creating global CGT transportation standards, there are still regulatory knowledge gaps present for CGTs. Therefore, it is essential to establish a baseline and foundation for CGT supply chains extending beyond the loading dock.

This study develops an analytical model based on the evolutionary game theory to analytically investigate the pricing and credit time strategies of a population of pharma-distributors towards demand promotion in the long term. This study determines the evolutionary stable strategy for the pharma-distributors’ population, and finds which marketing strategy of the pharma-distributors will ultimately be adopted by the majority of them. We investigate a supply chain (SC), including one pharma-manufacturer and a population of pharma-distributors where the pharma-distributors can either offer a credit time scheme or adopt a pricing strategy for customers’ convenience, using an evolutionary game theory approach. The uncertainty of customer default risk is incorporated into the pharma-distributors’ and pharma-manufacturer's payoffs. Both numerical and parametric sensitivity analyses are provided to give insights into the way SC managers use towards demand promotion. The results reveal that the credit time option considering the uncertain default risk is the evolutionary stable strategy for the pharma-distributors in the long term. Moreover, the findings demonstrate that under intense competition on the pricing strategy, the credit time scheme will be preferred by the majority of the population of pharma-distributors. However, under intense competition on the credit time scheme, the pricing policy will be employed by the majority of the pharma-distributors.

In early 2020, apparel brands and retailers cancelled US$40 billion worth of orders, with critical consequences for suppliers and workers. Their actions illustrate the power asymmetries in global supply chains and the unequal distribution of costs during crises. This article explores these dynamics through original survey data, supplier questionnaires, stakeholder interviews, a time-line analysis and trade data analysis. Findings point to certain limits of buyer power, reflected in the effective collaboration between suppliers and worker rights advocates in the "#PayUp" campaign. Yet buyers retain the power to squeeze suppliers with adverse impacts on workers, thus leading to calls for binding agreements.

Global warming and the detrimental impacts of fossil fuels on the environment and human life have led to focus on producing sustainable energy resources for future. One of the renewable and sustainable energy resources is biofuel. Today most of developed countries are focused on producing biofuels to improve economic and environmental opportunities. Because of carbon dioxide and other greenhouse gases emissions during supply chain activities, we present a mathematical model for designing a second generation of sustainable multi stage biofuel supply chain network which contains agricultural zones, bio-refineries and markets with the objective of maximizing the profit. Supply chain costs like growing, harvesting, collecting and agricultural residual storage, transportation of agricultural residual from farms to bio-refineries, producing biofuel in bio-refineries and transportation cost from bio-refineries to markets are also considered. Since considerable amount of Carbon dioxide is emitted during transporting agricultural residual from farms to bio-refineries and transporting biofuel from bio-refineries to markets, four different carbon emission regulations are considered in order to examine the environmental impacts, including: carbon cap, carbon tax, carbon cap-and-trade and carbon offset. Based on the carbon-cap mechanism, the maximum amount of carbon emissions is limited. Under the carbon tax mechanism, for each unit of carbon emission, a tax must be given to the regulations. Regarding a carbon cap-and-trade policy, a carbon cap is imposed on supply chain operations and companies can trade their carbon allowances in the market. Considering a carbon offset mechanism, a company can purchase additional carbon allowances. According to uncertainties in real-world problems, the uncertainty nature of parameters like selling revenue of biofuel, costs of growing, harvesting, collecting agricultural residual, transportation of agricultural residual and biofuel, production biofuel, carbon tax rate and amount of carbon emissions are reflected. A chance constrained fuzzy programming approach is used to deal with uncertain parameters. It is apparent by numerical results that proposed model is so efficient and it can be used in the future to produce and develop second generation biofuel supply chain from agricultural residual by considering the carbon emission regulations.

We study a buyer’s problem of auditing suppliers within an existing network to ensure social responsibility compliance. The buyer suffers economic damages if a violation at a supplier is exposed (whether by the media, regulator, or nongovernmental organization). To avoid damages, the buyer may audit the network to identify noncompliance. If a supplier fails an audit, the buyer must take one of two costly actions: either rectify the supplier or drop the supplier (along with any dependent suppliers). Dropping a supplier changes the network topology, reducing competition and thereby increasing the buyer’s input cost arising from an equilibrium. We show that the buyer’s optimal dynamic auditing policy has two subphases: the buyer will first audit and drop some suppliers before either auditing and rectifying all remaining suppliers or halting auditing altogether. By halting, the buyer tolerates some noncompliance in the network (“see no evil, hear no evil”). Within the audit-and-drop subphase, when auditing only in the upper tier, the buyer always audits a least valuable unaudited supplier, yielding greater balance in the network. When the buyer audits both tiers, it might choose a supplier other than the least valuable. The buyer may choose a supplier in a pivotal position to help ascertain the viability of a portion of the network (“litmus test”). In extensions, we find that when violations in tier 1 carry a higher penalty for the buyer, the buyer may audit and rectify only tier 1 suppliers; when audits may be inaccurate, the buyer more likely tolerates a greater level of noncompliance. This paper was accepted by Charles Corbett, operations management.

The emergence of the financial supply chain provides assistance for small, medium and micro enterprises in the supply chain through a secured credit model based on real trade. Moreover, in the multi-level structure of the financial supply chain of the Internet of Things enterprise, there are information barriers and information islands. Besides, data is often not transmitted smoothly, and the intermediate offline process is complicated. What is worse, the efficiency is low, and the verification cost is high. Therefore, based on supply chain finance, an evolutionary risk model is constructed in this paper. Firstly, the income matrix of the regulatory risk model is established, and the convolutional neural network used will pool the training data to the maximum and set the local corresponding normalization layer. With the help of the evolutionary risk theory, the dynamic equation of the financial supply chain is obtained, forming the dynamic path and abnormal model of strategy selection. Then, a compact pattern tree is added to the knowledge granularity method to mine data anomalies. Finally, an experimental platform is built to verify the effectiveness of the method proposed in this paper, and experiments are performed on the accuracy of model evolution conditions, abnormal data identification, and abnormal numerical examples. The experimental results prove that the algorithm in this paper is consistent with the set parameters, and the effect is significantly higher than other comparison methods. The experimental mining time and the comparison method are shortened by 6 ∼ 13S. The research results obtained from this paper solve the problem that the decision-making of supply chain finance and the supervision and review of supply chain enterprise are complex, which improves the characteristics identification of supply chain platform, and provides reference suggestions for financial institutions and supply chain platforms.

This study investigates the role of a credit guarantee company and a peer-to-peer (P2P) lending platform in the financing business of a capital-constrained retailer who faces uncertain demand over a single period. The credit guarantee company is divided into two types: conservative and adventurous. The conservative credit guarantee company aims to earn a certain expected return by setting its guarantee service fee rate, whereas the adventurous one sets the guarantee service fee rate to maximize its profit while ignoring the expected return. In a decentralized financing system, the guarantee types will influence all local optimal decision variables in Stackelberg equilibrium, and the optimal order quantity setting under the adventurous credit guarantee type is more flexible than that under the conservative one. We then analyze the centralized financing system and prerequisites for participation to obtain the supply chain financing (SCF) coordinating strategy. Under the adventurous credit guarantee, the P2P lending platform financing system can achieve SCF coordination, but under the conservative credit guarantee, SCF coordination cannot be achieved. When a credit guarantee company is adventurous and the coordination condition on order quantity is satisfied, the information service fee rate linearly decreases in the guarantee service fee rate, and the P2P lending platform’s and the credit guarantee company’s expected profits have different monotonic properties with the information service fee rate (or the guarantee service fee rate) increasing. Finally, we identify the boundary of the retailer’s initial working capital and the suitable ranges of the service fee rates to achieve SCF coordination.

Background: The nexus of agri-food and sustainability in economic development has recently attracted the interest of policymakers, as global challenges like climate change and food security are revisited and reassessed. The critical role of food production in economic development has been emphasized through targeted agricultural quality policies. Many developed countries worldwide, including EU member states, have introduced food quality policies that could support sustainability.Scope and approach: This paper combines knowledge obtained by several groups in a broad EU study and the reflections on policy-related results by EU-stakeholders, streamlined by a Delphi analysis.Current work presents research-based policy recommendations and statements on various quality schemes, introductory inferred from expert opinions throughout Europe, gauged through a modified policy Delphi framework.Key findings and conclusions: A roadmap of policy and practical proposals have been identified for all key stakeholders involved in these initiatives, implying the need to reshape the supply chain dynamics to continuously improve producers, processors, retailers, and consumers within the EU and definitively worldwide. Furthermore, implementing a holistic approach considering environmental and socio-economic features can improve the effectiveness of EU food quality policies.

In the Big Data environment, when green manufacturers invest in the green production technology, to satisfy consumer demand timely and accurately, they may begin to gain consumer performance information (hereafter, CBDI) to design and produce product. However, these will go up their extra costs. Meanwhile, for a green manufacturer who sells the green product through the online channel and the offline channel, the expression of its market demand needs to rethink in the new environment. In these conditions, for a dual-channel green supply chain (hereafter, DGSC), chain members pay more attention on the pricing problems considering the inputs of CBDI and greening R&D. Hence, to resolve this question, a DGSC a green manufacturer selling by the online channel and with one retailer selling by the offline channel was chosen. Afterwards, the demand function of the DGSC was revised, and we analyzed the profits models and its pricing rules in the proposed four common cost-sharing models. Results indicate that whether the retailer bears the CBDI costs or the greening R&D costs, the retailer will not change its retail price. If the retailer can bear some CBDI costs, the alteration tendencies of the best wholesale price are related to the cost-sharing parameter.

Kuningan Regency is the area that has potential in agriculture. One of the leading commodities in Kuningan Regency is sweet potato (Ipomea batatas L). Sweet potato cultivation continues to be developed, even in Cilimus District, it is known as one of the productive production centers in the West Java region which provides sweet potato supplies to several areas to supply sweet potato needs in the West Java region. The problems are faced by farmers today including the increasingly erratic price of sweet potatoes, lack of market opportunities, product diversification, and mastery of cultivation technology. This service activity was carried out in Cilimus Village, Cilimus District, Kuningan Regency with partners of sweet potato farmers. The purpose of this assistance is to provide supply chain assistance for sweet potato marketing so that farmers are able to continuously market sweet potatoes above the production price. Mentoring activities were started from identification of sweet potato problems at the farmer level, identification of production and identification of markets. The using of method is interactive discussion and market mapping conducted together with farmers. Focus Group Discussion (FGD) was used to confirm the cultivation system, production, and marketing system of sweet potato. The result of this activity is that farmers know the marketing potential of sweet potatoes other than middlemen and the quality criteria of sweet potatoes according to industry demand. In addition, farmers also use sweet potatoes as animal feed.