Search

Supply chain disruptions recurrently challenge end-to-end operations owing to the ambiguous understanding of the role of governance in impacting supply network resilience. This paper scrutinises the relevant literature to understand the plethora of interpretations in the domain of supply chain governance and resilience while further provides a new perspective on the representation of the interplay between governance and resilience in supply chains. In this regard, the Systems Thinking lens is adopted to pull together the typologies and constructs of supply chain governance and resilience from the literature. Methodologically, System Dynamics modelling principles are leveraged to capture the underpinning structural interdependencies in a causal loop diagram (CLD). The study reveals that endogenous and exogenous supply chain governance processes and mechanisms support the intrinsic and extrinsic resilience in networks. Overall, this research contributes to the supply chain risk management domain by synthesising the interplay between governance and resilience, identifying pertinent typologies and through articulating research propositions that can inform decision-making at policy and managerial levels.

We document the propagation through supply chains of the most damaging cyberattack in history and the important role of banks in mitigating its impact. Customers of directly hit firms saw reductions in revenues, profitability, and trade credit relative to similar firms. The losses were larger for customers with fewer alternative suppliers and suppliers producing high-specificity inputs. Internal liquidity buffers and increased borrowing, mainly through bank credit lines, helped affected customers maintain investment and employment. However, the shock led to persisting adjustments to the supply chain network.

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.

Post COVID-19 vaccine development, nations are now getting ready to face another challenge: how to effectively distribute vaccines amongst the masses to quickly achieve herd immunity against the infection. According to some experts, herd immunity for COVID-19 can be achieved by inoculating 67% of the population. India may find it difficult to achieve this service level target, owing to several infrastructural deficiencies in its vaccine supply chain. Effect of these deficiencies is to cause frequent lead time disruptions. In this context, we develop a novel modelling approach to identify few nodes, which require additional inventory allocations (strategic inventory reserves) to ensure minimum service level (67%) under the possibility of lead time disruptions. Later, through an illustrative case study on distribution of Japanese Encephalitis vaccine, we identify conditions under which strategic inventory reserve policy cannot be practically implemented to meet service level targets. Nodes fulfilling these conditions are termed as critical nodes and must be overhauled structurally to make the implementation of strategic inventory policy practically viable again. Structural overhauling may entail installation of better cold storage facilities, purchasing more quality transport vans, improving reliability of transport network, and skills of cold storage manager by training. Ideally, conditions for identifying critical nodes for COVID-19 vaccine distribution must be derived separately by substituting COVID-19 specific parametric values in our model. In the absence of the required data for COVID-19 scenario, JE specific criteria can be used heuristically to identify critical nodes and structurally overhaul them later for efficiently achieving service level targets.

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.

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).

The emergence of e-commerce has compelled original brand manufacturers to adopt cross-channel strategies. This research investigates how a manufacturer facing free riders should decide on channel differentiation strategy, i.e., selling homogeneous or differentiated products through his own online channel and via an independent retailer. We consider horizontal differentiation across channels and identify the optimal strategy. In addition, we develop an agent-based model with vertical and horizontal differentiation to derive managerial insights for more complex situations. We have analytically found: (1) consumers are more likely to engage in free riding when faced with differentiated products than homogeneous products, as the price gap across channels is larger under the former scenario; (2) the manufacturer should offer differentiated products if the free rider's online factor is high. Similarly, if the retailer's service cost is low (high), and online (offline) shopping cost is low, differentiated products should be offered. (3) Under different conditions, offering homogeneous or differentiated products could respectively be a win-win strategy for the manufacturer and the retailer. (4) The proposed channel differentiation strategies remain robust to the horizontal differentiation decision and integration of the retail channel. Through agent-based computational experiments, we derive several insights. Namely, (1) if consumers are highly heterogeneous, the manufacturer should horizontally differentiate products across channels; (2) the manufacturer should narrow the vertical differentiation between the two products in dual channels; and (3) the manufacturer should differentiate products if consumers are familiar with the products.

The objective of this study is to develop the Freight Trip Generation (FTG) models concerning establishment classification process for estimating freight trip activity. Establishment Based Freight Survey (EBFS) was performed to collect various supply chain variables involved in the urban freight system. Extensive data of 647 samples were collected from Tiruchirappalli city, India. Economic activity analysis shows that pure receiver and intermediate establishments do not follow the uniform freight trip activity among the industrial segments. Hence, a suitable methodology for the establishment classification process is developed using traditional and machine learning (ML) techniques to classify the establishment into an intermediate and pure receiver before estimating the freight trip activity. Supply chain variables like employment, FTA, industrial segment, mode of the commercial vehicle, type of delivery, number of suppliers, and gross floor area play a crucial role in the establishment classification process. Then, employment-based FTG models are developed with the classified data using linear and non-linear functional forms for each industrial segment. Finally, it is observed that FTG models result enhanced, when the establishment classification process is performed as an initial stage, with lower error and accurate estimation of urban freight trip activity.

This study examines the bullwhip effect in a manufacturing/remanufacturing supply chain consisting of one retailer, one manufacturer, one supplier, and one third-party collector. Products returned from the end users are converted to ‘as-good-as-new’ products through remanufacturing. Both manufactured and remanufactured products are used to meet the stochastic demand of the retailer. We incorporate the price of the product in the demand through an autoregressive moving average (ARMA) pricing process, realizing a market demand that evolves according to a non-standard ARMA(1,1) process. For this demand model, we employ the order-up-to inventory policy with a minimum mean square error forecasting scheme and measure the bullwhip effect at each echelon of the supply chain. We investigate the behaviour of the bullwhip effect analytically, and a numerical evaluation shows that the bullwhip effect or the anti-bullwhip effect may occur at each echelon depending on the values of the autoregressive and moving average parameters of the underlying demand process. We also investigate the effects of the remanufacturing yield, the variance of the market shock on price, and the lead times on the bullwhip effect.

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.

Consumers are increasingly concerned about pollution and are, at least in part, making their purchases accordingly. In this paper, we consider a supply chain where demand depends on the manufacturer’s environmental reputation, an asset that can only be built over time. We assume that this reputation depends on information emanating from the manufacturer itself about its environmental actions and on its objective environmental record when compared to an industry standard. In this paper, we look at the impact of consumers’ environmental concern on the strategies and outcomes of a supply chain. As the retailer has a direct influence on sales through its pricing policy, it seem more realistic to take a supply chain perspective instead of a single-firm one. Therefore, the contractual arrangement in the supply chain becomes a relevant issue. We model the supply chain as a two-player dynamic game and characterize and compare the equilibrium strategies and outcomes under wholesale-price and revenue-sharing contracts. We analyze the impact of the sharing parameter, the industry pollution standard and consumers’ degree of environmental sensitivity on the results, and in particular, on the region in the parameter space where a revenue-sharing contract is Pareto improving with respect to a wholesale-price contract. Also, we examine whether it is in the best interest of the retailer to behave myopically when setting its price.

Despite extensive research on the value of collaborative forecasting among supply chain partners, there has been limited attention to the actual mechanisms of forecast sharing. We propose using cost-function-based prediction markets as means of sharing demand forecasts. We consider a decentralized two-stage supply chain with a supplier who sells to a retailer, in which both partners receive demand forecast updates. In the first stage, the supplier and the retailer agree on a collaborative forecasting scheme to form a consensus forecast. We consider two schemes: collaborative forecasting using cost-function-based prediction markets in which partners pay a set-up cost to operate a prediction market, and direct collaborative forecasting in which partners directly share their forecasts with each other and resolve their forecast differences through costly actions. In the second stage, we analyze the game between the supplier and the retailer to determine the retailer’s optimal order quantity as well as the supplier’s optimal wholesale price. We show that demand forecast sharing using cost-function-based prediction markets results in a Pareto improvement of the partners’ profit over the alternative of directly sharing forecasts. Furthermore, we show that this Pareto improvement is monotone with respect to supply chain partners’ forecast accuracy. We conduct an extensive numerical study to provide further insights into the effect of the return on forecast sharing investment, forecast accuracy, and level of demand uncertainty on the benefits gained by implementing cost-function-based prediction markets.

Immunization is widely recognized as one of the most successful and cost-effective health interventions, preventing two to three million deaths from vaccine-preventable diseases each year. Although progress has been made in recent years, substantial operational challenges persist in resource-limited settings with frequent stock-outs contributing to sub-optimal immunization coverage and inequality in vaccine access. In this paper, we investigate the role of rainy season induced supply chain disruptions on vaccination coverage and inequalities. We develop a modeling framework combining spatial modeling—to predict flood disruptions in road networks—and a discrete-event simulation of a multi-tiered vaccine supply chain (VSC). Our models are fitted using data from the Malagasy VSC network and validated to the best extent possible with scarce data. Our baseline simulation predicts the national vaccination coverage with good accuracy and suggests that 67% of regions with low reported immunization coverage are affected by rainy season disruptions or operational inefficiencies, causing significant geographical inequalities in vaccine access. We investigate various mitigation strategies to increase the resiliency of VSCs and find that, by strategically placing buffer inventory at targeted facilities prior to the rainy season, the proportion of children receiving all basic vaccines in these areas is increased by 8% and the geographical inequality in vaccination coverage between areas affected and not affected by the rainy season is reduced by 11%. By also increasing the replenishment frequency from every third month to every month, the national vaccination coverage improves by 41%. Our results contribute to achieving the UN Sustainable Development Goals (SDGs) by providing actionable insights for improving vaccination coverage (SDG 3) and investigating the resiliency of the VSC to increased flooding due to climate change (SDG 13).

Guarantee credit financing (GCF), allows banks to offer loans to capital-constrained retailer (he) based on the guarantee contracts offered by the manufacturer (she). Therefore, this study investigates the signaling role of guarantee contracts when the retailer is less informed about its product's market potential. In particular, we explore a joint contract of guarantee credit and production quantity to deliver the manufacturer's demand information. We add a framework to the capital-constrained supply chain with asymmetric demand information under GCF. Using a signaling game to capture the demand information asymmetry, we identify the strategic interaction between the retailer and the manufacturer under GCF. Also, we investigate the value of GCF when both GCF and trade credit financing (TCF) are viable. We find that the single guarantee contracts cannot signal the manufacturer's demand information when the production cost is less than a threshold, otherwise, only the separating equilibria survive the intuitive criterion. Besides, the findings reveal that the demand information asymmetry can either benefit or harm the retailer or the manufacturer, but cannot benefit both of them. In addition, GCF remains an attractive financing option when both GCF and TCF are viable. A joint contract of guarantee credit and production quantity can be used to deliver the demand information if the guarantee contracts are invalid. Our paper helps to explain the impact of asymmetric demand information on supply chain partners’ decisions under GCF and sheds light on the design and use of guarantee contracts.

In many supply chains, suppliers that provide a key component to retailers in the wholesale market also have their own retail divisions in the retail market and form vertically integrated producers (VIPs) with these divisions. A VIP’s profit comes from two sources: (i) the wholesale profit from supplying the key component to retailers and (ii) the retail profit from its own retail division. In this situation, the VIP’s intra-company discount is often restricted by the arm’s length regulation (ALR) to induce fair competition in the retail market and improve the consumer benefit. However, the ALR may not always result in the desired outcome, especially when the retailers are asymmetric. Thus motivated, we investigate the impact of the ALR on the supply chain profit and the consumer benefit. Our analysis incorporates two types of asymmetry commonly observed among retailers: (i) retailer-specific selling costs and (ii) private information regarding the intra-company discount. Our results have several important implications. First, the ALR improves the supply chain profit only when the rival retailer is more competitive than the VIP’s retailer. Also, the ALR benefits consumers when the rival retailer is more competitive and the competition intensity is low. Second, under information asymmetry, while the rival retailer would not benefit from the VIP’s private information, the VIP’s gain does not always outweigh the rival retailer’s loss. Hence, the total supply chain profit may increase with the ALR. In addition, the consumer surplus can increase under information asymmetry unless the VIP’s intra-company discount is extremely limited.

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.

In the Make-To-Order (MTO) supply chain, for enticing the retailer to choose a shorter delivery lead-time, which improves the manufacturer's wholesale prices, the manufacturer adopts the Production Time Hedging (PTH) strategy as an incentive. Since the profit of the retailer depends not only on the Quoted Delivery Lead-Time (QDLT) but also on the Realized Delivery Lead-Time (RDLT), effectively hedging production time uncertainty reduces tardy delivery. We build an analytical model to investigate how PTH affects the retailer's QDLT decision and the supply chain performance. We consider models for four scenarios, namely (I) the centralized model, (II) the Nash model, (III) the manufacturer-led Stackelberg model, and (IV) the retailer-led Stackelberg model. We derive close-form results on the optimal hedging and QDLT decisions. In models II and III, PTH reduces the QDLT under all the conditions. However, in model IV, PTH can only coordinate the retailer when the hedging cost is low, or the holding cost/tardiness penalty is high. Besides, we find that model III is the dominant scenario for both players. Extending model IV to consider the case where the retailer sources from multiple manufacturers, we show that multiple sourcing is the dominant strategy when a manufacturer's hedging cost is high, or its holding cost/lead-time sensitivity factor is small. From the numerical study, we are interesting to find that the retailer's profit increases with the manufacturer's holding cost/lead-time sensitivity factor.

In this paper, we develop a supply chain network model in which firms compete noncooperatively in an oligopolistic manner in discrete time periods over a finite planning horizon. Each firm makes a strategic decision regarding its target sustainability rating and tactical decisions of product flows, in the presence of consumer preferences for sustainability and a variety of environmental policies. Such policies include ecological taxes for different types of pollution, subsidies for pollution control, command-and-control policies, as well as hybrid approaches with different possible combinations of policy instruments. Furthermore, our model captures dynamic changes in not only the consumer purchasing behavior, but also the operational costs and environmental pollution, as well as government environmental policies. A series of numerical examples evaluate the impacts of consumer preferences for sustainability and environmental policies on firms’ profitability and their environmental footprint. The results indicate that firms will improve sustainable operations as long as it is financially valuable for them to do so, which mandates governments and firms to educate consumers about sustainability. Numerical examples also reveal under which environmental policies sustainability can be profitable.

We are concerned with the interaction and integration between demand forecasting and inventory control, in the context of supply chain operations. The majority of the literature is fragmented. Forecasting research more often than not assumes forecasting to be an end in itself, disregarding any subsequent stages of computation that are needed to transform forecasts into replenishment decisions. Conversely, most contributions in inventory theory assume that demand (and its parameters) are known, in effect disregarding any preceding stages of computation. Explicit recognition of these shortcomings is an important step towards more realistic theoretical developments, but still not particularly helpful unless they are somehow addressed. Even then, forecasts often constitute exogenous variables that serially feed into a stock control model. Finally, there is a small but growing stream of research that is explicitly built around jointly tackling the inventory forecasting question.\ud \ud We introduce a framework to define four levels of integration: from disregarding, to acknowledging, to partly addressing, to fully understanding the interactions. Focusing on the last two, we conduct a structured review of relevant (integrated) academic contributions in the area of forecasting and inventory control and argue for their classification with regard to integration. We show that the development from one level to another is in many cases chronological in order, but also associated with specific schools of thought. We also argue that although movement from one level to another adds realism, it also adds complexity in terms of actual implementations, and thus a trade-off exists. The article makes a contribution into an area that has always been fragmented despite the importance of bringing the forecasting and inventory communities together to solve problems of common interest. We close with an indicative agenda for further research and a call for more theoretical contributions, but also more work that would help to expand the empirical knowledge base in this area.

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.

With the development of e-commerce, manufacturers have opportunities to sells products to consumers through direct channels in addition to independent retailers. Although manufacturers encroachment upon the retailing market of traditional goods has been extensively studied, there is a lack of research for manufacturers encroachment in a pharmaceutical supply chain. This paper analyzes a pharmaceutical manufacturer encroachment strategy by taking into account the distinct features of drugs, in which drugs expenses are covered by medical insurance only in physical channel and patients' channel preference is also considered. We find that under certain circumstance, the manufacturer encroachment may lead to a win-win outcome for both the manufacturer and the retailer, contradicting the conventional wisdom that manufacturer's encroachment into retail space is detrimental to the independent retailer. Additionally, the manufacturer is more likely to encroach when the incurred extra cost is sufficiently small, the perceived quality of the drug selling through the direct channel is sufficiently high and the out-of-pocket percentage cost of the drug selling in the physical channel is high. We further study the impact of manufacturer encroachment on social welfare and find that the introduction of encroachment decreases the social welfare when patients' perceived quality of the drug obtained through the online store is low and improves the social welfare when the perceived quality exceeds a certain threshold.

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.

This paper develops a model for a cold chain operated among a single product manufacturer and multiple retailers to minimize the total cost of the chain. A distinguishing feature of the cold chain is that the quality of the product degrades with time. The storage temperature and time influence the degradation rate. In this context, quality can be measured using multiple distinct indices. A global stability index is used to quantify the overall quality. The non-Arrhenius model is exclusively applied to measure the quality degradation during the transportation and at a retailer's storage as the product moves in the cold chain. Optimal replenishment times for the manufacturer and retailers are decision variables and the cold chain's total cost includes the cooling cost, carbon emission cost, and loss of value in addition to the traditional supply chain costs. It is found that for a given manufacturer's replenishment time, the total cost is convex on each retailer's replenishment time. Hence, an algorithm is developed based on this property to find the optimal replenishment times for the manufacturer and retailers. This paper also investigates how specific cold chain parameters influence optimal decisions and the total cost. The analyses show that the resulting costs will be significantly higher if quality degradation is ignored in a cold chain.

Rebate policies are widely used by manufacturers to stimulate sales. This paper analyzes a supply chain with revenue sharing and wholesale price contracts under manufacturer rebate policy, where the stochastic multiplicative demand function depends on both retail price and manufacturer rebate. We identify Stackelberg equilibrium for the supply chain under each contract. It is our finding that under the manufacturer’s respective optimal decisions for revenue sharing and wholesale price contracts with rebates, the retailer’s optimal retail prices are the same. We recognize sufficient conditions under which a revenue sharing contract and a wholesale price contract with rebate can achieve Pareto improvement, i.e., both the manufacturer and the retailer obtain a greater expected profit, compared with the cases without rebate. A sufficient condition is found, under which a revenue sharing contract with rebate policy can achieve Kaldor–Hicks improvement, i.e., yielding a greater expected profit for the manufacturer, a lower expected profit for the retailer, and a greater expected total profit, over pure revenue sharing contract without rebate. Further, it is shown that with rebate, a revenue sharing contract can achieve Kaldor–Hicks improvement over a wholesale price contract. Finally, our findings are demonstrated using numerical studies.

In order to explore the potential of profit margin improvement, a novel three-scale integrated optimization model of furnace simulation, cyclic scheduling, and supply chain of ethylene plants is proposed and evaluated. A decoupling strategy is proposed for the solution of the three-scale model, which uses our previously proposed reactor scale model for operation optimization and then transfers the obtained results as a parameter table in the joint MILP optimization of plant-supply chain scale for cyclic scheduling. This optimization framework simplifies the fundamental MINLP into several sub-models, and improves the interpretability and extendibility. In the evaluation of an industrial case, a profit increase at a percentage of 3.25% is attained in optimization compared to the practical operations. Further sensitivity analysis is carried out for strategy evolving study when price policy, supply chain, and production requirement parameters are varied. These results could provide useful suggestions for petrochemical enterprises on thermal cracking production.

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.

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.

We investigate a firm’s information acquisition and voluntary disclosure decisions regarding demand forecast information. We study the interaction among the firm, its supplier, and the external capital market investors who assess the firm’s interim equity price. We first analyze when it is beneficial for the firm to acquire demand forecast information, and if such information is acquired, when the firm should disclose it to the supplier and investors. Then, we investigate how the firm’s information acquisition and disclosure decisions influence the investors’ and the supplier’s pricing strategies. We show that the optimal information disclosure policy for the firm is highly dependent on the corporate myopia level (CML): when the CML is low, the firm discloses low demand information only; when the CML is medium, the firm always withholds demand information; and when the CML is high, the firm discloses high demand information only. Our findings provide a novel plausible explanation to firms’ non-disclosure behaviors commonly observed in practice and highlight the importance of considering the interaction between the supply chain and the capital market.

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.

Socially sustainable and resilient supply chains are critical for organizations to succeed during both normal and uncertain times. Informed by supply chain disruption events, this study uses the resource-based view to conceptualize a performance framework for firms to strategically measure supply chain social sustainability and resilience capabilities. The performance framework integrates (a) the environmental goods valuation to evaluate social sustainability and (b) digitalization using blockchain technology to enhance supply chain process sustainability and resilience. Using secondary COVID-19 supply chain disruption data, the performance framework illustrates various social sustainability implications, market-based valuation methods, and supporting blockchain capabilities for supply chains. The study identifies potential future research to further evaluate the effectiveness of the proposed performance measurement framework and to advance it theoretically. The study also suggests practitioners utilize the performance measurement framework to manage supply chain social sustainability issues and resilience such that it can contribute to their competitive advantages.

Influenza vaccine supply chains are subject to yield and demand uncertainty, which leads to the mismatch between supply and demand. This paper studies the production and procurement decisions in the influenza vaccine supply chain consisting of a manufacturer facing uncertain production yield and a social planner who faces uncertain demand and is responsible for social infection costs. We develop a novel model framework considering the risks resulting from uncertainties on both supply and demand sides that the manufacturer may delay part of delivery and the social planner may order under or over demand. Based on the framework, we first discuss the production and procurement decision-making problem in a centralized and a decentralized system. By comparing the two systems, we present the existence and extent of the inefficiency in the influenza vaccine supply chain. Further, we propose a procurement strategy that provides the social planner with two ordering opportunities and explore the conditions under which the two members would be willing to accept the strategy. The results show that such a strategy is effective on improving the influenza vaccine supply chain coordination. Additionally, considering large-scale outbreaks of influenza epidemics, we extend the models with a piecewise linear infection probability function to those with a generic one and describe the characteristics of the extended models and their solutions.

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.

The COVID-19 pandemic has affected global supply chains at an unprecedented speed and scale. This paper investigates the supply chain challenges that manufacturing organizations have faced due to the COVID-19 outbreak, particularly in emerging economies. We present a conceptual framework under the dynamic capability theory to analyze challenges and their pertinent mitigation strategies. Ten major challenges are identified based on a literature review, evaluation of several news articles, and discussions with experts. Further, the Grey-Decision-making Trial and Evaluation Laboratory (Grey-DEMATEL) method is applied to analyze the relationships between various supply chain challenges. Scarcity of Labor (PSL) emerges as the most significant challenge, closely followed by Scarcity of Material (SSM). The results also suggest that Inconsistency of Supply (PIS) is the challenge that correlates the most with other factors. Finally, in this paper we also provide guidelines and strategies for practitioners and scholars to better address supply chain challenges post-COVID-19 outbreak.

Resource effectiveness and the circular economy are crucial for the future of the construction sector. A number of initiatives in Brazil and France are examining how resource efficiency and circularity can be introduced in various construction stages. But there is no unifying arena where both countries can meet. The lack of financial resources and a proper management system for construction and demolition waste are the main challenges which developing countries need to stand. This could encourage the development of innovations mainly in specific areas such as concrete recycling, and also stimulate the society to become aware of the value of material waste in the production supply chain. This proposal follows a waste input-output model to compare recycling and non-recycling scenarios in two stages of the construction process; this approach provides a positive alternative for the analysis of environmental scenarios in the traditional construction process. This research proved that at the construction site, there is a decrease in the amount of waste, concrete, metal, and plastic. However, during demolition, the concrete is not decreasing in the recycling scenario, even with a considerable amount of plastic and metal, probably due to the lack of proper waste separation in the site.

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.

Improved supply chain optimization strategies can play a major role in addressing global food security and safety in years to come. In particular, tighter safety regulations, changing consumer quality requirements and more stringent market competition call upon integrated supply chain decision-making frameworks that explicitly consider product quality control. This effort requires metrics of quality that accurately reflect product physico-chemical properties, as well as consumer purchasing preferences. However, a critical challenge linked to embedding the complex dynamics of the evolution of product quality in time within supply chain models is the large-scale nature of the ensuing optimization problems, which are computationally intractable even for moderate-size, single-item systems. In the present work, we introduce a computationally efficient optimal production and distribution planning framework for perishable products having multiple quality attributes that evolve in time as a function of environmental conditions during shipment and storage. We also propose a model reduction strategy and a decomposition framework that enhance the scalability of our approach. We perform extensive numerical simulations using different network instances to validate our theoretical findings, as well as to demonstrate the advantages of the proposed supply chain management scheme.

To address gaps in coverage and quality of nutrition services, AliveThrive (AT) strengthened the delivery of maternal nutrition interventions through government antenatal care (ANC) services in Uttar Pradesh, India. The impact evaluation of the AT interventions compared intensive ANC (I-ANC) with standard ANC (S-ANC) areas and found modest impacts on micronutrient supplementation, dietary diversity, and weight-gain monitoring.This study examined intervention-specific program impact pathways (PIPs) and identified reasons for limited impacts of the AT maternal nutrition intervention package.We used mixed methods: frontline worker (FLW) surveys (n = ∼500), counseling observations (n = 407), and qualitative in-depth interviews with FLWs, supervisors, and block-level staff (n = 59). We assessed 7 PIP domains: training and materials, knowledge, supportive supervision, supply chains, data use, service delivery, and counseling.Exposure to training improved in both I-ANC and S-ANC areas with more job aids used in I-ANC compared with S-ANC (90% compared with 70%), but gaps remained for training content and refresher trainings. FLWs' knowledge improvement was higher in I-ANC than S-ANC (22-36 percentage points), but knowledge of micronutrient supplement benefits and recommended foods was insufficient (50%). Most FLWs received supervision (90%), but supportive supervision was limited by staff vacancies and competing work priorities. Supplies of iron-folic acid and calcium supplements were low in both areas (30-50% stock-outs). Use of monitoring data during review meetings was higher in I-ANC than S-ANC (52% compared with 36%) but was constrained by time, understanding, and data quality. Service provision improved in both I-ANC and S-ANC areas, but counseling on supplement benefits and weight-gain monitoring was low (30-40%).Systems-strengthening efforts improved maternal nutrition interventions in ANC, but gaps remained. Taking an intervention-specific perspective to the PIP analysis in this package of services was critical to understand how common and specific barriers influenced overall program impact.

The aggravation of environmental issues makes green manufacturing become inevitable and fuzzy uncertainties prevail in supply chain management. To further promote the development of green supply chain, this paper considers a two-echelon green supply chain models with governmental interventions composed of one supplier and one retailer under fuzzy uncertainties, in which the parameters of demand function and manufacturing cost are all characterized as fuzzy variables. Then the equilibrium decisions of the expected value and chance-constrained programming models are derived considering the different risk references of the supplier and the retailer. At the end, numerical examples are presented to demonstrate the theoretical underpinning of proposed models. Analytical results indicate that the supplier and the retailer can obtain different equilibrium decisions by adjusting different confidence levels. The equilibrium decisions reflect the risk attitudes of the supplier and the retailer to the uncertainties in supply chain system and their different predictions on possible level. Then, whether the supplier as a leader has the first-mover advantage is related to the risk attitudes of the supplier and the retailer when dealing with the uncertainties of the green supply chain system. Moreover, the strong governmental interventions can coordinate not only the conflict between pricing and green level decisions, but also the contradiction between the consumers and the supplier. In addition, the retailer may be the main puller of the green supply chain in developing the green product.

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.

With the development of e-commerce, manufacturers now have the opportunity to compete with existing retail channels by introducing their direct channels. Encroachment weakens the strength of retail channels, which may affect the manufacturer's decision on whether to provide trade credit financing to retailers. This study investigates the strategic interaction between manufacturer's encroachment and retailers’ financing choices (trade credit financing or external financing) in a supply chain consisting of a manufacturer and two capital-constrained retailers. We find that only encroachment cost below a certain threshold will make the manufacturer encroach on the market, while manufacturer encroachment is harmful to capital-constrained retailers. Surprisingly, these retailers can expand the ratios of equity financing in anticipation of manufacturer encroachment, which is a new strategic role of equity financing. In addition, the more intense the channel competition (the larger the credit gap between the two retailers) is, the less (more) likely the manufacturer will be to encroach. Further, we find that retailers prefer trade credit (external) financing at a low (high) bank loan interest rate in a non-encroachment scenario, while they prefer external financing in an encroachment scenario. However, the manufacturer always prefers the case that both retailers choosing external financing. Finally, there are financing choice conflicts between the manufacturer and retailers in the non-encroachment scenario. A high-credit retailer choosing trade credit financing may make all members achieve a Pareto improvement when the credit gap between two retailers is large; otherwise, both retailers choosing external financing is a Pareto improvement.

Coopetition is a business phenomenon that dominates many supply chains. We aim to understand why and how coopetition occurs in supply chains with the presence of process improvement in upstream component production. An original equipment manufacturer (OEM) can purchase the component from either a non-competing supplier (NS) or a competing supplier (CS) that also sells substitutable products in the end consumer market. We demonstrate that without process improvement, coopetition does not exist, because the OEM prefers sourcing from the NS, even though the CS is willing to sell the component to the OEM. Two cases are considered in which process improvement is present: supplier-initiated investment, where the suppliers conduct self-investment, and OEM-initiated investment, where the OEM invests in the supplier's process. We find that with supplier-initiated investment, the CS always prefers coopetition, but the OEM may not. When the investment is efficient, coopetition occurs as an equilibrium outcome; otherwise, competition occurs. The cause of coopetition equilibrium comes from variable process improvement incentives of the CS that derive from two driving forces: the vertical wholesale price effect and the horizontal quantity competition effect. When the degree of product substitution is low, the CS increases its investment and lowers its wholesale price, benefiting the OEM. When the degree of product substitution is high, the CS reduces its investment as well as production quantity, which also benefits the OEM. Interestingly, with OEM-initiated investment, the CS might not always choose to sell the component to the OEM, and as a result, coopetition never occurs.

The research is done to identify the constructs which affect the performance of a healthcare firm. Specifically, a mediating variable has been utilized to establish a relationship between the latent and dependent variables. The proposed model consists of three latent variables: vendor cooperation, SC efficiency, and quality measurement practices on afirm's performance through a mediator SC innovation. This model was developed using exploratory factor analysis and validated utilizing structural equation modeling. Information was collected from 310 respondents from various healthcare centers. The output suggested the proposed constructs significantly affected the firm's performance and contributed towards the goodness of fit. The output also indicates that a firm performance can be improvised through continuous SC innovation and cooperation with vendors, resulting in the firm's performance. Data utilized in this research were collected from various healthcare centers of India. The generalization of the results may be limited to hospitals in developingcountries. This research provides valuable information on planning in the healthcare segment. The outputs suggested firm's performance improvement is attained through continuous SC innovation.

Identifying the inter-sectoral relationships between the construction sector and other related sectors is crucial to reducing carbon emissions and promoting economic development. Non-competitive input–output models at comparable prices in 1992, 1997, 2002, 2007, 2012, and 2017 were used to conduct this study. The structural production layer difference (SPLD) method was employed in this study and complemented with the results of structural decomposition analysis to identify significant sectors affecting economic growth and carbon emissions in the construction sector. Overall, the carbon emissions and economic growth of China's construction sector in 2017 increased by 2.4 billion tonnes and 10512.4 billion yuan, respectively, compared to 1992 at the 2000 price level. Important sectors influencing economic growth and carbon emissions in the construction sector are identified. Wholesale and retail trade sector (s31) and finance sector (s33) increased the economic growth of the construction sector without the additional emission of CO2, which is economically and environmentally sustainable. Smelting and processing of the metals (s15) and transport and storage (s29) sectors simultaneously restrained economic growth and inhibited carbon emissions in the construction sector. The production and distribution of the electric and heat power sector (s25) stimulates the growth of carbon emissions in the sector of smelting and processing of the metals (s15), reducing the carbon reduction effect of smelting and processing of the metals (s15) on the construction sector. The SPLD results revealed that the direct impact of other services sector (s35) and transport and storage (s29) on carbon emissions in the construction sector has not been highlighted by the structural decomposition analysis (SDA). In terms of economic added value, processing of petroleum coking and the nuclear fuel sector (s12) is a pivotal sector in the supply chain influencing the added value from the extraction of petroleum and natural gas sector (s3) to the construction sector according to the results of SPLD.