Downstream Supply Research Articles

Corporate Social Responsibility along the global value chain

Locating substantial parts of the production process in developing and emerging economies, many firms face an increasing demand by stakeholders for Corporate Social Responsibility (CSR) along their value chains. Contractual incompleteness between firms and their suppliers at different stages of production can exacerbate the ability to meet these demands. We analyze a model of sequential production with incomplete contracts where CSR by independent suppliers differentiates the final product in the eyes of caring consumers. Progressing down the value chain, our model predicts an increasing CSR profile from upstream suppliers with low CSR to downstream suppliers with higher CSR. We confirm this prediction using Indian firm-level data – computing a firm’s value chain position by combining its product-level sales information with the World Input–Output Database. We find that more downstream firms report higher CSR expenditures as measured by a combination of staff welfare spending and social community spending.

COVID-19 disruptions and Norwegian food and pharmaceutical supply chains: Insights into supply chain risk management, resilience, and reliability.

The purpose of this study is to investigate how the COVID-19 crisis affected delivery security and firms' preparedness and responses in Norway. Investigations focus on supply chains which were critical for maintaining the supply of essential goods when large parts of society closed down. This includes four firms belonging to food and pharmaceutical industries, representing different parts of the respective supply chains, and covering imports, exports, domestic distribution, and home-delivery services. The originality of this article is that we employ theoretical models on supply chain risk management, resilience and reliability in conjunction, where these are usually used separately. Recognizing links, overlaps, and complementarity between the models, and using them step-by-step, we exploit synergies that enable more comprehensive assessments of strengths and weaknesses in firms' supply chains, covering gaps, prioritizing between improvement areas, and collecting input towards detailed, actionable risk mitigation actions. Investigations build on semi-structured interviews, systematically covering the formative elements for each of the models. Using the models in conjunction, we compare the firms and identify differences, similarities, strengths, and weaknesses in the consequences of pandemic-related disruptions and how firms approached the challenges. The main challenges for the firms were sudden demand changes early in the pandemic. While the firms had minor differences, their pre-pandemic contingency plans were generally not actionable or detailed enough, nor prepared for the pandemic's longevity. Therefore, more detailed and long-term guidelines are desirable, noting the importance and interrelationships of elements of supply chain risk management, resilience, and reliability. A common feature for all firms, and crucial for handling disruptions, is the importance of good and long-term relationships with upstream and downstream supply chain partners and the need for improving contingency plans and future resilience.

Gasoline Policy Simulation to Increase Responsiveness Using System Dynamics: A Case Study of Indonesia’s Gasoline Downstream Supply Chain

In the supply chain, inventory planning plays a crucial role in achieving a balance between supply and demand. This study aims to investigate a supply chain policy that can achieve an impressive level of responsiveness, reaching close to 100%. Additionally, by focusing on the supply chain of RON 92 gasoline in Indonesia, the research aims to identify the key factors influencing responsiveness instability. To achieve these objectives, a simulation model was used to analyze the inventory policy, considering various factors such as demand, production, safety stock coverage, transportation delays, production capacity, and importation due to insufficient production capacity. The results showed that forecasting accuracy is the main determinant of the responsiveness rate. Moreover, maintaining a minimum inventory level of 28 days yielded an impressive 99% responsiveness rate, provided that the deviation in demand does not exceed 5% of the forecast. The analytical tool used in the system dynamics framework was a simulation, which significantly contributed to the research findings. However, it is important to note that this research has limitations, specifically in its inability to analyze crude oil supply. Therefore, further research is necessary to thoroughly examine this aspect and gain a more comprehensive understanding of the overall supply chain dynamics.

Supply chain carbon transparency to consumers via blockchain: does the truth hurt?

PurposeThe purpose of this study is to determine if blockchain-supported carbon offset information provision and shipping options with different cost and environmental footprint implications impact consumer perceptions toward retailers and logistics service providers. Blockchain and carbon neutrality, each can be expensive to adopt and complex to manage, thus getting the “truth” on decarbonization may require additional costs for consumers.Design/methodology/approachExperimental modeling is used to address these critical and emergent issues that influence practices across a set of supply chain actors. Three hypotheses relating to the relationship between blockchain-supported carbon offset information and consumer perceptions and intentions associated with the product and supply chain actors are investigated.FindingsThe results show that consumer confidence increases when supply chain carbon offset information has greater reliability, transparency and traceability as supported by blockchain technology. The authors also find that consumers who are provided visibility into various shipping options and the product's journey carbon emissions and offset – from a blockchain-supported system – they are more willing to pay a premium for both the product and shipping options. Blockchain-supported decarbonization information disclosure in the supply chain can lead to organizational legitimacy and financial gains in return.Originality/valueUnderstanding consumer action and sustainable consumption is critical for organizations seeking carbon neutrality. Currently, the literature on this understanding from a consumer information provision is not well understood, especially with respect to blockchain-supported information transparency, visibility and reliability. Much of the blockchain literature focuses on the upstream. This study focuses more on consumer-level and downstream supply chain blockchain implications for organizations. The study provides a practical roadmap for considering levels of blockchain information activity and consumer interaction.

A vehicle imaging approach to acquire ground truth data for upscaling to satellite data: A case study for estimating harvesting dates

Crop harvesting date is critical information for crop yield prediction, financial and logistic planning of grain market and downstream supply chain. Remote sensing has the potential to map harvesting date at regional scale. However, existing studies generally lack ground truth data, and have not fully utilized spectral and temporal information of satellite data. To address these gaps, we present a new approach named Field Rover to acquire large volumes of binary harvesting status (harvested VS. unharvested) ground truth data at regional scale on a weekly basis, by repeatedly using vehicle-mounted cameras to collect time series images for sampled fields and interpreting them with a deep learning approach. With these vehicle-derived ground truth data, we present a machine learning approach to upscale harvesting status and subsequently estimate harvesting date to each field in a study area based on a new satellite platform Planet SuperDove which provides daily 8-band surface reflectance at 3 m resolution. We acquired >200,000 vehicle images from September to November for two years (2021 and 2022), and the deep learning model was able to generate harvesting status for each image with an accuracy of 0.998, which can be treated as ground truth. From a time series of harvesting status derived from revisiting vehicle images, harvesting dates for >500 fields were obtained by a change detection approach. We then trained a remote sensing classification model using harvesting status ground truth, and applied it to generate a harvesting status map for each Planet SuperDove overpass day. The classification model achieved an accuracy of 0.96 and subsequently accurate harvesting date maps were obtained by a curve fitting approach. We found that the Planet SuperDove harvesting date agreed well with the Field Rover harvesting date ground truth (R2 = 0.84, RMSE ≈ 5.5 days) at the field level in two years. When focusing on 2022 when more Planet SuperDove satellites were launched, the remote sensing of the harvest date achieved an accuracy of R2 = 0.91, and RMSE ≈ 3.3 days. This study demonstrated the efficacy of using repeated vehicle images to acquire time-related agricultural ground truth data, as well as the efficacy of using vehicle-satellite integrative sensing to upscale ground truth data to the regional scale. We envision this new method can be applied to monitor other agricultural management practices and therefore effectively advance the monitoring and modeling of smart farming and sustainable agriculture.

Risk assessment of power outages to inter-regional supply chain networks in China

The power industry is one of the most important infrastructures in the modern supply chain. Due to the deep interdependence of enterprises on the power industry and between enterprises, power outages will cause serious cascading risks propagating through the supply chain. To assess the risk and establish a more targeted and reliable electricity security policy, we developed a dynamic adaptive agent-based supply chain model to simulate the superimposed direct and cascading indirect economic loss risks of multiple small-scale power outages. We apply this model to assess the economic loss risks of China's power outage in 2018 as a case study. With a day-by-day simulation in a whole year, the results showed that total economic loss risks caused by power outages accounted for 0.49% (ranging from 0.32% to 0.63%) of the national GDP in 2018, while the indirect economic loss risks were 2.35 times (ranging from 1.18 to 3.28) the direct loss. From the perspective of two different mechanisms of material flow and information flow, the results showed different impacts of power outages on the upstream and downstream supply chains. In addition, scenario simulations were conducted to identify 20 priority control regions to provide policy implications for securing the stability of the power supply. Overall, our model can be used to evaluate the economic loss risks caused by any historical outage events with available data and enables the early-stage warning of the financial dangers by arising power intervention policy.

The encroachment strategy under eco-innovation collaboration with delayed realized efficiency information

PurposeEco-innovation products, which means achieving more efficient and responsible use of resources and reducing the detrimental impact on the environment, can win a competitive advantage for the enterprises. But it is not easy to implement due to the high cost of eco-innovative technologies development, the uncertainty of market needs and return risk of investment. Many enterprises seek collaborations from their upstream suppliers to jointly carry out eco-innovation, such as Apple, IBM and Nike. A unique feature of collaboration is that efforts by one party enhance the marginal value of the other party's efforts. However, the collaboration will make the partner know the eco-innovation technology and prompt the partner to encroach the market to sell competitive products by herself. Motivated by this observation, this paper considers the optimal collaboration strategy on eco-innovation between upstream and downstream supply chain member and the optimal encroachment strategy of upstream supplier in a supply chain.Design/methodology/approachThis paper models a supply chain wherein a supplier provides products or materials for her manufacturer and cooperates with her manufacturer in eco-innovation. Also, the supplier could encroach on the market to sell similar products by herself. Then this paper uses game theory and mathematical modeling to do relative analysis.FindingsThe analysis reveals several interesting insights. First, eco-innovation collaboration makes supplier encroachment no longer only rely on the encroachment cost. The delayed realized eco-innovation efficiency information also plays a vital role. Second, different from previous research, the authors find the manufacturer's preference for supplier encroachment depends on the uncertainty of eco-innovation efficiency and potential market demand. Third, both partial and full encroachment strategies of the supplier can effectively improve the eco-innovation level.Originality/valueThe paper is the first to take the interplay between collaboration and encroachment into account in a supply chain. The results caution enterprises and policymakers to take vertical collaboration and delayed realized information into account in the competitive supply chain before making any operational decisions. Furthermore, the authors propose that governmental intervention aimed at stimulating supplier encroachment in appropriate circumstances can contribute to the improved environmental performance of products.

Toward sustainable joint optimisation for product family and supply chain configuration with smart contracting consideration

This article underscores the necessity for sustainable and environmentally friendly manufacturing practices in product family configuration (PFC) projects, which are paramount to the global economy. Nevertheless, conventional approaches often fixate solely on design aspects, overlooking downstream supply chain configuration (SCC) considerations and the corresponding environmental benefits. Consequently, there is an escalating demand for an integrated optimisation approach that encompasses both PFC and SCC to realise economic and environmental advantages. This study delves into a methodology that integrates blockchain smart contracts as binary 0–1 variables with waste recycling and utilisation, yielding a comprehensive multi-objective model. The proposed methodology seamlessly incorporates considerations for both PFC and SCC. Furthermore, a nested leader-follower optimisation algorithm, based on the non-dominated sorting genetic algorithm-II (NSGA-II), has been devised with the objective of achieving triple benefits: augmented profits, maintenance revenue, and diminished environmental emissions. In conclusion, this research contributes to the advancement of sustainable collaborative optimisation through the innovative utilisation of blockchain smart contracts and multi-level modelling. To demonstrate the effectiveness of the proposed methodology, it is applied to a 60 KW DC electric vehicle (EV) charging piles, accompanied by a sensitivity analysis to assess its management implications.

Digitalisation for survival: managing resources in digitalizing operations and processes in the fashion industry

Digital transformation of the downstream supply chain is not simply a matter of technology; it requires the development of specific processes, competencies, and assets. The fashion industry has experienced significant disruption due to the digitalisation of business over the past 15 years. This paper explores how firms in the fashion context respond with innovative solutions to procure and use specific resources to develop successful digital sales channels. The results of our qualitative multiple case study approach, which employs an abductive approach and is in line with resource advantage theory, enable us to identify a specific digital resource category and its four foundations: technology, competency, policies, and control.

Research on Enterprise Supply Chain Management --- Taking Apple as an Example

The term supply chain management first appeared in the logistics literature in the mid-1980s. The goal of so-called supply chain management is to plan, implement and control in order to reduce production costs and improve production efficiency. This paper aims to analyze enterprise supply chain management. The supply chain involves most of the products in our lives. The paper starts by presenting an overview of supply chain and the importance of it. This paper chooses Apple as an example to analyze supply chain management. Apple is the world's leading high-tech company, which can offer me some experience. The supply chain was not pioneered by Apple, but they do a good job. In the supply chain, part of the enterprise's business is external, which reduces costs and improves production efficiency. Apple is consumer-oriented. Some businesses are external and so on, which makes it a win-win situation for him and his partners. But there are also some problems in Apple's supply chain management, such as excessive exploitation of downstream suppliers and neglect of employee rights and interests. Then this paper discusses how they make changes in order to improve supply management. Finally, we summarize how to effectively manage supply chains in businesses. Apple needs to pay attention to the low-end market, strengthen the supervision of suppliers, reduce the exploitation of suppliers, and truly protect the rights and interests of those suppliers' employees. In addition, it should shorten and optimize the supply chain to make the company's operations more stable.

Green product development framework: empirical evidence from Chinese automotive supply chains

PurposeThe study aims to develop and test a supply chain wide green product development framework of focal firms and their major suppliers, in the context of the Chinese automotive industry.Design/methodology/approachAn in-depth case studies approach is adopted for this study. Three automotive sector upstream supply chains involving 17 firms and 51 experts as respondents were interviewed on the importance and implementation effectiveness of 6Rs (reduce, redesign, recover, remanufacture, reuse and recycle) across the manufacturer and their respective tier 1 and tier 2 suppliers.FindingsThe results indicate that the Chinese automotive sector supply chains are mainly focused on “reduce” practices with immediate environmental and economic benefits. The investigated firms however had future implementation plans for “redesign” and “recovery” practices to become comprehensive in green product development (GPD).Research limitations/implicationsThe study facilitates automotive firms, industry policymakers and researchers the understanding of incorporating comprehensive GSCM practices across the upstream supply chain to achieve circularity. The study focused on upstream supply chain due to the concentration of major production practices in this section of the supply chain. However, the downstream supply chain equally deserve attention as well as the need to understand the mediating and moderating roles of the different Rs to tease out the pros and cons of achieving overall environmental sustainability.Originality/valueThere are very limited studies on comprehensive GPD for achieving optimal GSCM and sustainability. By simultaneous looking at a focal firm and its upstream supply chains GSCM practices, this study addresses a system-wide comprehensive GPD issues from implementation of 6Rs perspectives in the supply chain.

The role of visibility in supply chain resiliency: Applying the Nexus supplier index to unveil hidden critical suppliers in deep supply networks

Problem definitionOf the many factors affecting supply chain resiliency, visibility can have a profound effect on critical decisions for improving the readiness, response, and recovery from supply chain disruptions. The visibility of tier-1 suppliers gives only a narrow view of the entire picture. Methodology/resultsThis work expands on applying the Nexus Supplier Index [1] using a data-driven approach that deviates from the traditional analysis. It relies on the network topology, leveraging graph centralities. Data collection started with 40 focal companies representing 24 industries, 14 clusters, different sectors, and sizes, generating $1.7 T in revenue and 2.3 M jobs. We collected ∼16,000 data points covering upstream and downstream supply chains, the most extensive application of the NSI reported in the literature. We calculated different node centralities for the focal companies and all companies in their supply networks to increase supply chain visibility to key worldwide companies. We propose improvements for identifying hidden critical suppliers (HCS) within the network that, when combined, provide visibility of depths up to 11 tiers. Managerial implicationsThis work illustrates the results of a partnership between academia with governmental and non-governmental agencies in a data-driven approach to identify critical suppliers hidden in a US state's leading manufacturers' supply network. From this work, 43 companies were identified as hidden critical suppliers in an initial analysis, of which 35 had no presence in the analyzed state (82%). All of them were contacted for possible future economic development endeavors. It is also important to mention that 15 of the 43 critical suppliers were in semiconductor-related industries (35%). This data was collected in the fall of 2020, before the worldwide semiconductor shortage, illustrating the potential to identify industries with greater supply chain resiliency risk.

Carbon capture in blue hydrogen production is not where it is supposed to be - Evaluating the gap between practical experience and literature estimates

Blue hydrogen from natural gas reforming coupled with carbon capture and storage (CCS) is seen as one potential low-emission hydrogen production pathway. Diverging life cycle assessments (LCA) on the greenhouse gas (GHG) emissions of blue hydrogen, however, make its contribution in a future carbon-neutral energy system uncertain. Our objective is to determine how the technical performance of carbon capture (capture rate and energy consumption) in hydrogen production is depicted in literature and how it compares to blue hydrogen plants in practice, thereby gaining insights on how CCS influences the ambiguity around blue hydrogen's decarbonization potential. We first review the recent blue hydrogen LCA literature with a focus on the carbon capture technology. Our results show that energy consumption and sources, as well as the capture rate of CCS differ in the studies, with substantial impact on GHG emissions. We then compare literature results to existing and planned blue hydrogen production plants. None of the existing plants with CCS has the identified process configuration necessary to comply with the European GHG emissions threshold for renewable fuels (28.2 g CO2-eq./MJ H2). Due to non-harmonized assumptions hampering direct comparisons of GHG footprints, we conduct a German case study with harmonized data. It illustrates the impact of the energy balance and its links with upstream supply chains using practice conditions in the near future. Again, most of the evaluated supply chain and process configurations exceed the European GHG emissions threshold. From that we conclude that blue hydrogen's decarbonization potential in the short to medium term is most likely more limited than announced capture rates suggest. Hence, we recommend to establish policies for tracking the decarbonization of upstream and downstream supply chain elements in hydrogen project development, as well as to set regulations for accounting and monitoring of GHG emissions over the entire supply chain.

Trade credit or credit insurance? A green supply chain finance design scheme with multi-objective programming

Classical supply chain finance (SCF) primarily focuses on the financial service among all upstream and downstream supply chain participants. Due to the continuously deteriorating of the ecological environment, an environmental-friendly SCF system is urgently needed. In this paper, we propose a novel SCF design scheme with environmental concerns, i.e., green supply chain finance (GSCF), consider the financing channels both from banks and from consumers, and design a bi-objective optimization model that depicts the trade-off between the benefit and the emission. Further, an improved normalized normal constraint (INNC) Pareto method is developed to address the optimal financing strategy of the bi-objective model. We then conduct a numerical case of a Taiwanese steel firm to verify the effectiveness and efficiency of our method. Results show that our model provides a portfolio of optimal solutions on Pareto frontier which can be applied as an effective decision support system when designing a GSCF. Furthermore, the sensitivity analysis also presents the impact of environmental investment cost, technological ratio of companies and the interest rate of trade credit on the optimal configuration of the GSCF.

Stackelberg Social Equilibrium in Water Markets

Market power in water markets can be modeled as simultaneous quantity competition on a river structure and analyzed by applying social equilibrium. In an example of a duopoly water market, we argue that the lack of backward induction logic implies that the upstream supplier foregoes profitable strategic manipulation of water to the downstream supplier. To incorporate backward induction, we propose the Stackelberg social equilibrium concept. We prove the existence of Stackelberg social equilibrium in duopoly water markets with an upstream–downstream river structure and derive it in the example of a duopoly market.

Does global supply chain integration payoff? The case of maritime shipping firms

AbstractGlobal supply chains operate in a volatile environment characterized by risks like the 2008–2009 financial crisis, trade disputes, and the COVID‐19 pandemic. Maritime shipping firms, the backbone of global supply chains, are particularly affected by this volatility. In response, these firms have pursued two strategies. First, they have acquired tangible assets to increase their capacity. These assets, however, are neither easily re‐deployable to other uses nor quickly adjustable, preventing firms from flexibly matching supply and demand. Second, these firms have pursued global supply chain integration by acquiring similar firms or firms in their upstream or downstream supply chain to diversify into other supply chain activities. Anecdotal evidence suggests that some firms have successfully pursued these strategies, but others have failed, eventually exiting the market. We posit that one explanation for this difference may be how effectively these firms manage their assets relative to their supply chain integration activities. We test this proposition by drawing from resource‐based theory and transaction cost economics and using longitudinal data for 148 maritime shipping firms. We also test post hoc whether typically acquired supply chain activities are beneficial. Our findings offer insights into asset management and global supply chain integration and offer advice to practitioners.

Contract farming led by a seed enterprise and incentives to produce high quality: Which contract design performs best?

AbstractMotivated by real‐world practices in China, we consider a three‐level agri‐food supply chain consisting of a seed enterprise, a grower, and a buyer–processor, where the seed enterprise is fully vertically integrated in the seed industry and acts as the leader to coordinate the grower and buyer–processor of the agri‐food supply chain. We call this seed company‐led agri‐food contract farming. First, we develop analytical models to derive optimal solutions under penalty contracts, revenue‐sharing contracts and cost‐sharing contracts. Then, we analytically compare the optimal strategies of the three contracts using data from China's fresh maize industry as the numerical example. Finally, we do the sensitivity analysis of contract parameters. Results demonstrate that: (1) The seed company‐led agri‐food contract farming obtains quality advantages and improves profits by responding quickly to external demand changes and effectively coordinating internal technical capabilities. (2) The penalty contract performs poorly in both quality and profit. (3) The profit of the whole supply chain increases with the increase of the revenue‐sharing proportion from downstream supply chain participants to upstream participants; but the relationship between the proportion of cost‐sharing and the profit of the whole supply chain is nonmonotonic. [EconLit Citations: C79, O13, Q13].

An optimization model for the downstream supply chain network, considering consolidated warehouses and the selection of transportation mode

PurposeThe supply chain (SC) of the fast-moving consumer goods (FMCG) sector in India witnessed a significant change soon after introducing the Goods and Services Tax (GST). With the initiation of this tax, companies started moving from individual state-wise warehouses to consolidation warehouses model to save costs. This paper proposes a model that frames a mathematical formulation to optimize the distribution network in the downstream SC by considering the complexities of multi-product lines, multi-transport modes and consolidated warehouses.Design/methodology/approachThe model is designed as mixed-integer linear programming (MILP), and an algorithm is developed that works on the feedback loop mechanism. It optimizes the transportation and warehouses rental costs simultaneously with impact analysis.FindingsTotal cost is primarily influenced by the critical factor transportation price rather than the warehouse rent. The choice of warehouses at prime locations was a trade-off between a lower distribution cost and higher rent tariffs.Research limitations/implicationsThe study enables FMCG firms to plan their downstream SC efficiently and to be in line with the recent trend of consolidation of warehouses. The study will help SC managers solve complexities such as multi-product categories, truck selection and consolidation warehouse selection problems and find the optimum value for each.Originality/valueThe issues addressed in the proposed work are transporting products with different sizes and weights, selecting consolidated warehouses, selecting suitable vehicles for transportation and optimizing distance in the distribution network by considering consolidated warehouses.

Energy saving and consumption reduction in the transportation of petroleum products: A pipeline pricing optimization perspective

Pipeline transportation is a low-energy and economical mode of transporting petroleum products in the downstream supply chain, however, there is almost no theoretical research on its pricing strategies. The unreasonable pricing strategy has resulted in low utilization of multi-product pipeline capacity as well as high energy consumption of petroleum products transportation. Therefore, this paper aims to improve pipeline turnover and promote the low-carbon transportation market from the perspective of pipeline pricing optimization. We propose an integrated framework for multi-product pipelines that couples pricing strategy and logistics optimization model. This framework simulates the pricing behavior of the pipeline carrier and the corresponding logistics planning behavior of the oil shipper. We apply the framwork to 10 pipeline pricing schemes for two regions in China with different logistics structures, and analyze the economic and environmental benefits of the new strategy. The results show that the well-performing scheme can increase pipeline carriers' revenue by 11.41 million CNY per month, significantly improve the competitive advantage of long-distance pipelines, and reduce energy consumption by 272 tce. Based on these findings, we provide recommendations for policymakers at four levels. In conclusion, the new pricing strategy will help reverse the disadvantageous situation of the pipeline in the competitive market and promote energy conservation in the petroleum products logistics industry.

Identification of key drivers for improving inventory management in pharmaceutical supply chains

Existing literature on optimizing inventory levels in pharmaceutical supply chains has focused on a limited set of drivers. However, the global supply chain disruptions produced by the Covid-19 pandemic demonstrated the need for a more nuanced picture of the inventory management drivers in this sector to identify profitable inventory configurations while fulfilling demands and safety margins. To address this gap in the literature, this paper identifies key drivers impacting inventory levels and develops a framework for assessing inventory configurations in pharmaceutical supply chains. The framework is tested using a single case study approach. The case study showed that while external and downstream supply chain factors were recognized as being critical to pursuing inventory reduction initiatives, internal factors prevailed when making inventory management decisions. The framework developed in this paper may assist practitioners in identifying the most important factors impacting inventory levels within a specific pharmaceutical supply chain configuration and is in use in the industry today.