Underlying Supply Chain Research Articles

(Invited) The Evolving SiC Market and Impact on CMP Supply Chain

Silicon carbide (SiC) is a wide bandgap semiconductor with physical and electrical properties that provide superior performance in high-voltage or high-power applications. Compared to the more established silicon devices, SiC provides better thermal conductivity, ~10x higher breakdown voltage, faster switching speeds and lower resistivity. Even with the performance advantages, the adoption rate of SiC is slowed by high cost and the inherent difficulty of processing this material. SiC is extremely hard (just below diamond on the hardness scale) and chemically inert which makes processing boules into wafers rather difficult. This presentation will contrast some of the basic differences between process methods developed for silicon and other semiconductor materials versus those required for SiC.Demand for high-quality single crystal SiC substrates continues to rise as the worldwide demand for electric vehicles, charging infrastructure, green energy production, and more efficient power devices in general requires more and more SiC devices. SiC wafer manufacturers are trying to ramp output as quickly as possible but technical difficulties of processing SiC are often a limiting factor. In spite of aggressive capital spending by many of the major players, the actual growth in substrate production has been constrained to around 15% CAGR even though demand would support a much faster ramp. As end use markets continue to evolve, ripple effects are also evident in the underlying supply chains, such as CMP pads and slurries.

The Effects of Complexity and Coupling on Supply Chain Disruptions

Business executives have recently indicated that supply chain disruptions represent a major threat to their firm’s profitability and revenue growth (Smyrlis, 2006; Hendricks and Singhal, 2009). In the literature, a number of conceptual studies have suggested that supply chain complexity is a main driver of supply chain disruptions (Choi & Krause, 2006; Christopher & Lee, 2004; Juettner et al., 2003). Other studies have suggested that the degree of coupling in the supply chain is a major determinant of supply chain disruptions (Agrawal and Nahimias, 1997; Ahuja, 2000). Building on the theoretical foundation of Normal Accident Theory (NAT), this paper proposes a nuanced relationship between supply chain complexity and coupling and their collective impact on supply chain disruptions. Through an empirical examination, we seek to validate the theoretical proposition that complex, tightly coupled systems are inherently prone to failures or accidents. This study contributes significantly to the supply chain management discourse, providing a detailed analysis of the mechanisms underlying supply chain vulnerabilities and offering practical guidance for developing more resilient and responsive supply chain systems. Our findings invite future research to further explore the intricacies of supply chain disruptions, complexity, and coupling, aiming to refine and expand upon the mitigation strategies discussed herein.

Sources of Supply Chain Volatility: A Literature Review

Purpose: The purpose of this study was to identify the main source of supply chain volatility based on empirical literature, addressing the gap in existing research where consensus on this matter has been lacking.
 Methodology: Employing an interpretivist approach, this study utilized a bibliographic and qualitative research method. The researchers systematically reviewed literature from top publishing sites and journals, focusing on titles and abstracts containing the keyword 'supply chain volatility' spanning from 2013 to 2023. Through this process, a taxonomy of 15 articles was developed to synthesize existing knowledge on the subject.
 Findings: The results of the study indicate that demand variability emerges as the primary source of supply chain volatility, with 60% of the analyzed articles highlighting its significance. This finding underscores the critical role of demand fluctuations in driving supply chain disruptions and challenges.
 Unique Contribution to Theory, Practice and Policy: This study makes a unique contribution to existing literature by providing empirical evidence and consensus on the main source of supply chain volatility. By synthesizing and categorizing findings from diverse sources, it advances theoretical understanding of the factors underlying supply chain disruptions. The identification of demand variability as the primary source of supply chain volatility offers valuable insights for practitioners seeking to enhance supply chain resilience and mitigate disruptions. Understanding the central role of demand dynamics can inform strategic decision-making and risk management practices within organizations. The findings of this study have implications for policy-makers involved in shaping regulatory frameworks and industry standards related to supply chain management. By recognizing demand variability as a key driver of volatility, policymakers can tailor interventions and incentives to promote stability and efficiency in supply chains.

The impact of website design on consumer decision making – evidence from North Macedonia

Abstract Today, almost one third of the world population are digital buyers. The hypothesis that more life moves online, the less damage to our environment is still unclear. E-commerce sites and the underlying supply chain can have both positive and negative impacts on the environment. Sustainable web design is an approach to designing websites that puts people and the planet first. It is a growing movement as organizations look for opportunities to reduce their influence on the environment. This research elaborates on determinants of consumer behavior that shape online purchase processes and affect the final consumer decision to buy. It discusses the importance of website design on consumer decision-making in e-commerce. Consumer decision-making and behavior during online shopping in the literature are measured by numerous models. One of the primary motivators for any online store to attract customers is the quality of website design. Website quality refers to the overall excellence, effectiveness, and usability of a website. It influences consumers’ perceptions of product quality and affects online purchase intentions (Sun, Chen, and Huang, 2014) and even continuation intentions (Chawla et al., 2015). Website quality as well positively affects online impulse buying behaviour (Akram et.al. 2018). The design of a website interface plays an important role in online purchasing, and customers are more likely to visit and buy from better-designed websites (Chiu and Yang, 2016). This paper proposes that website design quality is a multi-dimensional construct. To support the importance of the construct, a review of different studies is conducted elaborating on the impact of website design on consumer attitude and behavioral intention in North Macedonia. This study has theoretical and practical implications on the existing knowledge and provides managerial insights for e-vendors implying that to promote online shopping, they need to improve the quality features of the website and enhance users’ trust.

Impact of special-denomination label constraints on fresh produce supply chains

Special Denomination labels for fresh food products, such as “local”, “fair-trade”, “organic” and similar market-narrowing movements have gained a lot of attention over the last few decades. While these movements have some clear benefits and beneficiaries, they also may increase the complexity of the management of the underlying supply chains resulting in unintended consequences such as increased food waste, higher prices, and reduced food availability for certain geographical areas and population segments. The implementation of local food movements may result in the exclusion of farmers of certain areas, enticing these farmers to move their operations to be close to large urban centers, increasing the competition for scarce resources such as land, water and labor. In this paper, we explore the use of optimization-based tools to assess the impact of different levels of implementation of these special denomination labels to fresh food, with particular emphasis on the “local food” label and the distance used to determine compliance with this label. The tools presented seek to contribute to the emergence and maturation of the design of efficient supply chains for the direct procurement of special denomination crops, particularly fresh vegetables by making the most efficient connections between a market demand and the suppliers of products with the required characteristics. A case study is used to analyze the impact of the definition of this label on the potential suppliers of a specific market. The results show that the implementation of distinct definitions of local food have different impacts on the potential supplying sources being considered, depending on their distance to the market and the other potential supply sites. The results also show that the relaxation of strict local-food label and the use of other proxy measures of local food may be a better approach to reduce CO2 emissions associated with the supply chain of fresh produce.

On a holistic view of supply chain financial performance and strategic position

Measuring corporate financial performance is an essential task in many supply chain decisions, such as supply chain strategic positioning and partner selection. This study introduces an analytical approach that can quickly scan financial data of many companies and produce a summary measure for each company. The approach offers organizations a less wearing way to obtain a holistic view of all target companies’ financial performance patterns, which imply the underlying supply chain strategies. The strategy map, a two-dimensional representation of the summary, provides a comprehensible means to apprehend the relative strategic position and measure the similarity between companies. The approach relies on three popular machine learning models, forecasting, clustering, and classification. It takes multi-year, multi-variate financial time series from the three standard financial statements, learns the patterns from the data, and tunes model parameters to configure the final settings for future applications. The input data needed are relatively easy to obtain and the self-learning modules only require modest domain knowledge to apply the approach. Its noise reduction, outlier detection, and feature selection functions ensure a consistent and robust performance. The empirical test using data from all US manufacturers and traders listed on NYSE and NASDAQ demonstrates the efficacy of the approach.

An agent-based infrastructure for assessing the performance of planning approaches for semiconductor supply chains

Semiconductor supply chains that manufacture integrated circuits consist of dozens of semiconductor wafer fabrication, assembly and testing and storage facilities. The sheer size of the geographically distributed facilities and the involved supply chains, the pervasive presence of different kinds of uncertainties and the rapid pace of change lead to large-scale, distributed planning problems. However, the interactions between the different planning functions in semiconductor supply chains are not well understood. Systematic study of the interplay between the various planning algorithms in a real-world setting is extremely difficult due to the different software systems and decision-makers involved. In this paper, we discuss the design and implementation of a software agent-based experimental infrastructure for assessing the performance of different planning functions in a risk-free simulation environment, using web services to implement parts of the planning functionality. The environment is highly scalable since the planning functionality is provided by cloud computing mechanisms. Discrete-event simulation is used to emulate the underlying supply chain and execute the planning functions in a rolling horizon setting. We illustrate the benefits of the experimental environment and the benefits of using distributed computing techniques by studying the interaction between master planning and demand fulfillment, and between master planning and production planning in simplified semiconductor supply chains.

Core Elements Underlying Supply Chain Management in the Construction Industry: A Systematic Literature Review

The relevance of supply chain management (SCM) is being increasingly recognized in the construction industry. However, its implementation has been limited and is still challenging for researchers and practitioners. An adequate and systematic understanding of context-specific core concepts and practices are considered fundamental to foster its implementation. This paper aims to provide a holistic look into the existing research on elements underlying SCM in the construction industry. It adopts a systematic literature review method to examine almost two decades of publications and uses a comprehensive SCM framework to synthesize the findings. The results revealed a set of 19 core elements clustered in five subject areas (i.e., ‘strategic management’, ‘logistics’, ‘relationships’, ‘best practices’ and ‘organizational behavior’) that have a prominent role in construction SCM. Every core element was analyzed in detail and the results were discussed in the context of other evidence. This study produced the first comprehensive picture of the current state of knowledge, providing relevant contributions to enhance the understanding and implementation of SCM within the construction industry.

Customer selection and incentivization for SKU rationalization in a packaged gas supply chain

This paper presents customer selection and incentivization methodologies necessary for the implementation of many SKU rationalization schemes. Our work accounts for the problem of business demand loss, which is undesirably associated with the benefits of rationalized product offerings. We apply our methodologies to a particularly complex instance of SKU rationalization established in the literature, namely a case of demand substitution within a packaged gas supply chain planning problem. This is done both to display the value of our contributions, and to provide a business setting for the workflow process we prescribe for decision makers. In our first contribution, we develop a customer selection heuristic which pre-processes targets for demand substitution, subject to demand characteristics and the supply chain features. The heuristic is shown to outperform objectives utilizing random customer selection by 10–20%, dependent on the desired amount of substitution required of the demand-base. Further, we show that the heuristic outperforms an MILP extension, which explicitly includes customer selection as a decision in the underlying supply chain problem's model, by 7% across a variety of cases. Our second contribution regards development of prescriptive incentivization methodologies for a business, in order to secure shifts in demand profiles across the selected customers. We present multiple strategies for both determining offerings and analyzing system implications, while recognizing stochastic and diverse customer behaviors. In addition to providing useful methodologies around SKU rationalization, trade-offs and business implications throughout the execution of such ideas in practice are heavily considered throughout this work.

Environmental Benefits and Economical Sustainability of Urban Wastewater Reuse for Irrigation—A Cost-Benefit Analysis of an Existing Reuse Project in Puglia, Italy

Besides benefits associated to increased water availability for irrigation, reuse projects of urban water can also provide positive environmental impacts, as they contribute to improve water quality of the receiving bodies by diverting wastewater from their outlet. This represents a typical win-win situation where significant synergies can be achieved between urban and agricultural sector, and the environment. These favorable conditions, however, do not necessarily imply that water reuse is either feasible from an economic perspective nor that the underlying supply chain is going to be triggered, if certain conditions are not met. Cost-Benefit Analysis (CBA) is considered a sound, theoretically well-grounded tool to analyze the financial and economical sustainability of an investment. The paper presents the CBA of an existing reuse scheme in Puglia, in southern Italy, reclaiming wastewater for irrigation from a coastal area with growing recreational, beach-related activities. Supported by operational data, official statistics and sector documents, the CBA reveals that in almost all scenarios the existence of environmental benefits must be invoked in order to consider the project economically sustainable. Coherent screening of the different impacts, isolating the ones that are applicable to the specific case-study, shows that these benefits are mainly non-use benefits related to the aesthetic enjoyment of clean water in the reclaimed stretch of coastline where wastewater discharge may no longer take place or take place in a way that significantly reduce seawater pollution.

Activity analysis based modeling of global supply chains for sustainability assessment

Assessing the sustainability of products is an intricate task that requires a thorough understanding of the underlying supply chains. Prominent challenges are the integration of the environmental, the economic, and the social dimension of sustainability as well as the consideration of spatial heterogeneity with regard to technology, environment, markets, and society. This paper proposes a novel modeling approach based on activity analysis to facilitate spatially differentiated sustainability assessments of global supply chains. The production and transportation activities in the supply chain and the exchanges between activities and their natural, economic, and social environments are formalized by means of activity vectors. Linking the activities and exchanges to specific locations allows for the calculation of regionalized sustainability indicators. The approach is used to analyze the environmental, economic, and social impacts of lithium-ion batteries. The comparison of alternative supply chain configurations with the spatially differentiated approach reveals that the assessment results differ significantly from those of the global average supply chain. These insights offer new opportunities to advance the design of sustainable supply chains.

Effects of trust-based decision making in disrupted supply chains.

The United States has experienced prolonged severe shortages of vital medications over the past two decades. The causes underlying the severity and prolongation of these shortages are complex, in part due to the complexity of the underlying supply chain networks, which involve supplier-buyer interactions across multiple entities with competitive and cooperative goals. This leads to interesting challenges in maintaining consistent interactions and trust among the entities. Furthermore, disruptions in supply chains influence trust by inducing over-reactive behaviors across the network, thereby impacting the ability to consistently meet the resulting fluctuating demand. To explore these issues, we model a pharmaceutical supply chain with boundedly rational artificial decision makers capable of reasoning about the motivations and behaviors of others. We use multiagent simulations where each agent represents a key decision maker in a pharmaceutical supply chain. The agents possess a Theory-of-Mind capability to reason about the beliefs, and past and future behaviors of other agents, which allows them to assess other agents' trustworthiness. Further, each agent has beliefs about others' perceptions of its own trustworthiness that, in turn, impact its behavior. Our experiments reveal several counter-intuitive results showing how small, local disruptions can have cascading global consequences that persist over time. For example, a buyer, to protect itself from disruptions, may dynamically shift to ordering from suppliers with a higher perceived trustworthiness, while the supplier may prefer buyers with more stable ordering behavior. This asymmetry can put the trust-sensitive buyer at a disadvantage during shortages. Further, we demonstrate how the timing and scale of disruptions interact with a buyer's sensitivity to trustworthiness. This interaction can engender different behaviors and impact the overall supply chain performance, either prolonging and exacerbating even small local disruptions, or mitigating a disruption's effects. Additionally, we discuss the implications of these results for supply chain operations.

False quality claims: Prevention and supply chain implications

False quality claims have recently rocked the automobile industry. To promote customer demand while seemingly complying with regulations, manufacturers may cheat even at the risk of incurring severe penalties. As a result, the production horizon becomes uncertain. Assuming it is socially critical to enforce quality standards (e.g., specific emission levels or safety levels for food, drugs, or transportation), we study dynamic production policies under the threat of penalties and assess when a false quality claim can be optimal for the firm. We find that regardless of the specific form of a convex penalty function, the production rate will gradually decrease to slow down the increase in the probability of getting caught. We show that the government or regulatory department can determine a minimal finite penalty to prevent the manufacturer from cheating. In the context of an underlying supply chain, we show that vertical competition between the manufacturer and its suppliers can play a socially positive role by reducing the batch produced under a false quality claim.

Modelling and solving spare parts supply chain network design problems

Spare parts are key operational assets in order to minimise unexpected equipment downtimes that may significantly impact a company’s results. The spare parts supply chain network supports the entire spare parts operations management and it is essential to achieve the planned goals. However, most of the traditional literature on spare parts management has not focused on the underlying supply chain network. Thus, this paper studies the integration of supply chain network design and control with traditional spare parts management. In particular, a generic network optimisation modelling structure is proposed, with simultaneous optimisation of warehouse locations and inventory control decisions, allowing minimising the total costs associated with the spare parts supply chain network. The generic model is specified based on three inventory control policies widely employed in the industry, which are suitable for managing a great variety of spare parts, i.e. (s, Q), (R, s, S) and (S-1, S). Furthermore, a solution approach is proposed based on Generalised Benders Decomposition. Finally, numerical results from a real-world application case in the process industry are shown and discussed.

Superfruit in the Niche—Underutilized Sea Buckthorn in Gilgit-Baltistan, Pakistan

Sea buckthorn is a medicinal plant occurring throughout the temperate regions of the northern hemisphere. Considered as a “superfood” given the nutritional properties of its berries, the latter have a large international market potential, particularly in China and Europe. Although sea buckthorn grows widespread in northern Pakistan, it is a neglected species there. Fruit marketing is severely hampered by low raw product quality, varying prices, and low local demand. During 2017–2018 a total of 111 collectors and 17 commission agents were interviewed from Gilgit-Baltistan, Pakistan using semi-structured questionnaires. The results provide comprehensive information about the current situation from collection to post-harvest management of sea buckthorn fruits including the analysis of vitamin C under different sun and shade drying conditions. The findings are complemented by an analysis of the underlying supply chain. Fruit sale prices were low for the collectors (1.82 US$ kg−1) since mostly poor households are involved in the harvest and sale. Traditional sun drying and storage conditions were inappropriate resulting in a decrease of chemical fruit quality and thus negatively affecting the sales price of produce. Supply chain analyses showed that the non-coordination among actors and lack of infrastructure affect the efficiency of the targeted sea buckthorn production at large. The study also shows the urgent need to set appropriate food quality standards, to increase communication among stakeholders, and to intensify training offers especially for collectors of sea buckthorn fruits.

Impact of risk aversion on two-echelon supply chain systems with carbon emission reduction constraints

This study examines a two-echelon supply chain consisting of two competing manufacturers and one retailer that has the channel power, in which one manufacturer is engaged in sustainable technology to curb carbon emissions under the cap-and-trade regulation while the other one operates its business as usual in a traditional manner. Two different supply chain configurations concerning risk attributes of the agents are considered, that is, (ⅰ) two risk-neutral manufacturers with one risk-averse retailer; and (ⅱ) two risk-averse manufacturers with one risk-neutral retailer. Under the mean-variance framework, we use a retailer-leader game optimization approach to study operational decisions of these two systems. Specifically, optimal operational decisions of the agents are established in closed-form expressions and the corresponding profits and carbon emissions are assessed. Numerical experiments are conducted to analyze the impact of risk aversion of the underlying supply chains. The results show that each risk-averse agent would benefit from a low scale risk aversion. Further, low carbon emissions could be attainable if risk aversion scale of the underlying manufacturer is small or moderate. In addition, the carbon emissions might increase when risk aversion of the traditional manufacturer or the retailer is of small or moderate scale.

Supply chain micro-communities in urban areas

An increase in urban freight transport is inevitable as growing urban populations require more goods, more conveniently. A deeper understanding of the geography and trends of urban freight transport must recognise that it is the aggregate result of a complex web of supply chain interactions. To understand the trends, the behaviour of the underlying supply chains must be understood. Using Global Positioning System (GPS) traces of commercial vehicles and network theory concepts, this paper examines the characteristics of supply chain micro-communities in three urban areas in South Africa. The similarity in the structure of these micro-communities across the three, very diverse, areas suggests that the dynamics that drive supply chain interaction are not dependent on local geography. Four prominent archetypes were identified that account for more than half of the micro-communities in each area. Directionality, geographic dispersion and the balance of importance in the micro-communities are studied in the context of these archetypes. This paper presents a first puzzle piece in deducing urban freight transport patterns from supply chain interaction. Furthermore the results are an empirical benchmark that can validate theoretic models of urban supply chain interaction.

The challenge of authenticity: Blockchain in the supply chain

Today’s complex and dispersed supply chains create significant challenges for supply chain managers. ‘Organic’, ‘non-GMO’, ‘fair trade’ and ‘conflict free’ are just some of the claims that require a transparency in the supply chain to maintain and verify. Product origin and authenticity are similarly at risk from a lack of transparency in supply chain data. Traditionally, supply chain managers use cumbersome and unreliable auditing to validate supply chain data to substantiate product information and provenance. But errors and fraud in supply chain information remain and threaten the brand reputation of affected products. Supply chain data is no stranger to technological enhancement. Enterprise resource planning systems have expanded the volume of real-time actionable data available. The reliability of that data is, however, still in question from its susceptibility to errors and falsification. Distributed ledger technology, best known as blockchain, offers the promise of greater transparency and reliability of supply chain data. Ultimately, that reduces the risks associated with product claims and provenance based on supply chain data. This paper examines the operation of blockchains and their resistance to falsification by looking at the mechanics of the bitcoin blockchain. The paper explores private blockchain alternatives to the bitcoin blockchain that can facilitate distributed data in a closed supply chain. The paper then describes several supply chain challenges where blockchain technology is being used to improve the reliability and integrity of the underlying supply chain data. Finally, the paper looks to the blockchain regulations that may have an impact on the adoption of blockchain in the supply chain. At the end of the day, substantiating supply chain product claims, minimising counterfeiting and enabling product recall all rely on the traceability and integrity of supply chain information, for which blockchain solutions are well suited.

A New Open-source System for Strategic Freight Logistics Planning: the SYNCHRO-NET Optimization Tools

Abstract Globalization and e-commerce facilities have yielded in the recent years an incredibly huge increment of freight movements. Consequently, the underlying supply chains have become more and more complex to manage for the shipping companies, in terms of costs, distances, times, and environmental sustainability. SYNCHRO-NET, a H2020 European research project, aims to de-stress the international supply chains by fostering cost-effective and greener transportation alternatives. Besides other important actions, the SYNCHRO-NET framework provides an optimization and simulation toolset to support decision-making in freight logistics planning at a strategic level. The synchronized use of different transportation modes and the exploitation of smart steaming strategies for ship movements are the two main aspects considered in this innovative optimization system. In this paper, we present the optimization toolset developed, its contribution with respect to the existing platforms, and the experimental set-up implemented to evaluate its performance, usability, and effectiveness. The system is, in fact, currently under evaluation by several world-wide leading companies in freight logistics and transportation. However, the toolset potentialities go beyond the SYNCHRO-NET context, being the system an open-source project that makes use of open data formats and technologies.

An Inventory-Location Modeling Structure for Spare Parts Supply Chain Network Design Problems in Industrial End-User Sites

Traditional literature on Spare Parts Management from industrial end-user sites has not focused on the underlying Supply Chain Network. Thus, this paper analyzes the relevance of integrating Supply Chain Network design with traditional Spare Parts Management. With this aim, the paper proposes a network optimization modeling structure, with simultaneous decisions for warehouse locations and inventory control, allowing to optimize the Spare Parts Supply Chain Network costs.The model is specified for three traditional and commonly used Inventory Control Policies suitable for a variety of Spare Parts (i.e., (s, Q), (R, s, S) and (S-1, S)). The proposed integrated approach yields Spare Parts Supply Chain system performance improvements.