Implications For Supply Chain Management Research Articles

The Impact of Technology and COVID-19 on Mergers and Acquisitions: Implications for Supply Chain Management

This paper explores the issue of MA as it pertains to Supply chain elements such as Enterprise Resource Planning (ERP), the role of technology, and supply chain efficiency. By exploring the issue further, the research seeks to assess the recent trend of increased mergers and acquisitions (MA) and how the activities affect the supply chain management (SCM) role. The results are important in understanding current trends in SCM when it comes to mergers and acquisitions. The discussion covered the role that COVID-19 played in increased trends in MA and technology's role in MA activities and success. The ultimate goal is to understand how technology and COVID-19 impact MA activities and how, in turn, the supply chain management role gets affected.

Spatial Analysis of Middle-Mile Transport for Advanced Air Mobility: A Case Study of Rural North Dakota

Integrating advanced air mobility (AAM) into the logistics of high-value electronic commodities can enhance efficiency and promote sustainability. The objective of this study is to optimize the logistics network for high-value electronics by integrating AAM solutions, specifically using heavy-lift cargo drones for middle-mile transport and using the mostly rural and small urban U.S. state of North Dakota as a case study. The analysis utilized geographic information system (GIS) and spatial optimization models to strategically assign underutilized airports as multimodal freight hubs to facilitate the shift from long-haul trucks to middle-mile air transport. Key findings demonstrate that electronics, because of their high value-to-weight ratio, are ideally suited for air transport. Comparative analysis shows that transport by drones can reduce the average cost per ton by up to 60% compared to traditional trucking. Optimization results indicate that a small number of strategically placed logistical hubs can reduce average travel distances by more than 13% for last-mile deliveries. Cost analyses demonstrate the viability of drones for middle-mile transport, especially on lower-volume rural routes, highlighting their efficiency and flexibility. The study emphasizes the importance of utilizing existing infrastructure to optimize the logistics network. By replacing truck traffic with drones, AAM can mitigate road congestion, reduce emissions, and extend infrastructure lifespan. These insights have critical implications for supply chain managers, shippers, urban planners, and policymakers, providing a decision support system and a roadmap for integrating AAM into logistics strategies.

Research on the Game Model of Green Technology Investment in a Two-Echelon Manufacturing Supply Chain Under Carbon Tax Regulation

Using a Stackelberg game model, this research examines the impact of government-imposed carbon taxes on the sustainability of a two-echelon supply chain. The analysis focuses on the interactions between upstream suppliers and downstream manufacturers, taking into account how manufacturers’ carbon emissions influence market demand, as well as how sustainability levels and price affect this demand. The results show that a centralized system has a lesser potential for total profit development in the supply chain than a decentralized system. To encourage investment in green technologies throughout the supply chain, this paper proposes two coordination mechanisms: a green subsidy and a two-part tariff contract. Numerical study reveals that a win–win scenario for the supply chain requires suppliers to share part of the costs. Furthermore, under a two-part tariff contract, successfully managing fixed costs can result in total profit levels comparable to those in a centralized system. The research also makes strategy recommendations, such as differentiating carbon levies, improving supply chain coordination, and assessing fixed costs. These aim to provide theoretical and practical implications for supply chain management in order to assist businesses and policymakers in effectively responding to the problems of climate change.

Competing buyers’ investment and ordering strategies under supply disruption

Supply chain disruptions can be costly and disruptive, and reducing supplier uncertainty through investments can be an effective strategy for mitigating these risks. In this study, we explore ordering and investment strategies in a downstream competitive environment, considering supply uncertainty. We consider two buyers ordering from a single supplier and competing in a Cournot market. Buyers must balance investment benefits against costs when making investment decisions. We find that without downstream competition, a relatively low investment proportion can yield a “win-win” outcome. Under downstream competition, an increased number of investors does not necessarily lead to higher supplier reliability. When both buyers invest at a high ratio, the significant decline in order quantities may results in lower supplier reliability. When there is only one investing buyer in the market, even though the competitor may benefit from spillover reliability enhancement — free-riding, the buyer may also be willing to provide an investment subsidy to improve the supplier’s reliability. When both buyers invest at a moderate ratio, downstream competition may benefit all supply chain members. Moreover, increasing wholesale price differentiation and endogenous investment ratios can effectively reduce free-riding behavior of the non-investing buyer. These findings have practical implications for supply chain managers aiming to reduce supply risks and allocate investment resources efficiently.

AI-enhanced inventory and demand forecasting: Using AI to optimize inventory management and predict customer demand

The advent of artificial intelligence (AI) has ushered in a new era of efficiency and accuracy across various industries, with inventory management and demand forecasting being at the forefront of these advancements. Traditional inventory management techniques, often reliant on historical data and simple statistical models, fall short in addressing the dynamic and complex nature of contemporary markets (Chopra & Meindl, 2016). AI, with its advanced algorithms and machine learning capabilities, offers a transformative approach to these critical business functions. This paper explores the integration of AI technologies in optimizing inventory management and predicting customer demand. AI-enhanced inventory management involves the application of various AI technologies such as machine learning, natural language processing (NLP), computer vision, and robotics process automation (RPA) (Ivanov et al., 2017). Machine learning algorithms analyze vast amounts of historical data to identify patterns and trends, enabling more accurate predictions and adjustments in inventory levels. NLP processes unstructured data from sources like social media and customer reviews to provide deeper insights into market trends and customer preferences (Cambria & White, 2014). Computer vision technologies assist in real-time monitoring of inventory levels and identifying discrepancies through visual data, while RPA automates repetitive tasks like order processing and inventory tracking, thereby reducing human error and increasing efficiency (Aguirre & Rodriguez, 2017). This paper highlights significant improvements in forecast accuracy and inventory turnover rates achieved through AI implementation and discusses future implications for supply chain management.

Research on the Application of Blockchain Technology in Global Supply Chain Information Sharing — Enhancing Transparency and Collaboration

The globalization of trade and commerce has introduced complexities in supply chain management (SCM), necessitating effective information sharing for enhanced transparency and collaboration. Traditional SCM systems, characterized by centralized databases and intermediaries, often lead to inefficiencies and information silos. This paper explores the application of blockchain technology in SCM, highlighting its potential to address these challenges by providing a decentralized, immutable, and secure platform for information sharing. Through a comprehensive review of literature and analysis of case studies in the food, pharmaceutical, and retail industries, this study demonstrates how blockchain enhances transparency, traceability, and efficiency. The findings indicate significant improvements in key performance metrics such as transparency, cost reduction, and risk management post-blockchain implementation. However, the study also identifies several challenges, including scalability, integration with existing systems, and regulatory compliance. The practical implications for supply chain managers and businesses are discussed, emphasizing the need for collaborative efforts and supportive regulatory frameworks to fully realize the benefits of blockchain technology in SCM.

How Can Vietnamese Companies Benefit from Management Accounting Systems and Supply Chain Integration Under Business Environment Uncertainty?

We develop and test a moderated mediation model to explain how management accounting systems impact supply chain integration and firm performance, and how perceived environmental uncertainty influences these relationships. Partial least squares structural equation modeling was used to analyze the survey data from 158 supply chain firms in Vietnam. Results indicate that the use of management accounting systems increases the extent of supply chain integration, which in turn enhances firm performance. Furthermore, perceived environmental uncertainty moderates the positive associations between the use of management accounting systems, supply chain integration, and firm performance. This study makes several contributions to existing literature. First, it elucidates the role of supply chain integration in promoting partner integration in the Vietnamese context. Second, it reveals the performance implications of the interaction between management accounting systems and supply chain integration. Our findings have important implications for supply chain management because they emphasize the need to develop effective management accounting systems and supply chain integration strategies in the context of environmental uncertainty.

Industry 4.0 Innovation: A Systematic Literature Review on the Role of Blockchain Technology in Creating Smart and Sustainable Manufacturing Facilities

Industry 4.0 has revolutionized manufacturing processes and facilities through the creation of smart and sustainable production facilities. Blockchain technology (BCT) has emerged as an invaluable asset within Industrial Revolution 4.0 (IR4.0), offering increased transparency, security, and traceability across supply chains. This systematic literature review explores the role of BCT in creating smart and sustainable manufacturing facilities, while exploring its implications for supply chain management (SCM). Through a detailed examination of 82 research articles, this review highlights three areas where BCT can have a dramatic effect on smart and sustainable manufacturing: firstly, BCT can promote green production methods by supporting efficient resource use, waste reduction strategies and eco-friendly production methods; and secondly, it allows companies to implement smart and eco-friendly manufacturing practices through BCT solutions. BCT promotes intelligent manufacturing systems by facilitating real-time data sharing, predictive maintenance, and automated decision-making. Furthermore, BCT strengthens SCM by increasing visibility, traceability, and collaboration between partners of SC operations. The review also highlights the potential limitations of BCT, such as scalability challenges and the need for standardized protocols. Future research should focus on addressing these limitations and further exploring the potential of BCT in IR4.0.

Heuristic approach for optimising reliable supply chain network using drones in last-mile delivery under uncertainty

ABSTRACT In addressing the challenges of last-mile logistics, the reliability of the supply chain network becomes paramount. These challenges are intensified due to drone performance limitations and various uncertainties in supply chain operations. While recent literature recognises the potential of drones for last-mile delivery, it falls short in effectively considering these uncertainties in drone-enabled supply chain models. Our research addresses this gap with two major contributions: first, a novel stochastic mixed-integer programming model is developed to construct a feasible delivery network, including warehouses and recharging stations, enhancing both coverage and reliability. Second, a modification in the genetic algorithm by considering each scenario independently improves computational efficiency, outperforming commercial software by an average of 40% and up to 55%. Empirical findings reveal that strategic investments in system hardening can yield substantial improvements in reliability. Despite the absence of real-world stochastic parameters as a limitation, this research pioneers the design of reliable networks under uncertainties and extends drone coverage through strategic charging stations. This work sets a significant milestone for future optimization in drone logistics, offering practical implications for supply chain managers considering drone adoption.

Unveiling the Influence: Exploring the Impact of Interrelationships among E-Commerce Supply Chain Members on Supply Chain Sustainability

This study explores the critical role of interrelationships among e-commerce supply chain members in shaping sustainability outcomes. It adopts a qualitative approach, drawing from Sustainable Supply Chain Management (SSCM) and Resource Dependency Theory (RDT) to gain a deeper understanding of sustainability within e-commerce supply chains. In a comprehensive investigation involving 35 key stakeholders from prominent e-commerce companies in China, such as Amazon, Alibaba, Suning.com, Shein, and Wayfair, this research examines how robust interrelationships, characterized by collaboration, knowledge exchange, trust-building, and joint problem-solving, facilitate efficient resource utilization, innovation, waste reduction, and enhanced social and environmental responsibility throughout the supply chain. The findings underline the practical implications for supply chain managers and practitioners, emphasizing the need to foster these robust interrelationships through effective communication, trust-building, collaboration, and information sharing as tangible strategies to elevate sustainability performance and gain a competitive edge in the dynamic e-commerce landscape. The insights are based on structured, in-depth interviews conducted in English with participants familiar with the language, lasting approximately 35 to 55 min.

Supply chain from start to finish: the implications of supply chain management for entrepreneurs

Supply chain from start to finish: the implications of supply chain management for entrepreneurs

What drives the dissemination of CSR practices in global value chains? An institutional and psychological perspective

This study investigates how supply chain professionals in buying and supplying firms are motivated to engage in corporate social responsibility (CSR) practices within global value chains (GVCs). Based on the multiple needs theory of justice, social exchange theory, and the institution-based view, we develop hypotheses and test them against data collected from 201 supply chain professionals. We find that buyers’ intentions to cascade CSR practices to suppliers is particularly driven by instrumental and relational motives. In contrast, suppliers’ intentions to engage in CSR is largely determined by moral outrage. Moreover, significant effects are revealed for the institutional conditions on buyers’ CSR cascading intentions and on suppliers’ CSR implementation intentions. The misalignment between buyers’ and suppliers’ motives to engage in CSR activities is discussed as a major challenge of cascading CSR practices in GVCs. The study contributes to the international business literature by combining an institutional and psychological examination of individuals’ motivation to engage in CSR along GVCs. Moreover, we derive practical implications for supply chain managers.

The Impacts of Supply Chain Capabilities, Visibility, Resilience on Supply Chain Performance and Firm Performance

This study explores the significance of two determinants: Supply Chain Capabilities and Supply Chain Visibility, in the intricate interplay among Supply Chain Resilience, Supply Chain Performance, and Firm Performance. A dataset comprising 221 participants from Vietnamese garment manufacturing firms was gathered and subjected to analysis using the PLS-SEM approach, revealing insights into the modeled complex relationships. The research findings reveal that visibility significantly influences supply chain resilience; while the hypotheses of a positive impact of supply chain visibility and supply chain resilience on firm performance have been rejected. Interestingly, these findings underscore the significant influence of indirect relationships mediated by factors, such as supply chain resilience and supply chain performance. Hence, this study bridges a gap in the existing body of literature and offers practical implications for supply chain management, particularly concerning performance measurement challenges in this sector. The article suggests that the Vietnamese garment supply chain could enhance supply chain and firm performance by focusing on supply chain capabilities and visibility.

Trends in weather-related marine cargo insurance claims: A South African perspective

Background: Marine cargo insurance covers the loss or damage to goods while in transit. It is an important supply chain risk management tool for organisations involved in international trade, especially in regions where cargo insurance penetration is low, and protection gaps are high. However, marine cargo insurance faces new challenges because of increasing frequency and severity of extreme weather events. This study focuses on the case of South Africa: a developing country with a strategic role in connecting Africa with the global market.Objectives: The research analyses the trends, differences, and seasonality of weather-related marine cargo insurance claims in South Africa from 2013 to 2022.Method: Statistical and general claims analysis was performed on a master dataset of 17 727 claims to answer the three research questions related to the research objectives.Results: The results show that weather-related marine cargo insurance claims have been increasing over the past decade, creating challenges and disruptions to the supply chain network in South Africa. Furthermore, this research shows that weather-related claims have higher average values and follow a seasonal pattern compared with non-weather-related events on supply chains in South Africa.Conclusion: This research reveals the growing impact of weather-related events in South Africa.Contribution: It provides practical and theoretical implications for supply chain managers and insurers to manage weather-related risks more effectively and proactively contributes to the literature by offering empirical insights from a developing country perspective, and provides considerations for future work.

Blockchain technology adaptation and organizational inertia: moderating role between knowledge management processes and supply chain resilience

PurposeSupply chain resilience and knowledge management (KM) processes have received increasing attention from researchers and practitioners. Nevertheless, previous studies often treat the two streams of literature independently. Drawing on the knowledge-based theory, this study aims to reconcile these two different streams of literature and examine how and when KM processes influence supply chain resilience.Design/methodology/approachThis research develops a conceptual model to test a sample of data from 203 Chinese manufacturing firms using a structural equation modeling method. Specifically, the current study empirically examines how KM processes affect different forms of supply chain resilience (supply chain readiness, responsiveness and recovery) and examines the moderating effect of blockchain technology adaptation and organizational inertia on the relationship between KM processes and supply chain resilience.FindingsThe findings show that KM processes positively affect three dimensions of supply chain resilience, i.e., supply chain readiness, responsiveness and recovery. Besides, the study reveals that blockchain technology adoption positively moderates the relationships between KM processes and supply chain resilience, whereas organizational inertia negatively moderates these above relationships.Originality/valueThis research linked the two research areas of supply chain resilience and KM processes, further bridging the gap in the research exploration of KM in the supply chain field. Next, this study contributes to supply chain resilience research by investigating how KM systems positively impact supply chain readiness, responsiveness and recovery. In addition, this study found a moderating effect of blockchain technology adaption and organizational inertia on the relationship between KM processes and supply chain resilience. These findings provide a reference for Chinese manufacturing firms to strengthen supply chain resilience, achieve secure supply chain operations and gain a competitive advantage in the supply chain. This studys’findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

Implications of Supply Chain Management and Total Quality Management Implementation for Operational Performance

Implications of Supply Chain Management and Total Quality Management Implementation for Operational Performance

Different types of innovations and dynamic capabilities in achieving timely responsiveness: Some implications for supply chain management

Timely responsiveness (TR) enables firms to outperform their competitors by responding rapidly to market changes and seizing opportunities promptly. However, how firms can achieve TR remains poorly understood. This study investigates the ways in which firms can improve TR and draws out the implications of these in managing supply chains. Specifically, this study examines the relationships between dynamic capabilities (DCs), namely, sensing and reconfiguring capabilities, different types of innovations, and TR. The findings show that the development of product, process, and management innovations improves TR. Sensing and reconfiguring capabilities are identified as core DCs that drive the development of different types of innovations.

Impacts of IT capability and supply chain collaboration on supply chain resilience: empirical evidence from China in COVID-19 pandemic

PurposeBuilding supply chain resilience is increasingly recognized as an effective strategy to deal with supply chain challenges, risks and disruptions. Nevertheless, it remains unclear how to build supply chain resilience and whether supply chain resilience could achieve a competitive advantage.Design/methodology/approachBy analyzing the data collected from 216 firms in China, the current study empirically examines how information technology (IT) capability and supply chain collaboration affect different forms of supply chain resilience (external resilience and internal resilience) and examines the performance implications of these two forms of supply chain resilience.FindingsResults show that IT capability is positively related to external resilience, whereas supply chain collaboration is positively related to internal resilience. The combination of IT capability and supply chain collaboration is positively related to external resilience. In addition, internal resilience is positively related to firm performance.Research limitations/implicationsThis study used only cross-sectional data from China for hypothesis testing. Future studies could utilise longitudinal data and research other countries/regions.Practical implicationsThe findings systematically assess how IT capability and supply chain collaboration contribute to supply chain resilience and firm performance. The results provide a benchmark of supply chain resilience improvement that can be expected from IT capability and supply chain collaboration.Originality/valueThe study findings advance the understanding of supply chain resilience and provide practical implications for supply chain managers.

A scenario-based experimental study of buyer supplier relationship commitment in the context of a psychological contract breach: Implications for supply chain management

Mutually beneficial long-term relationships between supply chain partners are the key to supply chain performance. However, these relationships may sometimes be undermined due to unforeseen events (e.g., supply chain disruptions). This study aims to originally examine the buyer-supplier relationship (BSR) commitment if the buyer's psychological contract is breached by the supplier. The study originally examines the effect of supplier-induced disruptions over a new product development project on the buyer's relationship commitment. It also evaluates the impact of the repair strategies employed by the supplier on the commitment to repair. These relationships are examined on two levels. First is the case where the buyer's focal manager has a cooperative or confrontational relationship with the supplier's focal manager. Second is the case where a prior (i.e., pre-disruption) relationship between the buyer and the supplier was collaborative or adversarial. We studied the research model using experimental methods on a sample of 204 supply chain managers from Pakistani industries. The results of this study show that the initial interpersonal and interorganizational relationships affected the response of the buyer when its psychological contract with the supplier was breached. The repair strategy of financial compensation is shown to have a considerable influence on repairing the commitment level of the buyer.

Continuous manufacturing technologies in upstream pharmaceutical supply chains: Combining engineering and managerial criteria

AbstractThe COVID‐19 pandemic exposed vulnerabilities in upstream pharmaceutical supply chains (PSC). One is that the global supply of active pharmaceutical ingredients (APIs) is overly dependent on few locations and large‐scale batch manufacturing. Regulators hope to enable more dependable location decisions and improved processing quality with the adoption of advanced technologies such as process intensification through continuous manufacturing (CM). Conceptual work suggests that the benefits of shifting from batch to CM accrue end‐to‐end across the PSC. Yet detailed quantitative information about CM is limited at an early stage of evaluation, and too specialised to inform managerial decisions about PSC reconfiguration. Supply chain and engineering criteria are rarely combined in the early‐stage evaluation of alternative CM technologies. Extant CM research typically overlooks implications for supply chain managers. To address the current gap, this article evaluates, at an early stage of adoption, alternative CM reactor technologies for the synthesis of APIs in selected therapeutic areas. With evidence from secondary data, relevant technologies and criteria are identified, and their relative importance is evaluated in a semi‐quantitative fashion following analytical hierarchy process (AHP) principles, ensuring that findings are intelligible to both engineers and managers. The proposed empirical work enriches previous conceptual frameworks predicated on volume‐variety considerations. Specifically, findings suggest that, all things considered, microreactor technologies outperform alternatives. However, PSC managerial considerations introduce nuances in specific therapeutic areas, for example, antivirals where a tension between complex chemistry and the need for flexibility in unit operations may favour batch manufacturing. For analgesics the need to exploit the existing manufacturing base whilst addressing inventory reduction favours technologies that incorporate elements of batch and CM. The proposed analysis is in line with real‐world decisions that global medicines manufacturers are increasingly facing, as governments seek to develop local health countermeasures to the COVID‐19 pandemic in the absence of detailed information.