Making Scope 3 emissions management count: enhancing shared responsibility in the supply chain

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.

PurposeThe purpose of this paper is to discuss complexity assessment in supply chains, to describe a methodology for measuring supply chain complexity in distributive trade and to illustrate the measurement of supply chain complexity and mechanisms to cope with supply chain complexity in distributive trade.Design/methodology/approachThe paper discusses literature on measuring supply chain complexity and uses five case studies among wholesale companies to illustrate a methodology to measure supply chain complexity and to discuss strategies to cope with supply chain complexity.FindingsThe study confirms the multifaceted nature of supply chain complexity. The paper identifies eight drivers of supply chain complexity and uses these to illustrate the measurement of supply chain complexity in a wholesale environment. The paper identifies six strategies used by wholesalers for coping with supply chain complexity and identifies interrelations between supply chain complexity drivers and these strategies.Research limitations/implicationsThe research is based on case studies in wholesale companies; future research may include survey research, including other sectors to analyze industry differences but may also focus on other parts of the supply chain.Practical implicationsThe study provides insights into how to identify and measure complexity in a supply chain and what can be done to manage supply chain complexity.Originality/valueThe measurement approach is new to supply chain management and is based on multiple drivers of supply chain complexity. The research is focused on wholesalers, which is a segment that has received limited academic attention in supply chain research to date.

ABSTRACTEcological and economic crises increasingly affect the long‐term resilience of the food supply chain. This qualitative study draws on semistructured interviews and public evidence to analyse the perspectives of British supply chain actors. Asking which pathways towards food system resilience arise and which forms of social and environmental governance they require, the aim is to elucidate power relations in the fresh produce supply chain and clarify governance requirements and responsibilities to transform food systems towards resilience and sustainability. The stakeholders addressed responsibilities for a sustainable and resilient food system, including effective policies and appropriate pricing, to ensure both high social and environmental standards in the supply chain and widespread affordability of healthy and sustainable foods. Findings emphasise the importance of policy to resolve conflicts of interest over low or high prices and the adoption of hybrid governance and shared responsibility, while also accounting for actors' different spheres of influence.

Postponement has been identified as an important instrument for supply chain management. Complexity is a factor that has wide influence on the performance of supply chains. Although there is not a simple relationship between complexity and performance, performance can be improved through managing or reducing complexity level in many situations. Postponement often brings about changes in the configuration of a supply chain and hence has an impact on supply chain complexity. In this study, we present a tentative classification of supply chain complexity and try to establish a relationship between different supply chain complexity dimensions and postponement applications based existing studies. We then present two cases where postponement is applied in the upstream stages of supply chains in contrast to the mid- and down stream postponement applications found in existing studies. By analysing the manner in which these postponement applications influence complexity and impact on supply chain performance, we try to enrich the concept of postponement on one hand and expand the evidence of the relationship between postponement and complexity. We also try to clarify the relationship between JIT and upstream postponement.

Purpose This study examines the relationship between operational supply chain transparency (OSCT) and sustainable supply chains using business regulatory compliance (BRC) as a moderator and supply chain complexity (SCC) as the mediator in manufacturing firms in Greater Kumasi, Ashanti region. Design/methodology/approach The survey used 200 of 223 manufacturing firms from Greater Kumasi. Both direct, mediating and moderating effects among the research variables were analyzed using partial least squares structural equation modeling and SPSS. Findings The findings indicate that BRC and OSCT significantly enhance sustainable supply chains. OSCT has a direct effect on the sustainable supply chain. Again, SCC did not support a sustainable supply chain, and SCC does not mediate this relationship either. However, BRC strengthens the effect of OSCT on sustainable supply chains. Practical implications This study gives manufacturing firm managers evidence-backed guidance on matching their operations with regulatory standards. The study also provides insights on how to use transparency and compliance together to boost sustainability results, which helps inform decisions in complex supply chain settings. Originality/value By integrating BRC and OSCT into a single model, this study breaks new ground in understanding how these variables jointly affect sustainable supply chains. The study offers a fresh viewpoint by exploring the ways these two elements work together, an area that has been largely overlooked by scholars.

There has been a paradigm shift in the functioning of global supply chains, particularly in thepost-pandemic era. This shift is characterized by the convergence of technology. deployment, geopolitical dynamics, and an increased awareness of environmental and social responsibilities. These transformative changes compel businesses to navigate a complex. web of challenges while simultaneously creating many opportunities for global supply chains. This includes delegating responsibilities to the supplier side, empowering suppliers, and promoting digital supply chain networks. Ongoing trade tensions between major economies, such as the United States and China, have resulted in fluctuations in global logistics patterns. Alterations in tariffs and trade agreements impact shipping routes, transportation costs, and the overall flow of goods. Consequently, supply chains must focus on end-to-end supply chains originating from low-cost sources to withstand unforeseen events like black swan occurrences and geopolitical and trade wars. The pandemic has underscored the critical importance of building resilient supply chains. Many firms reevaluate their supply chain strategies, emphasizing diversification to mitigate risk. This involves reassessing suppliers, exploring alternative sourcing options, and increasing safety stock levels. Geopolitical uncertainties and disruptions have prompted reconsidering global sourcing strategies, with reshoring and nearshoring gaining prominence. Companies seek to mitigate risks associated with distant and complex supply chains by bringing production closer to target markets, enhancing responsiveness, reducing lead times, and fortifying supply chain resilience amid uncertain business conditions. From the traditional supply chain model, there is a continuous effort to integrate information technology to transform value streams and increase processes' transparency. Blockchain is playing a significant role, from tracking the provenance of raw materials to reducing transaction fraud. This technology fosters a new level of trust among supply chain partners, safeguarding against potential disruptions and reinforcing the integrity of the entire supply chain ecosystem. These rapid transformations amid uncertain conditions have prompted a reevaluation of supply chain resiliency with a greater focus on risk mitigation strategies. In global logistics, owning ships and manufacturing/leasing containers for extended periods have become the guiding principles. The recent Brexit has also impacted global transport's European and UK legs. The European industry is grappling with significant shortages of resources, including drivers and trained supply chain manpower, affecting last-mile delivery and land transportation in numerous geographies. The growth of e-commerce has significantly influenced supply chains, leading to innovations in last-mile delivery solutions. Companies are investing in warehouse automation, drone deliveries, and other technologies to meet the demands of the rapidly expanding e-commerce market. x Furthermore, a seismic shift toward sustainability reshapes the global supply chain landscape. Businesses recognize the imperative to address environmental, social, and governance (ESG) concerns. Initiatives to reduce carbon footprints, optimize transportation routes, and embrace ethical sourcing practices are becoming integral components of supply chain strategies. Sustainability is no longer merely a corporate buzzword but a critical factor in ensuring long-term viability and meeting the expectations of socially conscious consumers. Overall, global supply chains are undergoing significant transformation driven by technological innovation, environmental consciousness, and a commitment to building resilient networks. Businesses that embrace these trends are not only adapting to the challenges of today but are also positioning themselves to thrive in the dynamic landscape of tomorrow. The key to success is navigating change, leveraging technology, and building sustainable businesses.

Pharmaceutical supply chains experience delays and disruptions affecting access to essential medicines across regions. These challenges are caused by weak forecasting, long procurement cycles, fragmented distribution, poor quality data and shortage of skilled workers. These factors are managed with both forward looking and response-based approaches. Regular stock review, good communication, fast purchasing and close supervision help limit shortages. Response-based strategies like keeping extra stock may instead prove unsustainable over time. Supply chain structure can be adapted to product risk and working with suppliers can improve the ability to manage uncertainty. Flexible systems, real time information and robust internal processes allow quick responses and prevent major supply failures. Similar risks are faced by pharmaceutical firms worldwide when setting up supply networks. Other common problems are product faults, sudden halts in production, slow order handling, late shipments and poor matching of supply and demand. Rather than taking these risks, firms plan to do production in-house near key markets, work with local partners or outsource non-core work to distant locations. Some have gone away from far-off suppliers and are using nearshore or in-house models. Moving production closer reduces delay/improves control. For non-core products, outsourcing to offshore locations is still common but some companies set up offshore centres to manage operations directly. Changing supply chains to cope with delays and risks requires better forecasting tools, better data systems and trained people. Firms work with partners, rely on digital systems and have the right setup for various products. Global medicine supply chains must respond quickly to changes while reducing costs and maintaining product flow constant. Global health needs require clear strategy, simple design and fast action. Study survey was conducted among 218 people from supply chain department of pharmaceutical industry to know the factors that show the complexity and challenges of supply chain in pharmaceutical industry and found that Regulatory Compliance, Cold chain, Long Supply Chains, and Product shelf life are the factors that show the complexity and challenges of supply chain in pharmaceutical industry.

With business environment becoming increasingly turbulent and competitive, firms are encouraged to enhance the agility capability across the supply chain in response. However, when it comes to supply chain agility, most studies only take supply chain flexibility into account. In fact, supply chain visibility is also an important indicator for supply chain agility. Furthermore, supply chain complexity is increased by more and more factors, but the influence of supply chain complexity on the relationship between ICT usage and supply chain agility has gained little attention in academic literature. This paper hypothesizes that supply chain complexity acts as a moderator between ICT usage and supply chain agility.

PurposeEasily employable quantitative supply chain complexity (SCC) measures considering the significant dimensions of complexity as well as the drivers that represent those dimensions are limited in the literature. The purpose of this paper is to propose an integrated interpretive structural modeling (ISM) and a graph-theoretic approach to quantify SCC by a single numerical index considering the interdependence and the inheritance of the SCC drivers.Design/methodology/approachIn total, 18 SCC drivers identified from the literature are clustered according to the significant dimensions of complexity. The interdependencies established through ISM and inheritance values of SCC drivers are mapped into a Variable Permanent Matrix (VPM). The permanent function of this VPM is then computed and the resulting single numerical index is the measure of SCC.FindingsA scale is proposed by computing the minimum and maximum threshold values of SCC with the help of expert opinions of the Indian automotive industry. The complexity of commercial and passenger vehicle sectors within the automotive industry is measured and compared using the proposed scale. From the results, it is identified that the number of suppliers, increase in spare-parts due to shortened product life-cycle and demand uncertainties increase the SCC of the passenger vehicle sector, while number of parts, products and processes, variety of products and process and unreliability of suppliers increase the complexity of the commercial vehicle sector. The result indicates that various SCC drivers have a different impact on determining the SCC level of these two sectors.Originality/valueThe authors propose an integrated method that can be readily applied to measure and quantify SCC considering the significant dimensions of complexity as well as the interdependence and the inheritance of the SCC drivers that contribute to those dimensions. This index further helps to compare the complexity of the supply chain which varies between industries.

The emergence of artificial intelligence (AI) and its related capabilities has led industries to rethink the existing practices of conventional supply chain management and data analysis. Machine learning (ML), Deep Learning (DL) and their unique ability to predict future data and classify data have led to important research in the supply chain (SC) domain, particularly in identifying and prioritizing supply chain risks. This paper proposes several DL methodologies to exploit the benefit of DL, particularly to identify whether any product will be delivered late due to any unforeseen reason in a complex SC system. Four different DL architectures (Simple-LSTM, Deep-LSTM, 1D-CNN, and TCN-1DSPCNN models) are proposed to extract features, while six variant classifiers: Softmax, random trees (RT), random forest (RF), K-nearest neighbor (KNN), artificial neural network (ANN), and support vector machine (SVM), were used to classify delay or non-delay information. By seamlessly capturing intricate temporal dependencies, these DL models enhance accuracy in robustly identifying supply chain late orders. Leveraging their hierarchical feature learning, these proposed DL models excel in recognizing subtle patterns and correlations, making them ideal for classifying late orders within the supply chain. Their parallel processing prowess facilitates real-time decision support, allowing organizations to address potential delays and allocate resources effectively and proactively. Five-fold cross-validation is presented to avoid over-fitting and to prove the efficiency of the proposed DL models. The total accuracies of the six ML classifiers are 74.03, 75.81, 93.35, 87.72, 93.59, and 95.10, respectively, while the maximum accuracies obtained from four proposed DL methodologies obtained an accuracy of 97.6, 98.63, 100, 100% respectively using the SVM classifier for predicting late orders based on five-fold cross-validation.

Staying Healthy to Avoid Illness

The interrelationships between system components are critical to improving the performance of a complex supply chain system. Thus, any improvement or development can be carried out systemically and comprehensively. The complexity of coordination grows as the number of echelons in a supply chain increases. In practice, coordination becomes more difficult to implement in a supply chain with more echelons. Through demand information sharing, this research attempts to figure out how coordination can have implications for complex multi-echelon supply chains with a modeling approach. The Aggregate Andesite Stone Supply Chain is used as an empirical model with four echelons. Changes in dimensions and values per ton of product in each echelon displacement add complexity. Total holding cost is not the only consideration. The timely completion of projects downstream is also a priority. So the system's behavior that runs and changes over time also needs to be observed. To accommodate this complexity, a system dynamics modeling approach is used. This modeling technique could capture fluctuations in volatile conditions that change in time sequences. The pattern of model behavior shows that demand information sharing in the andesite aggregate supply chain is faint, and the "bullwhip effect" occurs. The demand information sharing can eliminate this effect, reduce up to 73.5 % of total supply chain holding costs, and increase the percentage of project completion on time downstream of the supply chain. These results provide a scientific and practical understanding that although there are many obstacles, demand information sharing can significantly improve performance in multi-echelon complex supply chains and be worthwhile applied

The following chapter will elaborate on complexity in supply chains and the implications on supply chain design. It investigates the specific requirements of supply chain processes in terms of flexibility versus standardization, evaluating the feasibility of designing, customizing, assessing, and improving logistics processes within a framework provided by process reference models. Mass customization and, in particular, the configuration approach developed by Winter for financial services will be discussed for their applicability for reducing complexity in a process environment. Process reference frameworks will be used as elements of an “open variant process model”. The Supply Chain Operations Reference (SCOR) model defined by the Supply Chain Council as the major cross-industry standard for supply chain management will be discussed for its usefulness and shortcomings in “process mass customization”, with a focus on systems implementation.

PurposeThis study explores how factors arising from supply chain (SC) network and complexity work together in supply chain learning (SCL) behavior.Design/methodology/approachFuzzy set qualitative comparative analysis, which is an emerging configurational analysis method, was adopted to examine the complex combination of five influencing factors. The data were collected using a two-stage survey. First, the authors selected seven typical firms with an awareness of SCL. Second, questionnaires were sent to the partners of the seven selected firms, and 156 valid questionnaires were obtained from 76 firms.FindingsDrawing on emergent insights from the initiative, the authors find that multiple configurations of SC network and complexity lead to high SCL. Specifically, weak ties are necessary conditions of such learning, while strong ties are also conducive to this. Moreover, a moderate SC complexity is conducive to SCL.Practical implicationsThis study enriches the understanding of SCL and provides new insights for SC management practitioners to take measures to improve it.Originality/valueThis study addresses the lack of in-depth understanding of the antecedent conditions of SCL in the literature. It establishes an integrated and comprehensive theoretical framework of such learning based on contingency theory. Additionally, this study incorporates ambidextrous SCL (i.e. creation capability and dispersion capacity). An overall prototype of SCL capability is proposed on SC network and complexity theory.

Energy footprint controlled by urban demands: How much does supply chain complexity contribute?