The purpose of this research is to explore phenomena within the experience of consumer packaged goods (CPG) account representatives in customer-facing roles by investigating the impact of supply chain training, experience, and skills on sales role effectiveness in CPG companies. Findings suggest that skills needed for sales include technical competency, excellent communication skills, and the knowledge to keep commitments. Supply chain understanding within their industry impacts these identified skills by removing confusion, improving identification with their company, realistically aligning customer expectations, and building confidence.

Abstract

The paper examines whether common ownership along supply chains (i.e., vertical shareholding) is associated with better firm performance during supply chain shock. We find that supplier-customer dyads with vertical shareholding report higher combined monthly returns since the outbreak of the COVID-19 pandemic. The dedicated common investors have the most positive effects, followed by the common quasi-indexers.

Introduction

As overlapping institutional ownership becomes more prevalent, it has been heatedly debated whether it plays a positive role in market competition and corporate governance (e.g., Azar et al., 2018; Edmans et al., 2019; Schmalz 2021; Koch et al., 2021; Bebchuk and Hirst 2022). Most studies focus on its effects on industry rivals (i.e., horizontal shareholding). Compared to industry rivals, firms along the supply chain network have more collaborative and interdependent relationships. Hence, overlapping institutional ownership of supplier-customer dyads (i.e., vertical shareholding)1 may have distinct effects, especially in response to disruptive events that could jeopardize collaboration.

We utilize the COVID-19 pandemic as an exogenous supply chain shock to investigate whether vertical shareholding is associated with stock performance. Supply chain disruptions can be devastating to both upstream and downstream firms (e.g., Carvalho et al., 2021) and significantly exacerbate interfirm conflicts as opportunism and information asymmetry increase. Economic theories predict that cross-ownership can address inherent interfirm conflicts, such as the holdup problem (e.g., Klein et al., 1978; Grossman and Hart 1986). Institutional investors simultaneously holding shares of economically connected firms have incentives to prevent either contracting party from making a move that will hurt the value of their portfolios. Hence, they can influence the management of both upstream and downstream firms and thereby encourage information sharing and balance the bargaining power in supply chain contract renegotiations. For example, institutional investors can influence the supplier firms to prioritize the co-owned customer firms during supply shortages (Sheffi 2020).

Conclusion

We show that supply chain dyads with vertical shareholding have significantly better aggregate stock market performance since the COVID-19 pandemic. The effects vary with the incentives of common institutional shareholders. To our knowledge, we are one of the first empirical studies to show that vertical shareholding mitigates negative consequences of supply chain shocks. Our evidence sheds light on the debates over the roles common institutional investors play in interfirm relationships and supply chain risk management.

Abstract

Supply chain resilience and the ripple effect have been widely studied, mostly focusing on material flow-related practices. The financial flow adjustments to cope with supply chain disruptions have received much less attention. We contribute to the literature by examining the impact of adapting payment terms during and after disruptions. In particular, we perform a discrete event simulation analysis in anyLogistix for a complex supply chain network to investigate the impact of adjusting payment terms on supply chain cash flows. Our results suggest that collaboratively adjusting payment terms is an effective strategy for coping with disruptions. In contrast, ad hoc adjustments and immediate returns to pre-disruption payment schemes do not yield visible improvements. Positive effects on cash and loans are observed if an adjustment of payment terms occurs proactively and in a coordinated manner, especially when expediting payments downstream and payment slowing down upstream. The results from our sensitivity analysis on the impact of accelerating/decelerating cash conversion cycles favour shorter cycles when coping with disruptions. We deduce useful managerial insights and reveal some new theoretical tensions related to the impact of payment adjustments on cash flows in supply chains.

Introduction

Supply chain resilience and the ripple effect have been significantly visible research avenues ( Chervenkova and Ivanov, 2023 , Dolgui et al., 2023 , Sawik, 2023 , Ivanov, 2024a , Ivanov, 2024b ). The extant literature offers numerous strategies and practices for the preparedness and recovery of supply chains ( Hosseini et al., 2019 , Ivanov and Dolgui, 2021 , Ivanov et al., 2021 , Gruchmann et al., 2024 ). Most of these strategies and practices are related to material flows – e.g. backup suppliers, risk mitigation inventory, and capacity flexibility ( Lin et al., 2021 , Mitręga and Choi, 2021 , Brusset et al., 2023 , Hägele et al., 2023 , Aldrighetti et al., 2024 ). Some research examined the role of information flows in supply chain resilience, focusing on visibility, digital technology, and cybersecurity ( Ivanov, 2021 , Sawik, 2022 , Dubey et al., 2023 ). However, practices of financial flow adjustments to cope with supply chain disruptions have received much less attention ( Choi et al., 2023 ).

The role of financial flows in supply chain resilience is a distinct but underexplored topic of high practical relevance. Consider an example. In the fall of 2023, Ford’s supply chain experienced a series of disruptions caused by strikes ( Shepardson and White, 2023 ). Assembly plants stopped, leading to significant monetary losses at Ford ($1.7 billion in lost profits and about 100,000 units fewer wholesale vehicle sales from the strike) ( Gomes, 2023 ). Adversely, the ripple effect from the disruptions at the assembly plants could have resulted in setting Tier 2 suppliers at financial risk and danger of bankruptcy because of missing liquidity, higher interest rates, and difficulties to get loans from the banks ( Vicci, 2023 ).

Conclusion

In this study, we departed from the existing research gap about the role of cash flows in supply chain resilience and ripple effect analysis. The extant literature mostly focuses on strategies for preparedness and recovery related to material flows. Practices of financial flow adjustments to cope with supply chain disruptions have received much less attention. However, the practical and academic importance of this topic are unquestionable.

The main contribution of our study to the literature is an examination of the impacts of payment term adaptation during and after disruption responses, along with proposing useful coping strategies based on adjusting deferment periods and the role of coordination in this adaptation. The objective of our analysis was to investigate the impact of adjusting payment terms on supply chain cash flows.

Methodologically, we utilised a discrete event simulation analysis in anyLogistix applied to a complex supply chain network. We performed simulations with nominal (disruption-free) and disruption scenarios considering different response strategies. The computational results of this study have been translated into useful managerial insights on the importance of payment term adjustment during disruptions to avoid bankruptcies in the supply chain and improve its resilience.

Abstract

This research contributes to understanding the spillover effect of customer digital transformation along the supply chain. We take a supply chain relationship perspective to explore the influence of customers’ digital transformation on suppliers’ audit fees and find a significant reduction in such fees when customers undergo digital transformation. An economic mechanism analysis reveals that this transformation reduces audit fees by lowering the risks and costs encountered by auditors. This is achieved by mitigating suppliers’ business risks and improving earnings quality. Heterogeneity analysis reveals that the impact of customers’ digital transformation on suppliers’ audit fees is more pronounced when the supply chain is geographically distant, suppliers with more specific investments and with high levels of market competition.

Introduction

Digital transformation involves shifting from a traditional “industrialized” management model to a digital management model ( Verhoef et al., 2021 ). This transition goes beyond simply applying digital technologies to technical aspects of a business and involves a complete restructuring of business models and operational management. Research on the economic consequences of digital transformation emphasizes its potential influence on the quality of corporate disclosures and business risks. For example, digital technologies can improve operational management, promote networked and flattened organizational structures ( Nambisan et al., 2019 ), increase corporate disclosure transparency and the quality of accounting information and enhance communication, production and operational efficiency ( Wu et al., 2021 , Chen et al., 2022a ). By digitally collecting and analyzing data, firms can effectively visualize information, enhance interdepartmental coordination, refine risk control processes, mitigate operational risks and reduce management fraud and decision-making errors that lead to losses, thereby enhancing their market reputation ( Manita et al., 2020 , Zhou and Li, 2023 ). Most studies focus on the direct effects of digital transformation on firms’ risk responses and information transfer capabilities, while its broader effects on the supply chain have not been sufficiently investigated ( Guo et al., 2023 ).

The production operations of suppliers and their financial decisions are influenced and informed by their customers, who therefore play a vital role in the supply chain ( Ak and Patatoukas, 2016 ). Investing in supply chain relationships promotes the economic interdependence of suppliers and customers. The value of such investment depends on customers’ growth prospects, and ensuring the stability of their businesses can lead to higher expected returns from supply chain collaboration. Conversely, if customers face business challenges or go bankrupt, they can jeopardize the value of the assets allocated by suppliers ( Raman and Shahrur, 2008 ). This increases suppliers’ cash flow and operational risk ( Itzkowitz, 2013 ). Thus, suppliers are highly sensitive to the operations and activities of their customers. The risks and information associated with customers can generate a spillover effect in the supply chain, which can then trigger cascading changes in suppliers’ operational risks and influence their investments and financial decisions ( Hertzel et al., 2008 , Jacobson and von Schedvin, 2015 , Chiu et al., 2019 ). By gaining access to more transparent customer information, suppliers can better forecast customer demand, reduce transaction costs, alleviate shortages and losses and enhance production efficiency and inventory management ( Yang et al., 2020 ). Digital transformation can have positive effects on business risks and disclosure quality, in addition to the supply chain, but does the digital transformation of customer businesses also lead to additional spillover effects on suppliers?

Conclusion and discussion

Amid increased economic uncertainty, businesses are increasingly turning to digital transformation to enhance their resilience and optimize their resource allocation. The supply chain is a critical component of business operations that integrates logistics, information flow and capital flow. Microenterprises aiming to gain a competitive advantage can enhance their collaborations within supply chains. We investigated the spillover effect of customer digital transformation on suppliers through assessing its impact on audit fees. This extends research on the economic consequences of digital transformation beyond the boundaries of supply chain relationships. Our empirical findings indicate that customers’ digital transformation can reduce suppliers’ audit fees. Our heterogeneity analysis shows that this effect is more evident when there is a greater geographic distance between suppliers and customers, higher levels of dedicated investment and increased competitiveness in the supplier market. Through the economic mechanism of mitigating supply chain risk and facilitating collaboration and information transfer in supply chains, customers’ digital transformation reduces suppliers’ audit risks and costs, thus leading to lower audit fees.

Based on previous research findings, we offer the following conclusions. First, the implementation of digital transformation by suppliers’ customers can potentially cause a spillover effect across the supply chain, thereby affecting the economic interests and decisions of suppliers. Consequently, when faced with fierce market competition, firms should fully realize the beneficial effects of digital transformation on information transfer efficiency and collaboration within the supply chain. Such transformation should therefore be actively promoted, because through it firms can facilitate a seamless connection of resources, information and knowledge within the supply chain, thus fostering sustainable economic growth through enhanced coordination and cooperation.

Abstract

Semiconductor industry plays a critical role for the global economy. Semiconductor industry provides various necessary technologies such as IoT, AI, modern fabrication technologies and so on to various industries including automotive industry, electronic and communication industry, healthcare industry, construction and building industry, space industry, and so on. However, semiconductor supply chain experiences various supply chain related risks and challenges because of its procedural complexities, global supply chain integrations, government policy and regulations, competitiveness, technological complexities, and so on. Not many studies available which investigated the risk, resilience, and complexities regarding green supply chain adoption by semiconductor industry. In this context, the objective of this study is to examine the risks, resilience, and complexities for managing the green supply chain adoption for higher sustainability in the semiconductor industry. Utilizing the TOE framework (Technology-Organization-Environment) and DCV (Dynamic Capability View), we developed a research model to achieve this purpose. Subsequently, this model was validated through structural equation modelling, involving 356 respondents affiliated with the semiconductor industry. This study highlights that technological risk aspects comprising of technological turbulence and risk, compatibility and complexity, organizational dynamic capabilities, and resilience along with appropriate policy and regulations could help successful adoption of green supply chain management in the semiconductor industry.

Introduction

Semiconductors are vital components of modern electronics. They are used in many diverse products, such as phones and computers to cars and health devices. The devices mentioned above, and others use microchips, memory units, and chipsets. The semiconductor supply chain is a complex network that involves companies that design, make, test, pack, and distribute semiconductors ( Li et al., 2011 ; Oliveira et al., 2019 ). It is the interconnected framework of entities responsible for the various stages in the lifecycle of semiconductor products. The supply chain is complicated, requiring the alignment of several different steps, from getting parts and materials to the delivery to the ultimate customer ( Browning et al., 1995 ; Lai et al., 2022 ). A complicated web of companies, organizations, and people make up the semiconductor supply chain. They work on the creation, production, quality control, packaging, and delivery of semiconductors. The semiconductor supply chain usually has several steps involving complex supply chain flow ( Oliveira et al., 2019 ). It is to note that for ensuring green innovation to establish a healthier society, adoption of green supply chain management (GSCM) is needed for semiconductor industry. Besides, semiconductor chips manufactured in specialized plants also release carbon content gas polluting the atmosphere ( Awa and Ojiabo, 2016 ). To address these issues, it is essential to use the GSCM process that could help to mitigate such environmental hazards. Supply Chain Management (SCM), which supports the success of many leading companies, is a key element of operations management ( Teece, 2014a ; Stekelorum et al., 2021 ; Vrontis et al., 2022a ). The competitive landscape is not shaped by individual organizations, but by supply chains that have multiple workflows across collaborating partners ( Hwang et al., 2016 ). It is worth mentioning that GSCM practices are important for creating ecofriendly products ( Tseng et al., 2019 ). In the supply chain flow followed in the semiconductor industry, it is needed to resist disruptions of flow of supply of semiconductor chips. This needs the supply chain flow to be more resilient to ensure better performance of manufacturing plants of semiconductor chips which necessitates use of GSCM practices ( Li et al., 2011 ). The strategic SCM is a process that involves multiple interactions among various factors such as strategic sourcing orientation for lasting partnerships, communication between firms, teams across organizations and integration of buyers and suppliers ( Chen & Paulraj, 2004 ). As many businesses source, sell, or compete globally or with global competitors ( Oliveira et al., 2019 ), they use strategic management theories to find ways to cooperate and gain an edge in a global setting. Therefore, many firms and business schools have focused their attention on Global SCM ( Browning et al., 1995 ; Chaudhuri et al., 2022 ; Lai et al., 2022 ). In the semiconductor industry, the global production scenario prevails, characterized by a supply chain network spanning the globe ( Lee et al., 2010 ). Dominated by leading technology-based firms, this industry demands cost efficiency, mass production, and operational flexibility. The semiconductor industry is characterized by its high demand for capital, as it involves sophisticated R&D processes, with few companies that can compete in the market. Management models in this global industry rely heavily on outsourcing and offshoring in SCM processes ( Pan et al., 2015 ). Stekelorum et al. (2021) contend that implementing green supply chain management (GSCM) would enhance the global semiconductor industry’s supply chain network in terms of effectiveness, sustainability, and environmental friendliness. It is important to mention here that the regulatory bodies of all the industries strive to motivate the firms to be environmentally conscious and restrict their activities binding them with some salient regulations to be followed ( Ratusny et al., 2022 ). In the dynamic business environment, semiconductor industry manufacturing firms need to develop their dynamic capabilities to successfully address the volatile situations for survival ( Mousavi et al., 2019 ; Song & Dong, 2024 ).

Conclusions

The present study has taken a novel attempt to enrich the extant literature by synthesizing the factors which include the risks, resilience, and complexities facilitating and impeding the smooth adaptation of GSCM in the semiconductor industry. This study has highlighted how the semiconductor industry could comply the policies and regulations of the governments while adopting the GSCM. This study has also discussed how the business practices in the semiconductor industry which consumes huge energy and pollutes the environment could use green supply chain practices that could lead to business sustainability and fulfils existing environmental related regulations to achieve sustainability goals. This research work has successfully been able to integrate TOE framework along with DCV to develop a hybrid theoretical framework highlighting how semiconductor industry can ensure better adoption of GSCM to achieve their sustainability goals. The proposed framework acts as a tool and guideline for future researchers who intend to ensure GSCM practices in other types of industries by updating the proposed model commensurate with the context of that study. Thus, the proposed model acts as a baseline for future researchers. This study has successfully been able to identify the factors like risk, resilience, and complexity which affect the adoption of GSCM. This study has also found that improvement of dynamic capabilities of the organizations related to semiconductor industry helps to successfully adopt GSCM. Finally, this study has also demonstrated that government policies and regulations have considerable influence on organizations towards achieving sustainability goals through adoption of GSCM.

Abstract

Although artificial intelligence can contribute to decision-making processes, many industry players lag behind pioneering companies in utilizing artificial intelligence-driven technologies, which is a significant problem. Explainable artificial intelligence can be a viable solution to mitigate this problem. This paper proposes a research model to address how explainable artificial intelligence can impact decision-making processes. Using an experimental design, empirical data is collected to test the research model. This paper is one of the pioneer papers providing empirical evidence about the impact of explainable artificial intelligence on supply chain decision-making processes. We propose a serial mediation path, which includes transparency and agile decision-making. Findings reveal that explainable artificial intelligence enhances transparency, thereby significantly contributing to agile decision-making for improving cyber resilience during supply chain cyberattacks. Moreover, we conduct a post hoc analysis using text analysis to explore the themes present in tweets discussing explainable artificial intelligence in decision support systems. The results indicate a predominantly positive attitude towards explainable artificial intelligence within these systems. Furthermore, the text analysis reveals two main themes that emphasize the importance of transparency, explainability, and interpretability in explainable artificial intelligence.

Introduction

Automotive industry leaders, such as Tesla, have made substantial investments in artificial intelligence (AI) to expedite the introduction of self-driving vehicles to the market, enhancing their competitive capabilities. The integration of AI in supply chain operations has played a crucial role in enabling Tesla to optimize its operational costs [64] while simultaneously facilitating the establishment of a Gigafactory in China [78]. We are witnessing a rapid digital transformation driven by the integration of AI in supply chain management. The COVID-19 pandemic forced companies and organizations to expedite the digitalization of their operations [6]. To enhance their competitive edge, prominent companies, including Amazon, Walmart, Alibaba, Siemens, and Toyota have embraced AI-based technologies to automate and digitalize their operations and supply chain activities [1,32]. Digital transformation also introduces new possibilities for potential cyberattacks. However, using AI-based technologies for decision-making during cyberattacks (e.g., American Express monitoring; [75]) offers significant advantages that outweigh the potential losses incurred.

Although AI-based technologies can contribute to decision-making processes in operations and supply chain management, many industry players are lagging behind pioneering companies in utilizing AI-driven technologies, which is a main problem. Therefore, the adoption of AI-based technologies in decision-making processes, particularly during sensitive situations such as cyberattacks, may encounter potential barriers that delay their usage. Due to its vital advantages, AI has received much attention from decision-makers to address resilient case studies [45] and other sensitive problems such as healthcare [69]. The lack of explanations of the underlying AI processes leads to the rejection of AI in decision support systems [60]. Leveraging AI-powered decision-making platforms can significantly facilitate and expedite the decision-making process, which results in improved overall performance. For instance, the Colonial Pipeline, a U.S. oil supplier, faced a cyberattack and, after a week of deliberation, opted to pay around $4.4 million to solve the issue [21]. A quick decision on the first day through agile decision-making could have saved them money and enabled the uninterrupted continuation of their operations with stockholders.

Results

We employed regression analysis to test the hypothesized relationship between research model variables. We conducted required tests relating to the experimental design along with method assumptions and bias checks.

4.1. Design check
To check the design, the scenario test, the realism test, the validity test, and the manipulation test were performed. We conducted the scenario check to measure the participants’ learning process regarding the provided information. The results showed that participants’ learning was strong enough to support the scenario design (in the first scenario, the Mean = 5.3 out of 7, with a Standard Deviation = 0.99, and in the second scenario, the Mean = 5.5 out of 7, with a Standard Deviation = 0.85). The realism check was conducted through a face validity process and tested using the quantitative approach proposed by Thomas et al. [65]. Participants supported the realism check by agreeing that the scenarios were close enough to reality (Mean = 4.08 out of 5; Standard Deviation = 0.44). Similarly, the validity check supported the scenario design (Mean = 4.07 out of 5; Standard Deviation = 0.43). The manipulation test supported the manipulation by showing a significant difference between the two manipulated levels (p-value <0.001, the first level, the low level of XAI: Mean = 2.68 out of 7; Standard Deviation = 0.12; and the second level, the high level of XAI: Mean = 5.9 out of 7; Standard Deviation = 0.10).

Abstract

The purpose of this research is to systematically review the state-of-the-art literature on Supply Chain Finance (SCF) and Environmental, Social, and Governance (ESG) and Value Chain within the supply chain management domain. We meticulously screened closely related themes through a systematic literature review of selected fifty-one manuscripts using the PRISMA method. Three-phase approach of planning, conducting and reporting is considered in this review. The outcomes of our review demonstrate the contributions of SCF to decision-making within the supply chain domain. This review highlights synergies, distinctions, and intersections in SCF, ESG, and value chain. Based on themes, the study led to four propositions to develop a comprehensive framework. Additionally, the literature is elucidated based on the approaches employed for SCF development, accompanied by the underlying theories. The categorization primarily separates the literature into two main groups: one focused on theory development, and the other on practical applications, revolving around SCF, ESG, and the value chain. Professionals in corporate settings and academic scholars will likely derive significant value from this review. The study thoroughly reviews, categorizes, and analyzes existing research and offers an integrated framework on SCF, ESG, and the value chain, which can be helpful for professionals. This is the first research that uses a structured approach to analyze studies on a novel topic and propose a framework for SCF, ESG, and value chain.

Introduction

In the last twenty years, a notable pattern has surfaced in the realm of corporate sustainability. This trend encompasses a range of initiatives, from mandates that encourage voluntary commitments to sustainable practices (Freeman et al., 2010; Wang et al., 2016; Aragòn-Correa et al., 2020; Fiandrino et al., 2022; Agrawal et al., 2023). Thus, along with sustainability strategies companies have also started sharing information about environmental, social, and governance (ESG) matters (Baid and Jayaraman, 2022; Asif et al., 2023; Kumar et al., 2024). Sustainability and ESG have attracted significant importance in the business landscape. Business need to incorporate these revolutionary changes to comply to emerging business environment. ESG captured the interest of various stakeholders such as scholars, governments, and enterprises through a report published by United Nations in 2006 (Atkins, 2020; Clément et al., 2023; Wang et al., 2023a,b). In 2021, ESG-focused portfolios accomplished nearly $40 trillion in assets further expecting a 30% increase by 2025 (Bloomberg Intelligence, 2021). This brought transparency in all the activities that could impact the environment. Exposure by social media and non-government firms led to an increase in global SC visibility (Clarke and Boersma, 2017; PRI, 2020; Saini et al., 2022; Fiandrino et al., 2022; Agrawal and Jain, 2022; Agrawal et al., 2024).

The global financial crisis of 2008–2009 witnessed increase in research on Supply Chain Finance (SCF) (Kaur et al., 2023). This crisis revealed that companies and their SC faced cash flow constraints and challenges in securing financing from banks. These difficulties were often attributed to a lack of understanding of liquidity and working capital management (Caniato et al., 2016; Baid and Jayaraman, 2022; Huang et al., 2022; Rijanto, 2024). Since then, SCF has progressively evolved as a crucial tool for tackling these challenges. The primary focus of SCF revolves around “planning, managing, and controlling SC cash flows,” as Wuttke et al. (2013) emphasized. According to Jia et al. (2020), aims to help companies fulfill their daily financing needs, optimising cash flow at the inter-organizational level. The concept of SCF is a recent development as compared to equity financing or mortgages and it faces numerous challenges, as emphasized (More and Basu, 2013; Joshi et al., 2024). It is evident that number of start-ups are also emerging in SCF space to facilitate businesses in their transactions. Emerging approaches in SCF include purchase order financing (Reindorp et al., 2018) and inventory financing (Yan and Sun, 2013). As SCF garners increasing attention, the volume of literature in this area is also rising (Gomm, 2010; Elliot et al., 2020; Jia et al., 2020; Medina et al., 2023). However, investigation on SCF or the convergence of finance and operations is yet in its early stages, primarily because of its innovative nature. As per the PRI (2020), adeptly managing ESG factors in SCF can yield a range of short-term and long-term financial benefits.

Conclusion

This review assesses 51 papers from 1999 to 2023 from the Scopus database. Fig. 4 illustrates the evolution of ESG, SCF and VC research over time, showing a significant upswing in activity from 2018 onwards. Fig. 2 reveals that in ESG, SCF, and VC, research predominantly occurs within decision sciences, engineering, computer science, business management, and accounting. Additionally, the analysis explores the facilitators and gaps associated with ESG, SCF and VC, as outlined in Section 2.3. The rising interest and application of ESG, SCF and VC, focused on tasks like economic values and minimizing its environmental impact, all the stakeholders are ethical and transparent, optimize the cash flow, improve efficiency and financial stability for offering practical solutions to contemporary business challenges. The exhaustive nature of this inquiry aims to provide a valuable and practical resource to all the stakeholders, particularly for future researchers in the field of production research. This investigative framework developed here can be a foundation for forthcoming research endeavors.

Abstract

We estimate the effect of global supply chain disruptions on inflation for a panel of 28 European countries. Adverse shocks have a stronger and more persistent effect than favorable shocks.

Introduction

Disruptions to global supply chains, e.g. due to natural disasters and lockdowns, are considered a major driver of the drastic increase in inflation in Europe and other advanced economies after the COVID-19 pandemic. The evidence (Carrière-Swallow et al., 2023, Burriel et al., 2023, Ascari et al., 2023, Laumer, 2023, Khalil and Weber, 2022, Finck and Tillmann, 2023, Finck et al., 2023, Liu and Nguyen, 2023, Elsayed et al., 2023, De Santis, 2023) suggests that supply chain shocks indeed have a significant effect on inflation.

More recently, supply bottlenecks eased and indices of supply chain conditions (Benigno et al., 2022) are back at pre-pandemic levels. However, inflation remains high. The Economist (2023) asks: “Supply chains are back to normal. Why is inflation still so high?” This note provides one potential answer to this question. We estimate local projections for a panel of 28 European economies between 2010 and 2023 in order to quantify the effect of a supply chain disruption on headline inflation, core inflation and producer price inflation. The supply chain shock we use is the purified change in the Global Supply Chain Pressure Index (Benigno et al., 2022). Importantly, we allow positive, i.e. restrictive, and negative, i.e. expansionary, shocks to have different absolute effect sizes.

Conclusions

This note showed that the inflationary effects of disruptions to global supply chains are asymmetric. An increase in supply chain stress strongly contributes to the increase of inflation as seen after the COVID-19 pandemic. However, an easing of supply chain pressure contributes much less to the decline of inflation. Hence, our results provide one potential answer to the question asked by The Economist (2023).

Of course, asymmetric supply chain shocks are just one potential explanation of persistent inflation rates despite an easing of supply chain conditions. A tendency to de-globalize supply chains could raises costs even as shipping conditions normalize. Inflation could also remain elevated due to second-round effects of the initial spike in energy prices and costs of intermediate goods on wages. In addition, a shortage of labor post-Covid might also prevent inflation from returning to low levels. Finally, the sectoral shift of demand during the pandemic from services to goods is still visible in the data, which causes inflationary pressure in the presence of frictions.

Abstract

This study aims to identify and prioritize the strategies for overcoming digital supply chain (DSC) implementation barriers. Twenty-five DSC barriers and seventeen DSC strategies are formulated through an extensive literature review and expert discussion. An integrated Modified Stepwise Weight Assessment Ratio Analysis (SWARA) and Combined Compromise Solution (CoCoSo) based framework has been used to fulfil the research objective. A case study in the automotive industry is undertaken to assess the applicability of the proposed framework. With the help of experts, a pairwise comparison matrix has been developed for critical DSC barriers and DSC strategies. The result shows that “absence of urgency for SC digitalization”, lack of proper innovation strategies”, and “Inadequate leadership to lead digital transformation “are the highest-ranked DSC barriers that needs to be overcome on a priority basis, and “determined top management commitment to digitalization to gain a competitive edge”, “planning and coordination for implementing digital technologies in SC”, and “Adequate management of investment for comprehensive digitalized business” are the top-ranked DSC strategies which has to be considered on priority basis by the management to overcome most of the barriers. Accordingly, the management should effectively plan to mitigate the DSC barriers and implement strategies phase-wise for successful DSC implementation. This study will also guide the practitioner to select the optimal strategies within the available resources. Sensitivity analysis has also been done for the obtained results, whose analysis shows that the proposed research model is robust as ranking strategies are relatively sensitive to barrier weights.

Introduction

Supply chain (SC) managers are under enormous pressure because of the growing influence of the corporate world and the internet on consumer purchasing behaviour and demand patterns [1]. Therefore, it is imperative that SC managers prioritize the enabling new processes, boosting corporate connectivity, and expanding business agility [2]. Over the past decade, the proliferation of social media platforms and smart connected devices has dramatically altered consumers’ reaction time and multi-channel service expectations [3], [4], [5]. Technology, especially the Internet of Things (IoT) and information and communication technologies (ICTs) [6], has had a profound effect on the manufacturing setup of any typical organization, and the SC is just one functional area that has been profoundly altered as a result [7], [8]. Digital transformation is critical for modern firms due to innovation acceleration in businesses. Customer service, supplier relationships, sales, and company growth all benefit from digital transformation [5]. According to [9] The use of advanced digital tools and technology to modify and improve business practices, policies, corporate cultures, and customer experiences to meet shifting business demands is known as “digital transformation”. Digital transformation can help businesses identify consumer preferences, strengthen customer connections, acquire real-time visibility into processes, and create a more agile SC [10]. It also facilitates the expansion of production, product availability, pricing, and delivery schedules, as well as, most notably, sustainable development [11]. Digitizing the SC has many benefits for businesses in all sectors, but it entails operational and financial factors that can hinder long-term performance [12]. However, SC digitization faces some obstacles which would require cautious solutions [13]. The gradual adoption of digitalization across SCs may have two key impacts; firstly, there are a variety of roadblocks that prevent companies from deploying digitization strategies throughout the entire SC. Second, some of the enabling components may prove useful in the future for the SC and for enterprises as they make the move to digital technology. Due to the low rate of digital technology adoption, SC managers need to be aware of both the challenges that come with digitization and the opportunities it presents [14], [15]. For the effective digital transformation of the SC, the organization must create the necessary innovative environment to enable effective action, performance, and continuous progress to maintain the necessary enthusiasm and confidence amongst the employees [16], [17]. Digitization is still an emerging phenomenon that requires more administrative insight than theoretical comprehension [18]. The term “digitalization” refers to a modern business strategy that goes beyond the single and limited application of technology to include SC wide systematic implementation [19], [20]. The automotive industry is now affected by the disruptive effects of digitization, which is the most significant development in recent years. There were many different factors that have an increasing amount of influence on the automotive industry [21], [22], [23], [24]. These include consumer and product diversification, globalization, which enables manufacturers to enter new markets and a shorter product lifecycle in order to keep up with the rapidly changing demands of consumers with innovative products [25].

Result and discussion

This research thoroughly explains DSC implementation by outlining its strategies and challenges in descending order of importance. It is difficult to claim that DSC can be adopted in an enterprise environment without challenges. How these DSC barriers are managed will have a significant impact on an organization’s ability to develop and adopt digital technologies. This study majorly focuses on to prioritize DSC strategies to effectively remove barriers to DSC adoption. According to the literature and expert opinion, a total of 25 DSCBs have been identified, as well as 17 strategies to mitigate all the DSCBs in a phased manner. An integrated modified SWARA and CoCoSo has been used, and detailed analysis was performed. The modified SWARA method is used to rank the most influential DSCBs, and CoCoSo is used to prioritize DSCB solutions as strategies. A case study has also been conducted in the Indian automobile industry to examine the applicability of the proposed framework. The findings for the weights of DSCBs are shown in Table 3. The results show that the “absence of urgency for SC digitalization” (SB3) received the highest priority weight (0.230) amongst the set of 25 DSCBS, as shown in Table 3. It is one of the major barriers to DSC adoption and this should be alleviated immediately. The digital transformation effort with SB3 must begin by installing and maintaining a sense of urgency with the organization [5]. Higher-level management plays a critical role in controlling SB3, and more focused attention is required to minimize SB3 for successful DSC implementation. Barriers such as “Lack of proper innovation strategies” (SB2) and “Inadequate leadership to lead digital transformation” (LB2) were ranked second and third, with priority weights of 0.125 and 0.119, respectively. Organizations must pay close attention to innovation strategies to succeed in capturing new markets, increasing market share, gaining a competitive edge, and adopting new technologies. Rapid technological advancements and intense market competition necessitate the implementation of effective innovation strategies, as any organization that fails to do so will not be able to remain competitive in the market [240]. The development of digital technologies has been the result of a global surge of innovation and disruption. These disruptive technologies have been found in a variety of areas, such as mobile phones, advanced robotics, and automated guided vehicles [241]. Management must be able to effectively communicate the motivations for change to employees and inspire them to embrace new technologies, modify work processes, experiment with novel concepts, and work with internal teams [130]. “Inadequate strategic roadmap for digitalization (SB1)”, “Lack of top management support and commitment (OB4)”, and “Lack of governance mechanism adoption” (LB3) were ranked fourth, fifth, and sixth, with priority weights of 0. 0.0783, 0.0644 and 0.0614, respectively. The company’s strategic roadmap for managing its digitization process may help manufacturers understand the need for digital evaluation and better support their digital transformation process [159]: [242]. Inadequate digital skill and capability is a major barrier for organizations that want to grow at a faster rate.

Abstract

In this paper, we examine which of an agency selling or a wholesale contract offered by an e-commerce platform competing suppliers with typical dual-channel supply chains should adopt, where the products are not differentiated between a direct channel and an indirect platform channel, as in the case of digital goods. Specifically, we consider the situation in which each of two competing suppliers chooses its distribution strategy regarding whether it sells via a direct channel and/or an indirect channel via the platform. In addition, a supplier also chooses an agency selling contract or a wholesale contract if selling via the platform. Constructing and solving a game-theoretic model, we derive the primary result that, in equilibrium, one supplier sells products only via the direct channel, while the other supplier sells via both the direct channel and the platform channel through adopting a wholesale contract, even given the assumption of symmetric suppliers. This finding yields the managerial implication that a supplier selling products of the same quality between direct and platform channels in a competitive environment should not adopt agency selling but instead a regular wholesale contract when selling via a platform. Moreover, this finding reverses the conventional insight from existing models in previous studies that at least one competing supplier always adopts an agency contract when the suppliers are without their own direct sales channels.

Introduction

Currently, a wide variety of products ranging from technologically advanced industrial products to daily necessities including food and groceries are sold through online e-commerce platforms worldwide. Consequently, platform companies have experienced tremendous growth over the past decade. For example, Amazon announced that its net sales for 2020 increased 37.6% to $386 billion, compared with $281 billion in 2019. Reflecting the development of these e-commerce platforms, the US Department of Commerce has documented that online retail sales in the US were $791.7 billion in 2020, accounting for 14% of all retail sales in the US.1 Likewise, in China, where the development of e-commerce has been especially rapid, online retail sales reached 11.76 trillion yuan in 2020, accounting for some 30% of total retail sales.2 Accordingly, manufacturers increasingly regard these online e-commerce platforms as one of their essential sales channels.

While online retailers have typically played the role of simple resellers in the past, the rapid adoption of online shopping by consumers has induced major platform companies, including Amazon in the US, Taobao in China, and Flipkart in India, to introduce a sales format known as marketplace in addition to their traditional reseller format. Accordingly, when selling products or services through an online platform, a supplier needs to select between a wholesale contract or an agency contract, depending on whether the supplier wishes to sell products wholesale to the platform or use its marketplace. The essential difference between the two contracts is who has the right to determine the retail price. With the wholesale contract, while a supplier determines the wholesale price of its products, the platform company determines the retail price. Conversely, the retail price decision is delegated to the supplier in the agency contract, such that the supplier directly determines the retail price of its products based on the revenue-sharing rules as determined by the royalty rates and commission fees set by the platform. A major benefit of agency selling to the supply chain is that it resolves the problem of double marginalization, unlike a wholesale contract, and thereby prevents a reduction in the transaction quantity.

Conclusions

Currently, many manufacturing companies are not only utilizing rapidly growing e-commerce platforms as important sales channels, but also they are opening their direct channels and selling directly to end-consumers using advanced IT technologies. Given that many suppliers are now using such dual-channel supply chains, this paper investigates whether a wholesale contract or an agency contract offered by an e-commerce platform is chosen by competing suppliers, in the situation where products are undifferentiated between the direct channel and the indirect platform channel, as is typically the case of digital goods.

The key result from our model is that if there is no differentiation between channels such that consumers perceive the direct and platform channels as substitutable, then neither of the competing suppliers chooses the agency contract. This result holds regardless of how much the platform increases the suppliers’ share of profits by lowering its royalty rate and thereby making the agency contract more profitable to them. This yields the managerial implication that a supplier selling products of the same quality across channels, such as digital goods in a competitive environment, should adopt a regular wholesale contract, not an agency contract when selling through a platform. Intuitively, if a supplier adopts a wholesale contract, this appears undesirable for the supplier because the problem of double marginalization is likely to occur. However, our results lie contrary to this intuition. Moreover, it is also a notable result that even though suppliers are assumed to be symmetric regarding demand and cost conditions in our model, their distribution strategies emerging in equilibrium are asymmetric. These asymmetric distribution channel strategies allow a supplier to differentiate itself from the rival supplier if the former sells through the platform. Because we have obtained all our main results and implications clearly in analytical form solely by solving our model, we do not conduct numerical analysis in this paper.

Abstract

Nowadays, creating a blockchain-based system for supply chain tracing is a complex task. This paper defines a model, a graphical domain specific language, and a set of tools aimed at helping supply chain domain experts to create blockchain based tracing systems for their supply chains. Starting from a graphical representation of the supply chain, the solidity smart contracts implementing the related tracing system are automatically generated by our framework. Small interventions of programmers are required to customize and finalize such smart contracts. A set of web based interfaces to interact with such smart contracts are also automatically generated. We are confident that our results will increase blockchain usage for supply chain traceability thanks to the automatic process of smart contract generation.

Introduction

A Supply Chain (SC1) has been defined in [1] as an organizations network involved in different processes and activities with the aim of producing value (products or services) at the benefit of the ultimate consumer. Focusing on the product/service, an SC represents a sequence of (even complex) operations which transform the initial assets into intermediate products/services and then into the final one.

In order to give a more precise definition of an SC, it is necessary to understand which aspects of the products/services and which operations are under analysis, the type of process represented, and the actors operating in the network. Regardless of the specific process represented by the SC, having the capability of automatically tracing and controlling the actions performed by the actors of the SC is of paramount importance to obtain an effective and efficient process. Auditability is a fundamental feature of such a tracing system, assuring that the records tracing the actions that have been performed on the SC assets must be always available and that they cannot be deleted or altered.

Supply Chain Management (SCM) systems are software systems that allow to follow and record the execution of the steps of the process represented by a given SC [2], [3]. A number of SCM system implementations, both from academy and industry, are currently available.234 A commonly used approach to have auditable SCM systems is to implement them over blockchain infrastructures.

A number of blockchain-based solutions tailored for SCs [4], [5], [6], [7] are already available but, according to the researchers proposing them, such solutions are still focused on a specific scenario and very difficult to be generalized. Consequently, to promote the usage of blockchain technology for SC tracing and with the aim to make the SCM systems development easier and usable by supply chain domain experts, who are not necessarily distributed ledger technology experts as well, we propose the *-chain framework.

Conclusion and future work

We presented *-chain, a framework defining a model, a DSL, and a set of tools for helping supply chain domain experts in designing and developing their supply chain Management Systems on top of blockchain technology. Our framework allows domain experts to easily represent the main types of supply chains through a simple and user-friendly graphical interface, and – once designed – to translate such supply chain scheme into: (i) a set of smart contracts skeletons implementing the related supply chain Management System, and (ii) two web interfaces for operating on such management system: one for the supply chain administrator, and the other for the supply chain participants. These interfaces allow supply chain administrators to register the participants to their Supply Chain Management systems assigning them roles and rights, and supply chain participants to the register the operations they executed on assets according to the designed supply chain and to the required roles.

We validated our framework, by using it to represent a well-known supply chain use case: the soybean traceability study case [7]. We built the corresponding model, adding more detail to the original schema, introducing role-based authorization controls and also other constraints on operations. We used our framework to translate the supply chain schema into solidity code, and to produce the supply chain Administrator and Participants interfaces.

Abstract

     This paper investigates the transformation of information sharing and multi-tier supply chain management (MSCM) from the perspective of small and medium-sized enterprises (SMEs) in the context of Industry 4.0. SMEs are typically sharing less information digitally, are less active in conducting MSCM, but must be integrated in digital supplier networks to achieve supply chain transparency or traceability. For this purpose, this paper empirically analyzes SMEs from the manufacturing industry in Austria and Germany are investigated regarding information sharing and MSCM. The responses are analyzed to test three hypotheses, using 81 replies from manufacturing SMEs in Austria and Germany. The three hypotheses investigate the upstream and downstream MSCM practices of SMEs as well as which kind of information is shared with and by SMEs. The results help to understand and reveal potential barriers for information sharing besides technical possibilities to SMEs in order to be actively involved in MSCM.

Introduction and background

     Digital information sharing across supply networks represents a relevant topic since it enables data-based potentials such as in the concept of Industry 4.0 or for using Artificial Intelligence [1,2]. However, many companies do not recognize the importance of data availability and data quality yet. This is particularly true for small and medium-sized enterprises (SMEs), which are often impeded by missing trust, standardization, data exchange interfaces, or technological readiness [3-6] and do not recognize the relevance of digital technologies for their business [7]. Likewise, digital information sharing in multi-tier supply chain management (MSCM) is still in its early stages of development.

     This research investigates information sharing and subsequent data analysis in MSCM, focusing on SMEs. It aims at determining basic characteristics, e.g., size and vertical network position (up- or downstream), of early adopters of data-based MSCM. Raw material suppliers and upstream suppliers have a higher probability of being pressured by large buyer companies, which demand information sharing [2]. Hence, we argue that data based MSCM is more likely to be implemented in the upstream supply chain (H1). Moreover, five categories of information were evaluated if they are shared with SMEs or by SMEs (H1a and H1b): a) inventory level, b) state of delivery, c) expected delay, d) forecast data, and e) production plan

Discussion and Conclusion

Interpretation of Results

     From the interviews, we derived the motives of SMEs for carrying out MSCM and to share data. Mainly, SMEs aim to serve customer requests and to be able to fulfil their own production plan. This is in line with Arend and Wisner [14], who found that conducting supply chain management (SCM) is negatively related to SME performance since they do not implement SCM thoroughly enough or do it because they are forced by more powerful partners while not having benefits for themselves. Hence, before SMEs are able to conduct profitable MSCM, data exchange must be established with mutual benefits for supply chain partners [2]. In addition, we found that not all kinds of information may be relevant for partners in the supply network. For SMEs, binary notes would often suffice, e.g., whether the delivery is on time or not.

     In summary, it can be argued that SME must invest primarily in the area of data structures and availability in order to create the basis for data-based analyses. Particularly regarding network partners that are not directly connected to the company, there is a great need for data so that the entire structures can be analyzed and optimized. It is noticeable that there are differences between the companies in many areas of analysis, which result from the size of the company. Differences are particularly noticeable regarding data availability and the application of analyses in the supply chains. Larger companies are better equipped in terms of data availability and perform more analytics – presumably because they work more intensively with data and therefore also rate the potential higher than smaller ones. Likewise, larger companies have more power in the network and can therefore de facto secure better data availability from their network partners.

Abstract

     The purpose of the study is to analyse how green reverse logistics technology impacts agricultural entrepreneurial marketing firms’ operational efficiency and sustainable competitive advantage. Systematic literature review and meta-analytical methodology was adopted to execute the current study. Reverse Logistics Model has been used for the current study as the theoretical model grounding the study as it enables a quick reaction and finding resolution for the customer return whilst regaining the highest value that is possible on each returned item. Results indicate that green reverse logistics technology has a strong influence on agricultural entrepreneurial marketing firms’ operational efficiency and sustainable competitive advantage. The study further shows existing research gaps that can be closed by future research studies. The study has limitations which may affect the generalisability of the results since they can only be applied testing the validity and reliability of the developed conceptual model. The study adds to theoretical literature development by extending knowledge on the Reverse Logistics Model theoretical modelling framework since there is paucity of research that have directly applied the same model in agricultural inputs entrepreneurial marketing firms’ operational efficiency and sustainable competitive advantage. Practically, the study enhances the need for adoption of contemporary technologies to solve the current challenges facing agricultural inputs entrepreneurial marketing firms’ sustainable operational efficiency and competitive advantage in the marginalised areas, not only in developing and emerging economies, but also dotted around the world. The study contributes to the conceptual development, theoretical and practical policy directions applicable to any agricultural inputs entrepreneurial marketing firms. A model can be tested to prove its validity and reliability in future similar studies, using alternative methodologies.

Introduction

     Environmental concerns have affected how business is done world over (Alnoor, Eneizan, Makhamreh & Rahoma, 2018; Kiatcharoenpol & Sirisawat, 2020). This has caused agricultural entrepreneurial marketing firms to re-design and re-align their processes in such a way that they are environmentally friendly (Kariuki, Ngugi & Mburu, 2022; Kazancoglu, Ekinci, Mangla, Sezer & Kayikci, 2021). The need for agricultural entrepreneurial marketing firms and consumers to ensure the dismantling of used products in a bid to extract parts for reuse, recycling or alternatively to ensure safe disposal (Martín & Fernandez, 2022). This allows companies to seamlessly integrate value creating activities of different supply chain partners (Martínez, Carracedo, Comas & Siemens, 2021). Seamless integrating of value creating activities include the movement of end of useful life goods or products from consumers to agricultural entrepreneurial marketing firms for the purposes of recapturing value and or ensuring disposal in an environmentally friendly manner (Martínez, Puertas, Martín & Ribeiro-Soriano, 2022; Nyagadza, 2021). This process of moving goods or products from the consumers to the manufacturer for recapturing value or ensuring disposal in an environmentally friendly manner is known as reverse logistics (Hills & Hultman, 2013; Isernia, Passaro, Quinto & Thomas, 2019; Julianelli, Caiado, Scavarda & Cruz, 2020). Firms aim at attaining operational efficiency as they strategically manage the process of product returns (Guarnieri, Cerqueira-Streit & Batista, 2020; Alharthi, 2012; Hersleth et al., 2022). By gaining operational efficiency through strategic management of reverse logistics (RL) can result in the improvement of the agricultural entrepreneurial marketing firm’s competitive position. Operational efficiency (OE) lead to improved competitive advantage of a firm (Job, Njihia, Maalu & Iraki, 2020). In many agricultural inputs industries RL costs tend to exceed the costs of production. Lack of an integrated supply chain strategy may in the long-term influence the agricultural entrepreneurial marketing firm’s competitiveness (Nyagadza, Pashapa, Chare, Mazuruse & Hove, 2022).

Discussion and conclusion

     With the perspective of the stated hypotheses, the modelling conceptual framework in Fig. 2 shows the antecedents of GRLT such as Reuse (X1), Repair (X2), Remanufacture (X3), and Recycle (X4), directly influence Operational Efficiency (OE) (M1) and Sustainable Competitive Advantage (SCA) (Y1 ) of the agricultural inputs entrepreneurial marketing firms. During the process of validating the structural modelling framework and its proposed hypotheses, future researchers need to make verifications of the absence of endogeneity through the simultaneity between Y1 and X1. If there is endogeneity on X1then an instrumental factor should be applied to have a solution for the problem under study.

     Further to this, suppliers and other supply chain participants receive returned goods, materials, and sub-assemblies for remanufacturing (Beamon, 1999). The basic design of a product must account for disassembly processes. Having suppliers on board is crucial for creating environmentally friendly products (Wu & Dunn, 1995). A company’s environmental impact can only be reduced by taking into account the entire system in which it operates (Andrushchak, 2018; Beamon, 1999; Richnák & Gubová, 2021). For widespread greening efforts, the green supply chain is the perfect emphasis since it reflects this comprehensive, systems-level perspective. The importance of constructing decision frameworks for reverse logistics processes for effective product take-back, reuse, and recycling of specific components and materials of end-of-life structures. The research also suggests effective choice approaches for reverse logistics vehicle routing (Lee & Lam, 2012; Kassem & Chen, 2012). Consequently, many experts in the field have proposed and executed several approaches to making decisions (Job et al., 2020). Recently, Chanintrakul, Coronado Mondragon, Lalwani and Wong (2009) provided a state-of-the-art review of the design of reverse logistics networks.