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This chapter provides an in-depth look at how digital supply chain management (DSCM) can revolutionize supply chains in the post-COVID world. The COVID-19 pandemic exposed the vulnerabilities of traditional supply chains, highlighting the need for resilience and adaptability. The chapter begins by examining these COVID-induced disruptions, setting the foundation for the discussion on DSCM. DSCM, leveraging advanced technologies and data insights, offers a solution to these challenges, promoting agility, transparency, and sustainability in supply chain operations. This represents a significant shift from traditional practices, equipping organizations to cope with the dynamic postpandemic environment. Key capabilities of DSCM, such as resilience, integration, agility, and risk management, are discussed, supported by real-world examples from leading companies. These examples showcase the successful implementation of DSCM and its benefits in navigating the complexities of modern supply chains. However, the adoption of DSCM is not without challenges, including cybersecurity risks and integration difficulties. The chapter suggests strategies to overcome these challenges, emphasizing the importance of technology, collaboration, sustainability, and data-driven decision-making. By embracing these strategies, organizations can effectively manage their supply chains in the evolving global market, leveraging DSCM to withstand future uncertainties.

Blockchain technology is one of the major contributors to supply chain sustainability because of its inherent features. However, its adoption rate is relatively low due to reasons such as the diverse barriers impeding blockchain adoption. The purpose of this study is to identify blockchain adoption barriers in sustainable supply chain and uncovers their interrelationships.

A three-phase framework that combines machine learning (ML) classifiers, BORUTA feature selection algorithm, and Grey-DEMATEL method. From the literature review, 26 potential barriers were identified and evaluated through the performance of ML models with accuracy and f-score.

The findings reveal that feature selection algorithm detected 15 prominent barriers, and random forest (RF) classifier performed with the highest accuracy and f-score. Moreover, the performance of the RF increased by 2.38% accuracy and 2.19% f-score after removing irrelevant barriers, confirming the validity of feature selection algorithm. An RF classifier ranked the prominent barriers and according to ranking, financial constraints, immaturity, security, knowledge and expertise, and cultural differences resided at the top of the list. Furthermore, a Grey-DEMATEL method is employed to expose interrelationships between prominent barriers and to provide an overview of the cause-and-effect group.

The outcome of this study can help industry practitioners develop new strategies and plans for blockchain adoption in sustainable supply chains.

The research on the adoption of blockchain technology in sustainable supply chains is still evolving. This study contributes to the ongoing debate by exploring how practitioners and decision-makers adopt blockchain technology, developing strategies and plans in the process.

Economic costs and benefits are at the core while taking decision to adopt digitalization in the supply chain. The present chapter provides an in-depth exploration of the economic dimensions of digital supply chain management (DSCM) adoption in a firm. Drawing from a diverse source of literature, this chapter discusses the effect of economic outlook on DSCM adoption, the economic benefits of DSCM adoption and costs associated with it, and economic analysis and evaluation methodologies. The chapter also shares the case studies illustrating the real-world implications of economic considerations within DSCM initiatives. The chapter highlights how changing international socioeconomic and political dynamics can influence businesses across the globe. By analyzing the impacts of evolving market trends, changing consumer preferences, and geopolitical tensions, organizations can considerably forecast the possible impacts of these macroeconomic forces adeptly. The chapter also undertakes discussion on the economic cost and benefits associated with DSCM adoption. The economic analysis helps understand that the expected benefits outweigh economic costs, substantiating the economic viability of DSCM projects. The chapter concludes by discussing the examples of some real-world companies, highlighting how organizations have successfully applied economic analyses to their DSCM initiatives. This also highlights as to how showcasing how detailed economic assessments can justify substantial investments, deliver operational efficiencies, and reshape industries.

The present chapter discusses evolution, definitions, dimensions, capabilities, and the present state of the art of digital supply chain management (DSCM). The objective of the chapter is to offer a detailed understanding of DSCM, by shedding light on its historical development, exploring its multipronged definitions, and highlighting its core dimensions and capabilities in the contemporary business landscape. The evolution of DSCM appears as a central theme, rooted in the background of industrial revolutions. It starts by relooking at the First Industrial Revolution (IR) with its mechanization and steam power, progresses through the Second IR with electrification and mass production, and arrives at the Third IR, characterized by the rise of computers and the internet. The pivoting transition into the Fourth IR, also called Industry 4.0, marks the start of DSCM with its fusion of digital technologies (DTs) in the supply chain (SC) processes. Analysis of key definitions of DSCMs unveils their role as an enabler of SC collaboration, customer-centric nature, having overarching reliance on DTs. Moreover, the chapter explores the core dimensions of DSCM, exposing its ability to improve SC resilience, sustainability, visibility, efficiency, and agility. These capabilities stem from seamlessly woven DT developments into SC: artificial intelligence (AI), machine learning, the Internet of Things (IoT), and advanced analytics. The chapter concludes by highlighting the present state of the art in DSCM, reflecting its indispensable role in the contemporary turbulent business dynamics. In short, this chapter offers a synthesized view of DSCM's definitions, dimensions, evolution, capabilities, and present status within the larger context of supply chain management (SCM) literature.

The purpose of this study is to adopt a supply chain performance measurement (SCPM) framework as proposed by (Dweiri and Khan 2012) to model a novel SCPM index (SCPMI) system to measure and improve supply chain performance (SCP).

The adopted SCPM framework developed by Dweiri and Khan (2012) is used to model a generic SCPMI framework aided by analytic hierarchy process (AHP) method and inputs from industrial experts. To exemplify the applicability and efficiency of the generic SCPMI system, an automobile assembling company from an emerging economy was used. This SCMPI system is used to measure, improve and measure post-improvement SCP guided by DMAIC (define, measure, analyze, improve and control) methodology.

The study’s initial measurement results showed an average SCP of the case company over a four-month period as 82 per cent. DMAIC methodology was used to identify inherent problems and proposed improvements. The post-improvement SCP measurement saw an improvement from an average of 82 to 83.82 per cent over the four-month period.

The proposed generic SCPMI framework aided by AHP-DMAIC has been successfully implemented in a case company. After implementation, managers and decision-makers saw an improvement in their SCP. The proposed SCPMI system and results can be useful for benchmarking by manufacturing organizations for continuous SCP improvement.

An original SCPMI framework proposed is general in nature and can be applied in any organization.

Digital technologies (DTs) have emerged as a major driving force, transmuting the ways Supply Chains (SCs) are managed. The integration of DTs in supply chain management (SCM), Digital Supply Chain Management (DSCM), has fundamentally reshaped the SCM landscape, offering new opportunities and challenges for organizations. This chapter provides a comprehensive overview of modern DTs and the way they impact modern SCM. This chapter has twofold objectives. First, it illustrates the major changes that DTs have brought to the supply chain landscape, unraveling their multifaceted implications. Second, it offers readers a deeper and comprehensive understanding of the challenges and opportunities arising from the incorporation of DTs into supply chains. By going through the chapter, readers will be able to have a comprehensive grasp of how DTs are reshaping SCM and how organizations can survive and thrive in the digital age. This chapter commences by shedding light on how DTs have and continue to redefine SCM, improving supply chain resilience, visibility, and sustainability in an increasingly complex and interconnected world. It also highlights the role of DTs in enhancing SC visibility, agility, and customer-centricity. Furthermore, this chapter briefly highlights the challenges related to the adoption (pre and post) of DTs in SCM, elucidating on issues related to talent acquisition, data security, and regulatory compliance. It also highlights the ethical and societal implications of this digital transformation, emphasizing the significance of responsible and sustainable practices. This chapter, with the help of three cases, illustrates how the adoption of DTs in SC can impact the various SC performance indicators.

This research aims to propose a framework for measuring customer loyalty for third party logistics (3PL) industry by exploring the attributes that are more attractive to customers and ascertain the mechanisms for increasing customer loyalty in 3PL industry.

Data were collected from one hundred and thirty-three (133) respondents who were employees of different industries that outsource 3PL services. The partial least square structural equation modeling (PLS–SEM) was deployed for analysis.

The results showed that service quality has a significant positive impact on customer orientation, customer satisfaction and relationship quality. On the other hand, customer orientation has been observed to positively impact customer satisfaction but an insignificant impact on customer loyalty and relationship quality. Customer satisfaction has a significant positive impact on relationship quality but an insignificant impact on customer loyalty. Also, relationship quality has a significant positive impact on customer loyalty.

The results recommend that 3PL companies' managers focus more on developing quality relationships with their customers, delivering exemplary service quality and offering customer orientation.

This study will help the stakeholders gain much more understanding and insights on how competitive advantage can be achieved and, consequently, help 3PL become the market leaders.

The advent of the digital technologies (DTs), coincided with the pandemic and global conflicts, has proven to be an unprecedented and transformative era for supply chain management (SCM). DTs are reshaping the way organizations plan, execute, and optimize their SC operations. Throughout this book, we posit that the adoption of digital supply chain management (DSCM) has become essential for staying competitive and responsive in a rapidly evolving business environment. However, amid technological advancements and digital solutions, there exists a critical factor that often goes overlooked – the significance of intangible assets, specifically intellectual capital (IC). This chapter comprehensively explores the role of an organization's IC in the adoption and performance of DSCM. We employ a comprehensive analytical approach, drawing upon existing literature from various sources to elucidate the relationship between IC and DSCM. Synthesizing insights from the literature, the chapter shows how each constituent of IC contributes to the adoption, operation, and performance improvement of DSCM. The discussion in the chapter shows that human capital (HC) forms foundations, as the knowledge, skills, and abilities (KSAs) of the employees are prerequisites essential for understanding, adopting, and capitalizing on DTs in SCM. The analysis also reveals that SC, which represents organizational processes, digital tools, and knowledge repositories, supports the seamless integration of DTs within SCs. Similarly, RC, by nurturing trust, open communication, and collaborative networks, plays an instrumental role in establishing ecosystems that help the adoption and effective functioning of DSCM. This chapter makes a convincing case to consider IC as the strategic component while DSCM adoption and performance.

One of the fundamental objectives of adopting digital supply chain (DSC) is to uplift the performance of an organization. Although a wide variety of literature confirms the impact of DSC on performance, it is hard to explore as to which dimensions of the performance is affected by DSC and how much. This chapter undertakes discussion on the impact of DSC on the various organizational performance indicators. The chapter also denotes some major key performance indicators (KPIs) that organization can track to gauge the impact of DSC on performance. A brief discussion on the challenges related to the development, adoption, and continuation of KPIs is also appeared in the later part of the chapter. The chapter concludes by denoting that the utilization of digital technologies (DTs) such as artificial intelligence (AI), the Internet of Things (IoT), and complex analytics in DSC has prospects for enhancing the operational efficiency, transparency, and agility of a supply chain (SC). Organizations that adopt these DTs have experienced better demand forecasting, reduced time order fulfillment time, and higher levels of consumer satisfaction. Nonetheless, the successful use of DSC requires development and implantation of KPIs regularly.