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The purpose of this paper is to demonstrate modularity degree in terms of interfaces and innovation.

The research objective is achieved through a modeling approach for deciding modular architecture and its implementation regarding unique components and product innovation. A case example is presented to elaborate on the concept of modularity degree and provide an option for choosing the best module from different alternatives.

The presented approach can be considered a product design strategy, in which loose coupling is achieved through standardized component interfaces. Loosely coupled component interfacing is a prerequisite for developing mass customized products. There needs to be a decision support system to formulate the interfacing in order to achieve maximum benefits. This is illustrated in this paper.

The modeling strategy for measuring the modularity level is formulated theoretically. This approach needs to be validated through an empirical study in order to generalize its findings.

In the industrial arena there is a research gap in identifying and measuring the modularity level, which is formulated in the presented approach. It is hoped that this approach will contribute to filling this research gap in the business environment, which would further benefit managers of firms in their corresponding production processes.

The unique contribution of this modeling approach is articulated through analyzing product architecture, with a view to interpreting the component interfaces in a more productive way. This formulation triggers the decision‐making process in complex product development processes.

The purpose of this paper is to understand the drivers that create complexity in the supply chain and develop a mathematical model to measure the level of supply chain complexity (SCC).

Through extensive literature review, the authors discussed various drivers of SCC. These drivers were classified into five dimensions based on expert opinion. Moreover, a novel hybrid mathematical model was developed by integrating analytical hierarchy process (AHP) and grey relational analysis (GRA) methods to measure the level of SCC. A case study was conducted to demonstrate the applicability of the developed model and analyze the SCC level of the company in the study.

The authors identified 22 drivers of SCC, which were further clustered into five complexity dimensions. The application of the developed model to the company in the case study showed that the SCC level of the company was 0.44, signifying that there was a considerable scope of improvement in terms of minimizing complexity. The company that serves as the focus of this case study mainly needs improvement in tackling issues concerning government regulation, internal communication and information sharing and company culture.

In this paper, the authors propose a model by integrating AHP and GRA methods that can measure the SCC level based on various complexity drivers. The combination of such methods, considering their ability to convert the inheritance and interdependence of drivers into a single mathematical model, is preferred over other techniques. To the best of the authors' knowledge, this is the first attempt at developing a hybrid multicriteria decision-based model to quantify SCC.

The unpredictable distribution of globalization has directed the world economy and revealed the need to establish cooperation in all business processes. This global structure also highlights the necessity of designing an agile supply chain that is capable of continuous information sharing during end-to-end transportation for the purpose of creating sustainable connections. In this process, various strategies enhanced with contemporary information and communication technologies have been developed to create a fast and accurate data-sharing network between logistics service providers and supply chain parties. However, unlike the short-term interruptions experienced in the past, COVID-19 has caused unprecedented problems in the dynamics of most economies. In eliminating these problems, it has been seen that information communication technologies, which provide the advantage of digital visibility in normal operations, need to be redesigned with the technology of the autonomous age. To meet this requirement, Industry 4.0, a revolutionary conceptual trend that started roughly a decade ago but that has become considerably more widespread during COVID-19, has been integrated into business models as a key concept that governs intelligent transformation in the chain. This process, which is today considered a compulsory intelligent transformation rather than an alternative method, has however led to some conflicts, especially in adaptation, expertise, and security subjects. This chapter of the book evaluates, within the scope of cybersecurity and workforce in logistics services, the conflicts created by the digital solution methods that have been integrated into business models to reduce the negative effects of COVID-19.

Blockchain, in general, diversifies supply chain management in record-keeping and maintains authenticity. In addition, traditional issues and challenges like overflow and information overload press down mysteriously whenever the blockchain steering wheel of the supply chain turns. Factually, the miracle and twists in supply chain resilience have not been incorporated under systematic review homogeneously. As a result, this study reviews the potential impact of blockchain on logistics and supply chain (LSC) efficiency. The methodology of this study provides a subjective assessment of the utility of blockchain-based LSC performance.

On the other hand, the review reveals new insights on its current acceptance and applications, with a particular emphasis on the Limit Redundancy Mechanism and Core Information-based Direct Comparison. Prospectively, the identified facts under the research paradigm and extensive literature survey will subsidize the practices of blockchain technology and possible areas of extension in supply chain resilience in luminous fashion in the future. After all, this study materializes new solid magnitudes, adaptability, and a realistic overview of blockchain-based LSC movements.

The aim of this paper is to investigate the importance of information management in modular product architecture for customized product development.

The objective of this research is to analyze product architecture in terms of information exchange and show its influence in product customization. A case study is presented with a view to modelling the information tracking necessary for product architecture and customization.

In today's volatile business environment, appropriate ways of information management could be an added value for manufacturing firms. This paper deals with the importance of information flow in product architecture. The role of information exchange influences the basic architecture of the product development process, which also affects the general theme of product customization.

The importance of information flow highlights the design architecture and brings flexibilities to the product development process. This concept is illustrated through a single case example, which may not be translated as a generic output. Multiple case study approaches could be undertaken in future research to rigorously analyze the influence of information exchange on product architecture.

In order to comply with growing customization, firms are looking for flexible design architecture in their product development process. The presented approach will be beneficial for designers and organizational managers in developing flexible customized product or services.

This paper implements a unique approach to modular product architecture through information dependencies among components and sub‐assemblies. The basic principle of modular product architecture and how it affects product customization are also reported.

The purpose of this paper is to determine supply chain practices that contribute most to the success of agile manufacturing (AM), and to examine their effects on its implementation levels in the Jordanian manufacturing sector. It also investigates the effect of AM on operational performance (OP).

The study is based on survey data collected from 294 manufacturing companies from different industry types in Jordan. Validity and reliability analyses were performed using SPSS and AMOS, and the study hypotheses were tested using structural equation modeling.

The results revealed that supplier involvement, internal integration, and modularization of products positively and significantly affect AM. Customer involvement and postponement were insignificantly related to AM. Further, the results demonstrated that AM positively and significantly affect OP.

A limited number of previous studies investigated supply chain antecedents of AM. Further, there is no consensus among researchers on these practices. In addition, this area is underinvestigated in the developing countries in general and in Jordan in particular. The current study contributes to the literature by determining the most commonly linked supply chain practices to AM and examining their effects on its implementation levels in the context of a developing country, Jordan.

The purpose of this paper is to help organizational managers to keep track of the information management needed not only for product design and development but also to track between different organizational levels.

The research objectives are achieved through implementing the concept in a case company, where various measures of information management are taken into consideration. This empirical study is conducted with a view to formulating and validating the information flow among product development (PD) participants.

The strategic management of information exchange transforms the nature of competition through reducing complexities in product design and bringing flexibility into the production process. This achievement could orientate firms towards rapid and continuous growth of their PD strategies, which are essential for survival in a global business environment.

This research was conducted through a single case study approach, which limits its scope for generalizing the concept. It would be more authentic if the approach was validated over multiple case studies.

Managing the information flow among PD participants has been considered to be an important issue in today's competitive business environment. It helps to formulate the design architecture, both at the product and organizational level.

The strategic management of information exchange transforms the structure of product architecture, which helps to reduce the complexities in product design and bring flexibility into the production process. The presented approach shows the intrinsic relationships between firms' resources and customers' requirements, which could help product developers to improve their production flexibility, overcome bottlenecks and achieve product customization.

The purpose of this paper is to provide practical justification for performance measurement and management within a collaborative business network. The basic performance measurement indicators are elaborated within the scope of this research.

Performance measurement techniques are highlighted through the application of an ICT‐based solution approach, with special focus on business collaboration among small and medium sized enterprises (SMEs).

From the basic need to measure the performance of individual partners within a business network, this research proposes a generic framework and process flow with the objective of evaluating the individual partners in terms of various performance indicators such as key success factors (KSF), key performance factors (KPF) and key performance indicators (KPI). The outcomes from this framework or process flow will help partners in the network to build valuable trust, cooperation and coordination.

The focus of this paper is to demonstrate the methodological approach of measuring the performance through identifying and prioritizing the performance indicators (KSF, KPF, KPI) among collaborative partners and to highlight their importance for successful business operations.

Traditional supply chain arrangements have failed to keep up with escalating customer demands and breakthrough innovations. The way forward is a flexible yet innovative network that leverages ecosystem partners and digital tools to unlock new agility. The paper aims at identifying and analyzing numerous critical success factors (CSFs) that may improve the efficiency of a digital supply chain.

Twelve CSFs are identified in this paper through an extensive literature survey. Expert opinion has been considered and the hierarchical structure built using total interpretative structural modeling (TISM) which highlights the interdependencies between these CSFs. Cross-impact matrix multiplication (MICMAC) is used to determine the driving and dependence power of each factor.

This study identified 12 CSFs through an extensive literature survey. The ISM model resulted in six different levels beginning from redesign organization at the bottom of the structure. The TISM model explained why redesigning the organization is pivotal to bringing about novel agility in the supply chain. MICMAC analysis confirmed that the following enhanced the success of a digital supply chain: Sales and Operation Planning Strategies, Strategic Sourcing Techniques, Smart Manufacturing Processes and Warehouse Management.

Various other components contributing to the 12 CSFs identified in this paper may be discovered and detailed in future research. Additionally, further research is required to expand the existing technology-based services structural model to a more empirical form.

This study offers a comprehensive but not exhaustive list of CSFs essential to digital supply chain growth. It will enable market experts and leaders to concentrate on key factors leading to tactical decisions and maximum value for firms.

The paper seeks to add to the body of knowledge on real digitally-led supply chain transformation, which is still in its early stages. This study is one of the first, if not the first, to examine success factors critical to the improvement of the performance of the supply chain. It lays the foundation for further research in this field.

With its presence, which can create inefficiencies, uncertainties and risks, information asymmetry poses a significant challenge to successfully managing the agri-food supply chain (AFSC). Understanding the variables that influence information asymmetry is crucial for devising more effective strategies to mitigate it. This study, therefore, explores the variables that influence information asymmetry in the AFSC.

A qualitative analysis was conducted, relying on semi-structured interviews with 17 experts representing different actors in the AFSC (e.g. seed producers, retailers, etc.) in Germany. The collected data was analysed using the GABEK® method.

The study confirms that the influencing variables derived from the existing theory, such as price performance, digitalisation, environmental, process and quality measures, contribute to information asymmetry. It further reveals new variables that associate with information asymmetry, including documentation requirements, increasing regulation, consumer behaviour, incorrect data within the company as well as crises, political conflicts and supplier–buyer conflicts. Furthermore, the study shows that supply chain actors counteract asymmetry by focusing on social behaviour and monitoring suppliers through key performance indicators, employees and social aspects.

The study was limited to the universal influence of the variables on information asymmetry in the AFSC, making the magnitude of the influence and its context-specific nature unexplained.

This study is one of the very few that examines information asymmetry across the AFSC from the perspective of different actors, providing a more overarching and deeper understanding of information asymmetry.