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In recent years, both academics and institutions have acknowledged the crucial role multinational enterprises (MNEs) can play in addressing the sustainability challenges, as formalized by the sustainable development goals (SDGs). Nevertheless, because of their extensiveness and their design as country-level targets, SDGs have proven challenging to operationalize at a firm level. This problem opens new and relevant avenues for research in international business (IB). This chapter attempts to frame the topic of extended value chain sustainability in the IB literature. In particular, it addresses a specific topic, that is, how sustainability and resilience-building practices interact in global value chains (GVCs). To do so, the present study develops the case of STMicroelectronics (ST), one of the biggest semiconductor companies worldwide.

This chapter analyzes the efficiency levels of a circular economy (CE) with an emphasis on transaction costs. It examines the governance aspect of CE activities in comparison to the predominant linear value creation. Extant CE research in business studies tends to be descriptive and lacks a theoretical foundation, particularly in understanding CE management. Transaction cost theory explains efficiency in economic organizing, lending itself to the study of arrangements that maximize resource efficiency at continued economic virtue. The conceptualization proposes that CE transaction costs are greater than those within the linear economy (LE), primarily due to the uncertainties about reciprocal dependencies, looping material complexities, exchanging novel information, and increased contracting efforts. Geographically bounded and institutionally homogeneous CE initiatives may curb these rising costs. By bringing efficiency concerns into CE analysis, the chapter demonstrates the applicability of transaction cost theory and highlights CE relevance to international business by pointing out spatial choice implications.

Building industrial clusters is getting much more political attention and strategic orientation in all developing countries. This study started by revising the conceptual and theoretical frameworks for industrial clusters, followed by some insights and contributions about empirical bases for clusters' dynamics and processes. The study focused on the case of Agadir Agreement between four Arab countries (Egypt, Jordon, Morocco, and Tunisia), which was initiated after the Euro-Mediterranean partnerships, and the rationale of the agreement was based on the concept of cumulative value-added origin. The study based its methodology on analyzing the international and bilateral trade flows of six industrial goods from the automotive sector among the four countries and with the EU countries to detect the degree of industrial collaboration and the achieved success of each country in this sector. The study indicated that the four countries used the concept of industrial clusters for economic development, but the results of the analysis showed that till now Agadir Agreement only achieved a shallow integration, while failed to deeply integrate as one big collaborative industrial cluster.

This book chapter takes an institutional perspective on competing logics in global markets concerned with sustainability values and how market actors in the form of buyers and sellers attempt to solve these conflicting situations. We do this by identifying competing institutional logics in global market contexts aiming for sustainability values, together with techniques for navigating these competing institutional logics in the organizational field studied. As an empirical illustration, we use a case study of buyers and sellers in two different markets where sustainability has come into focus for their market relationships. This viewpoint allows us to better understand how global market actors deal with the competing institutional logics in their market context. We make three contributions with this research: firstly, we identify the institutional logics in global markets towards sustainability; secondly, we demonstrate how global market actors prioritize among the competing logics and their market relationships and thirdly, we outline what this means for the relationship between buyers and sellers in global markets towards sustainability.

This chapter analyzes how the industry environment determines corporate dividend decisions. First, common participants in the product market are competitors, suppliers, and customers. These micro-stakeholders create competitive pressures on firms and thus affect their current and future performance. Competitors influence dividend decisions through three mechanisms, namely predation threat, corporate governance, and imitation. Predation threat reduces firms' incentives to pay dividends when facing high rivalry. Competition helps firms improve corporate governance. However, strong corporate governance may increase or decrease dividend payments since dividend policy may be the outcome of strong corporate governance or the substitute for weak corporate governance, respectively. Besides, firms tend to imitate their industry peers in dividend policy. Second, as a financial policy, dividend policy is also affected by participants in the financial market like investors, creditors, and auditors. These financial stakeholders' behaviors are important to stock prices. Due to the agency problem, creditors have high incentives to restrict firm's dividend payments in order to protect their benefits. On the other hand, creditors are effective external monitors who help firms improve their corporate governance. Outside investors affect corporate dividend policy through their valuation. Firms pay more dividends if investors prefer dividends to capital gains. Auditors play the role of a third-party monitor, and thus, they help firms reduce managers' expropriation of shareholders and improve the quality of accounting information. Furthermore, we also investigate dividend policy of regulated industries in both financial sector (banking, insurance, and real estate) and utilities sector (energy, telecommunications, and transportation).

Although extant post-acquisition literature has mainly focused on the integration of stand-alone firms, many acquisitions involve select units that were divested from former parents. Scholars have therefore recently called for moving beyond the dominant dyadic acquirer–target view of the acquisition process to a triadic view that considers the roles of, and interactions between, divestors, targets, and acquirers in the acquisition process. The authors set out to build an extended process view of such triadic relations based on a five-year longitudinal case study of one entrepreneurial company, acquiring two divested units from large multinational companies. The case sheds light on how divestors and acquirers together shape synergy realization efforts and identity-building by targets, causing dramatic shifts in perceptions of success throughout the acquisition process. The authors hope the case offers greater understanding, and triggers more research, into mingled integration and disintegration processes. The authors also highlight three impediments that can shape post-acquisition choices and discontinuous processes when acquiring divested units.

Purpose: Technological innovations and frameworks that provide a framework for unification have evolved to improve information exchange across organisational units and information security. These integration technologies share and communicate information using defined protocols and different data. Service-oriented architecture (SOA) is a significant emerging approach that enables modular design solution construction.

Methodology: These designs are beneficial when many apps operating on different architectures and networks need to connect. A well-defined strategy and company-specific guidelines are essential for ensuring the firm’s systematic adoption of such an architecture. The critical components of MASSOASCM ‘(Multi-Agent System Service Oriented Architecture Supply Chain Management’ are a multi-agent system (MAS), a service-oriented structure, and supplier management. The MASSOASCM model has been made, and a production unit has been made to show how it works.

Findings: It has been stated that it saves development costs, and inventory management, all of which are critical concerns in any company. Our goal is to create an inventory control approach that relies on MAS and SOA but also a simulation that demonstrates how it works and may enhance Supply Chain Management (SCM) productivity in a production plant.

Practical Implications: The SCM implementation comprises three different services: SCM, SOA, and MAS. These facilities are constructed, maintained, planned, and implemented individually before being brought together collectively using MAS and SOA techniques.

Cities’ population growth goes in hand with the development of new technologies that are becoming the key factor of the Smart City (SC) concept. It allows the implementation of efficient management solutions, operation, and sustainable development of a city to face the challenges of urbanization and improve the services for the citizens and visitors.

The concept of the SC 5.0 was first presented in Svítek, Skobelev, and Kozhevnikov (2020), where the problems of the complexity of current cities due to rigid management processes, variety of infrastructure, and SC modules, systems, subsystems, and applications were described.

To prove the concept, several practical examples were developed to cover the topics: modeling in SCs, practical implementation of multiagent technologies, the approach of creating city ontology and the city knowledge base as the instrument of semantic interoperability, and visualization possibilities of Smart Evropská as a SC Testbed used for teaching purposes.

The new organizational structure is proposed based on knowledge graphs, and practical examples are shown. The applicability of knowledge graphs to be used in combination with data management platforms for monitoring SC key performance indicators (KPIs) and providing interoperability of services is presented.

This chapter of the book seeks to use famous mathematical functions (statistical distribution functions) in evaluating and analyzing supply chain network data related to supply chain management (SCM) elements in organizations. In other words, the main purpose of this chapter is to find the best-fitted statistical distribution functions for SCM data. Explaining how to best fit the statistical distribution function along with the explanation of all possible aspects of a function for selected components of SCM from this chapter will make a significant attraction for production and services experts who will lead their organization to the path of competitive excellence. The main core of the chapter is the reliability values related to the reliability function calculated by the relevant chart and extracting other information based on other aspects of statistical distribution functions such as probability density, cumulative distribution, and failure function. This chapter of the book will turn readers into professional users of statistical distribution functions in mathematics for analyzing supply chain element data.