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The purpose of this theoretical chapter is to rework a promising but limited theory of the foundations of reciprocity. Reciprocity is often attributed to an “internalized norm of reciprocity” – a deeply felt moral obligation to help those who have helped us in the past. Leifer's theory of local action develops a radically different and compelling foundation for reciprocity – one in which the impetus for reciprocity is a thinly veiled battle for status. We rework the theory to offer a new one that addresses its limitations. The key idea is that the impetus for reciprocity is the desire to signal that one intends to create joint value rather than to capture it from the counterparty.

Our analytical approach rests on close examination of a puzzling and underrecognized feature of social exchange: people who initiate social exchange routinely deny giving anything of value (“it was nothing”) while the receiver inflates their indebtedness to the giver (“this is too much!”). We refer to this negotiation strategy as reverse bargaining and use it as a window into the logic of social exchange.

We develop a more general theory of how people manage the threat of opportunism in social exchange that subsumes local action theory. The key insight is that people who initiate social exchange and seek reciprocity must balance two competing objectives: to ensure that the person receiving a benefit recognizes a debt she must repay; and to mitigate the receiver's suspicion that the giver's ulterior motive is to capture value from the receiver.

Due to its high leverage nature, a bank suffers vitally from the credit risk it inherently bears. As a result, managing credit is the ultimate responsibility of a bank. In this chapter, we examine how efficiently banks manage their credit risk via a powerful tool used widely in the decision/management science area called data envelopment analysis (DEA). Among various existing versions, our DEA is a two-stage, dynamic model that captures how each bank performs relative to its peer banks in terms of value creation and credit risk control. Using data from the largest 22 banks in the United States over the period of 1996 till 2013, we have identified leading banks such as First Bank systems and Bank of New York Mellon before and after mergers and acquisitions, respectively. With the goal of preventing financial crises such as the one that occurred in 2008, a conceptual model of credit risk reduction and management (CRR&M) is proposed in the final section of this study. Discussions on strategy formulations at both the individual bank level and the national level are provided. With the help of our two-stage DEA-based decision support systems and CRR&M-driven strategies, policy/decision-makers in a banking sector can identify improvement opportunities regarding value creation and risk mitigation. The effective tool and procedures presented in this work will help banks worldwide manage the unknown and become more resilient to potential credit crises in the 21st century.

This chapter is devoted to sustainable human resource management that leads to sustainable competitiveness. It features the ways human resources can be managed to carry out sustainable goals and the impact of sustainability on employees' attitudes and behaviours. The aim of this study is to explore the complex objectives of sustainability and human resource management and empirically investigate the dynamic relationship between human resources in science and technology and sustainable competitiveness in the case of 35 European countries. Our contribution emphasizes this interrelationship and its causality. For this research, we applied a vector auto-regression (VAR) model, and the Granger causality method to examine the relationship between human resources in science and technology and sustainable competitiveness. A panel data included 314 observations between 2012 and 2021. The panel VAR for analysing the impulse response function was enriched with the 5% and 95%, using Monte Carlo simulations. The research results revealed bidirectional causality in the European countries between human resources in science and technology and sustainable competitiveness. Human resources in science and technology trigger sustainable competitiveness and vice versa. As an element of originality, our study demonstrates that human resources in science and technology contribute to sustainable performance, and, on the other hand, a more competitive and sustainable environment contributes to the development of human resources in science and technology. Thus, the chapter outlines the role of human resources in science and technology with regard to sustainable human resource management (HRM), and how to navigate these objectives so that they can positively influence sustainable competitiveness.

“First principles” of international business (IB) thinking should be applied systematically when assessing the functioning of internationally operating firms. The most important first principle is that entrepreneurially oriented firms seek to create, deliver and capture economic value through cross-border linkages. Such linkages invariably require complementary resources from a variety of parties with idiosyncratic vulnerabilities to be meshed. Starting from first principles allows bringing to light evidence-based insight. For instance, most companies are not global and even the world’s largest firms rarely change the location of key strategic functions. International new ventures (INVs), emerging economy multinational enterprises (MNEs) and family firms face unique vulnerabilities but also command resources that can be used to create value across borders. The quest for “optimal” international diversification appears to be a futile academic exercise, and in emerging economies with institutional voids, relational networks – and more broadly, informal institutions – are unlikely to function as scalable substitutes for formal institutions. In global value chains (GVCs), many lead firms and their partners have been able to craft governance mechanisms that reduce bounded rationality and bounded reliability challenges, and it is also critical for them to use governance as a tool to create entrepreneurial space. Finally, many of the world’s largest companies have been on successful trajectories toward reducing their climate change footprint for a few decades. But these firm-specific trajectories are fraught with challenges and cannot just be imposed via unilateral, macro-level targets decided upon by individuals and institutions lacking a clear understanding of innovation and capital expenditure processes in business.

Introduction: Today the ability of nations to develop and implement innovations is core for their international competitiveness. Ukraine is striving for innovation progress; however, its innovation performance is relatively low. The research problem is to find the bottlenecks, affecting Ukraine’s innovation capability.

Purpose: This study aims to research the national innovation capability profiles, based on cluster analysis, to develop an understanding of drivers and threats for the innovation capability of Ukraine.

Need of the study: The knowledge-based economy, which had already turned into one of the most efficient developmental models of the 21st century, became a key driver of international competitiveness for the leading developed countries due to their progressive structural shifts towards the growth of high-technology manufacturing and knowledge-intensive sectors. These trends are significant to capture for the sake of increasing the innovation capability of the economy of Ukraine.

Methodology: The study is based on the K-means clustering method, which is employed for identifying 10 country clusters based on the indicators of their R&D and innovation activities, which allowed us to assess the innovation capability of Ukraine in comparison with 140 countries of the world. Data selection and normalisation were based on the 2019 Global Competitiveness Report indicators.

Findings: The study showed that Ukraine’s innovation capability problems are typical for most developing countries and are prevalently connected to low R&D expenditures, patent applications, and international co-invention activities. Most countries, except for the technologically developed ones, follow the so-called ‘passive technological learning’ strategies, which usually result in low economic productivity.

Practical implications: Several innovation policy implications have been developed for the government of Ukraine based on the cluster analysis results and accounting for the problems of the national innovation system (NIS).