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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.

This study examines factors that influence organizations’ choices of an internal human capital development strategy and an external human capital acquisition strategy. The human resource architecture indicates that organizations will use different human capital acquisition strategies. Following the resource-based view, human capital theory and the human resource architecture, we examine factors that impact the choices of different human capital acquisition strategies.

We examine these important human capital decisions in the context of Major League Soccer. Data to test the hypotheses were collected from a variety of publicly available sources. We tested the hypotheses with regression analyses.

We find that while organizations employ both internal and external human capital strategies, organizations may have one dominant human capital strategy and the other strategy may be used to supplement the human capital needs of organizations. Additionally, our results indicate that organizations with an older workforce tend to use an internal human capital development strategy, while higher performing organizations are less likely to use an internal human capital development strategy.

This study makes contributions by examining the choices between internal and external human capital strategies and factors that influence the choice of an internal or external human capital strategy.

This article aims to develop a new theory that can better explain and predict how and when humans interact with commercial robots. To this end, utility maximization theory (UMT) along with four principles and propositions that may guide how human-to-commercial robot interactions are developed.

This article conceptualizes UMT by drawing from social exchange, conservation of resources, and technology-driven theories.

This article proposes UMT, which consists of four guiding principles and propositions. First, it is proposed that the human must invest sufficient resources to initiate a human-to-commercial robot interaction. Second, the human forms an expectation of utility gain maximization once a human-to-commercial robot interaction is initiated. Third, the human severs a human-to-commercial robot interaction if the human is unable to witness maximum utility gain upon the interaction. Finally, once the human severs a human-to-commercial robot interaction, the human seeks to reinvest sufficient resources in another human-to-commercial robot interaction with the same expectation of utility maximization.

This article is one of the few studies that offers a theoretical foundation for understanding the interactions between humans and commercial robots. Additionally, this article provides several managerial implications for managing effective human-to-commercial robot interactions.

Innovation is critical for businesses to stay competitive in today's world, as it allows them to constantly look for new ways to differentiate their products or services from their competitors as well as improve cost-effectiveness. This study explore the role of strategic human resource practices in developing organizations' competitive capabilities-differentiation and cost-effectiveness, which, improves their innovation performance to create a competitive advantage.

The authors collected data from 387 employees from 25 knowledge-intensive information technology organizations in India through a questionnaire-based survey. After checking for biases, reliability and validity, the hypothesized relationships were tested by structural equational modeling using AMOS 26.

Strategic HR practices have a significant and positive effect on innovation performance and both competitive capabilities-differentiation and cost-effectiveness. While the differentiation capability had a strong positive effect on innovation performance, cost-effectiveness capability was not significantly related to innovation performance. The differentiation capability mediates the relationship between strategic HR practices and innovation performance link, whereas the cost-effectiveness capability did not have a mediating effect.

This study provides practical insights to HR and knowledge managers to focus on development of human capital and invest in hiring, training, development, strategic performance management practices to enhance employees' knowledge behaviors, which, stimulates innovation performance.

The paper adds to the strategic HRM paradigm by clarifying the underlying process of how strategic HR practices leads to higher innovation. It affirms the vitality of choosing appropriate competitive capabilities, and supporting organizational factor for business's success. It fills an important research gap by providing original empirical evidence from knowledge intensive information technology organizations in the emerging economy of India.

Machine learning (ML) techniques are increasingly important in enabling business-to-business (B2B) companies to offer personalized services to business customers. On the other hand, humans play a critical role in dealing with uncertain situations and the relationship-building aspects of a B2B business. Most existing studies advocating human-ML augmentation simply posit the concept without providing a detailed view of augmentation. Therefore, the purpose of this paper is to investigate how human involvement can practically augment ML capabilities to develop a personalized information system (PIS) for business customers.

The authors developed a research framework to create an integrated human-ML PIS for business customers. The PIS was then implemented in the energy sector. Next, the accuracy of the PIS was evaluated using customer feedback. To this end, precision, recall and F1 evaluation metrics were used.

The computed figures of precision, recall and F1 (respectively, 0.73, 0.72 and 0.72) were all above 0.5; thus, the accuracy of the model was confirmed. Finally, the study presents the research model that illustrates how human involvement can augment ML capabilities in different stages of creating the PIS including the business/market understanding, data understanding, data collection and preparation, model creation and deployment and model evaluation phases.

This paper offers novel insight into the less-known phenomenon of human-ML augmentation for marketing purposes. Furthermore, the study contributes to the B2B personalization literature by elaborating on how human experts can augment ML computing power to create a PIS for business customers.

With Industry 4.0 and the extensive rise of smart technologies, we are seeing remarkable transformations in work practices and workplaces. Scholars report the phenomenal progress of smart technologies. At the same time, we can hear the rhetoric emphasising their potential threats. This study focusses on how and where intelligent machines are leveraged in the workplace, how humans co-working with intelligent machines are affected and what they believe can be done to mitigate the risks of the increased use of intelligent machines.

We conducted in-depth interviews with 15 respondents working in various leadership capacities associated with intelligent machines and technologies. Using NVivo, we coded and churned out the themes from the qualitative data collected.

This study shows how intelligent machines are leveraged across different industries, ranging from chatbots, intelligent sensors, cognitive systems and computer vision to the replica of the entire human being. They are used end-to-end in the value chain, increasing productivity, complementing human workers’ skillsets and augmenting decisions made by human workers. Human workers experience a blend of positive and negative emotions whilst co-working with intelligent machines, which influences their job satisfaction level. Organisations adopt several anticipatory strategies, like transforming into a learning organisation, identifying futuristic technologies and upskilling their human workers, regularly conducting social learning events and designing accelerated career paths to embrace intelligent technologies.

This study seeks to understand the emotional and practical implications of the use of intelligent machines by humans and how both entities can integrate and complement each other. These insights can help organisations and employees understand what future workplaces and practices will look like and how to remain relevant in this transformation.

This paper aims to examine the influence of big data (BD) on human resource management (HRM). It defines how these data can be a useful tool in the decision-making process of companies’ human resources to obtain a sustainable competitive advantage.

This paper emphasizes the need to develop a holistic approach to emphasize these relations. Starting from these observations, the document proposes empirical research employing Eurostat data to test the benefits of BD in HRM decisions that optimize the relationship between training, productivity, and well-being.

The findings estimate HRM decisions and their impact in a broader macroeconomic and microeconomic perspective.

BD research is emerging as a crucial discipline in human resources. To overcome this problem, the paper develops an analysis of the literature on cleaner production and sustainability context; it creates a conceptual framework to clarify whether the existing studies consider the growing intensity of BD on human resources.

Drawing upon social judgment theory, the research examines whether changes in psychological involvement with a sport human brand owing to their sporting success can generate spillover effects on people's national pride, a proxy for the collective level of well-being and whether the individual's behavioral engagement in sport spectating will moderate this relationship.

Leveraging a quasi-natural experiment grounded in the 2021 Indian Premier League championship, the authors solicit responses from 296 representative individuals residing in India twice using a two-wave panel design. The authors conducted confirmatory factor analysis, repeated measures T-test, latent change score analysis, and structural regression analysis to examine the relationship between psychological involvement with sport human brand and national pride.

The results demonstrate a positive association between psychological involvement with sport human brand and national pride. Further, the findings indicate that an increase in psychological involvement with sport human brand was associated with an increase in national pride due to the successful athletic endeavor involving the sport human brand. However, the relationship between psychological involvement with sport human brand and national pride was invariant irrespective of patrons' spectatorship behavior.

This research demonstrates that sport human brands possess transformative soft power that extends their prerogative cultural identity personified by their athletic ability and success, allowing them to shape public sentiments of national pride via their profound influence through and beyond the complex network of brand ecosystems.

This paper investigates the two-way relationship between foreign direct investment (FDI) inflows and higher education across 36 Organisation for Economic Co-operation and Development (OECD) countries for 1998–2019 periods. To demonstrate this relationship, the authors take into account the total number of graduates as well as the number of graduates from different fields. Accordingly, the authors gathered graduates in four groups which are education, social sciences, technical sciences (tech) and health. In addition to investigating two-way relationship between FDI and graduates, the authors also examined the contribution of primary and secondary level education to FDI.

The authors use two models to investigate the bidirectional relationship between FDI inflows and graduates from four fields. In the first model, the dependent variable is FDI inflows, and in the second model, graduates from each field are the dependent variable. To investigate the dual relationship, the authors employ ordinary least squares (OLS) and two-step system generalized method of moments (GMM) developed by Arellano Bover (1995) and Blundell Bond (1998).

For the first model, the results show that secondary level and higher education have a positive impact on FDI. In terms of graduates by fields, it is seen that education and health graduates contributed the most to FDI. For the second model in which the authors analysed the effect of FDI on total graduates and graduates from different fields, the authors find that FDI positively affects the number of graduates from all fields, and the strongest effect is on graduates from the social science field.

Based on the results, the authors can say that well-educated people promote FDI inflows to OECD countries, and FDI is also a driving force in raising highly educated people. So, the authors think that the results will help design higher education policies in accordance with FDI and higher education connection.

To the best of the authors’ knowledge, this paper is the first to examine the impact of FDI inflows on graduates by fields and also to investigate the impact of graduates by fields on FDI.