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This paper investigates effective human-robot collaboration (HRC) and presents implications for Human Resource Management (HRM). A brief review of current literature on HRM in the smart industry context showed that there is limited research on HRC in hybrid teams and even less on effective management of these teams. This book chapter addresses this issue by investigating factors affecting intention to collaborate with a robot by conducting a vignette study. We hypothesized that six technology acceptance factors, performance expectancy, trust, effort expectancy, social support, organizational support and computer anxiety would significantly affect a users' intention to collaborate with a robot. Furthermore, we hypothesized a moderating effect of a particular HR system, either productivity-based or collaborative. Using a sample of 96 participants, this study tested the effect of the aforementioned factors on a users' intention to collaborate with the robot. Findings show that performance expectancy, organizational support and computer anxiety significantly affect the intention to collaborate with a robot. A significant moderating effect of a particular HR system was not found. Our findings expand the current technology acceptance models in the context of HRC. HRM can support effective HRC by a combination of comprehensive training and education, empowerment and incentives supported by an appropriate HR system.

This paper aims to specifically focus on the challenges that human resource management (HRM) leaders and departments in contemporary organisations face due to close interaction between artificial intelligence (AI) (primarily robots) and human workers especially at the team level. It further discusses important potential strategies, which can be useful to overcome these challenges based on a conceptual review of extant research.

The current paper undertakes a conceptual work where multiple streams of literature are integrated to present a rather holistic yet critical overview of the relationship between AI (particularly robots) and HRM in contemporary organisations.

We highlight that interaction and collaboration between human workers and robots is visible in a range of industries and organisational functions, where both are working as team members. This gives rise to unique challenges for HRM function in contemporary organisations where they need to address workers' fear of working with AI, especially in relation to future job loss and difficult dynamics associated with building trust between human workers and AI-enabled robots as team members. Along with these, human workers' task fulfilment expectations with their AI-enabled robot colleagues need to be carefully communicated and managed by HRM staff to maintain the collaborative spirit, as well as future performance evaluations of employees. The authors found that organisational support mechanisms such as facilitating environment, training opportunities and ensuring a viable technological competence level before organising human workers in teams with robots are important. Finally, we found that one of the toughest challenges for HRM relates to performance evaluation in teams where both humans and AI (including robots) work side by side. We referred to the lack of existing frameworks to guide HRM managers in this concern and stressed the possibility of taking insights from the computer gaming literature, where performance evaluation models have been developed to analyse humans and AI interactions while keeping the context and limitations of both in view.

Our paper is one of the few studies that go beyond a rather general or functional analysis of AI in the HRM context. It specifically focusses on the teamwork dimension, where human workers and AI-powered machines (robots) work together and offer insights and suggestions for such teams' smooth functioning.

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.

Due to the global labor market challenges, international companies react and adjust fast to these circumstances by implementing digital solutions into all business processes. Organizational ambidexterity is seen as the response of digital transformation and it can be divided into structural, contextual, and sequential dimensions. In this context, organizations representing the smart industry will need employees with specific competencies which let them meet technological challenges.

This chapter aims to clarify the state of opinion on expectations towards, and preparedness for, the impact of Industry 4.0 on human resources management and the implementation of various types of ambidexterity in these companies. We have conducted interviews with key HR informants from manufacturing companies operating in Germany and Poland. We have found that Industry 4.0 has a significant impact on HR practices. In both international companies, various digital solutions in employee recruitment, development, and performance, have been implemented. There have also been mature examples in both companies of structural, contextual, and sequential ambidexterity.

Drawing on self-concept theory, this study evaluates the mediating effects of employees' psychological states on the relationship between human resources (HR) practices and employee engagement.

Through random sampling, 434 customer-contact frontline employees from five-star hotels in Malaysia participated in the cross-sectional survey.

The results produced by the Smart-PLS (partial least squares) indicate that HR practices positively and significantly influence employees' psychological states of safety, meaningfulness and availability. All these psychological states also exert positive influences on employee engagement (organisational and work engagement). Safety and availability mediate the links between HR practices and employee engagement, but not meaningfulness.

HR practices and employees' psychological states are necessary in ensuring positive employee outcomes and improving customer service provision.

The findings contribute to the further extension of self-concept theory and employee engagement by incorporating the mediating roles of employees' psychological states in the relationships between HR practices and employee engagement.

以自我概念理論為依據，本研究擬評估僱員的心理狀態、如何在人力資源做法與員工敬業度之間的聯繫上起著仲介的效應。

透過隨機抽樣法，434名在馬來西亞五星級酒店工作、接觸顧客的一線員工被選參與一個橫斷面調查。

以SmartPLS (偏最小平方)取得的研究結果顯示、人力資源做法正面地影響著員工的安全感、工作給予的意義和感知的組織支援；而且，這些心理狀態，均會對員工的敬業度(對組織的自豪感及對工作的投入)起著正面的影響。另外，安全感和感知的組織支援在人力資源做法與員工敬業度之間的聯繫上、起著仲介之效應；唯工作給予的意義則沒有這個效應。

研究結果進一步伸展了自我概念理論及員工敬業度方面的論述，這是由於本研究把員工心理狀態所扮演的中介角色，納入人力資源做法與員工敬業度的聯繫中。

若要確保積極的員工成果及提供更佳的顧客服務，有效的人力資源做法和正面的員工心理狀態是不可或缺的。

This paper studies the impact of certain characteristics of companies to training programs in the Industry 4.0 (I4.0) context. Partial objective is to rank the main human barriers companies have to overcome so that they can digitalize.

To accomplish the objectives, a closed-ended questionnaire was sent to Slovak and Italian companies and analyzed using statistical nonparametric tests. The partial objective was achieved using the so-called Henry-Garrett’s ranking method.

Results show the significance impact of companies’ characteristics such as foreign participation and company dimension on training practices whereas economic situation (financial health) seems not to influence it.

The study may lack generalizability as only 102 answers were collected. Perhaps, the outcome would be different with another sample from other countries. Moreover, using closed-ended questions, certain features may not have been covered.

Companies should always guarantee training for the resulted benefits. It is fundamental for organizations to find a time gap, resources and professionals who can teach these programs. Even when companies are incurring financial problems they should do so since human capital development can increase their competitiveness. The most critical barriers should be carefully addressed by companies. Training can help to overcome I4.0 barriers related to Human Resources (HR) and contribute to its growth.

This paper gives insights of the impact of certain characteristics of companies to the training programs. Because past research has limited their analysis on the identification of barrier, its novelty lies in the attempt to rank the most significant barriers among those detected by other authors in previous research.