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Today, companies are struggling to develop their human resources analytics (HRA) capability, although interest in the subject is rapidly increasing. Furthermore, the academic literature on the subject is immature with limited practical guidance or comprehensive models that could support organisations in the development of their HRA capability. To address this issue, the aim of this paper is to provide a maturity model – i.e. HRAMM – and an interdependency matrix through which an organisation can (1) operationalise its HRA capability and assess its organisational maturity; (2) generate harmonious development roadmaps to improve its HRA capability; and (3) enable benchmarking and continuous improvement.

The research described in this paper is based on the popular methodology proposed by Becker et al. (2009) and the procedure for maturity evaluation developed by Gastaldi et al. (2018). This method combines academic rigour and field experience in analytics, in a process spanning eight main phases that involves literature reviews and knowledge creation techniques.

We define HRA maturity through four areas and 14 dimensions, providing a comprehensive model to operationalise HRA capability. Additionally, we argue that HRA maturity develops through an evolutionary path described in four discrete stages of maturity that go beyond traditional analytics sophistication. Lastly, the interdependency matrix reveals specific enablers for the development of HRA.

This paper provides practitioners with useful tools to monitor, evaluate and plan their HRA development path. Additionally, our research helps practitioners to prioritise their work and investment, generating an effective roadmap for developing and improving their HRA capability.

To the best of the authors’ knowledge, this study is the first to provide a model for evaluating the maturity of HRA capability plus an interdependency matrix to evaluate systematically the prerequisites and synergies among its constituting dimensions.

This paper analyzes employees’ perceptions of data collection processes for human resource analytics (HRA). More specifically, we study the effect that information sharing practices have on employees’ attributions (i.e. benevolent vs malevolent) through the perceived legitimacy of data collection and monitoring processes. Moreover, we investigate whether employees’ emotional reaction (i.e. fear of datafication) depends on their perceived legitimacy and attributions.

The research is based on a sample of 259 employees operating for an Italian consulting firm that developed and implemented HRA processes in the last 3 years. The hypothesized model has been tested using structural equation modeling (SEM) on Stata 14.

This paper demonstrates the mediating role of perceived legitimacy in the relationship between information sharing practices and employees’ benevolent and malevolent attributions about data collection and monitoring processes for HRA practices. Results also reveal that perceived legitimacy predicts employees’ fear of datafication, with benevolent attributions that partially mediate this relationship.

This research indicates that employees perceive, try to make sense of and emotionally react to HRA processes. Moreover, we reveal the crucial role of information sharing practices and perceived legitimacy in determining employees’ attributions and emotional reactions to data collection and monitoring processes.

Combining human resource (HR) attributions, HR system strength, information processing and signaling theories, this work explores employees’ perception, attributive processes and emotional reactions to data collection processes for HRA practices.

Due to the constantly increasing competitiveness along with the complexity of knowledge, firms perceive collaboration as a key strategy that preserves firms' radical innovation performance. In this context, this paper aims to examine how firms’ partners’ diversity in open innovation activities influences the development of radical innovations, critical for social development. In particular, this study analyzes how the functional and geographical breadth of the firm’s collaboration portfolio affects its radical innovation performance. Furthermore, it also explores the role of firm size as a moderator in the relationships proposed.

This research employs panel data analysis, using a sample of 4,677 Spanish firms, with data sourced from the PITEC database.

The results of this study show that there is an inverted U-shaped relationship between the functional and the geographical breadth of collaborations and the firms’ radical innovation performance. Moreover, this study finds partial support for the moderating role of firm size, in the sense that small and medium-sized enterprises (SMEs) and large firms vary in their optimal number of diversity of partners.

This research provides a better understanding on how partners’ functional and geographical diversity, along with organizational characteristics such as firm size, affect how firms benefit from collaboration for innovation. This study shows that both SMEs and large firms experience diminishing returns when their collaboration networks become overly diverse in pursuit of radical innovation, due to increased costs. However, in SMEs, the turning point occurs at a later stage, consistent with the idea that small firms need broader functional networks to access complementary and novel resources they usually lack.

The purpose of this paper is to examine the effects of cross-border mergers and acquisitions (M&As) by firms in the emerging marketing on stock market cumulative abnormal returns (CARs). This research focuses on the acquiring firms in emerging markets and broadens the existing scope which highlights the M&As by firms in developed countries.

Regarding the controversial argument on the effect of cross-border M&As, the authors introduce a resource-based theory to explain the motivation of M&As by Chinese firms, conduct an event study analysis of 472 international acquisitions by Chinese firms from 2010 to 2015 and indicate cross-border M&As as a positive signal in the stock market.

The results reveal that cross-border M&As result in significantly positive CARs in a short term for the acquiring firms listed in mainland markets but not for that in the Hong Kong market. Furthermore, consistent with signaling theory and the investors’ heuristic thinking in decision-making, investors may adopt the technological innovation capability of the country where the target firms locate, and the acquiring firm’s preannouncement in shaping their positive judgment of the acquiring firm’s near future performance.

The authors distinguished the responses of the investors from the mainland and Hong Kong stock markets and investigated how the knowledge of the national innovation capability of the target firm and acquisition preannouncement influence the investors’ interpretation of the cross-border M&As as a market signal.

This study aims to propose a comprehensive framework for assessing circular economy (CE) performance in the agri-food sector. It identifies those indicators that should be used to measure circularity regarding CE strategies, applies them at a microeconomic level and examines the impact of key business determinants (financial, internalization, knowledge, awareness and digitalization).

A literature review was conducted with a focus on CE strategies and related indicators. The framework obtained is applied on a Spanish agri-food sector survey to provide an empirical CE analysis at firm level. A partial least squares based-structural equation modelling method is applied.

The research suggests a set of circularity indicators to assess CE strategies at micro level. The findings reveal the heterogeneity of CE sub-indicators related to narrowing, slowing, closing and regenerating strategies. It also highlights the strong effects that the drivers tested have on CE, especially awareness and knowledge.

This study provides a framework that can guide public policies and business decisions in sectors with significant environmental impacts. It provides a conceptual framework that explains which CE indicators should be considered by governments and regulators when developing policies that seek to promote circular strategies.

In the case of companies, the results show that acquiring more environmental awareness and knowledge is essential for promoting more sustainable work habits that enhance CE.

The paper offers a novel contribution to the CE literature by introducing a multidimensional indicator framework comprehensively applied to the agri-food sector, integrating miscellaneous pillars of circular strategies and business determinants.