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This paper aims to enlarge ongoing debate about corporate social responsibility (CSR) proposing reflections about the role of cognitive and information flows in influencing companies’ approaches and market expectations related to CSR.

The paper builds upon the research streams related to the information asymmetry and cognitive distance, for identifying through the interpretative lens provided by systems studies, possible key drivers on which policymakers, researchers and practitioners should act for building a suitable, shared and long-term oriented path for CSR.

The paper defines a scenario map about CSR in the light of information asymmetry and cognitive distance. Such a map supports both researchers and practitioners in better understanding actions and paths required for building a shared approach to CSR.

Recognizing the multidimensionality of CSR and the multiple managerial and organizational contributions provided for underling its advantages for companies, the paper focuses the attention on the elements and conditions able to promote, stimulate and encourage companies’ CSR strategies.

The paper provides a fresh conceptual framework for explaining conditions and elements required for ensuring the success of strategies for CSR. Adopting a systems view, the paper overcomes the limitations related to a reductionist view about advantages and results of CSR to call the attention on the conditions that should be met for ensuring the emergence of a shared approach to CSR.

In recognising the key role of business intelligence and big data analytics in influencing companies’ decision-making processes, this paper aims to codify the main phases through which companies can approach, develop and manage big data analytics.

By adopting a research strategy based on case studies, this paper depicts the main phases and challenges that companies “live” through in approaching big data analytics as a way to support their decision-making processes. The analysis of case studies has been chosen as the main research method because it offers the possibility for different data sources to describe a phenomenon and subsequently to develop and test theories.

This paper provides a possible depiction of the main phases and challenges through which the approach(es) to big data analytics can emerge and evolve over time with reference to companies’ decision-making processes.

This paper recalls the attention of researchers in defining clear patterns through which technology-based approaches should be developed. In its depiction of the main phases of the development of big data analytics in companies’ decision-making processes, this paper highlights the possible domains in which to define and renovate approaches to value. The proposed conceptual model derives from the adoption of an inductive approach. Despite its validity, it is discussed and questioned through multiple case studies. In addition, its generalisability requires further discussion and analysis in the light of alternative interpretative perspectives.

The reflections herein offer practitioners interested in company management the possibility to develop performance measurement tools that can evaluate how each phase can contribute to companies’ value creation processes.

This paper contributes to the ongoing debate about the role of digital technologies in influencing managerial and social models. This paper provides a conceptual model that is able to support both researchers and practitioners in understanding through which phases big data analytics can be approached and managed to enhance value processes.

With the aim to enrich the ongoing debate about healthcare management, the paper has a twofold intent: [1] to emphasise the interpretative contribution that intellectual capital can provide to a better understanding of the relevant role of patients in the healthcare sector and [2] to investigate the relationships between the three main dimensions of intellectual capital – human capital, relational capital and structural capital – and patient satisfaction in the healthcare sector.

The intellectual capital framework is contextualised in the healthcare sector, and the relationships among patient evaluations of human capital, relational capital and structural capital and patient satisfaction are tested via structural equation modelling (SEM) using primary data collected with reference to a sample of 561 Italian patients involved in post survey treatments in three Italian hospitals.

The role of intellectual capital in supporting a better understanding of processes and dynamics of patient satisfaction in the healthcare sector is underlined. The empirical research provides possible guidelines for recovery patients centrality in healthcare management.

The paper shows how an intellectual capital framework can support a better understanding and management of dynamics and processes through which patient centrality and satisfaction in healthcare management can be enforced.

Through the human resources (HR) and knowledge management (KM) perspective as human-centric processes, the aim of this study is to explore how companies’ engagement in diversity (DIV), inclusion (INC) and people empowerment (PEMP) policies influences companies’ organizational performance, to support organizations in the shift to the Industry 5.0 framework.

Combining the HR management and the KM-driven organizational culture, a conceptual model is proposed for explaining companies’ higher organizational performance. Proposed hypotheses are tested with reference to a set of listed international companies traced by Refinitiv on a five-year time horizon (2016–2020) through 24,196 firm-year observations.

This research shows that companies engaged in DIV policies, INC practices and PEMP through education have higher profitability and are more valued by capital markets’ investors.

This paper draws attention to the need to overcome the reductionist view of HR and rethink KM architecture to cope with the growing challenge of HR integration according to the Industry 5.0 paradigm.

Human and artificial intelligence has often been examined through competitive and oppositional lenses, which may no longer suffice in modern digital and knowledge-based societies. This paper advocates for a holistic perspective by integrating human and artificial intelligence within the conceptual framework of intellectual capital (IC).

Employing a deductive approach rooted in systems theory, this study reinterprets established dimensions of IC for the era of artificial intelligence.

Drawing inspiration from the Information Variety Model and the 4C Curve Model, both developed within the research framework of the Viable Systems Approach, a conceptual framework is proposed to transcend fragmented perspectives. It aims to provide researchers and practitioners with a comprehensive understanding of human–artificial intelligence relations within the realm of IC.

This paper contributes to the ongoing discourse on the potential evolution of IC in the era of artificial intelligence by presenting a multidisciplinary framework that challenges reductionist perspectives. It underscores the importance of systems thinking in reframing, analyzing and discussing key dimensions of IC in the context of the artificial intelligence era.

Analyzing the entrepreneurial ecosystem related to the ARCA consortium, the purpose of this paper is to study the relationships among the start-up firms inside an incubator.

Thanks to the adoption of the relationships concentric model and the density concentric model, the paper highlights the role of relational conditions for innovative projects in partnership among the incubated firms. Reflections herein are tested via a qualitative research approach based on a single case study: the ARCA consortium.

This research found that about 32 percent of relationships inside the incubator support the emergence of short-term relationships among the incubated firms. Furthermore, about 18 percent of the relationships support the emergence of strong collaborative strategies for the implementation of long-term relationships resulting in innovative pathways: innovative projects in partnership.

The most interconnected firms inside the incubator are those that play a central role also in the innovation pathway developing the higher number of innovative project in partnership. This finding emphasizes a correlation between collaborative relationships and innovation inside an incubator ecosystem.

This paper aims to recall the attention on a key challenge for customer relationship management related to the role of human agents in the management of the “switch point” for ensuring the effectiveness and efficiency in a customer-machine conversation.

This study contributes to the discussion about the firms’ approach to artificial intelligence (AI) in frontline interactions under the conceptual umbrella provided by knowledge management studies.

This paper provides a theoretical model for clarifying the role of human intelligence (HI) in AI-based frontline interactions by highlighting the relevance of the actors’ subjectivity in the dynamics and perceptions of customer-machine conversations.

An AI-HI complementarity matrix is proposed in spite of the still dominant replacement view.

The paper aims to enrich current debate about human–technology dichotomy in socio-economic settings by decoding and systematizing the main phases through which it has been approached in managerial and social studies.

A multi-interpretative framework is built thanks to the adoption of a qualitative approach inspired by the inductive logic, and for analyzing the historical evolution of the approach to human–technology dichotomy and for explaining them through an innovative conceptual model.

An innovative conceptual model is proposed for depicting connections and evolutions among the main four phases in the evolution of the approaches to human–technology dichotomy.

Reflections and conceptual model herein can support researchers in rereading the multiple theoretical and practical contributions provided with reference to human and technology relations in socio-economic settings.

The paper can support managers and entrepreneurs in defining and evaluating managerial approaches for efficiently enhancing human–technology interaction.

The paper proposes an innovative conceptual model based on a multi-interpretative framework for decoding the historical evolution of the approaches to human–technology dichotomy in business settings. New variables are added to the current debate about the topic for building an original interpretive viewpoint.

The purpose of this paper is to provide evidence regarding the contributions of ambidextrous workforces as a source of value for dynamic companies and organizations facing emerging market turbulence.

Using structural equation modeling, the paper analyses the data collected via a semi-structured questionnaire administered to a sample of 1,227 employees from 37 Italian small- to medium-sized enterprises to investigate the effect on companies’ economic performance of ambidextrous workforce-related elements such as study background, previous work experience, work flexibility and soft capabilities.

The research shows that multidisciplinary human resources’ study background, previous human resources’ work experience and human resources’ soft capabilities are positively linked to companies’ return on sales, providing indirect evidence about the role of ambidextrous workforces in supporting companies facing emerging market turbulence.

The research demonstrates the relevant role of human resources in supporting companies to better align themselves to the emerging social and economic variety.

Recognising the increasing relevance of digital platforms in socio-economic dynamics, the paper aims at investigating in which ways digital platforms can influence the economic performances of Italian small and medium enterprises (SMEs) actively engaged in foreign countries.

The paper adopts the interpretative lens provided by the exploration–exploitation dichotomy within current studies in knowledge management for defining knowledge-based factors able to influence the economic performance of Italian SMEs in foreign countries. An explorative study on secondary data related to 746 Italian SMEs is conducted for testing via structural equation modelling (SEM) the positive relationships between (1) SME's investment in information and communication technologies (ICT), (2) number of languages available for the SME's website and (3) number of languages available for SME's social pages and SME's return on sales (ROS) in foreign countries.

The results underline the key role of exploitation factors in terms of influence on SME's performance in foreign countries.

The paper enriches current studies about international marketing providing preliminary evidence about the key role of exploitation factors in influencing SME's performance in foreign countries.