Search results

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.

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.

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.

This paper aims to investigate materiality judgement providing insights, critiques and future research paths in light of the open debate on the role of materiality in corporate financial disclosure, highlighting potential connections and implications with sustainability and intellectual capital (IC) reporting.

The research presents an overview of the analysis of financial materiality, including new stimuli from recent studies and regulatory requirements for financial and non-financial reporting. Accordingly, this study used a systematic literature review (SLR) based on a combination of content, text and bibliometric analysis of materiality in accounting research studies, collecting data from the Scopus database as one of the most relevant repositories.

The SLR identified four relevant research trends, concerning: (1) the relevance of materiality principles in corporate disclosure; (2) financial reporting practices and materiality; (3) theories and approaches in defining financial materiality and (4) the existence of quantitative and qualitative thresholds in the materiality judgement.

The results provide theoretical and practical implications when comprehending the development of the concept of financial materiality in financial statements and whether they can be appropriate in reporting IC as well. We identified future research paths.

From a practical perspective, this study is useful for companies implementing financial materiality based on stakeholder engagement and improving their transparency in financial and non-financial reporting practices.

The research investigates if the process for assessing materiality is in line with the expectations of all stakeholders involved in financial and non-financial reporting.

This research is the first to investigate the scientific basis and applicability of the concept of financial materiality to sustainability and IC reporting.

Drawing on the microfoundations theory and rational choice sociology, this study aims to investigate knowledge-sharing microfoundations through knowledge sabotage behaviours in the workplace. As such, it aims to shed light on the adverse impact of knowledge sabotage on a knowledge-sharing climate.

As a quantitative deductive study, it is based on information collected from 329 employees of European companies by self-administered online surveys. Data validity and reliability has been assessed through a confirmatory factor analysis, and data analysis was carried out by using a covariance-based structural equation modelling technique.

The findings from the empirical investigation supported the baseline hypotheses of the multilevel conceptual model, which is the positive relationship between organizational trust and environmental knowledge sharing. Then, recurring to a microfoundational exploration, this study supports the mediating indirect effect of job satisfaction and knowledge sabotage in affecting knowledge sharing as a social outcome.

This study concurs to broaden knowledge-sharing awareness among scholars and practitioners, by focusing on knowledge sabotage as its most pernicious counterproductive behaviour. Furthermore, this research provides valuable guidance for the future development of research based on multilevel investigations.

This study builds on the need to explore the numerous factors that affect knowledge sharing in economic organizations, specifically focusing on knowledge sabotage. Adapting Coleman’s bathtub, the authors advance the first multilevel conceptual model used to unveil the knowledge-sharing microfoundations from the perspective of a counterproductive knowledge behaviour.

This research aims to determine how abusive leadership negatively affects knowledge workers' productivity and its potential influence on digital innovation. The present study also explores the mediating role of a knowledge worker’s competence between abusive leadership and knowledge worker productivity.

The study employed a quantitative research approach. Data were gathered through purposive sampling using 255 questionnaires completed by IT industry knowledge workers in Pakistan. The data were analyzed using the SMART-PLS 4.0 software.

The findings demonstrated a negative correlation between abusive leadership and knowledge worker productivity. Additionally, the relationship was partially mediated by knowledge worker competence. Furthermore, the study asserts that knowledge worker productivity has a substantial positive impact on digital innovation.

This study contributes substantially to the existing body of evidence on the productivity of knowledge workers and digital innovation by examining the interlocking effects of abusive leadership. It also implies the interpersonal mechanism of employee competence that connects abusive leadership with the productivity of knowledge workers and digital innovation. Thus, this study is one of the first inquiries to analyze this paradigm.

This work aims to assess the potential of a Bio-District as a model for applying the circular economy concerning the waste scope. It aims to understand the capability of organic farms to manage waste with a circular perspective, starting with the use of indicators that directly or indirectly impact the waste scope.

This study is based on previous work that identified and systematised the circular indicators of the agri-food sector within a dashboard. With this research as a basis, the indicators within the waste scope in the dashboard were extracted. Cross-linked indicators with an indirect connection to the waste scope were also systematised and tested in a case study. Primary and secondary data were used for the study. The primary data came from a semi-structured interview, and the secondary data were from official databases.

The work highlights two important results. The first allows the definition of a subclassification of indicators by product and organisation, extracting those with a cross-linked characteristic concerning the waste scope. Secondly, the indicators' application shows the farm's circular and waste valorisation potential within the Bio-District. The study also made it possible to test a new indicator, the “Potential Energy Biomass Recovery”, to measure the farm's potential to produce energy from waste.

This research proposes a new circular economy approach to evaluate waste management in the agri-food sector.

Global environmental and social threats challenge humans’ well-being and the survival of posterity. Industry 4.0 (I4.0) transformed the industry sector, enabling process automation and scalability, increasing manufacturers’ productivity, efficiency, and profitability, and supporting manufacturing innovation and firms’ competitive advantage. Despite this, the I4.0 paradigm, as currently conceived, does not fit for purpose in the context of the climate crisis and planetary emergency, nor does it address deep social tensions.

Therefore, a new revolution focusing on human and environmental needs is strongly required to address society’s economic and social problems. Combining digitalization and social purposes may address local, national, and international issues by involving a human-centered perspective in traditional business-oriented entrepreneurship.

Depending on the above, this chapter provides an in-depth understanding of Digital Entrepreneurship (DE), Digital Social Entrepreneurship (DSE), and how entrepreneurs may employ digital technologies to reach business and social aims.