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This paper aims to propose an interpretive framework to understand how machine learning (ML) affects the way companies interact with their ecosystem and how the introduction of digital technologies affects the value co-creation (VCC) process.

This study bases on configuration theory, which entails two main methodological phases. In the first phase the authors define the theoretically-derived interpretive framework through a literature review. In the second phase the authors adopt a case study methodology to inductively analyze the theoretically-derived domains and their relationships within a configuration.

ML enables multi-directional knowledge flows among value co-creators and expands the scope of VCC beyond the boundaries of the firm-client relationship. However, it determines a substantive imbalance in knowledge management power among the actors involved in VCC. ML positively impacts value co-creators’ performance but also requires significant organizational changes. To benefit from VCC via ML, value co-creators must be aligned in terms of digital maturity.

The paper answers the call for more theoretical and empirical research on the impact of the introduction of Industry 4.0 technology in companies and their ecosystem. It intends to improve the understanding of how ML technology affects the determinants and the process of VCC by providing both a static and dynamic analysis of the topic.

This paper aims to give an integrated framework for analysing the main opportunities and threats related to the exploitation of Big Data (BD) technologies within intellectual capital (IC) management.

By means of a structured literature review (SLR) of the extant literature on BD and IC, the study identified distinctive opportunities and challenges of BD technologies and related them to the traditional dimensions of IC.

The advent of BD has not radically changed the risks and opportunities of IC management already highlighted in previous literature. However, it has significantly amplified their magnitude and the speed with which they manifest themselves. Thus, a revision of the traditional managerial solutions needed to face them is required.

The developed framework can contribute to academic discourse on BD and IC as a starting point to understanding how BD can be turned into intangible assets from a value creation perspective.

The framework can also represent a useful decision-making tool for practitioners in identifying and evaluating the main opportunities and threats of an investment in BD technologies for IC management.

The paper responds to the call for more research on the integration of BD discourse in the fourth stage of IC research. It intends to improve this understanding of how BD technologies can be exploited to create value from an IC perspective, focussing not only on the potential of BD for creating value but also on the challenges that it poses to organizations.

Drawing on expectancy theory, this research explores how and when volunteers’ motivational drives for volunteering relate to organizational policies and practices. The paper analyses four areas of motivational association – affiliation, beliefs, career development and egoistic motives – together with organizational human resource (HR) policies and practices.

The study used a qualitative approach and through 17 interviews of the volunteer managers associated with 13 non-profit organizations (NPOs) examined that how through HR policies and practices, an NPO efficiently taps motivational drives of volunteers and maintains their spirit of volunteering.

The findings of the study indicated that the same behaviour may serve different functions for different individuals. Most of the motivational drives need to be tapped with specific tasks and events to become a source of fulfilment for volunteers, this plays a vital role in their decisions to continue volunteering. NPOs’ HR practices without volunteers’ motivation cannot serve any purpose. In the same vein, volunteers’ motivation cannot sustain for a longer period if it is not properly linked with organizational HR practices.

The research findings may lack generalizability because of the selected research approach.

A great part of existing research, not previously captured in literature, is focussed on the assessment of the motivational underpinnings with respect to HR policies and practices.

The purpose of this paper is to identify some of the critical organizational support factors and efforts that facilitate better employee participation in corporate volunteering (CV) programs. There is a growing interest to understand the role of organization in enhancing better employee participation in volunteering programs.

The authors conducted an empirical investigation with (n = 461) employee volunteers, who participated in company sponsored volunteering programs. The authors tested the hypothesized relationship using structural equation modelling (SEM).

The SEM results indicate that cultural fit, organizational CV communication and implementation of CV programmes facilitate better employee participation.

This study provides insights for organizations in terms of increased internal communication and alignment of organizational values with CV programmes to attract better employee participation in volunteering programmes.

This study contributes to the literature on the phenomenon of employee volunteering by examining various organizational efforts that facilitate better employee participation in volunteering programmes.

This study defines a three-angled research plan to intensify the knowledge and development undergoing in the retail sector. It proposes a theoretical framework of the customer journey to explain the customers' intent to adopt artificial intelligence (AI) and machine learning (ML) as a protective measure for interaction between the customer and the brand.

This study presents a research agenda from three-dimensional online search, ML and AI algorithms. This paper enhances the readers' understanding by reviewing the literature present in utilizing AI in the customer journey and presenting a theoretical framework.

Using AI tools like Chatbots, Recommenders, Virtual Assistance and Interactive Voice Recognition (IVR) helps create improved brand awareness, better customer relationships marketing and personalized product modification.

This study intends to identify a research plan based on investigating customer journey trends in today's changing times with AI incorporation. The research provides a novel model framework of the customer journey by directing customers into different stages and providing different touchpoints in each stage, all supported with AI and ML.