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This study aims to provide an overview of the past two decades of lifelong learning (LLL) policies for enhancing employability and reduce social exclusion in young people of European countries through the development of the so-called LLL key-competences.

Built on a quasi-systematic review, this contribution explores traditional and new methods for promoting the LLL transition, and then employability, in young adults (e.g. apprenticeship, vocational training, e-learning, etc.).

It argues the need to identify all the possible approaches able to support policymakers, as they can differently impact key-competence development.

Finally, based on the consolidated EU policy experience, we propose a strategy of implementation of the LLL programmes that facilitates the institutions’ decision processes for policy-making through the use of decisional support system.

Due to the recent development of Big Data and artificial intelligence (AI) technology solutions in customer relationship management (CRM), this paper provides a systematic overview of the field, thus unveiling gaps and providing promising paths for future research.

A total of 212 peer-reviewed articles published between 1989 and 2020 were extracted from the Scopus database, and 2 bibliometric techniques were used: bibliographic coupling and keywords’ co-occurrence.

Outcomes of the bibliometric analysis enabled the authors to identify three main subfields of the AI literature within the CRM domain (Big Data and CRM as a database, AI and machine learning techniques applied to CRM activities and strategic management of AI–CRM integrations) and capture promising paths for future development for each of these subfields. This study also develops a three-step conceptual model for AI implementation in CRM, which can support, on one hand, scholars in further deepening the knowledge in this field and, on the other hand, managers in planning an appropriate and coherent strategy.

To the best of the authors’ knowledge, this study is the first to systematise and discuss the literature regarding the relationship between AI and CRM based on bibliometric analysis. Thus, both academics and practitioners can benefit from the study, as it unveils recent important directions in CRM management research and practices.

The purpose of this research is to investigate the use of Twitter in business as a medium for knowledge sharing and to crowdsource information to support innovation and enhance business relationships in the context of business-to-business (B2B) marketing.

This study uses a combination of methodologies for gathering data in 52 face-to-face interviews across five countries and the downloaded posts from each of the interviewees' Twitter accounts. The tweets were analysed using structural topic modelling (STM), and then compared to the interview data. This method enabled triangulation between stated use of Twitter and respondent's actual tweets.

The research confirmed that individuals used Twitter as a source of information, ideas, promotion and innovation within their industry. Twitter facilitates building relevant business relationships through the exchange of new, expert and high-quality information within like-minded communities in real time, between companies and with their suppliers, customers and also their peers.

As this study covered five countries, further comparative research on the use of Twitter in the B2B context is called for. Further investigation of the formalisation of social media strategies and return on investment for social media marketing efforts is also warranted.

This research highlights the business relationship building capacity of Twitter as it enables customer and peer conversations that eventually support the development of product and service innovations. Twitter has the capacity for marketers to inform and engage customers and peers in their networks on wider topics thereby building the brand of the individual users and their companies simultaneously.

This study focuses on interactions at the individual level illustrating that Twitter is used for both customer and peer interactions that can lead to the sourcing of ideas, knowledge and ultimately innovation. The study is novel in its methodological approach of combining structured interviews and text mining that found the topics of the interviewees' tweets aligned with their interview responses.

This paper aims to provide and empirically test a conceptual model in which artificial intelligence (AI), knowledge management processes (KMPs) and supply chain resilience (SCR) are simultaneously considered in terms of their reciprocal relationships and impact on manufacturing firm performance (MFP).

In the study, six hypotheses have been developed and tested through an empirical survey administered to 120 senior executives of Italian manufacturing firms. The data analysis has been carried out via the partial least squares structural equation modelling approach, using the Advanced Analysis for Composites 2.0 variance-based software program.

Using a conceptual model validated using an empirical survey, the study sheds light on the relationships between AI, KMPs and SCR, as well as their impacts on MFP. In particular, the authors show the positive effects of the adoption of AI on KMPs, as well as the influence of KMPs on SCR and MFP. Finally, the authors demonstrate that KMPs act as a mediator through which AI affects SCR and MFP.

This study highlights the critical role of KMPs for manufacturing firms that can deploy AI to stimulate KMPs and through attaining a high level of the latter might succeed in enhancing both their SCR and MFP.

This study demonstrates that manufacturing firms interested in properly applying AI to ameliorate their performance and resilience must carefully consider KMPs as a mediator mechanism.

The purpose of this paper is to develop, implement, test and further enhance a framework for measuring organizational change initiatives.

The conceptual part of the framework is based on the structured analysis of existing literature. The framework was further developed during an action research (AR) study where the authors developed, implemented, evaluated and improved the measurement system for organizational change initiatives.

The academic literature is rich in conceptual articles providing required characteristics of a “good” measurement system and frameworks for how organizations should measure performance. However, academia provides less empirical evidence of how these performance measurement systems can be implemented, evaluated and improved. In this paper, the authors present a study where the developed measurement system has been implemented, evaluated and improved. The results in terms of how the actual framework worked as well as the response from the case organizations are equally positive.

The framework has been implemented in two different, major change initiatives in one case organization. While the results are truly encouraging, the framework needs to be further tested and refined in more organizations.

There is a gap between academic perception and practical reality regarding how organizations should measure performance in general as well as measuring organizational change initiatives. The presented, and empirically tested, framework measures both the results of the change initiative (effectiveness) the actual change process (efficiency) as well as the perception of the change initiative and process from different key stakeholders.

This is the first developed, implemented and further improved measurement system for organizational change which measures both the efficiency and effectiveness of the change initiative (process).

In spite of the merits of artificial intelligence (AI) in marketing and social media, harm to consumers has prompted calls for AI auditing/certification. Understanding consumers’ approval of AI certification entities is vital for its effectiveness and companies’ choice of certification. This study aims to generate important insights into the consumer perspective of AI certifications and stimulate future research.

A literature and status-quo-driven search of the AI certification landscape identifies entities and related concepts. This study empirically explores consumer approval of the most discussed entities in four AI decision domains using an online experiment and outline a research agenda for AI certification in marketing/social media.

Trust in AI certification is complex. The empirical findings show that consumers seem to approve more of non-profit entities than for-profit entities, with the government approving the most.

The introduction of AI certification to marketing/social media contributes to work on consumer trust and AI acceptance and structures AI certification research from outside marketing to facilitate future research on AI certification for marketing/social media scholars.

For businesses, the authors provide a first insight into consumer preferences for AI-certifying entities, guiding the choice of which entity to use. For policymakers, this work guides their ongoing discussion on “who should certify AI” from a consumer perspective.

To the best of the authors’ knowledge, this work is the first to introduce the topic of AI certification to the marketing/social media literature, provide a novel guideline to scholars and offer the first set of empirical studies examining consumer approval of AI certifications.

This study aims to estimate the value of the impact from digital transformation (DX) focusing on its automation effect, looking at the time and cost savings coming from the substitution effect with an adoption of digital technologies. For example, cloud and artificial intelligence technologies such as ChatGPT have the potential to change ways of working, substituting and replacing several of the tasks that are currently carried out by public administration (PA) employees and labor processes underpinning PA services.

The paper outlines a new framework to estimate the potential impact of DX on the public sector. The authors apply this framework to estimate the value of the impact of DX on the Italian PA, defining the latter by the collection of the value of its labor (i.e. PA workforce salaries) and by the collection of the value of its outputs (i.e. public services’ costs).

This study ultimately maps out the magnitude and trends of how likely the PA occupations and services could be substituted in a wider process of DX. To do this, the authors apply their framework to the Italian PA, and they triangulate secondary data collection, from official accounts of the Italian Ministry of Economics and the National Statistical Institute, with methodological antecedents from the UK Office for National Statistics and experts’ insights. Results provide a snapshot on the type and magnitude of PA jobs and services projected to be affected by automation over the next 10 years.

To the best of the authors’ knowledge, this paper provides for the first time an approach to estimate the value of the impact of DX on the public sector in a data-constrained environment – or in the lack of the required primary data. Once applied to the Italian PA, this approach provides a granular map of the automatability of each of the PA occupations and of the PA services. Finally, this paper mentions preliminary insights on potential challenges related to equity in public sector jobs and implications on recruitment processes.

To assess the effectiveness of an integrated care program for post-acute care of stroke patients, the return home program (RHP program), deployed in Barcelona (North-East Spain) between 2016 and 2017 in a context of health and social care information systems integration.

The RHP program was built around an electronic record that integrated health and social care information (with an agreement for coordinated access by all stakeholders) and an operational re-design of the care pathways, which started upon hospital admission instead of discharge. The health outcomes and resource use of the RHP program participants were compared with a population-based matched control group built from central healthcare records of routine care data.

The study included 92 stroke patients attended within the RHP program and the patients' matched controls. Patients in the intervention group received domiciliary care service, home rehabilitation, and telecare significantly earlier than the matched controls. Within the first two years after the stroke episode, recipients of the RHP program were less frequently institutionalized in a long-term care facility (5 vs 15%). The use of primary care services, non-emergency transport, and telecare services were more frequent in the RHP group.

The authors' analysis shows that an integrated care program can effectively promote and accelerate delivery of key domiciliary care services, reducing institutionalization of stroke patients in the mid-term. The integration of health and social care information allows not only a better coordination among professionals (thus avoiding redundant assessments) but also to monitor health and resource use outcomes of care delivery.

This literature review explores the potential of gamification in workplace learning beyond formal training. The study also highlights research gaps and opportunities for scholars to develop new theories and methodologies to enhance the understanding and application of gamification in workplace learning. It provides guidance for managers to use gamification to enhance learning and engagement. Ultimately, this review presents gamification as a promising field of study to increase individual and organizational performance.

Literature review of 6625 papers in the timeframe 1990–2020, with an update to include papers published in 2023.

This article examines the impact of gamification beyond formal learning and its potential to enhance employee productivity and well-being in the workplace. While there has been extensive research on gamification in formal learning contexts, little is known about its impact on informal learning. The study argues that the context of gamification is crucial to extending its effects and discusses the role, antecedents and consequences of game design elements in the workplace. The article also explores how the learning context relates to employee learning during work. Further research is necessary to investigate the impact of individual characteristics on work experience and performance.

Intended contribution of the present study is the development of a theoretical framework exploring the benefits of gamification in a work context.

For practicing managers, this paper shows how to use gamification to increase workplace learning and employee engagement, not just in the context of formal learning—as some companies already do today—but also systematically, in the context of informal learning.

This study explores the impact of gamification on informal workplace learning and emphasizes the significance of the context of gamification in extending its effects to improve individual and organizational performance.

The paper aims to understand how the spread of coronavirus disease 2019 (COVID-19) influenced public employees' perception of smart working and how this approach was used during the pandemic. The authors asked about smart working's positive and negative aspects and how these changed during the pandemic.

The authors explored the strengths and weaknesses of smart working before and after COVID-19. The authors interviewed 27 Italian public employees who had experienced smart working before the pandemic. The questions and discussion aimed to broadly explore the strengths and weaknesses of smart working and smart working's impact on working performance, work relationships and work–life balance (WLB).

Smart working had a widespread and positive impact on organizational flexibility. Smart working improved the response and resilience of Italian public organizations to the pandemic. However, some critical factors emerged, such as the right to disconnect and the impact on WLB.

The authors suggest that the pandemic exposed the need for public administrations to consolidate work flexibility practices, such as smart working, by paying more attention to the impact of these practices on the whole organization and human resources management (HRM) policies and practices.

This study makes an important contribution to the literature on the public sector by discussing the positive and negative aspects of smart working. The study also provides managerial and policy implications of the use of smart working in public administrations.