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The purpose of this paper is to investigate the impact of early-stage maintenance clustering. Few researchers have previously studied early-stage maintenance clustering. Experience from product and service development has shown that early stages are critical to the development process, as most decisions are made during these stages. Similarly, most maintenance decisions are made during the early stages of maintenance development. Developing maintenance for clustering is expected to increase the potential of clustering.

A literature study and three case studies using the same data set were performed. The case studies simulate three stages of maintenance development by clustering based on the changes available at each given stage.

The study indicates an increased impact of maintenance clustering when clustering already in the first maintenance development stage. By performing clustering during the identification phase, 4.6% of the planned work hours can be saved. When clustering is done in the planning phase, 2.7% of the planned work hours can be saved. When planning is done in the scheduling phase, 2.4% of the planned work hours can be saved. The major difference in potential from the identification to the scheduling phase came from avoiding duplicate, unnecessary and erroneous work.

The findings from this study indicate a need for more studies on early-stage maintenance clustering, as few others have studied this.

Although risk culture is a key determinant for an effective risk management, identifying the risk culture of a firm can be challenging due to the abstract concept of culture. This paper proposes a novel approach that uses unsupervised machine learning techniques to identify significant features needed to assess and differentiate between different forms of risk culture.

To convert the unstructured text in our sample of banks' 10K reports into structured data, a two-dimensional dictionary for text mining is built to capture risk culture characteristics and the bank's attitude towards the risk culture characteristics. A principal component analysis (PCA) reduction technique is applied to extract the significant features that define risk culture, before using a K-means unsupervised learning to cluster the reports into distinct risk culture groups.

The PCA identifies uncertainty, litigious and constraining sentiments among risk culture features to be significant in defining the risk culture of banks. Cluster analysis on the PCA factors proposes three distinct risk culture clusters: good, fair and poor. Consistent with regulatory expectations, a good or fair risk culture in banks is characterized by high profitability ratios, bank stability, lower default risk and good governance.

The relationship between culture and risk management can be difficult to study given that it is hard to measure culture from traditional data sources that are messy and diverse. This study offers a better understanding of risk culture using an unsupervised machine learning approach.

The purpose of this paper is to provide a comprehensive framework that identifies thematic clusters and their interconnections within Global Talent Management (GTM), global careers and talent management (TM).

In this paper, this study conducted a co-citation analysis using bibliographic data to unveil the intellectual connections and relationships among thematic articles related to GTM sourced from the Web of Science.

This review highlights three key research themes: experiences working abroad, TM approaches and the complex nature of GTM as a living system.

The main limitation of this research is the sample itself. Content analysis based on the co-citation method resulted in some more recent releases being omitted.

The practical implications of the paper include providing a structured framework for understanding the complexities of GTM.

Research into the academic literature in this area is divided into various clusters, empirically demonstrating how GTM and global mobility are intertwined, revealing the need for us to more thoroughly comprehend the social ramifications of GTM practices and activities and the need to further analyse the influencing social aspects in a GTM strategy, like diversity, increased mobility and virtual reality.

The analysis revealed the emergence of three distinct thematic groups: (1) global work experiences, (2) TM approaches and (3) GTM.

This paper aims to elaborate on current research on fourth party logistics “4PL” by offering a taxonomy that provides a deeper understanding of 4PL service offerings, thus drawing clear frontiers between existing 4PL business models.

The authors collected data using semi-structured interviews conducted with 60 logistics executives working in 44 “4PL” providers located in France. Using automatic analysis of textual data, the authors combined spatial visualisation, clustering analysis and hierarchical descending classification to generate the taxonomy.

Two key dimensions emerged, allowing the authors to clearly identify and distinguish four 4PL business models: the level of reliance on interpersonal relationships and the level of involvement in 4PL service offering. As a result, 4PL providers fall under one of the following business models in the taxonomy: (1) The Metronome, (2) The Architect, (3) The Nostalgic and (4) The Minimalist.

The study focuses on investigating 4PL providers located in France; thus, future studies should explore the classification of 4PL business models across different cultural contexts and social structures.

The findings offer valuable managerial insights for logistics executives and clients of 4PL to better orient their needs, the negotiations and the contracting process with 4PLs.

Using a Lexicometric analysis, the authors develop taxonomy of 4PL service providers based on empirical evidence from logistics executives; the work addresses the existing confusion regarding the conceptualisation of 4PL firms with other types of logistical providers and the role of in/formal interpersonal relationships in the logistical intermediation.

The interest in sustainable human resource management has grown in the last decades. However, comprehensive, and systematic research concentrating on the evolution of this field, is still needed. The purpose of this study is to provide an overview and synthesis of the existing body of knowledge on human resource management (HRM) related to sustainability through a bibliometric study of articles published until 2022, identifying the most relevant research in this field. In the literature review, special attention is given to articles that link sustainable HRM to employees’ attitudes, identifying gaps and future research opportunities.

A bibliometric analysis and literature review was conducted over 105 documents obtained from the WoS database, using VOSviewer software program, from which 27 were selected for full-text reading. The applied database filters were: document type (article and early access); index (SSCI and SCI-expanded) and year (2019–2022).

The results show that: sustainable HRM literature is growing, especially after 2019; “Sustainability” is the journal with more publications; and England is the leading country. The network of co-occurrence of keywords analysis unveiled that performance, job satisfaction and behaviors are the most frequently studied topics in HRM.

For successful adoption of sustainable HRM practices, organizations should engage all staff comprehensively, focusing not only on consistent implementation but also on fostering a supportive organizational climate. This is vital for establishing a sustainable workplace where employees who strongly identify with the organization are less willing to leave it.

Through the Systematic Literature Review carried out on the articles published from 2019 to 2022, it was possible to identify opportunities for future research. These topics include employees' perceptions of the implementation of sustainable HRM practices in companies, as well as the impact of these practices on their attitudes and behaviors, taking into account the various HRM practices.

The past decade has seen growth in the number of businesswomen/mothers, known in the literature as mumpreneurs. As this is a recent, fragmented topic, no systematic literature review (SLR) has been carried out, justifying the objective defined here: scientific and bibliometric mapping of mumpreneurs.

To fulfil this aim, this SLR was supported by bibliometrics (performance analysis and scientific mapping) and the use of VosViewer software. A survey was conducted in Web of Science, and several documents were obtained dated between 2011 and 2021.

The results of this study show the existence of two clusters: Dilemma – motherhood and mumpreneurs, and the rise of the mumpreneur concept. The evidence obtained showed it is very important to address entrepreneurship from the perspective of entrepreneur-mothers, as at this stage of their lives, these women often find it difficult to reach a harmonious balance between work and family.

This study contributes to developing research in the area of entrepreneurship in general, and mumpreneurship in particular, through mapping the research done on the latter topic, as well as identifying its main contributions to theory and practice.

This study is innovative in underlining the relevance of mumpreneurship in the context of research in the area of entrepreneurship, and how this topic can be crucial to release women’s entrepreneurial potential.

This study aims to further develop the CLC stage/path’s identification model that distinguishes between path’s emergence (emergence stage), path’s development (growth stage), path’s sustainment (maturity stage), path’s decline (decline stage) and path’s transformation (renewal stage), and by applying it, define the current stage/path of the Demarcated Douro Region (DDR) cluster. The Port wine industry, which is the dominant industry of the DDR cluster, is at the maturity/decline stage – is the same for the cluster itself?

It is a case study with a longitudinal perspective based on the analysis of the dynamics of the parameters of cluster evolution using available secondary sources (cluster identity/brand; number of firms; number of employees; network; innovation; policies and regulations; and external markets – exports), especially addressing the past decade, that represent the stage of maturity/decline of the cluster’s dominant Port wine industry.

The conclusion is that since the 1990s the Demarcated Douro Region has gone through a “path transformation” where during the following 20 years new “anchors” for the cluster were gradually introduced, such as Doc Douro Wines, new forms of consumption of Port wine, tourism and olive oil. Since 2010 the cluster has entered a growth stage/(new) path’s development, where these “anchors” are in steady growth. The Douro brand is becoming more internationally recognized and established, the number of firms and employees is increasing, the network is restructuring with the creation of cluster-specific official institutions, innovation is especially reflected with increasing heterogeneity through diversification of the clusters into new activities and regulations and policies are supportive for expansion – all these parameters are indicating the rise of the new cycle for the cluster. Thus, the DDR cluster represents an attractive business environment and requires attention from regional policymakers to support the cluster’s development. Especially institutions have been highlighted as internal factors driving clusters growth, European integration as an external factor and firms’ strategies of diversification and internationalization as an appropriate de-locking mechanism for new path’s development.

This research contributes to the CLC theory by further developing and applying a CLC stage/path identification model. It provides a better understanding of the dynamics of the DDR cluster that diverge from its dominant industry life cycle, which is relevant for regional policies and firms’ strategies. This study has its limitations. It provides an exploratory application of the theoretical framework proposed, and consequently, no general conclusions are possible yet. More empirical studies with different clusters in different stages are necessary to test the framework.

These findings are useful to policymakers when designing their policies for cluster development but also for clusters’ entities and actors when making their strategic decisions as it allows based on the verification of the established parameter of CLC to identify its current stage/path of development.

The paper presents a theoretically grounded model for CLC identification and for the first time to the best of the authors’ knowledge applies it to a cluster case – the DDR cluster. This case applies the proposed model and illustrates its usefulness. The model provides the tools for a better understanding of cluster dynamics.

This chapter offers a comprehensive review the literature on authentic leadership (AL). The authors employ a bibliometric approach to identify, classify, visualise and synthesise relevant scholarly publications and the work of a core group of interdisciplinary scholars who are key contributors to the research on AL. They review 264 journal articles, adopting a clustering technique to assess the central themes of AL scholarship. They identify five distinct thematic clusters: authenticity in the context of leadership; structure of AL; social perspectives on AL; dynamism of AL; and value perceptions of AL. Velt and Sinkovics assert that these clusters will help scholars of AL to understand the dominant streams in the literature and provide a foundation for future research.

Despite enormous literature on Human Resource Management (HRM) practices in the context of Mergers and Acquisitions (M&As), researchers have not come up with a synthesis that integrates the role and importance of HRM practices during M&As. This study aims to identify, analyse and synthesise existing literature to discover associated HRM practices that facilitate organisational change during M&As.

Bibliometric analysis is performed using 473 research articles entailing 871 authors from 62 countries (published in Scopus and WoS listed journals), followed by a thematic cluster analysis using bibliographic coupling. The analysis is performed using different means as citation analysis, cluster analysis and keyword analysis to reveal the most significant publications, authors, keywords, trends and future research questions.

The results are primarily descriptive and aim at capturing a panoramic view of what was already written on the topic so far. The bibliometric analysis is conducted using different means like citation analysis, cluster analysis and keyword analysis to reveal the most significant publications, notable authors, keywords, current research trends and future research questions. Further, the bibliographic coupling analysis led to the identification of the following six clusters: (1) coping strategies during and post-M&As; (2) changes in individual and organisational identification during and post-M&As; (3) role of cultural and transformational leadership in M&As success; (4) HRM practices to develop employee capabilities post-M&As; (5) case studies and success stories of M&As; and (6) organisational readiness for M&As.

This study has theoretical and practical implications and suggests future research directions. The authors also propose an abstruse model for HRM practices during M&A process for further investigation.

This is the first bibliometric study to explore the vast extant literature in M&A research related to the role of HRM practices in the execution of successful M&As.

The unique employment status of gig workers as independent contractors and their impact on consumers provide an important opportunity for the current research to understand gig workers' perceptions of their employment and how that affects job performance outcomes. These gig workers serve as the frontline service providers for platforms like Airbnb hosts, Lyft drivers and Wag walkers performing customer-facing services. However, their status as gig workers, not traditional employees, presents challenges to platforms. The purpose of this research is to gain insights into the profiles of gig workers, examine the challenges platforms have in retaining high-performing workers and provide a research agenda on this important group of frontline service providers.

Incorporating variables deemed important in examining self-determination theory, a large-scale data collection via an online survey was administered, yielding 447 completed surveys. A two-step cluster analysis procedure was conducted to categorize sample respondents into four distinct groups.

Four groups emerged from the cluster analysis, labeled “Ambivalent Outsider,” “Competent Cog,” “Independent Insider” and “Committed Comrade.” The results suggest that there are significant differences across all variables and groups based on gig worker responses and self-reported customer satisfaction scores. The gig worker profiles developed are then utilized to formulate research propositions that are the basis for the research agenda presented.

The goal of many collaborative consumption platforms may be to hire Independent Insiders or Committed Comrades; however, that is difficult to attain with every hire. Thus, the segmentation results provide insights for companies seeking to hire, retain, and successfully motivate their workforce.

Given the freedom and flexibility afforded to gig workers, and the importance they have on the service experience for customers, understanding their own perceptions of employment and performance is critical to ensuring a positive experience for all parties. Research on collaborative consumption has largely focused on consumers or the management of freelance workers with only tangential applicability to gig work. This paper offers a comprehensive research agenda for gig worker management based on the typology of gig workers created.