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This paper aims to use text mining methods to explore the similarities and differences between countries’ national digital transformation (DT) and Industry 4.0 (I4.0) policies. The study examines the applicability of text mining as an alternative for comprehensive clustering of national I4.0 and DT strategies, encouraging policy researchers toward data science that can offer rapid policy analysis and benchmarking.

With an exploratory research approach, topic modeling, principal component analysis and unsupervised machine learning algorithms (k-means and hierarchical clustering) are used for clustering national I4.0 and DT strategies. This paper uses a corpus of policy documents and related scientific publications from several countries and integrate their science and technology performance. The paper also presents the positioning of Türkiye’s I4.0 and DT national policy as a case from a developing country context.

Text mining provides meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, aligned with their geographic, economic and political circumstances. Findings also shed light on the DT strategic landscape and the key themes spanning various policy dimensions. Drawing from the Turkish case, political options are discussed in the context of developing (follower) countries’ I4.0 and DT.

The paper reveals meaningful clustering results on similarities and differences between countries regarding their national I4.0 and DT policies, reflecting political proximities aligned with their geographic, economic and political circumstances. This can help policymakers to comparatively understand national DT and I4.0 policies and use this knowledge to reflect collaborative and competitive measures to their policies.

This paper provides a unique combined methodology for text mining-based policy analysis in the DT context, which has not been adopted. In an era where computational social science and machine learning have gained importance and adaptability to political and social science fields, and in the technology and innovation management discipline, clustering applications showed similar and different policy patterns in a timely and unbiased manner.

This study aims to identify the determinants of adopting financial technology (FinTech) in Haryana (India). Further, the authors also compare the behavioural intention among male and female respondents to deliver a comprehensive understanding of the adoption of FinTech.

The current study contains two cross-sectional surveys about males and females. Study M is completed with (333) males, and Study F is conducted on (317) female users towards FinTech adoption. This study used “Partial least squares-structural equation modelling (PLS-SEM)” for data analysis.

The outcomes indicate that in both (Studies M and F), perceived usefulness and perceived ease of use substantially impact attitude and behavioural intention. Moreover, the results show that perceived value significantly influences, while perceived risks insignificantly influence behavioural intention. Surprisingly, relative advantage (in Study M) and trialability (in Study F) has insignificant impact on behavioural intention. Further, the outcomes also confirm that in both studies (M and F), attitude and behavioural intention substantially influence the actual use of FinTech.

To the best of the authors’ knowledge, this is the preliminary research on FinTech to inspect the role of gender in the technology adoption process. The adoption difference between males and females and the insightful result that the authors found help shed light on the uniqueness of the context. This study is also one of the initial to test three credible technology determinant theories and then offer a robust model for the actual use of FinTech that is to be used by both practitioners and researchers.

This research aims to analyze the literature on Quality 4.0 and pinpoint the essential factors contributing to its success. Additionally, the research aims to develop a framework that can be used to create a capable workforce necessary for the successful implementation of Quality 4.0.

By following a systematic approach, the authors could ensure that their literature review was comprehensive and unbiased. Using a set of pre-determined inclusion and exclusion criteria, the authors screened 90 research articles to obtain the most relevant and reliable information for their study.

The authors' review identified essential findings, including the evolution of literature in the field of Quality 4.0 and the systematization of previous literature reviews focusing on training and development. The authors also identified several training barriers to implementing Quality 4.0 and proposed a model for building a competent workforce using Kolb's experiential learning model.

The authors' research offers insights into the training barriers that must be considered when building a competent workforce. Using the framework proposed in the authors' research, consultants and managers can better integrate Quality 4.0 into their organizations.

The adoption of Quality 4.0 has significant social implications and is essential for advancing sustainability. It can improve efficiency, reduce waste, minimize environmental impacts and better meet the needs and expectations of stakeholders.

The authors' study stands out as one of the earliest reviews of the literature on Quality 4.0 to incorporate the theory-context-method (TCM) framework, allowing to provide unique insights into future research directions that had not been previously explored.

This study is motivated to provide a theoretically informed, data-driven assessment of the consequences associated with the participation of non-human bots in social accountability movements; specifically, the anti-inequality/anti-corporate #OccupyWallStreet conversation stream on Twitter.

A latent Dirichlet allocation (LDA) topic modeling approach as well as XGBoost machine learning algorithms are applied to a dataset of 9.2 million #OccupyWallStreet tweets in order to analyze not only how the speech patterns of bots differ from other participants but also how bot participation impacts the trajectory of the aggregate social accountability conversation stream. The authors consider two research questions: (1) do bots speak differently than non-bots and (2) does bot participation influence the conversation stream.

The results indicate that bots do speak differently than non-bots and that bots exert both weak form and strong form influence. Bots also steadily become more prevalent. At the same time, the results show that bots also learn from and adapt their speaking patterns to emphasize the topics that are important to non-bots and that non-bots continue to speak about their initial topics.

These findings help improve understanding of the consequences of bot participation within social media-based democratic dialogic processes. The analyses also raise important questions about the increasing importance of apparently nonhuman actors within different spheres of social life.

The current study is the first, to the authors’ knowledge, that uses a theoretically informed Big Data approach to simultaneously consider the micro details and aggregate consequences of bot participation within social media-based dialogic social accountability processes.

Romanian women migrant entrepreneurs (RWMEs) are amongst the largest EU migrant communities in the UK and make significant socioeconomic contributions to both their host and origin nations, but academic research and policy discussions have ignored them. Intersectionality raises complex contextual issues that require comprehensive examination and inclusive policies and programmes. This study is aimed at exploring how Romanian women migrant entrepreneurs experience their transnational intersectional journeys of belonging, as they create, negotiate and enact their intersectional identities of the country of origin, gender and being entrepreneurs in the UK and Romania.

This Interpretative Phenomenological Analysis (IPA) draws on draws upon Crenshaw's (1991) intersectional and Social Identity theories (Tajfel and Turner, 1979) to investigate how nine interviewed RWMEs have experienced their transnational journeys of acculturative belonging in the UK and Romania.

The study findings show how RWMEs undo and negotiate their intersecting identities to adhere to socio-cultural standards in both their host and native nations. In the UK, they feel empowered as women entrepreneurs, but in patriarchal Romania, their entrepreneurial identity is revoked, contradicting the prescribed socio-cultural roles.

This study responds to the call regarding inequalities in entrepreneurship opportunities (Vershinina et al., 2022). By focussing on the understudied community of RWMEs and exploring new intersectional and transnational contextual insights, it contributes to the literature and practice of migrant entrepreneurship. These empirical findings are essential for the development of evidence-based, disaggregated entrepreneurship programmes and policies.

This study responds to the call regarding inequalities in entrepreneurship opportunities (Vershinina et al., 2022). By focussing on the understudied community of RWMEs and exploring new intersectional and transnational contextual insights, it contributes to the literature and practice of migrant entrepreneurship. These empirical findings are essential for the development of evidence-based, disaggregated entrepreneurship programmes and policies.

The purpose of this paper is to provide answers regarding the factors that motivate or discourage the quadruple helix (QH) stakeholders and the wider public in citizen science (CS) activities. The research reveals a current overview of the perceptions, attitudes, concerns and motivation with regard to development of CS ecosystem in four countries: Greece, Lithuania, the Netherlands and Spain.

The researchers deploy a mixed methodology, entailing an in-depth literature review and a large-scale quantitative survey (approximately 2,000 citizens) targeting QH stakeholders and general public from the local national ecosystems. The results contain both descriptive statistics and statistical analysis per country. After the comprehensive overview of drivers and barriers regarding the participation in CS activities in general, the focus is narrowed down on the engagement motivation of different QH stakeholders and the differences in enabling/hindering factors at the local ecosystems.

Depending on the country and the pre-existing level of CS maturity, the results provide a complicated network of factors that unlock or block participation in CS activities. These factors include, to name a few, political maturity, civic engagement, technological infrastructures, economic growth, culture of stakeholder collaboration, psychological stimulus and surplus of resources. The implications of the findings necessitate the alignment of the envisioned CS ecosystem with the local dynamics in each country.

The quantitative nature of the survey method, limited sample size and only four countries context are noted as limitations of the study and offer future research potential for longitudinal settings and mixed-methods studies.

The results contribute to the wider literature on CS that focuses on perspectives, possibilities and differences in local contexts with respect to the public engagement by developing CS ecosystem. At the same time, its added value lies in the overall practical proposition, and how the latter can effectively and efficiently attract and retain different stakeholder groups and citizens, under a collaborative approach.

The research questions probe into the heart of participatory learning’s scholarly landscape. They inquire about historical trends, shifts in research interest, and regional contributions, highlighting the global reach of participatory learning discourse. The study also reaches into the most cited papers, emphasizing their pivotal role in shaping the field’s trajectory.

The research design of our study involves a retrospective analysis focused on the topic of participatory learning in education. A retrospective analysis is a methodological approach that entails examining existing literature, data, and publications within a specific field to identify trends, patterns, and insights over a defined period. In the context of participatory learning in education, this research design allows us to gain a comprehensive understanding of the evolution, contributions, and emerging directions within this pedagogical approach.

The culmination of this study lies in formulating 75 thought-provoking future research questions. These questions are designed to guide the future trajectory of participatory learning research, addressing existing gaps and propelling the field toward new horizons. The findings of the study contribute to a panoramic view of participatory learning’s evolution, global impact, and potential for reshaping education. It is a compass for researchers, educators, and policymakers navigating the intricate landscape of participatory learning in education.

Themes and topics are thoroughly explored, unrevealed the multidimensional nature of participatory learning research. The investigation spans time, revealing enduring themes while unveiling emerging areas of inquiry that capture the attention of researchers and practitioners. Current trends and focus areas are scrutinized, offering insights into the ever-evolving scholarly pursuits within participatory learning.

This comprehensive study investigates the evolution and impact of research on participatory learning in education from 1995 to 2023. The research objectives encompass a broad spectrum, including trend analysis, geographical distribution assessment and identification of influential papers, thematic exploration, and the formulation of future research questions. Through a meticulous examination of published literature, this study aims to shed light on the development of participatory learning as a transformative educational approach.

This study’s originality lies in its comprehensive analysis of participatory learning in education from 1995 to 2023, revealing temporal trends, global contributions, influential papers, thematic nuances, and emerging trends. By amalgamating these dimensions, it offers a holistic view of participatory learning’s evolution, impact, and future directions, enriching the understanding of this transformative educational approach and guiding further research and practice.

Through the reconstruction of the events of some foreign entrepreneurs who worked in the territory of the Italian city of Bari in the first half of the 19th century, this paper aims to analyze the role of entrepreneurial migration in the economic development of Apulia land in this period.

This study adopts a theoretical framework that combines the concept of mixed embeddedness in a multifocal perspective, with the model of the diffusion of innovation focusing on the role of the so-called agency of actors, and of the network, in the dissemination of innovation. The theoretical framework is applied to multiple case studies to compare the evidence that emerged from the simultaneous analysis of several situations.

By analyzing how innovations have spread within the network of entrepreneurs of that time, it is possible to identify some relevant aspects related to the mechanisms of dissemination of innovations in the context of entrepreneurial migration. Specifically, the opportunity structure is intended in an even broader sense than indicated in the classic approach to mixed embeddedness: it is considered as the result of the joint interaction of the political, institutional and economic context of several places, and the behavioral dynamics of several groups.

Due to the specific method chosen, the outcomes of the research might apply to a narrow context. Therefore, the results need to be tested and confirmed in further empirical studies, and by applying multiple research methods.

Findings are useful and significant in the analysis of the link that exists between the diffusion of innovations and migrant entrepreneurship, and then the conclusions can be applied and extended to the current phenomenon of migration-related innovations, with specific reference to developing countries.

Findings can be applied and extended to the current phenomenon of migration-related innovations and highly skilled migration, with specific reference to developing countries.

This paper contributes to shed new light on the contextual and multifocal factors that influence the development of innovations in the networks of migrant entrepreneurship, in a specific historical period and a specific context. Combining social, human and financial capital with the wider opportunity structure, this study also provides a comprehensive understanding of the modalities through which migrant and high-skilled entrepreneurs could innovate.

A small-world network is a type of network structure in which nodes are highly clustered and at short distances without being directly linked. This article analyzes whether the network of interlocking directorates among the largest Brazilian corporations follows a small-world network structure and if the small-world properties (high clustering and short distance between nodes) influence the occurrence of M&A at the domestic and international level.

The authors tested hypotheses regarding the relationship between small-world network properties and M&A based on a sample of large publicly-listed corporations in Brazil for the time series of 2000–2015 and using network analysis and regression techniques (probit and OLS).

The results show that while the Brazilian corporate network fits the small-world features of high clustering and short path lengths, only the distance among connected firms has a significant effect on international M&A: the shorter the distance between firms, the more likely firms undertake M&A abroad. Moreover, being integrated into the main component has a significant positive effect on national and international M&A. These findings suggest that the information and knowledge to undertake M&A can be better acquired by belonging to large business communities and not local cohesive clusters.

This research contributes to theories and ongoing debates about the network effects on organizational decisions and the determinants of M&A in emerging markets. In addition, this is the first study to analyze the impact of small-world networks on international M&A while controlling for country-level variables.

The lack of knowledge has hindered the successful implementation of lean in the construction industry. This has alarmed the need for lean learning practices. Out of numerous models, the learning-to-learn sand cone model received a wider acknowledgment for learning practices. Thus, this study aims to propose a learning-to-learn sand cone model integrated lean learning framework for the construction industry.

The research adopted an interpretivism stance. A qualitative research approach was adopted for the study. Consequently, fifteen (15) semi-structured interviews and document reviews were carried out to collect data in three (3) cases selected through purposive sampling. Code-based content analysis was used to analyse the data.

Fifty-two (52) sub-activities pertaining to nine lean learners at each stage of the lean learning procedure were identified. The most significant practices in the lean learning procedure to continuously improve lean learning in the organisation were maintaining records, providing a performance update to senior management and preparing and distributing several hierarchical manuals for all levels of staff to aid in the implementation of lean approaches.

The findings of the research can be aided to successfully implement lean by following the identified sub-activities via various parties within the organisation. The proposed lean learning framework opens several research areas on lean learning in the construction industry. This is the first research to uncover a lean learning framework in the construction industry rather than at the educational institute level.