Search results

This study aims to explore the impact of board size, board gender diversity and federation age on the likelihood of having a female chair in National Sports Federations (NSF).

A quantitative methodology compares 300 sports boards in five countries (Italy, Portugal, Spain, Turkey and the UK), using data collected from NSF’s websites.

The board size and federation age have no significant impact on having a female board chair when the countries and the percentage of female directors are included in the model. When the number of women is measured in absolute value rather than in relative terms, the only variable that predicts a woman chair is the country. When the model does not include country differences, the percentage of female directors is key in predicting a chairwoman, and when the number of women is used as a variable instead of the percentage, a board’s smaller size increases the odds of having a chairwoman.

There are some limitations to this study which we believe provide useful directions for future research. Firstly, the authors have not considered the role of gender typing in sports activities which explains the extent that women participate in specific sports (Sobal and Milgrim, 2019) and the related perception of such sports in society. The social representation of sports activities classified as masculine, feminine or gender-neutral can hypothetically influence women’s access to that specific federations’s leadership. The authors included the country factor only partially, as a control variable, as the social representation of sports usually goes beyond national boundaries.

This study has implications for sport policymakers and stakeholders, and for institutions such as the IOC or the European Union that implement equality policies. If the aim is to increase female presence in the highest position of a sports board and to achieve gender equality more generally, other policies need to be implemented alongside gender quotas for the sports boards, namely, those specifically related to the recruitment and selection of the sports board chairs (Mikkonen et al., 2021). For example, given the implications of critical mass and its ability to increase more female’s engagement then the role of existing chairs acting as mentors and taking initiative in this objective may be warranted. Furthermore, attention should be paid to the existing gender portfolio of each board and its subsequent influence on recruiting a female chair, regardless of the organization’s age. Knoppers et al. (2021) concluded that resistance to gender balance by board members is often related to discriminatory discourses against women. The normalization of the discourses of meritocracy, neoliberalism, silence/passivity about the responsibility of structures and an artificial defence of diversity emphasise that equality should not only be determined by women (Knoppers et al., 2021).

When countries are included in the model, the results suggest that the social representation of a female board member is different from that of a female board chair.

The originality of the study is that it shows the factors that constrain women taking up a chair position on NSFs. Theoretically, it contributes to existing literature by demonstrating how a critical mass of females on boards may also extend to the higher and most powerful position of chair.

This study problematizes the prevailing normative and managerial-dominated view of self-initiated employee ambassadorship on social media from a power perspective. The aim is to provide a more nuanced and critical understanding of the negative aspects of this phenomenon.

The empirical material encompasses qualitative interviews with employees from 14 organizations and Foucault’s concept of disciplinary discursive power to analyze which and how discourses exert power over employee communication on social media and what role visibility plays in it.

This study indicates that employee ambassadors’ social media communication is governed by two discourses that create complex tensions, where ambassadors constantly must negotiate between self-branding requirements and an authenticity paradox. These tensions intensify through visibility on social media, where employees strategize and situationally silence their communication through self-monitoring and self-surveillance practices. Conclusively, the findings also outline the need for further critical research to offer a deeper understanding of power relations that influence the communication practices of organizational members.

The paper contributes to a more nuanced understanding of self-initiated employee ambassadorship on social media and highlights disciplinary power relations that go beyond organizational borders.

The findings underscore that organizations need to address the critical aspects of self-initiated employee ambassadorship and act as facilitators to support employees in their navigation process.

This paper contributes a new critical power perspective on employee ambassadorship on social media.

Previous studies show that the implementation of gender equality encounters resistance in military organizations, but it is often invisible or seen as confined to anonymous structures or troubled individuals. This paper aims to show how the Swedish Armed Forces (SAF) use organizational principles to resist implementing gender equality measures.

The study is a qualitative analysis of discursive strategies in the SAF’s 2013–2018 annual reports to government.

The organizing principles of instrumentality and distance, while existing in parallel with gender equality efforts, actually pursue logics that prevents the SAF from implementing gender equality. The principle of instrumentality in this context means that gender equality in the SAF is of secondary interest to organizational members. The principle of distancing from the problem includes strategies that alienate female from male officers.

The contribution of this paper is the finding that the use of organizing principles represents conscious organizational resistance to gender equality efforts. This kind of use needs to be revealed and criticized to change military organizations.

Sarcasm is a linguistic expression that usually carries the opposite meaning of what is being said by words, thus making it difficult for machines to discover the actual meaning. It is mainly distinguished by the inflection with which it is spoken, with an undercurrent of irony, and is largely dependent on context, which makes it a difficult task for computational analysis. Moreover, sarcasm expresses negative sentiments using positive words, allowing it to easily confuse sentiment analysis models. This paper aims to demonstrate the task of sarcasm detection using the approach of machine and deep learning.

For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre-processed using natural language processing methods, and additional features were extracted and analysed. Several machine learning models, including logistic regression, ridge regression, linear support vector and support vector machines, along with two deep learning models based on bidirectional long short-term memory and one bidirectional encoder representations from transformers (BERT)-based model, were implemented, evaluated and compared.

The performance of machine and deep learning models was compared in the task of sarcasm detection, and possible ways of improvement were discussed. Deep learning models showed more promise, performance-wise, for this type of task. Specifically, a state-of-the-art model in natural language processing, namely, BERT-based model, outperformed other machine and deep learning models.

This study compared the performance of the various machine and deep learning models in the task of sarcasm detection using the data set of 1.3 million comments from social media.

The purpose of this paper is to identify the differences between Hungarian family-owned businesses (FOBs) and non-family-owned businesses (NFOBs) concerning the elements of SME competitiveness and financial performance.

The research covers the Hungarian data set of the Global Competitiveness Project (GCP, www.sme-gcp.org) of 738 (data collection between 2018 and 2020) non-listed SMEs, of which 328 were FOBs. The study uses the comprehensive, multidimensional competitiveness measurement of the GCP built on the resource-based view (RBV) and the configuration theory. Financial performance was captured with two composite indicators: short-term and long-term financial performance (LTFP). The comparative analysis between FOBs and NFOBs was conducted using binary logistic regression.

The results show that FOBs are more prone to focusing on local niche markets with higher longevity and LTFP than NFOBs. However, FOBs have lower innovation intensity and less organised administrative procedures. The most contradicting finding is that the FOBs’ higher LTFP is accompanied by significantly lower competitiveness than in the case of NFOBs.

This study goes beyond other GCP studies by including composite financial performance measures among the variables examined. The combination of performance-causing (resources and capabilities) and performance-representing (financial performance) variables provides a better understanding of the non-listed SMEs in terms of family ownership. The results help academia to enrich the RBV-competitiveness, the non-listed SME management and finance literature, and policymakers to design business development and support schemes. They also show future entrepreneurs the impact of family ownership on entrepreneurial success.

This study aims to conduct performance and clustering analyses with the help of Digital Government Reference Library (DGRL) v16.6 database examining the role of emerging technologies (ETs) in public services delivery.

VOSviewer and SciMAT techniques were used for clustering and mapping the use of ETs in the public services delivery. Collecting documents from the DGRL v16.6 database, the paper uses text mining analysis for identifying key terms and trends in e-Government research regarding ETs and public services.

The analysis indicates that all ETs are strongly linked to each other, except for blockchain technologies (due to its disruptive nature), which indicate that ETs can be, therefore, seen as accumulative knowledge. In addition, on the whole, findings identify four stages in the evolution of ETs and their application to public services: the “electronic administration” stage, the “technological baseline” stage, the “managerial” stage and the “disruptive technological” stage.

The output of the present research will help to orient policymakers in the implementation and use of ETs, evaluating the influence of these technologies on public services.

The research helps researchers to track research trends and uncover new paths on ETs and its implementation in public services.

Recent research has focused on the need of implementing ETs for improving public services, which could help cities to improve the citizens’ quality of life in urban areas. This paper contributes to expanding the knowledge about ETs and its implementation in public services, identifying trends and networks in the research about these issues.

The research paper examines the complex relationship between gamification, student engagement and academic performance in educational environments. The study employed a structural equation model that highlights important connections among key constructs within the educational setting.

This research aims to explore the connection between gamification, student engagement and academic performance in educational settings. The study employs various statistical techniques such as factor analysis, Kaiser–Meyer–Olkin (KMO), Bartlett’s test, component transformation matrix, correlation and regression analysis, descriptive statistics, ANOVA, coefficients and coefficient correlations, residual statistics and confirmatory factor analysis (CFA) to analyze the data.

It was found that active participation by the instructor and good time management skills have a positive impact on student engagement levels (β = 0.380, p < 0.001; β = 0.433 and p < 0.001). However, peer interaction does not significantly predict student engagement (β = −0.068 and p = 0.352). Additionally, there is a positive correlation between student engagement and performance (β = 0.280 and p < 0.001).

The study highlights the importance of innovative design to fully utilize gamification. Future research should consider design, user characteristics and educational context. The findings can guide informed decisions about gamification in education, fostering motivation and learning objectives.

The study presents a reliable tool for assessing student engagement and performance in educational settings, demonstrating high Cronbach’s alpha and robust reliability. It identifies student engagement and time management as significant predictors of Global Learning Outcome. The findings can inform decisions on implementing gamification in educational settings, promoting intrinsic motivation and aligning with learning objectives.

The research highlights the transformative impact of gamification on educational practices, highlighting its potential to enhance student experiences, motivate, promote diversity and improve long-term academic performance, highlighting the trend of integrating technology into education.

In today’s ever-changing education landscape, it is essential to incorporate innovative techniques to keep students engaged and enthusiastic about learning. Gamification is one such approach that has become increasingly popular. It is a concept that takes inspiration from the immersive world of games to enhance the overall learning experience.

This study seeks to examine the relationship between macroeconomic shock indicators, namely geopolitical risk (GPR), global economic policy uncertainty (GEPU) and financial stress (FS), and returns as well as volatilities on seven carefully selected stock markets in Africa. Specifically, the study intends to unravel the co-movement and interdependence between the respective macroeconomic shock indicators and each of the stock markets under consideration across time and frequency.

This study employed wavelet coherence approach to examine the strength and stability of the relationships across different time scales and frequency components, thereby providing valuable insights into specific periods and frequency ranges where the relationships are particularly pronounced.

The study found that GEPU, Financial Stress (FS) and GPR failed to induce significant influence on African stock market returns in the short term (0–4 months band), but tend to intensify in the long-term band (after 6th month). On the contrary, stock market volatilities exhibited strong coherence and interdependence with GEPU, FSI and GPR in the short-term band.

This study happens to be the first of its kind to comprehensively consider how the aforementioned macro-economic shock indicators impact stock markets returns and volatilities over time and frequency. Further, none of the earlier studies has attempted to examine the relationship between macro-economic shocks, stock returns and volatilities in different crisis periods. This study is the first of its kind in to employ data spanning from May 2007 to April 2023, thereby covering notable crisis periods such as global financial crisis (GFC) and the COVID-19 pandemic episodes.

The current study evaluated (1) characteristics of the community leadership development program associated with successful participant recruitment, (2) active ingredients that promoted fellow engagement and program completion and (3) how the program addressed blackness and racism.

Individual interviews were conducted with a representative subset of former program fellows.

Results indicated that offering training in small cohorts and matching fellows with individual mentors promoted program interest. Program strengths and unique ingredients included that the program was primarily led by people from the Black community, program malleability, and that the program was a partnership between fellows and leadership. Additionally, the program was responsive to fellows’ needs such as by adding a self-care component. Fellows also noted dedicated space and time to discuss race and racism. Results offer a unique theoretical perspective to guide leadership development away from the uniform or standardized approach and toward one that fosters diversity and equity in leadership.

Altogether, this work demonstrates how leadership development programs can be participant-informed and adapted to participants’ social and cultural needs.

The purpose of this paper is to find out which research topics and methods in information science (IS) articles are used in other disciplines as indicated by citations.

The study analyzes citations to articles in IS published in 31 scholarly IS journals in 2015. The study employs content analysis of articles published in 2015 receiving citations from publication venues representing IS and other disciplines in the citation window 2015–2021. The unit of analysis is the article-citing discipline pair. The data set consists of 1178 IS articles cited altogether 25 K times through 5 K publication venues. Each citation is seen as a contribution to the citing document’s discipline by the cited article, which represents some IS subareas and methodologies, and the author team's disciplinary composition, which is inferred from the authors’ affiliations.

The results show that the citation profiles of disciplines vary depending on research topics, methods and author disciplines. Disciplines external to IS are typically cited in IS articles authored by scholars with the same background. Thus, the export of ideas from IS to other disciplines is evidently smaller than the earlier findings claim. IS should not be credited for contributions by other disciplines published in IS literature.

This study is the first to analyze which research topics and methods in the articles of IS are of use in other disciplines as indicated by citations.