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This research investigates how the value creation interests and activities of different stakeholder groups within one open source software (OSS) project influence the project's development over time.

The authors conducted a case study of OpenSimulator using textual and thematic analyses of the initial four years of OpenSimulator developer mailing list to identify each stakeholder group and guide our analysis of their interests and value creation activities over time.

The analysis revealed that while each stakeholder group was active within the OSS project's development, the different groups possessed complementary interests that enabled the project to evolve. In the formative period, entrepreneurs were interested in the software's strategic direction in the market, academics and SMEs in software functionality and large firms and hobbyists in software testing. Each group retained its primary interest in the maturing period with academics and SMEs separating into server- and client-side usability. The analysis shed light on how the different stakeholder groups overcame tensions amongst themselves and took specific actions to sustain the project.

The authors extend stakeholder theory by reconceptualizing the focal organization and its stakeholders for OSS projects. To date, OSS research has primarily focused on examining one project relative to its marketplace. Using stakeholder theory, we identified stakeholder groups within a single OSS project to demonstrate their distinct interests and how these interests influence their value creation activities over time. Collectively, these interests enable the project's long-term development.

This study aims to evaluate the issue of household food waste in Greece, with an emphasis on assessing the level of awareness and key behaviours among consumers. Moreover, the study focuses on examining consumer behaviours related to food waste and identifying distinct consumer profiles that can provide valuable insights into the issue in order to uncover unique behavioural factors and offer targeted interventions to curb food waste in the country.

A nationwide survey was conducted in Greece using a structured online questionnaire, which was sent to 1,270 participants, through the snowball technique. However, due to some incomplete responses, only 1,238 of the responses were considered suitable for analysis. Common descriptive statistics were used to sketch the respondents' profiles, and a non-hierarchical K-means cluster analysis was performed to identify distinct subgroups in the sample.

The study revealed a significant level of food waste awareness among Greek consumers. The cluster analysis identified four distinct consumer groups and substantial differences among them. Notably, sociodemographic analysis underscored a pronounced inclination towards food wastage among younger individuals. Additionally, each cluster's attributes, including their environmental awareness, shopping behaviours meal-planning tendencies and propensity for excess purchases, were examined. Consequently, this study underscored the imperative for targeted informational campaigns tailored for consumer segmentation, offering a pathway to identify prospective interventions conducive to the promotion of sustainable food-consumption practices.

The originality and value of this work lie in its unique focus on addressing the significant issue of household food waste within the context of Greece. What sets this study apart is the application of non-hierarchical K-means cluster analysis (which allowed the authors to identify distinct consumer profiles), a method not widely utilised in the Greek context. By filling this knowledge gap, this study offers crucial insights that can inform targeted interventions aimed at reducing food waste, in alignment with global sustainability initiatives such as the United Nations Agenda 2030 and the European Union's “Farm to Fork” strategy. Additionally, this study contributes to the efforts to provide innovative solutions to prevent household food waste and foster a sustainable future in an ever-changing international environment marked by various crises

The concept of productivity is central to performance management and decision-making, although it is complex and multifaceted. This paper aims to describe a methodology based on the use of Big Data in a cluster analysis combined with a data envelopment analysis (DEA) that provides accurate and reliable productivity measures in a large network of retailers.

The methodology is described using a case study of a leading kitchen furniture producer. More specifically, Big Data is used in a two-step analysis prior to the DEA to automatically cluster a large number of retailers into groups that are homogeneous in terms of structural and environmental factors and assess a within-the-group level of productivity of the retailers.

The proposed methodology helps reduce the heterogeneity among the units analysed, which is a major concern in DEA applications. The data-driven factorial and clustering technique allows for maximum within-group homogeneity and between-group heterogeneity by reducing subjective bias and dimensionality, which is embedded with the use of Big Data.

The use of Big Data in clustering applied to productivity analysis can provide managers with data-driven information about the structural and socio-economic characteristics of retailers' catchment areas, which is important in establishing potential productivity performance and optimizing resource allocation. The improved productivity indexes enable the setting of targets that are coherent with retailers' potential, which increases motivation and commitment.

This article proposes an innovative technique to enhance the accuracy of productivity measures through the use of Big Data clustering and DEA. To the best of the authors’ knowledge, no attempts have been made to benefit from the use of Big Data in the literature on retail store productivity.

The purpose of this study is to examine how different feminist Facebook groups in Israel operate in order to better understand the main issues in their discussions about feminism in Israel. The study will also identify the variances between the different subgroups. A secondary research question examined was whether Voyant Tools can be used as an effective content text analysis tool in general and in Hebrew in particular.

The study's research method analyzes the content of Facebook posts using the Voyant Tools online toolkit to quantitatively analyze and visualize the results of text mining and data visualization. The sample consists of the texts of posts of three groups representing different currents in Israeli feminism, gathered over a period of three months.

The results show that there are high-frequency words occurring in all groups, each group has its unique words, which distinguish it from the other groups. Feminist and Halachic Feminist groups had few words in common, while the Religious Feminist groups had more words in common with both the Feminist and the Halachic Feminist groups and more so with the latter group. While all groups discussed the issue of violence against women, especially sexual violence, the degree of engagement varied greatly between the groups. In addition, there were clear differences in the prominent issues concerning the various groups. This paper demonstrates the possibility of using Voyant Tools for text mining and analysis.

This paper demonstrates the possibility of using Voyant Tools for text mining and analysis. Voyant Tools shed light on common concepts, their location and prevalence in the text.

This study aims to explore the role of team personality and leader’s humor style on the use of humor in group communication and the extent to which group humor mediates the association between team personality on the one hand, psychological safety, collective emotional intelligence and group satisfaction on the other hand.

The authors used a survey to collect data from 304 employees nested in 83 groups working in organizations from various sectors in Romania.

The study results show that extraversion is positively associated with group affiliative humor, while neuroticism has a positive association with group aggressive humor. The leader’s affiliative humor style had a significant positive effect on group affiliative humor, while the effect of leader’s aggressive humor style on the use of aggressive humor in groups was not significant. Furthermore, the authors examined the mediation role of group humor in the relationship between team personality and team emergent states and satisfaction. The authors found that group aggressive humor mediates the association between neuroticism and group emotional intelligence, psychological safety and satisfaction, while affiliative humor mediates the association between extraversion and emotional intelligence and team satisfaction.

The study reports one of the first attempts to explore the multilevel interplay of team personality and humor in groups as they relate to emergent states.

This study aims to examine the impact of information overload (referred to as the saddling effect in this study) of underlying contracts on the sales performance of the salesforce at takaful institutions with special reference to addressing the heterogeneous effect among distribution channels.

A total of 311 samples were collected from the sales professionals of the takaful industry in Malaysia using a purposive sampling technique and the empirical analysis was conducted with the measures of model fit and bootstrapping technique using partial least square structural equation modeling and multi-group analysis.

Empirical results indicate that the saddling effect of the underlying contracts is evident among salesforce and the magnitude of the impact was found to be heterogeneous between the groups of salesforces in different distribution channels.

Findings recommend respective authorities of takaful institutions to intensify capacity building for their salesforce, particularly in the area of shariah knowledge and nature of underlying Islamic contracts used in the takaful products. A significant heterogeneous effect between distribution channels suggests that the actions and policy formulations should be diverse between the salesforce at different distribution channels and higher attention should be catered for the salesforce at the direct selling channel.

The increased information expectation (i.e. underlying contract knowledge) on takaful salesforce and its impact on their sales performance have not been documented before. The increase in information may create a burdening effect or what is referred to in this study as the information or knowledge “saddling effect.” If a saddling effect is identified, this may be a formidable reason for the slowing growth of the takaful industry in the respective market. It is expected that the outcome of this study would assist not only to fill the gap in the literature of personnel selling in the takaful industry but also will assist the takaful institutions in formulating appropriate policies for tackling the issue of the saddling effect of underlying contracts.

The purpose of this paper is to develop the teaching strategies of alternating peer teaching and progressive project-oriented learning, and apply them to the curriculum design of digital animation game production, and conduct teaching experimental research.

This research method under the teaching strategies of alternating peer teaching and progressive project-oriented learning, to the design of digital animation game and use teaching experiment animation game production tool was Game Maker animation game production software to develop the study. The production of learning history data was used in-game projects, to verify the digital animation game design effectiveness was used SPSS statistics method, and was to compare the learning effectiveness of the different teaching modes.

Through experimental design, learners can acquire the knowledge and skills of digital animation game production under the guidance of progressive project-oriented teaching strategies. In terms of the cognition and skills of animation game production, learners have acquired the skills of taking them in animation game design to be able to independently produce and design digital animation games. The research results can be used as a reference for future research on digital animation game teaching and curriculum development.

This study proposed a new approach to develop the teaching strategies of alternating peer teaching and progressive project-oriented learning, to design digital animation games. The research results show that effective teaching strategies guide successful learning, it can be used as a reference for future research on digital animation game teaching and curriculum development.

This study aims to conduct a quantitative meta-analysis of previous research on lifelong vocational education to generate generalized conclusions about its effects, set directions for future lifelong vocational education and identify implementation measures.

To conduct a meta-analysis on research results that have a heterogeneous distribution, it is important to specify the analysis category for examining the effects of research variables.

First, lifelong vocational education has an effect on dependent variables. And action appears to have the highest effect size on dependent variables. Next, when calculating the size of variables that had an effect on lifelong vocational education by educational type, the effect size of informal education was found to be larger than that of formal education. Finally, regarding the effect on the participants, office workers were influenced most, followed by university students, North Korean defectors, job seekers and foreigners.

Although this study attempted to conduct an in-depth analysis of subcomponents, it was not possible to analyze variables at a more detailed level. Therefore, future studies should aim to conduct a more comprehensive analysis of different variables based on a wider composition. Because lifelong vocational education is relevant to people’s daily lives, it should be investigated in the context of their personal characteristics and social backgrounds.

This research was designed to uncover general effects of lifelong vocational education and discover relevant variables affecting lifelong vocational education in South Korea. A meta-analysis of 15 studies with 67 subgroups examining lifelong vocational education was conducted.

In the current era of VUCA (Volatility, Uncertainty, Complexity and Ambiguity), lifelong vocational education needs to be organized systematically, unlike in the past. With the rapid advancements in technology influenced by artificial intelligence and the fourth industrial revolution, there is a surge in social demands for continued reeducation and redevelopment of employees to prepare for talent development paradigm innovation, increasing unemployment among unskilled workers and competence enhancement needs among job seekers and employed individuals.

This study aims to conduct a quantitative meta-analysis of previous research on lifelong vocational education to draw generalized conclusions on its effectiveness and discuss its implications for implementation measures. Specifically, this study will analyze the general effect size; differences in the effect size among different dependent variable groups; and the effect size based on lifelong vocational education participants.

This study aims to use big data analysis and sheds light on key hotel features that play a role in the revisit intention of customers. In addition, this study endeavors to highlight hotel features for different customer segments.

This study uses a machine learning method and analyzes around 100,000 reviews of customers of 100 selected hotels around the world where they had indicated on Trip Advisor their intention to return to a particular hotel. The important features of the hotels are then extracted in terms of the 7Ps of the marketing mix. This study has then segmented customers intending to revisit hotels, based on the similarities in their reviews.

In total, 71 important hotel features are extracted using text analysis of comments. The most important features are the room, staff, food and accessibility. Also, customers are segmented into 15 groups, and key hotel features important for each segment are highlighted.

In this research, the number of repetitions of words was used to identify key hotel features, whereas sentence-based analysis or group analysis of adjacent words can be used.

This study highlights key hotel features that are crucial for customers’ revisit intention and identifies related market segments that can support managers in better designing their strategies and allocating their resources.

By using text mining analysis, this study identifies and classifies important hotel features that are crucial for the revisit intention of customers based on the 7Ps. Methodologically, the authors suggest a comprehensive method to describe the revisit intention of hotel customers based on customer reviews.