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Today’s technological advancements have had a significant impact on the construction industry. Managing and controlling complex construction projects has been made significantly easier using technological tools. One such advancement is the automatic identification of workers’ activities. This study aims to classify construction worker activities by analyzing real-time motion data collected from sensors.

In accordance with our specific goals, we utilized advanced deep-learning methodologies such as deep neural networks, convolutional neural network, long short-term memory and convolutional long short-term memory to analyze the data thoroughly. This involved experimenting with various window sizes and overlap ratios to determine the optimal combination that would result in the most accurate predictions.

Based on the analysis results, the convolutional long short-term memory (ConvLSTM) deep learning model with a window size of 4.8 s and an overlap rate of 75% was found to be the most accurate prediction model. This model correctly predicted 98.64% of the basic construction worker activities in a real construction site environment.

Previous studies have mainly been conducted in laboratory environments and have focused on basic construction activities such as lifting, moving, sawing and hammering. However, this study collected data from real workers in a real construction site environment. Various deep learning models were employed to determine the most accurate one. Additionally, several options were tested to determine the optimal window size and overlap ratio during the data segmentation phase, aiming to select the most suitable ones for preparing the data for the model.

The study is aimed to compare the prediction success of basic machine learning and ensemble machine learning models and accordingly create novel prediction models by combining machine learning models to increase the prediction success in construction labor productivity prediction models.

Categorical and numerical data used in prediction models in many studies in the literature for the prediction of construction labor productivity were made ready for analysis by preprocessing. The Python programming language was used to develop machine learning models. As a result of many variation trials, the models were combined and the proposed novel voting and stacking meta-ensemble machine learning models were constituted. Finally, the models were compared to Target and Taylor diagram.

Meta-ensemble models have been developed for labor productivity prediction by combining machine learning models. Voting ensemble by combining et, gbm, xgboost, lightgbm, catboost and mlp models and stacking ensemble by combining et, gbm, xgboost, catboost and mlp models were created and finally the Et model as meta-learner was selected. Considering the prediction success, it has been determined that the voting and stacking meta-ensemble algorithms have higher prediction success than other machine learning algorithms. Model evaluation metrics, namely MAE, MSE, RMSE and R², were selected to measure the prediction success. For the voting meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0499, 0.0045, 0.0671 and 0.7886, respectively. For the stacking meta-ensemble algorithm, the values of the model evaluation metrics MAE, MSE, RMSE and R² are 0.0469, 0.0043, 0.0658 and 0.7967, respectively.

The study shows the comparison between machine learning algorithms and created novel meta-ensemble machine learning algorithms to predict the labor productivity of construction formwork activity. The practitioners and project planners can use this model as reliable and accurate tool for predicting the labor productivity of construction formwork activity prior to construction planning.

The study provides insight into the application of ensemble machine learning algorithms in predicting construction labor productivity. Additionally, novel meta-ensemble algorithms have been used and proposed. Therefore, it is hoped that predicting the labor productivity of construction formwork activity with high accuracy will make a great contribution to construction project management.

Around the world, people are confronted by a variety of complex and pervasive environmental, social and economic challenges. In many cases, including anthropogenic climate change, resource depletion, financial system disruption and poverty, there has been an increasing recognition that ‘wicked problems’ require entirely new ways of thinking, and that the solutions are unlikely to be found by governments, businesses or civil society actors operating in isolation. In parallel with these developments, many observers have commented on a growing interest in various forms of social entrepreneurship and in new models of enterprise that seek alternative ways of delivering products and services, while also securing the ‘triple bottom line’ of social, environmental and economic sustainability. This volume draws together a selection of contemporary entrepreneurship research studies that explore different aspects of this phenomenon. Our original call for papers was based around the themes addressed in one of ISBE's longstanding annual conference tracks. It attracted some strong submissions from within and beyond the ISBE research community. The editors reviewed papers relating to social and sustainable entrepreneurship, the environmental impacts of enterprise, and ethics and social responsibility in enterprise.

This remastered analysis focuses on the impact of entrepreneurial interventions in higher education institutions (HEI), particularly in social entrepreneurship. The study evaluated the effectiveness of such interventions through a pre-and post-test approach, examining various skill sets in students. The primary goal was to analyze the influence of entrepreneurial training programs on students' competencies in social entrepreneurship by analyzing changes in personal behavior, leadership, innovation, social value and management skills before and after the educational interventions.

The study employed a quasi-experimental design, analyzing pre-and post-test results in three distinct social entrepreneurship training experiences. The sample consisted of 304 participants, providing a comprehensive view of the impact of these interventions.

The main findings were: (1) Educational interventions in social entrepreneurship must emphasize strategies for self-awareness, emotional intelligence and personal development improvement. The analysis revealed significant improvements in these areas, indicating that targeted strategies in these domains are essential for enhancing the effectiveness of social entrepreneurship education. (2) The impact of educational interventions on these capabilities can be effectively evaluated using machine learning methods such as ordinary least squares (OLS) regression. This approach allows for the inclusion of variables such as gender, age or location, providing a comprehensive assessment of the interventions' impact. (3) The interventions were particularly effective in improving students' innovation and leadership competencies. The analysis demonstrated substantial enhancements in these areas, underscoring the success of the interventions in developing these critical skills. (4) The study highlighted the need for a more focused approach in future interventions, emphasizing the importance of management, social value and personal skills. Additionally, it pointed out the necessity of developing and utilizing appropriate tools to create and evaluate these interventions effectively.

The study provides insights into improving educational interventions in social entrepreneurship to better develop essential skills in students.

This research introduces a significant approach to educational interventions for educational communities and decision-makers by demonstrating the effectiveness of entrepreneurial training for competencies in innovation and leadership, which are crucial for societal and economic development.

Using elements of Bourdieu’s (1986) capitals framework as an underpinning conceptual architecture, this paper theorises the role of symbolic capital in resourcing a specific example of socially entrepreneurial behaviour.

This paper relies on data collected via a qualitative variant of the critical incident technique.

The analysis resulted in three focal themes: power (a dynamic of cooperation rather than domination), age (youth as a means of legitimation) and temporality (as both lever and conduit).

These themes further current understanding of socially entrepreneurial behaviour and potentially catalyse additional questioning and investigation specific to the construct of symbolic capital in this context.

The insights offered in the paper may assist those tasked with supporting success (policymakers and practitioners) in the social entrepreneurship domain.

Relatively little is known about the operationalisation of capitals in the context of social entrepreneurship, and even less about symbolic capital specifically. Particular emphasis is given to moving beyond a focus on the simple mechanics of capital exchange and conversion.

Social entrepreneurship education (SEE) is gaining increasing attention globally. This paper aims to focus on how SEE may be better understood and reconfigured from a Bourdieusian capital perspective with an emphasis on the process of mobilising and transforming social entrepreneurs’ cultural, social, economic and symbolic resources.

Drawing on qualitative research with a sample of social entrepreneurship educators and mentors, the authors generate insights into the significance of challenging assumptions and establishing values and principles and hence that of developing a range of capitals (using the Bourdieusian notion of capital) for SEE.

The findings highlight the significance of developing a range of capitals and their transformative power for SEE. In this way, learners can develop dispositions for certain forms of capitals over others and transform them to each other in becoming reflexive social agents.

The authors respond to the calls for critical thinking in entrepreneurship education and contribute to the field by developing a reflexive approach to SEE. The authors also make recommendations to educators, who are tasked with implementing such an approach in pursuit of raising the next generations of social entrepreneurs.

Sustainability is viewed as an encompassing perspective, as endorsed by the international policy context, driven by the UN’s Sustainable Development Goals (SDGs). We aim to examine how women entrepreneurs transform capitals to pursue sustainability, and to generate policy insights for sustainability actions through tourism entrepreneurship.

Applying qualitative approach, we have generated empirical evidence drawing on 37 qualitative interviews carried out in Turkey, whereby boundaries between traditional patriarchal forces and progressive movements in gender relations are blurred.

We have generated insights into how women entrepreneurs develop their sustainability practice by transforming their available economic, cultural, social and symbolic capitals in interpreting the macro-field and by developing navigation strategies to pursue sustainability. This transformative process demonstrates how gender roles were performed and negotiated in serving for sustainability pillars.

In this paper, we demonstrate the nature and instrumentality of sustainable tourism entrepreneurship through a gender lens in addressing some of these SDG-driven challenges.

We advance the scholarly and policy debates by bringing gender issues to the forefront, discussing sustainable tourism initiatives from the viewpoint of entrepreneurs and various members of local community and stakeholder in a developing country context where women’s solidarity becomes crucial.

Purpose – The purpose of this research is to identify the CSR dynamics through a social capital lens in a developing country's context.

Approach – The research design underpinning this study is qualitative. Semi-structured interviews have been conducted with SMEs owner-managers.

Findings – Adopting a pragmatic stance, the research highlighted the significant role of the social capital concept in enabling or hindering SMEs’ engagement in the CSR discourse in the Egyptian context.

Implications/limitations – A holistic understanding of the subject has been achieved by examining core issues at different levels. It is recommended that micro-individual (SME owner/manager), meso-organisational (SME context and industry), and macro-environmental (socio-economic and cultural environment) dynamics be explored by employing suitable research methods grounded in research paradigms that allow for qualitative exploration.

Practical implications – By giving prominence to SMEs as the research focus, the significance of these enterprises for sustainable development is highlighted at the policy level by developing tools and mechanisms that deal with effective implementation of CSR programmes in that sector.

Social implications – An in-depth understanding of the CSR practices of SMEs as embedded in their operational management will help policy makers in promoting sustainable practices by integrating social and environmental activities in the day-to-day operations of SMEs.

Originality/value – The chapter makes a contribution to academic theory in the area of CSR in SMEs by examining the phenomenon through a social capital lens using a multi-layered approach from a developing country's perspective.

The purpose of this paper is to investigate the effect of service quality on graduates’ satisfaction as perceived by Middle East University (MEU) graduates.

This research is cross-sectional and aims to explore the effect of service quality dimensions (academic staff, administration, classrooms and library services) on graduates’ satisfaction. Data were collected from 399 graduates. After confirming validity, reliability and normality of the data, and the correlation between variables, multiple regressions were used to test the hypothesis.

The results show that all service quality dimensions are highly implemented by the MEU. The relationships between all service quality dimensions and graduates’ satisfaction are strong. Finally, results show that all service quality dimensions affect graduates’ satisfaction.

To generalize the results of this research, further studies are recommended to be carried out on other universities especially in Jordan. Testing the perception and satisfaction of other universities, stakeholders will help to improve service quality and to gain suitable competitive strategies.

Service quality is a key driver for universities’ sustainable competitive advantage; therefore, dimensions of service quality should be included within universities plan, strategies and daily activities.

Considering service quality in higher education improves countries’ economic development, quality of life and well-being. All corporate social responsibility pillars (social, economic, environmental responsibilities and national and international regulation and norms) should be adapted and adopted within services quality systems and programs.

Most of previous studies were carried out to test the students’ perception while this research is dedicated to explore graduates’ perception regarding service quality offered by the MEU.

This research aims to determine the contribution of publications in the context of Türkiye to the international entrepreneurship literature between 2005 and 2022. We examined 471 articles published in international journals in the Web of Science (WoS) Core Collection database using bibliometric analysis techniques. We analyzed the data with the software Biblioshiny+Bibliometrix, SciMAT, and VOSViewer. We used performance, theme and evolution, co-authorship, and document analysis in data analysis. Performance analysis findings show that the most publications were made in 2021, the journal with the most publications was sustainability, and the author with the most publications was Bakır, C. Theme and evolution analysis revealed that the motor themes were corporate entrepreneurship, gender and entrepreneurial intentions in the first period (2005–2014), while institutional entrepreneurship stood out as the niche theme. In the second period (2015–2022), “corporate entrepreneurship” and “performance” emerged as the motor themes, while the niche themes in this period were “Syrian refugees” and “entrepreneurial intentions.” Document analysis findings show that the most studied entrepreneurship types are gender, family, corporate, social, and small business, respectively. In addition, immigrant/refugee entrepreneurship is emerging as a new topic, while indigenous entrepreneurship, informal entrepreneurship, sustainable entrepreneurship, and religion entrepreneurship are the most minor studied topics in entrepreneurship. Evidence-based decision-making inputs were obtained for those holding the resource allocation authority in Türkiye. Policymakers and funders, as well as individuals and institutions that want to design the future in terms of resources, can benefit from the findings and analysis of this chapter. Türkiye, which ranks 26th in the world regarding entrepreneurship, must develop a policy based on data.