Search results

This paper aims to measure and unveil the relationship between customer satisfaction and efficiency levels in the most relevant Brazilian airports.

The authors utilize a two-stage network DEA (data envelopment analysis) and AHP (analytic hierarchy process) model as the cornerstones of the study. The first stage of the network productive structure focuses on examining the infrastructure efficiency of the selected airports, while the second stage assesses their business efficiency.

Although the results indicate that infrastructure and business efficiency levels are heterogeneous and widely dispersed across airports, controlling the regression results with different contextual variables suggests that the impact of efficiency levels on customer satisfaction is mediated by a set of socio-economic and demographic (endogenous) and regulatory (exogenous) variables. Furthermore, encouraging investment in airports is necessary to achieve higher infrastructural efficiency and scale efficiency, thereby improving customer satisfaction.

There is a scarcity of studies examining the relationships among customer satisfaction, privatization and airport efficiency, particularly in developing countries like Brazil.

Family businesses (FBs) have a high rate of extinction through generations; hence, it is crucial for their owners to give succession planning top priority. In light of this, the study aims to determine the key factors that significantly influence effective succession.

This study illuminates the crucial factors of effective succession among Palestinian FBs (PFBs) by relying on the relay race model. A self-administered questionnaire used to gather the data; partial least squares structural equation modeling was used to analyze the data obtained from 282 participants based on the two-step approach to evaluate structural equation models. In the first analysis stage, measurement items’ validity and reliability were tested. Convergent and discriminant validity tests for the measurement (outer) model were performed. The square root of average variance extracted (AVE) and the correlation between latent constructs were compared to evaluate the discriminant validity. The structural (inner) model and hypotheses were tested in the second analysis stage. The research model’s hypotheses relations were predicted using the coefficient of determination (R²).

As they draw attention from existing and future founders and incumbents of FBs that successfully complete a succession process within the Palestinian setting, the findings offer a deeper understanding of the primary familial succession factors. Where it is important to place a focus, among other things, on familial bonding and trust placed in the next generation, as well as on next generation’s credentials and capabilities, financial and operational performance of FBs, next generations desire to join the business beside the job satisfaction and the financial returns they will earn. Additionally, findings show that the size of the FB and generation, as well as the incumbent’s age and education, have positive impact on the incumbents’ willingness to step down.

The value of this study comes from the following: first, to the best of the authors’ knowledge, it is the first that conduct a quantitative analysis on succession factors, the thing that adds value to the PFBs literature. Second, this study adheres to its own willingness scale, as it aims to analyze other success factors that PFBs are not fully aware of, particularly, family bonding and trust, the qualifications and capabilities of the next generation, plus financial and operational performance of the FB.

The main objective of this study is to evaluate the driving forces behind the adoption of indoor environmental quality (IEQ) principles in building designs from the perspectives of Nigerian quantity surveying firms.

A quantitative approach was used which involved administering a well-structured questionnaire to a sample of 114 quantity surveyors. The collected data were analyzed using various statistical methods, including frequencies, percentages, mean item scores, Kruskal–Wallis test and exploratory factor analysis.

The top five ranked drivers were climate change mitigation, conservation of natural resources, reduction of waste and pollution, use of sustainable building materials and development of new materials and building systems. Based on the factor analysis, the study identified five clusters of drivers: (1) health and well-being drivers (2) economic drivers (3) environmental drivers (4) innovation and technology drivers and (5) regulatory drivers.

The findings from this study suggest that to effectively integrate IEQ principles, quantity surveying firms should consider developing comprehensive guidelines and checklists that align with the identified drivers and clustered categories. These resources can serve as practical tools for project teams, facilitating a structured and holistic approach to the incorporation of IEQ factors throughout the project lifecycle.

The study’s identification of the top drivers and the subsequent clustering of these drivers into five distinct categories contributes to the existing body of knowledge on IEQ. This approach provides a structured framework for comprehensively understanding the factors influencing IEQ adoption, offering a valuable tool for researchers, policymakers and industry practitioners.

This study aims to analyse the influence of the pillars (hard and soft skills) of digital academic entrepreneurship on students' entrepreneurial intention.

This was done by adopting a quantitative methodology involving empirical research with a sample of 761 university students from two countries and adopting structural equation analysis to validate the theoretical model proposed.

The results indicate a direct influence between hard and soft skills and entrepreneurial intention, and a positive, indirect influence between these and entrepreneurial intention mediated by the dimensions of the theory of planned behaviour (TPB) – entrepreneurial attitude, subjective norms and perceived behavioural control. Therefore, the pillars of digital academic entrepreneurship have a direct and indirect influence on university students' entrepreneurial intention.

This study also contributes to better operationalization of entrepreneurial education in university environments, since the development of hard and soft skills can be planned better based on the model proposed here. Considering the relations between the dimensions of hard and soft skills and those of TPB, this study shows there can be an influence on students' entrepreneurial intention.

In this study, a new and innovative construct is inserted in the model of entrepreneurial intention: “structural pillars of digital academic entrepreneurship” through structural equation modelling, to determine the degree of influence of these pillars (hard and soft skills) constructs on HEI students' entrepreneurial intention.