Search results

This study aims to investigate the synergies between the economic environment and the smart living dimension embedded in the current smart city initiatives, focusing on the localization of female entrepreneurship in contemporary cities. This interaction is under-investigated and controversial as it includes cities' practices enabling users and citizens to develop their potential and build their own lives, affecting entrepreneurial and economic outcomes. Building upon the perspective of the innovation ecosystems, this study focuses on the impact of smart living dimensions and R&D investments on the localization of female entrepreneurial activities.

The study uses a Generalized Method of Moments (GMM) and a panel dataset that considers 30 Italian smart city projects for 12 years to demonstrate the relationship between smart living practices in cities and the localization of female entrepreneurship. The complementary effect of public R&D investment is also included as a driver in the “smart” city transition.

The study found that the advancement of smart living practices in cities drives the localization of female entrepreneurship. The study highlights the empirical results, the interaction over the years and a current overview through choropleth maps. The public R&D investment also affects this relationship.

This study advances the theoretical discussion on (1) female entrepreneurial intentions, (2) smart city advancement (as a context) and (3) smart living dimension (as a driver) and offers valuable insight for governance and policymakers.

This study offers empirical contributions to the preliminary academic debate on enterprise development and smart city trajectories at the intersection between human-based practices and female entrepreneurship.

This study offers empirical contributions to the preliminary academic debate on enterprise development and smart city trajectories at the intersection between human-based practices and female entrepreneurship. The findings provide valuable insights into the localization of female entrepreneurship in the context of smart cities.

The study aims to examine the indirect relationships via application (app) brand self-relevance emotions and self-relevance that underlie the relationships between perceived value of mobile apps and (brand) love with respect to mobile apps. The study further investigates the moderating role of user–app relationship duration in the formation process of brand love for mobile apps from a dynamic and long-term perspective.

A multiple moderated-mediation model is developed and empirically tested with a sample of 396 users of popular Chinese mobile educational apps.

The study reveals that utilitarian value exhibits positive indirect relationships with brand love for mobile apps through increased positive self-relevance emotions. All three types of perceived value of mobile apps (utilitarian, hedonic and social) affect app brand love positively via self-relevance. These three types of perceived value were found to be serially linked to brand love through self-relevance and self-relevance emotions. Furthermore, empirical evidence is found for the moderating effects of user–app relationship duration.

By testing mechanisms simultaneously in an integrative model, this study investigates the reasons for app brand love that attract a user into a lasting relationship with an app and extends knowledge of the app brand love building process in inducing strong and positive brand–self connections. Our study also makes practical contributions by offering insights into delivering the most desired benefits to mobile app users according to different contextual conditions, in order to attract and retain users in a more cost-effective manner.

The purpose of this paper is to address the challenging issue of developing a quantitative approach for the representation of cultural significance data in heritage information systems (HIS). The authors propose to provide experts in the field with a dedicated framework to structure and integrate targeted data about historical objects' significance in such environments.

This research seeks the identification of key indicators which allow to better inform decision-makers about cultural significance. Identified concepts are formalized in a data structure through conceptual data modeling, taking advantage on unified modeling language (HIS). The design science research (DSR) method is implemented to facilitate the development of the data model.

This paper proposes a practical solution for the formalization of data related to the significance of objects in HIS. The authors end up with a data model which enables multiple knowledge representations through data analysis and information retrieval.

The framework proposed in this article supports a more sustainable vision of heritage preservation as the framework enhances the involvement of all stakeholders in the conservation and management of historical sites. The data model supports explicit communications of the significance of historical objects and strengthens the synergy between the stakeholders involved in different phases of the conservation process.

The United Nations Convention on the Rights of Persons with Disabilities (2006) recognizes the right of disabled people to access work. Against this legislative backdrop, this study explores the strengths and weaknesses of the Italian system of targeted placement for disabled people, based on Law 68/1999, which delegates to regional authorities the management of the labor market. The examination centers on the perspective of companies, the primary stakeholders in the inclusion of persons with disabilities within organizational structures.

The article discusses the results of focus groups conducted with 28 managers of large, medium and small enterprises in Lombardy (Italy). Qualitative analysis was employed, and the results were structured using a simplified strengths, weaknesses, opportunities and threats (SWOT) analysis, incorporating practical recommendations.

The analysis leads to practical suggestions to improve the entire targeted placement process at the regional level, from selection and accompaniment to evaluation, such as improving the networking of local stakeholders who deal with the inclusion of disabled people, homogeneity of the procedures in different regions, making all employees aware of diversity management, etc. The territorial network and the welfare environment are particularly important in achieving a successful targeted placement and to promote an inclusive corporate culture.

This study is not representative of Italy as a whole, as it remains a qualitative investigation focused on a single region.

This contribution accomplishes an in-depth study of the law of labor inclusion of people with disabilities observed from the point of view of companies, which are still usually reluctant to integrate people with disabilities into their organizations or encounter difficulties in doing so.

Although there is a growing body of literature on how celebrity involvement impacts the effectiveness of destination marketing, the underlying mechanisms of that relationship are still underexplored. Based on the affect transfer and meaning transfer theories, this study aims to examine the impact of celebrity attachment on customer delight toward K-culture and K-culture attachment, affective and cognitive images of Korea, and the intention to visit Korea.

Online survey data were collected from 2,614 US residents, representing various demographic characteristics. For the data analysis, the partial least squares-structural equation modeling was conducted to evaluate the structural model and test the hypotheses.

The results showed that celebrity attachment is positively related to customer delight toward K-culture and K-culture attachment, which, in turn, positively influences affective and cognitive images of Korea. Additionally, K-culture attachment positively influences cognitive and affective images of Korea, which are positively related to the intention to visit Korea.

By using the affect transfer theory and meaning transfer theory, this study provides valuable insights into how consumer’s attachment to celebrities has spillover effects on the decision-making process. This study also adds a new concept, customer delight connected to cultural experience, in the context of destination marketing.

By understanding the importance and influence of people’s intimacy with media characters, practitioners can apply parasocial relationship theory, affect transfer theory and meaning transfer theory to their marketing strategies.

As one of the few empirical studies that examines the impact of celebrity attachment on consumers’ perceptions and behaviors, this study can make significant contributions to the destination marketing literature.

Mainland Tanzania has seen two decades of significant social policy reforms and transformations in its social and economic structures, whilst the country continues to grapple with persisting gender inequalities. This article examines Tanzania's social policy developments from a gender perspective. The authors analyse the level, reach and quality of social policy delivery to working-age women across the areas of health policy, social protection and employment policy during 2000–2021.

The article draws on qualitative research deploying the scoping review method. The data consist of diverse secondary materials, including academic publications, government policy documents, relevant statistics and other types of “grey” literature.

Tanzania has made significant advancements in the legal frameworks around welfare provision and has instituted increasingly gender-responsive government policy plans. The health and social protection sectors, in particular, have witnessed the introduction of large-scale measures expanding social policy implementation. However, social policy delivery remains two-tiered, with differences in provisions for women in the formal and informal sectors.

Social policy delivery and implementation have increased and diversified in Sub-Saharan Africa (SSA) during the new millennium, with a growing integration of gender-specific policy objectives. However, limited social policy scholarship has focused on the gendered effects of broader social policy models in SSA. The article remedies the concomitant knowledge gaps by examining various social policies and their impacts on working-age women in Mainland Tanzania. The authors also engage with the theoretical welfare regime literature and present an analytical framework for gender-sensitive assessment of emerging social policy models in the Global South.

Nearly 75% of EU buildings are not energy-efficient enough to meet the international climate goals, which triggers the need to develop sustainable construction techniques with high degree of resilience against climate change. In this context, a promising construction technique is represented by ventilated façades (VFs). This paper aims to propose three different VFs and the authors define a novel machine learning-based approach to evaluate and predict their energy performance under different boundary conditions, without the need for expensive on-site experimentations

The approach is based on the use of machine learning algorithms for the evaluation of different VF configurations and allows for the prediction of the temperatures in the cavities and of the heat fluxes. The authors trained different regression algorithms and obtained low prediction errors, in particular for temperatures. The authors used such models to simulate the thermo-physical behavior of the VFs and determined the most energy-efficient design variant.

The authors found that regression trees allow for an accurate simulation of the thermal behavior of VFs. The authors also studied feature weights to determine the most relevant thermo-physical parameters. Finally, the authors determined the best design variant and the optimal air velocity in the cavity.

This study is unique in four main aspects: the thermo-dynamic analysis is performed under different thermal masses, positions of the cavity and geometries; the VFs are mated with a controlled ventilation system, used to parameterize the thermodynamic behavior under stepwise variations of the air inflow; temperatures and heat fluxes are predicted through machine learning models; the best configuration is determined through simulations, with no onerous in situ experimentations needed.