Augmented Reality (AR) technology adoption has been growing worldwide in recent years. The potential of AR to blend digital information into the physical world has been a challenge for both academia and industry, who attempt to realize and anticipate its impact on users’ perceptions, adoption intention and use. The present paper is an empirical study aimed at making substantial suggestions and investigating an integrative theoretical paradigm which attempts to establish the significance of specific factors which allow using mobile augmented reality apps in shopping malls. The study employs information from the extant literature with a view to extending the Unified Theory on Acceptance and Use of Technology (UTAUT). The results show that performance expectancy, enjoyment and reward are direct determining factors of adopting the specific technology in shopping malls, whereas facilitating conditions, social influence, innovativeness and trust exert an indirect effect on behavioral intention adoption. The research findings have far-reaching theoretical and practical implications for the development, marketing and application of mobile AR apps in the context of the specific contemporary form of shopping.

The banking sector has been considered as one of the primary adopters of Information and Communications Technologies. Especially during the last years, they have invested a lot into the digital transformation of their business process. Concerning their retail customers, banks realized very early the great potential abilities to provide value added self-services functions via mobile devices, mainly smartphones to them; thus, they have invested a lot into m-banking apps’ functionality. Furthermore, the COVID-19 pandemic has brought out different ways for financial transactions and even more mobile users have taken advantage of m-banking app services. Thus, the purpose of this empirical paper is to investigate the determinants that impact individuals on adopting or not m-banking apps. Specifically, it examines two groups of individuals, users (adopters) and non-users (non-adopters) of m-banking apps, and aims to reveal if there are differences and similarities between the factors that impact them on adopting or not this type of m-banking services. To our knowledge, this is the second scientific attempt where these two groups of individuals have been compared on this topic. The paper proposes a comprehensive conceptual model by extending Venkatech’s et al. (2003) Unified Theory of Acceptance and Use of Technology (UTAUT) with ICT facilitators (i.e., reward and security) and ICT inhibitors (i.e., risk and anxiety), as well as the recommendation factor. However, this study intends to fill the research gap by investigating and proving for the first time the impact of social influence, reward and anxiety factors on behavioral intention, the relationship between risk and anxiety and the impact of behavioral intention on recommendation via the application of Confirmatory Factor Analysis and Structural Equation Modeling (SEM) statistical techniques. The results reveal a number of differences regarding the factors that impact or not these two groups towards m-banking app adoption; thus, it provides new insights regarding m-banking app adoption in a slightly examined scientific field. Thus, the study intends to assist the banking sector in better understanding their customers with the aim to formulate and apply customized m-business strategies and increase not only the adoption of m-banking apps but also the level of their further use.

Universities are aware of the imperative of sustainability and are focusing on promoting the aims and principles of sustainable development, such as greening their curriculum, enhancing the environmental performance of their campus and using sustainable criteria in their investment and purchasing behavior. Also, the scope of sustainable development was broadened by the introduction of 17 Sustainable Development Goals (SDGs) proposed by the United Nations’ (UN) 2030 Agenda which stipulates new directions for sustainability at a global level. Given this background, this paper examines the level of alignment of universities with the 17 SDGs through an analysis of sustainability reports prepared by universities, in order to highlight the issues which are mostly discussed by universities in relation to SDGs. To do so, an empirical analysis was carried out on a sample of 37 sustainability reports using a methodological framework based on scoring techniques to analyze their content. The findings show that the universities have disclosed more information about climate change mitigation and adaptation practices and less about SDGs regarding quality of education and peace, democracy and strong institutions.

Artificial intelligence agents (chatbots), which are programs to communicate with users primarily in customer service contexts, are an alternative interaction channel supporting businesses in the digital environment and vital components in customer service. The present empirical paper, which is aimed at identifying and discussing the factors motivating nonusers to adopt the specific technology in mobile contexts, proposes a comprehensive conceptual model, which combines the UTAUT 2 behavioral theory with variables of mobile service quality contexts, such as information quality, privacy concerns, interface, and equipment, as well as trust and mobility factors. Data analysis, based on the partial least squares structural equation modeling (PLS-SEM) statistical method, revealed that performance expectancy, facilitating factors, hedonic motivation, mobility, trust, and service quality positively affect nonusers’ behavioral intention to adopt chatbots. In addition, equipment, interface, and trust have a significant impact on users’ trust in the context of mobile chatbots. Personal data privacy issues also have a negative effect on trust, in contrast to effort expectancy, which positively affects performance expectancy. As mobile service quality factors have not been investigated before in the context of chatbots, the findings of the present research are expected to provide useful insights both to academia and the business industry.

The purpose of this paper is to investigate the factors, both internal and external, that impact the adoption of digital governance in public administration. The quantitative data were collected through online questionnaires from 556 public servants, all of whom were enrolled in a Master of Public Administration program, representing a variety of public organizations, in a non-random way. The study draws from a comprehensive literature review and leverages structural equation modeling (SEM) analysis to derive empirical insights. The empirical analysis revealed positive relationships between digital governance, service quality, safety, trust, and transparency within public services. Contrary to previous results, internal factors such as leadership, organizational culture, and skillsets do not exhibit significant impacts. Overall, the study supports the idea that improving the quality of digital services and embracing innovative technologies are key drivers of digital governance in public administration, leading to increased transparency and public trust. These findings can guide policymakers and administrators in implementing effective digital governance strategies tailored to the specific context of each public organization.