American Journal of Business

Today, the use of smart technologies in healthcare systems is experiencing exponential growth, and the future of healthcare is seemingly closely intertwined with such technologies. Thus, any exploration of the factors that influence human health and healthcare systems inevitably touches upon the subject of new technologies. This study aims to design a conceptual model to investigate the elements that affect individuals' openness to accepting and using mobile healthcare applications (mHealth apps) and their reciprocal effects. After a brief review of the literature, the authors identify the influential factors in the acceptance of smart technologies in healthcare systems and present a conceptual model in this regard. Next, the authors analyze the factors and variables and the extent of their impact by a structural equation modeling (SEM) approach. The statistical population of this study consists of 421 individuals including the developers, consultants and users (i.e. patients) of mHealth apps. Data analysis was done on the statistical software SPSS v.26, while SEM was carried out using the partial least squares (PLS) method on the modeling software SmartPLS. The results indicate that user, consultant and developer preferences have a positive and significant impact on time, quality of life, managing chronic conditions and cooperation, and these constructs (system performance) finally have a positive and significant impact on the acceptance of mobile healthcare technologies. This paper shows that mHealth apps can have a remarkable role in the prevention and treatment of medical conditions, and it is strongly recommended that this technology be utilized in the studied region.

This paper aims to describe the results of applying ethical AI requirements to a healthcare use case. The purpose of this study is to investigate the effectiveness of using open educational resources for Trustworthy AI to provide recommendations to an AI solution within the healthcare domain. This study utilizes the Hackathon method as its research methodology. Hackathons are short events where participants share a common goal. The purpose of this to determine the efficacy of the educational resources provided to the students. To achieve this objective, eight teams of students and faculty members participated in the Hackathon. The teams made suggestions for healthcare use case based on the knowledge acquired from educational resources. A research team based at the university hosting the Hackathon devised the use case. The healthcare research team participated in the Hackathon by presenting the use case and subsequently analysing and evaluating the utility of the outcomes. The Hackathon produced a framework of proposed recommendations for the introduced healthcare use case, in accordance with the EU's requirements for Trustworthy AI. The educational resources have been applied to one use-case. This is the first time that open educational resources for Trustworthy AI have been utilized in higher education, making this a novel study. The university hosting the Hackathon has been the coordinator for the Trustworthy AI Hackathon (as partner to Trustworthy AI project).

Using various proxies for the firms' return on equity (ROE) and retention ratios (b) the authors calculate 36 sustainable growth rates, on a rolling basis, for a comprehensive set of firms over a 52-year period. The authors then assess the ability of these different sustainable growth rates to predict the actual, out-of-sample, five-year growth rates of the firms' earnings. The authors compare the forecast to determine which method of estimating ROE and b produce the lowest mean-squared-errors and then determine the estimation method that works best for firms with different characteristics and for firms in different industries. Overall, using the median ROE of all firms in the market and the 5-year average of the specific firm's retention ratio produces the lowest, statistically significant, forecast errors. Variations are documented based on firm characteristics, including dividend payout, level of ROE and industry. The findings can guide practitioners in using the best earnings forecasting method. Financial textbooks seem universally to suggest that one method of estimating the growth rate of a firm's earnings is to calculate the “sustainable growth rate” by multiplying the firm's ROE by the firm's b. At the same time, multiple methods of proxying for both ROE and b have been suggested; therefore, it is an interesting and useful empirical question, which, heretofore, has not been addressed in the literature, as to which estimation of the sustainable growth rate best approximates the actual future growth of the firm's earnings. The findings can guide practitioners in using the best earnings forecasting method.

There has been a great deal of exploratory, conceptual and empirical research on digital financial literacy (DFL) in the fields of finance, economics, business and management. But up until now, there has not been any attempt to provide a thorough scientific mapping of the area. Therefore, by combining various knowledge systems, this study seeks to identify the current research trend. A sample of 158 papers was subjected to bibliometric analysis in the areas of DFL or digital finance. Assembling, organising and evaluating are the three phases that make up the bibliometric analysis process derived from the most dependable and genuine sources, the Scopus database, and the Web of Science (WoS) database. This study was done using a scientific search technique on the Scopus and WoS databases for the years 2015 through 2022. The study made use of Biblioshiny, a web-based tool created in R-studio and part of the Bibliometrix package. Prominent journals, authors, nations, articles and themes were identified with the use of the software's automated workflow. “Citation, co-citation, and social network analysis” were also carried out. The study' outcomes indicate that, as an interdisciplinary discipline, the themes of digital finance have changed throughout time. Researchers first concentrated on socioeconomic and demographic variables, but over time the subject expanded to include themes like influencing, promoting, and behavioural factors that affect digital financial literacy (DFL). This research shows the conceptual framework of the area in addition to its intellectual and social structure. This study offers crucial insights into subjects that demand more research. Since the current study is a bibliometric analysis, the usual restrictions on such studies apply. A meta-analysis, a thorough literature review and other methods would be beneficial for future researchers to develop a solid conceptual framework. This current research work's science mapping is restricted to the Scopus and WoS databases because this research includes more high-quality articles and has organised formats that work with the Bibliometrix application. Present research provides critical insights into saving behaviour, retirement planning, digital finance and the interdependence of these. This research highlights the most prevalent problems in the field and points in the direction of potential areas for further study. Exposing the social and intellectual structure of the domain educates upcoming scholars about the themes, contexts and opportunities for collaboration in this field. The study will be useful for future learning as the study gives broad exposure to the current literature in the field of digital finance. On the other hand, people will also grow aware of the effects of digital finance and make the proper choices as a result. Additionally, the report might offer crucial insights for developing policies on digital finance and literacy. In the past, a significant number of conceptual and empirical studies were conducted internationally in the research fields of economics, finance, business, management and consumer behaviour. This research makes a significant addition by bringing together disparate literature in the field, highlighting reliable sources, authors and documents, and examining the relationship between digital finance, saving behaviour and retirement planning.

Previous research shows a positive effect of job satisfaction and retention on both workers’ and organizations’ welfare, it is important to understand whether the characteristics of a job and workers’ perceptions of certain job traits can predict job satisfaction and retention in an organization. This paper explores the effect of 18 job characteristics on the likelihood that a worker is satisfied with his or her job, the chance that he or she looks for an alternative employer in the following year and the number of years employed by the same organization. The author adds to the current state of the literature on the importance of job characteristics in several ways. First, the author utilizes a list of 18 job characteristics or perceptions, which to the best of our knowledge is one of the most extensive sets of characteristics that has been considered. This allows us to examine lots of aspects of the job, and their connection to the outcomes of interest. Second, the author uses not only basic regression methods but also ordered Logit specifications to obtain more precise estimates of the effect of job characteristics on job satisfaction and workers’ propensity to look for a new job. Third, the author considers the possibility that a combination of job characteristics, rather than a single factor, influences the level of satisfaction with the job and retention, measured by the likelihood that a worker plans to look for an alternative job in the following year and the years at the current job. The author explores the latter through principal component analysis. Fourth, the author explores gender differences in the effect of job characteristics on job satisfaction and retention. Finally, the author discusses the implications of this research to policy decision-making and managerial decisions. The author finds that personal development opportunities and job security are positively related to job satisfaction, and negatively related to the likelihood of looking for a new job. Opportunities for personal development have a stronger effect on job satisfaction of men than women. Male workers’ job satisfaction also depends on whether they are given enough time to complete assigned tasks. The perception of security in the current job, having reliable coworkers and receiving sufficient help in a job make it less likely for women to perform a job search. Fringe benefits encourage workers of both genders to stay in an organization longer. Job security also has a positive relationship with the years in a given job for women, but not for men. The findings have implications for managers and policy decision-makers. For managers, it is important to be aware of the value male and female workers place on different job characteristics, because a number of studies show the importance of job satisfaction on the success of companies (Porter et al. 1977; Mobley et al., 1979; Tett et al. 1993; Posner et al. 1993), and the author shows that job satisfaction depends on different characteristics for men and women. In addition, managers’ awareness of the findings related to the factors that are likely to retain workers in a company is important because of the costs of recruiting new workers, including hiring, training and opportunity costs. For policy considerations, programs that help in matching employers with potential workers are likely to find good fits for both sides of the labor market if they direct women to jobs that provide more security, opportunities for personal development, and help at work. Jobs that offer more time to complete tasks would retain and increase the chance of keeping male workers satisfied with their job.