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This study aims to statistically verify the links of income and education with information and communication technology (ICT) diffusion across 191 countries of the world taking into account a total of 9 indicators best representing the socio-economic variables.

Multivariate regression analysis was used as a prime method to rigorously test the relationships of income and education with ICT diffusion across 191 countries. Statistical Package for the Social Sciences (V. 22) was used to analyze and predict patterns in the data.

The results support the hypotheses that income and education are positively related to ICT diffusion. The findings statistically confirm that poverty is a leading cause of digital divide worldwide.

Academic, policy and practice groups should work in collaboration to fight against digital divide. Present results also imply that digital divide shall never end but rather it can be controlled to an extent with multiple collaborative efforts.

Prior research assignments on the digital divide concentrate on exploring the links between few socio-economic and ICT variables in select few regions theoretically. The present work addresses this literature gap by developing and testing two hypotheses to statistically investigate the relationships between a broad set of socio-economic and ICT indicators.

This paper aims to study the automotive 4.0 context to understand the consumers’ propensity towards high-tech automated cars. The paper analyses the antecedents that lead to the use of innovative vehicles. Theory of planned behaviour (TPB) is adopted and extended by including further constructs, such as environmental aspects and inhibitors.

The advent of smart technologies and the internet of things has given rise to several contributions that look at consumers’ intention towards innovation adoption in the automotive industry. Furthermore, this study rises from the growing interest that sustainable mobility achieved. Based on the previous technology acceptance models and particularly TPB, this paper develops a structured questionnaire. After a pilot survey, the final questionnaire was administered online through email and social media in the Italian context. Structural equation modelling technique has been used for analysing data and testing the conceptual model.

The number of questionnaires filled out was 310, with a sample composed of young adults, characterised by different addiction levels towards technology. The results explain the drivers that lead to accept and adopt high-tech automated vehicles. This topic is still under investigation and offers potential research opportunities, considering the evolution of the market and the consumers’ habits and needs. Future research studies in this area should focus on generalising the present findings in other countries. Moreover, once this technology starts to be adopted, other constructs could be discovered, investigated and included in the model.

Mobility has raised a growing interest with the fast increasing demand for sustainability and growth of innovative solutions embedded in mobility. This research explores the TPB model’s application and the relation between its constructs, environmental aspects, inhibitors and intention to adopt automated vehicles. On this strength, it is possible to identify each construct’s relevance for obtaining social consensus on the market.

The study considers time-varying risk premium in investigating the capability of technical analysis (TA) to predict and outperform a buy–hold strategy in Bitcoin exchange rate returns.

The study tests the technical trading rule of fixed moving average (FMA) on daily actual and equilibrium returns of Bitcoin exchange rates. The equilibrium returns are computed using dynamic CAPM in conjunction with a VAR-MGARCH (1, 1) system. The empirical evaluation of the study uses a case study of four Bitcoin exchange rates (BTC/AUD, BTC/EUR, BTC/JPY and BTC/ZAR) for the period 19 June 2010 to 30 October 2020.

The findings are consistent with related studies in conventional foreign exchange markets that find TA to be profitable, especially in emerging markets. Nevertheless, the consideration of risk premium has the effect of reducing the abnormal returns. Also, further robust tests reveal that Bitcoin returns possess a momentum effect which prompts further study in efficient market hypothesis research.

The empirical findings of this study should benefit portfolio managers and active investors on the strength of TA to predict returns in a speculative market like the Bitcoin exchange rate market.

The study takes cognisance that cryptocurrency trading is speculative in nature which renders it a good candidate for TA methods. While there are studies that have explored the value of TA in Bitcoin exchange rates, these studies fail to incorporate the effects of time-varying risk premiums, the strength and focus of the current paper.

This study aims to explore the holistic context of organisational staff retention in small, medium and large organisations. It also aims to identify the factors affecting the retention of organisations of different sizes.

The study implements an empirical test of a model created during previous research with the participation of 511 employees. The responses to the online questionnaire and the modelling were analysed using the partial least squares structural equation modelling method. The models were tested for internal consistency reliability, convergent and discriminant validity, multicollinearity and model fit.

Two models were tested by organisation size, which revealed a total of 62 significant correlations between the latent variables tested. Identical correlations were present in both models in 22 cases. After testing the hypotheses, critical variables (nature of work, normative commitment, benefits, co-workers and organisational commitment) were identified that determine employees’ organisational commitment and intention to leave, regardless of the size of the organisation.

As a result of this research, the models developed are suitable for identifying differences in organisational staffing levels, but there is as yet no empirical evidence on the use of the scales for homogeneous groups of employees.

The results show that employees’ normative commitment and organisational commitment are critical factors for retention. Of the satisfaction factors examined, the nature of work, benefits and co-workers have a significant impact on retention in organisations, so organisational retention measures should focus on improving satisfaction regarding these factors.

The readers of the journal would appreciate the work, which highlights the significance of employee psychology and retention for organisational success.

The study is based on primary data and, to the best of the authors’ knowledge, is one of the few studies that take a holistic approach to organisational staff retention in the context of the moderating effect of organisational size. This study contributes to a comprehensive understanding of the phenomenon of employee retention and in contrast to previous research, examines the combined effect of several factors.