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The paper aims at analyzing the co-movements between stock returns and oil prices (West Texas Intermediate, Brent) controlling or not for COVID-19.

It uses continuous wavelet transforms and wavelet coherence over the period July 19, 2019 to August 16, 2021 based on daily data. Continuous wavelet transforms provide an over complete representation of stock returns signals by letting the translation and scale parameters of the wavelets vary continuously.

There are not significant evidence supporting the fact that the COVID-19 has altered the relationship between stock returns and oil prices except perhaps in the case of South Africa. In fact, Southern African Development Community stock markets react more to oil prices than to health shock such as the COVID-19.

The findings of the study are original and have not been published anywhere prior.

The purpose of this study is to investigate the interplay between fiscal dominance and monetary policy in South Africa from 1960 to 2023.

The study employs a structural vector autoregression (SVAR) medel to analyze the relationship between fiscal dominance and monetary policy. Short-term and long-term shocks of government borrowing and deficits are examined to understand their impact on inflation dynamics.

Fiscal dominance has a significant effect both in the short and long run. There is evidence that government debt and deficits increase inflation, overriding the effects of monetary policy aimed at maintaining price stability. On the other hand, the study reveals that money supply shocks have a greater effect in reducing fiscal dominance compared to interest rate shocks. The variance movement on inflation is significantly explained by government debt and deficits. This emphasizes the persistence of inflationary pressures associated with fiscal dominance, highlighting the importance of effective policy interventions to mitigate inflationary risks.

This study contributes to the existing literature by providing insights into the dynamics of fiscal dominance in South Africa. Moreover, this study extends the theoretical framework of the fiscal theory of the price level (FTPL) and the government budget constraint. This study contributes valuable insights into the dynamics of fiscal dominance in South Africa and offers guidance for policymakers in formulating strategies to safeguard economic stability.

While operational performance is important for a company's competitiveness and profitability, this study claims that procurement may be required to drive operational performance. This study aims to focus on how procurement practices is related to operational performance among selected manufacturing firms.

The model was tested on a sample of 329 manufacturing firms in clothing and textiles, chemicals and plastics, food and beverages processing, wood processing, metal processing and pharmaceutical manufacturing industries in a developing economy.

The results indicate that firms with higher and optimal level of procurement practices achieve higher levels of operational performance. Regardless of the H1 rationale, this study suggests that increasing procurement techniques has a limit in terms of improving operational performance. This study establishes that extreme level of procurement practices is associated with decreasing operational performance.

This study calls attention to how managers can guide organizations in refining their procurement strategies and practices; there is the need to strive to strike a balance between diversification and efficiency in procurement.

Manufacturing firms are often integral parts of local communities. The decisions they make regarding procurement practices can impact the economic health of these communities. Striking a balance between diversification and efficiency can contribute to sustainable business practices that benefit both the company and the local community.

As the main contribution, this study brings the additional perspective that extreme level of procurement practices is associated with decreasing operational performance.

The present study aims to propose a framework elucidating the attributes of mobile augmented reality (AR) shopping apps (i.e., spatial presence, perceived personalization and perceived intrusiveness) and how they translate to downstream consumer-related outcomes (i.e., immersion, psychological ownership and stickiness to the retailer).

By conducting a questionnaire-based survey, 308 responses were collected, and the data were submitted to partial least square structural equation modeling (PLS-SEM) and artificial neural network (ANN) analyses.

A few important findings were generated from the present study. First, attributes of mobile augmented reality shopping apps (i.e., spatial presence, perceived personalization and perceived intrusiveness) influence stickiness to the retailer through immersion and consumer empowerment in serial. Second, immersion positively influences psychological ownership. Third, the optimum stimulation level moderates the relationship between spatial presence and immersion. Lastly, a post-hoc exploratory finding yielded by the multigroup analysis uncovered the moderating effect of gender.

This study offers a novel contribution to the smart retail literature by investigating the role of mobile AR shopping apps in predicting consumers' stickiness to the retailer. A holistic framework elucidating the serial mediating effect of immersion and consumer empowerment, and the moderating roles of optimum stimulation level and gender were validated.

This chapter examines three common fintech use cases transforming the financial industry. First, the chapter introduces fintech's role in enhancing financial services and promoting financial inclusion, especially through digital platforms. Second, it investigates various fintech applications that support financial institution management by harnessing the power of artificial intelligence (AI) and machine learning (ML). Finally, the chapter explores fintech use cases related to the regulatory environment, including regulatory technology (regtech), blockchain technology, and cryptocurrencies. The insights presented in this chapter cater to researchers and practitioners keen on better understanding fintech's diverse applications in the ever-evolving financial industry landscape.

The United Arab Emirates (UAE) offers a level playing field to all ethnic entrepreneurs (EE’s) operating from within it. The purpose of this qualitative research case study is to explore the reasons underpinning the relatively greater success that Indian-origin EE’s in the UAE have been enjoying for sustained periods – and across diverse industries – relative to their counterparts belonging to several other nations.

Qualitative research case study that draws from data gathered through 30 interviews of participants identified through expert sampling.

Whereas the UAE treats all its ethnic entrepreneurs (EE’s) alike and provides them with a level platform to operate from, the EE’s from India have consistently been outperforming those from all other nations, particularly within the context of the UAE’s large businesses spanning diverse industries. Three features seem to explain their success: their high tolerance for ambiguity; thriftiness; and intercultural competence.

Two key limitations were faced: firstly, the negligible research literature on ethnic entrepreneurship in the UAE, and related official statistics such as details (by ethnicity/nationality) of EE-owned businesses, and secondly, the industry-wise break down of such businesses and their performance, as available in other developed nations hosting EE’s. Resultantly, alternate sources of data have been used to complete this research.

Given the UAE’s national-level institutionalised efforts to promote entrepreneurship amongst its citizens and wider populace, there are many implications that this study holds for existing and future entrepreneurs.

While on the one hand, the UAE and the wider Gulf Cooperation Council region have been witnessing frenetic ethnic entrepreneurial activity in the past decade, the research literature on the regions’ ethnic entrepreneurship is extremely patchy. This case study serves to significantly bridge this gap, and to the best of the authors’ knowledge, this is the first work, that extensively explores the entrepreneurial trajectory of Indian EE’s in the UAE, and the factors driving their success.

This study aims to analyze government hotline text data and generating forecasts could enable the effective detection of public demands and help government departments explore, mitigate and resolve social problems.

In this study, social problems were determined and analyzed by using the time attributes of government hotline data. Social public events with periodicity were quantitatively analyzed via the Prophet model. The Prophet model is decided after running a comparison study with other widely applied time series models. The validation of modeling and forecast was conducted for social events such as travel and educational services, human resources and public health.

The results show that the Prophet algorithm could generate relatively the best performance. Besides, the four types of social events showed obvious trends with periodicities and holidays and have strong interpretable results.

The research could help government departments pay attention to time dependency and periodicity features of the hotline data and be aware of early warnings of social events following periodicity and holidays, enabling them to rationally allocate resources to handle upcoming social events and problems and better promoting the role of the big data structure of government hotline data sets in urban governance innovations.