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This paper analyzes the effect of institutional quality and economic freedom on investment and economic growth in sub-Saharan Africa (SSA).

Focusing on a panel of 27 countries, the study employed the panel fixed and random effect models to analyze data spanning from 2005 to 2018. The study also employed the Wu–Hausman test to determine if the endogeneity problem exists in the model.

The findings of the study show that individually, an improvement in economic freedom stimulates economic growth while the improvement in institutional quality is effective in spurring investment. However, the interaction effect of improvement in institutional quality and economic freedom is the stimulation of both investment and economic growth. The findings are robust to alternative model specifications.

The study implies that for SSA countries to effectively achieve higher investment and economic growth outcomes, there is the need to simultaneously strengthen institutional quality and improve economic freedom. Focusing on either of the factors without the other leads to less desirable growth and investment outcomes.

The study examined the combined influence of institutional quality and economic freedom on investment and growth in SSA. To the best of the authors’ knowledge, no study has investigated this in the context of SSA.

Given resource constraints such as time and staffing, hotels cannot respond to all negative online reviews (NORs). Therefore, this study investigates (1) what types of NORs hotels should prioritize responding; and (2) what response strategies are more effective in handling different types of NORs to minimize the negative ramifications.

Four experiments in the context of hospitability were used to test the hypotheses.

Our findings show that NORs with implicit conclusions (e.g. “I do not believe that is a good choice, you know what I mean.”) are more dissuasive than NORs with explicit ones (e.g. “Do not buy it.”) because the former NORs are perceived as more objective than the latter NORs. More importantly, our results show that firms do not need to respond to explicit NORs. When responding to implicit NORs, firms should prioritize those related to service failures caused by external (e.g. weather, technological misfunction) rather than internal (e.g. poor management, employee skills) factors.

Our studies focus on the language styles of Chinese NORs, and future research should investigate how language styles influence dissuasion in other languages.

Our results show that NORs with implicit conclusions negatively impact consumer attitude and thus hurt performance more significantly than those with explicit conclusions. Therefore, firms should allocate limited staffing and resources to NORs with implicit conclusions. When responding to implicit NORs, firms should select NORs that can be attributed to external factors.

Our findings shed light on the importance of the language styles of NORs and provide marketers with insights into how to handle NORs. Our results reveal that consumers perceive higher objectivity of NORs when these reviews are implicit than when they are explicit. Furthermore, this study contributes to the online review literature by suggesting that firms should tailor their response strategies for NORs based on the reviewers’ language styles.

The aim of this paper is to summarise the state-of-the-art debate on impact of artificial intelligence on unemployment and reporting up-to-date academic findings.

The paper is designed as a review of the labour vs capital conundrum, the differences between industrial automation and artificial intelligence, threat to employment, the difficulty of substituting, role of soft skills and whether technology leads to the deskilling of human workers or favors increasing human capabilities.

Some authors praise the bright future developments of artificial intelligence while others warn about mass unemployment. Therefore, it is paramount to present an up-to-date overview of the problem, compare and contrast its features with what happened in past innovation waves and contribute to academic discussion about the pros/cons of current trends.

The main value of this paper is presenting a balanced view of 100+ different studies, the vast majority from the last five years. Reading this paper will allow to quickly grasp the main issues around the thorny topic of artificial intelligence and unemployment.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-05-2023-0338