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Service quality is becoming an important issue for Dutch car service firms. In order to measure the service quality delivered develops an instrument based on the quality dimensions and the SERVQUAL questionnaire developed by Berry, Parasuraman and Zeithaml. Describes the building and testing of the instrument. The outcome of the research is that the instrument is easily applicable for Dutch garage firms. However, in contrast with the five SERVQUAL dimensions, the customers in the Dutch car service firms only distinguish three dimensions to judge the delivered quality, one of which appears to be totally specific to this sample. The three dimensions found in the research in car service firms are: customer kindness, tangibles, and faith. Only customer kindness contributes directly to the measured service quality.

The purpose of this paper is to test the so-called “Sell in May” effect in globally listed private equity markets based on monthly data covering the period 2004–2017.

Ordinary least squares regressions, generalized autoregressive conditional heteroscedasticity regressions and robust regressions are used to investigate the existence of the “Sell in May” effect in globally listed private equity markets. Additionally, the authors conduct robustness checks by dividing the sample period into two subperiods: pre-financial and post-financial crisis periods.

The authors find limited statistically significant evidence for the “Sell in May” effect. In particular, the authors observed a statistically significant “Sell in May” effect when taking time-varying volatility into account. These findings indicate that the “Sell in May” effect is driven by time-varying volatility. By contrast, economic significance as measured by visual return inspection and the magnitude of the estimated “Sell in May” coefficients in combination with their positive signs was found to be considerable.

The findings are important for all kinds of investors and asset managers who are considering investing in listed private equity.

The authors present a novel study that examines the “Sell in May” effect for globally listed private equity markets by using LPX indices, offering valuable insight into this growing asset class.

This study aims to establish a comprehensive understanding of the intricacies of how individuals engage with deepfakes, focusing on limiting adverse effects and capitalizing on their benefits.

This study conducted a meta-synthesis of qualitative studies on deepfakes, incorporating study-specific analysis followed by a cross-study synthesis.

Based on the meta-synthesis, the study developed an integrated conceptual framework based on the perspectives from the social shaping of technology theory embedding deepfake-related assertions, motivations, the subtleties of digital platforms, and deepfake-related repercussions.

The study offers crucial insights into the evolving nature of deepfakes as a socio-technical phenomenon and the significance of platform dynamics in deepfake production. It enables researchers to comprehend the cascading effects of deepfakes and positions them to evaluate deepfake-related risks and associated mitigation mechanisms.

The framework that emerges from the study illustrates the influence of platforms on the evolution of deepfakes and assists platform stakeholders in introducing effective platform governance structures to combat the relentless proliferation of deepfakes and their consequences, as well as providing guidance for governments and policymakers to collaborate with platform leaders to set guardrails for deepfake engagement.

Deepfakes have been extensively contested for both their beneficial and negative applications and have been accused of heralding an imminent epistemic threat that has been downplayed by some quarters. This diversity of viewpoints necessitates a comprehensive understanding of the phenomenon. In responding to this call, this is one of the first to establish a comprehensive, theoretically informed perspective on how individuals produce, process, and engage with deepfakes through a meta-synthesis of qualitative literature on deepfakes.