European Journal of Economics

Cross-Border E-Commerce and Its Implications for Consumer Protection (2019–2024): A Systematic Literature Review

Philipp Goetzinger — 2025-07-01

This paper provides a systematic literature review examining the implications of cross-border e-commerce (CBEC) for consumer protection from 2019 to 2024. The study identifies key challenges, including technological vulnerabilities, regulatory discrepancies, and consumer manipulation risks in the global e-commerce landscape. Utilizing Scopus database searches, 16 articles were analyzed to explore the evolving nature of consumer vulnerabilities due to innovations such as algorithmic price discrimination, deceptive marketing practices, and deepfakes. The findings highlight the need for harmonized international regulations, enhanced digital literacy programs, and adaptive frameworks to mitigate privacy violations and promote trust in cross-border transactions. The Stimulus-Organism-Response (SOR) model, Technology Acceptance Model (TAM), and insights from behavioral studies underpin the discussion of consumer behavior and its susceptibility to manipulative tactics. Open research gaps are identified, emphasizing the need for future studies on psychological manipulation mechanisms, jurisdictional regulatory harmonization, and consumer digital literacy initiatives. The study concludes with recommendations for policymakers and businesses to prioritize transparency, consumer education, and technological safeguards to ensure a secure, fair, and trustworthy CBEC environment.

‘The Effect of Critical Factors on Product Quality’: An Applied Research on Electrical Industry in Egypt

Mohamed Khafaga — 2025-07-01

The purpose of this study is to investigate the effect that critical factors on product quality. Which investigates the influence that five essential elements—markets, manpower, money capital, management, and raw materials—have on the product quality produced in the electrical sector. The study utilised a quantitative methodology, and it gathered information from 369 individuals that participated in the survey inside Elsewedy Electric. Structural Equation Modelling (SEM) was utilised for the purpose of data analysis, and the SmartPLS software was utilised for Confirmatory Factor Analysis (CFA) in order to test the hypothesised correlations between the essential elements and product quality. At Elsewedy Electric, the results of the SEM study suggest that all five essential factors—Markets, Manpower, Money Capital, Management, and Raw Materials—have a strong beneficial effect on product quality. This is the conclusion that can be drawn from the findings of the analysis. With a confidence level of 99%, these data were statistically significant at a level of p < 0.05, thereby verifying all five hypotheses that were being investigated in this study. A detailed evaluation of many essential aspects that influence product quality within the specific context of Egypt's electrical industry is provided in this study.

Assessing Volatility of Returns in Select Stock Markets: Evidence from India, Singapore and USA

Arshi Firdous — 2025-07-01

Volatility can be regarded as one of the crucial aspects to judge movements of stock price while making financial decisions. This article tried to articulate the movements of stock return during the time comprising before, after COVID-19 pandemic period empirically. To accurately incarcerate the volatility of asset returns, the study presented the commonly used GARCH (1,1) volatility model for assessing the volatility of daily returns of STI (Singapore), Dows and Jones (USA), BSE Sensex (India) stock prices from 1st Jan 2018- 31st Dec 2022, where from 1st Jan 2018 to 16th Jan 2020 is denoted as pre covid-19 phase and From 17th Jan 2020- 31st Dec 2022 is considered as during COVID- 19 phase. The findings suggest that all the markets under study had strong GARCH effect and the volatility clustering is relatively relentless and also the effect of older news upon volatility is quite persistent. In upcoming period, researchers can assess the performance of time series models with multiple variables using day by day return data of more such global markets.