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Research background: Faced with multiple media scandals concerning the pollution resulting from manufacturing activities, and encouraging the overconsumption of clothing, international fast fashion retailers have often had to resort to the elaboration and implementation of sustainable strategies aimed at environmental protection and reducing resource consumption. Generating customer satisfaction and loyalty depends increasingly on the extent to which retailers manage to employ socio-environmental responsibility besides the traditional retail store attributes. The purpose of this article: The objective of the paper is to evaluate the influence of consumer-oriented store attributes in generating satisfaction and loyalty towards the fast fashion store, highlighting the influence of socio-environmental responsibility on the two constructs. Methods: Based on the literature review, a conceptual model considering the effects of stores' attributes on store satisfaction and store loyalty and influenced by socio-environmental responsibility is proposed. Data were collected with the help of face-to-face administrated questionnaires before the outbreak of the COVID-19 pandemic in an emerging market (Romania). The data were analyzed via structural equation modeling in SmartPLS, for the three considered consumer generations: Generation X, Millennials and Generation Z. Findings & value added: For all consumer generations, all store attributes contribute to the direct generation of fast fashion store satisfaction and store loyalty; nevertheless, the intensity varies in levels of significance. Socio-environmental responsibility does not significantly determine store satisfaction, but does have a strong influence on fast fashion store loyalty. The results detailed according to the generations indicate a similar situation: each store attribute influences the satisfaction of one or other generation, apart from socio-environmental responsibility. This work makes an essential contribution to the extension of the generational theory, highlighting the various individualities, perceptions, and behaviors. This cross-generational research broadens knowledge on how different consumer generations behave when shopping from fast fashion stores. The research also extends the S-O-R model, which is used to understand the relationship between store attributes (stimulus), consumer satisfaction (organism), and consumer loyalty (response) towards fast fashion stores.
EN
Research background: This article discusses how artificial intelligence (AI) is affecting workers' personal and professional lives, because of many technological disruptions driven by the recent pandemic that are redefining global labor markets. Purpose of the article: The objective of this paper is to develop a systematic review of the relevant literature to identify the effects of technological change, especially the adoption of AI in organizations, on employees’ skills (professional dimension) and well-being (personal dimension). Methods: To implement the research scope, the authors relied on Khan's five-step methodology, which included a PRISMA flowchart with embedded keywords for selecting the appropriate quantitative data for the study. Firstly, 639 scientific papers published between March 2020 to March 2023 (the end of the COVID-19 pandemic according to the WHO) from Scopus and Web of Science (WoS) databases were selected. After applying the relevant procedures and techniques, 103 articles were retained, which focused on the professional dimension, while 35 papers were focused on the personal component. Findings & value added: Evidence has been presented highlighting the difficulties associated with the ongoing requirement for upskilling or reskilling as an adaptive reaction to technological changes. The efforts to counterbalance the skill mismatch impacted employees' well-being in the challenging pandemic times. Although the emphasis on digital skills is widely accepted, our investigation shows that the topic is still not properly developed. The paper's most significant contributions are found in a thorough analysis of how AI affects workers' skills and well-being, highlighting the most representative aspects researched by academic literature due to the recent paradigm changes generated by the COVID-19 pandemic and continuous technological disruptions.
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