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Despite the growing popularity of SHVL fashion, there is little empirical focus on the antecedent factors that influence consumers’ intention to purchase and recommend SHVL fashion. Drawing on insights from the stimulus–organism–response framework, this paper aims to investigate the motivational factors influencing the consumers’ attitudes and their intention to purchase and recommend SHVL fashion.

Primary data was gathered from 232 present customers of SHVL fashion products and analysed using the partial least square structural equation modelling.

Research findings show that eco-consciousness, treasure hunting, status consumption and the need for uniqueness were positively linked to intentions to purchase SHVL fashion through the intervening role of attitude. Attitude was positively linked with purchase intentions, which also positively influenced intention to recommend SHVL fashion.

The study findings assist brand managers in understanding how they can cater to the diverse needs of SHVL fashion consumers.

This research contributes significantly to the SHVL domain by examining core antecedents that motivate consumers’ intention to purchase and recommend SHVL fashion.

A pesar de la creciente popularidad de la moda de lujo vintage de segunda mano (SHVL), hay poco enfoque empírico en los factores antecedentes que influyen en la intención de los consumidores de comprar y recomendar moda de lujo vintage de segunda mano. Basándose en ideas del marco S-O-R, este documento investiga los factores motivacionales que influyen en las actitudes de los consumidores y su intención de comprar y recomendar moda de lujo vintage de segunda mano.

Se recopilaron datos primarios de 232 clientes actuales de productos de moda de lujo vintage de segunda mano y se analizaron utilizando el modelado de ecuaciones estructurales de mínimos cuadrados parciales.

Los hallazgos de la investigación muestran que la conciencia ecológica, la búsqueda de tesoros, el consumo de estatus y la necesidad de unicidad están vinculados positivamente con las intenciones de comprar moda de lujo vintage de segunda mano a través del papel intermediario de la actitud. La actitud se vinculó positivamente con las intenciones de compra, lo que también influyó positivamente en la intención de recomendar moda de lujo vintage de segunda mano.

Los hallazgos del estudio ayudan a los gerentes de marca a entender cómo pueden atender las diversas necesidades de los consumidores de moda de lujo vintage de segunda mano.

Esta investigación contribuye significativamente al dominio de la moda de lujo vintage de segunda mano al examinar los antecedentes clave que motivan la intención de los consumidores de comprar y recomendar moda de lujo vintage de segunda mano.

尽管二手复古奢侈品时尚（SHVL）日益流行, 但关于影响消费者购买和推荐二手复古奢侈品意图的前因因素的实证研究却很少。基于S-O-R框架的洞察, 本研究探讨了影响消费者态度及其购买和推荐二手复古奢侈品时尚意图的动机因素。

从232名现有二手复古奢侈品时尚产品的顾客中收集了主要数据, 并使用偏最小二乘结构方程模型（PLS-SEM）进行了分析。

研究发现, 环保意识、寻宝乐趣、地位消费和独特性需求通过态度的中介作用, 与购买二手复古奢侈品的意图正相关。态度与购买意图正相关, 购买意图也正向影响推荐二手复古奢侈品的意图。

研究结果帮助品牌经理了解如何满足二手复古奢侈品消费者的多样化需求。

本研究通过考察核心前因因素对消费者购买和推荐二手复古奢侈品时尚意图的动机的影响, 为二手复古奢侈品领域做出了重要贡献。

Current knowledge and research on students’ utilization and interaction with generative artificial intelligence (AI) tools in their academic work is limited. This study aims to investigate students’ engagement with these tools.

This research used survey-based research to investigate generative AI literacy (utilization, interaction, evaluation of output and ethics) among students enrolled in a four-year public university in the southeastern USA. This article focuses on the respondents who have used generative AI (218; 47.2%).

Most respondents used generative AI to generate ideas for papers, projects or assignments, and they also used AI to assist with their original ideas. Despite their use of AI assistance, most students were critical of generative AI output, and this mindset was reflected in their reported interactions with ChatGPT. Respondents expressed a need for explicit guidance from course syllabi and university policies regarding generative AI’s ethical and appropriate use.

Literature related to generative AI use in higher education specific to ChatGPT is predominantly from educators’ viewpoints. This study provides empirical evidence about how university students report using generative AI in the context of generative AI literacy.

Large classes pose challenges in managing different types of skills (e.g. maths, subject-specific knowledge, writing, confidence and communication), facilitating interactions, enabling active learning and providing timely feedback. This paper shares a design of a set of assessments for a large undergraduate economics course consisting of students from diverse cultural backgrounds. The benefits, challenges and learning experiences of students are analysed.

Students worked in groups to complete an assessment with several questions which would be useful as a revision for the individual assessment, the following week. Survey questionnaires with Likert-type questions and open-ended questions were used to analyse the learning and skill development that occurred because of the group work. Responses to the open-ended survey questions were coded and analysed by identifying the themes and categorising the various issues that emerged.

This assessment design developed group working skills, created opportunities to interact and enhanced learning. The analysis of the responses found that working with peers enabled the students to generate their own feedback, clear doubts and learn to solve problems. Effective communication, planning meetings and working around the diverse group members’ strengths and weaknesses are some graduate skills that are developed in this group assessment. The challenges were arranging meetings, finalising assessments, engagement of group members and unreliable technology. However, the students found ways to overcome these challenges.

This assessment design can be useful in higher education practice by introducing a mechanism for authentic collaborative practice. This paper adds to the literature on peer interactions and group work and enables effective learning at scale.

The increased digital interactions in the B2B industry have enhanced the importance of customer engagement as a measure of firm performance. This study aims to map and analyze temporal and spatial journeys for customer engagement in B2B markets from a bibliometric perspective.

The extant literature on customer engagement research in the B2B context was analyzed using bibliometric analysis. The citation analysis, keyword analysis, cluster analysis, three-field plot and bibliographic coupling were used to map the intellectual structure of customer engagement in B2B markets.

The research on customer engagement in the B2B context was studied more in western countries. The analysis suggests that customer engagement in B2B markets will take centre stage in the coming times as digital channels make it easier to track critical metrics besides other key factors. Issues like digital transformation, the use of artificial intelligence for virtual engagement, personalization, innovation and salesforce management by leveraging technology would be critical for improved B2B customer engagement.

The study provides a comprehensive reference to scholars working in this domain.

The study makes a pioneering effort to comprehensively analyze the vast corpus of literature on customer engagement in B2B markets for business insights.