Abstract
Integrating emerging technologies, such as AI, the Metaverse, and IoT, revolutionizes management and brand practices. Brands can create captivating virtual experiences within the metaverse, including virtual storefronts and interactive events. Scientific data on brand management in the metaverse must be improved due to the concept’s early-stage development. While virtual environments exist, they do not fully encompass the metaverse’s scope. So, this research bridges this gap by exploring the relationship between brand management and the metaverse, focusing on consumer perceptions and their contribution to brand equity in this virtual realm. Netnography with a data mining approach was the methodology followed in this paper. Data were extracted by a metaverse community on the Reddit platform and, in total, 696 posts and comments were analyzed from June 2022 until May 2023. The results highlighted a positive and favorable consumer perception of brand management in the metaverse reality. This research contributes to the emerging field of metaverse brand management, investigating the impact of consumer perceptions on brand equity. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.

Abstract
A major challenge in Natural Language Processing is obtaining annotated data for supervised learning. An option is the use of crowdsourcing platforms for data annotation. However, crowdsourcing introduces issues related to the annotator’s experience, consistency, and biases. An alternative is to use zero-shot methods, which in turn have limitations compared to their few-shot or fully supervised counterparts. Recent advancements driven by large language models show potential, but struggle to adapt to specialized domains with severely limited data. The most common approaches therefore involve the human itself randomly annotating a set of datapoints to build initial datasets. But randomly sampling data to be annotated is often inefficient as it ignores the characteristics of the data and the specific needs of the model. The situation worsens when working with imbalanced datasets, as random sampling tends to heavily bias towards the majority classes, leading to excessive annotated data. To address these issues, this paper contributes an automatic and informed data selection architecture to build a small dataset for few-shot learning. Our proposal minimizes the quantity and maximizes diversity of data selected for human annotation, while improving model performance. © 2024 The Association for Computational Linguistics.

Abstract
Shopping on the Internet is now an everyday activity for consumers. An understanding of which constructs are relevant in this activity is of crucial importance for online stores to adapt their strategies. The existence of a holistic model with these relevant constructs, however, is lacking in the literature. This research is exploratory in nature. The study aimed to identify the constructs that are closely and consistently related to the customer experience in online stores. In the literature review, 15 constructs were identified. They are web content, customer service, service quality, terms and conditions, digital channels, security and privacy, brand, perceived price, perceived risk, word of mouth, perceived value, trust, satisfaction, and loyalty. The review of the literature also revealed the imperative of building or revising the measurement scales of those constructs that were identified to allow for their operationalization. For this reason, a questionnaire with scales that have been adapted from several authors has also been proposed. This questionnaire has a feasible number of questions to be answered.

Abstract
Objetivo: descobrir a razão pela qual resultados inesperados foram gerados na determinação das publicações historicamente mais influentes (landmarks) de Ciência da Informação e Biblioteconomia (CI&B) da Web of Science (WoS). Metodologia: Recuperamos dados de todos os artigos e revisões do CI&B, do período 1980-2017 (N=93.330), identificamos e analisamos as áreas de periódicos dos artigos que citaram os landmarks. Resultados: Mostramos que os periódicos que mais citam os dois primeiros landmarks da CI&B são da área de Gestão, Negócios e Sistemas de Informação. Mostramos também que cinco dos dez primeiros landmarks possuem conteúdos fortemente voltados para Gestão, Sociologia, Marketing, Comunicação e Sistemas de Informação e que só aparecem como landmarks da CI&B porque são citados por periódicos da área de Gestão, categorizados no WoS, também, como CI&B. No caso da área “Métricas da Informação”, o resultado revela publicações reconhecidas na literatura como cruciais. Conclusões: Quando se desenvolve um estudo de uma área de pesquisa utilizando a categorização da WoS como base para a amostra, outra área pode interferir neste estudo, produzindo resultados inconsistentes. A análise da categorização dos periódicos, conforme realizada por este estudo, é fundamental para avaliar corretamente o impacto de um artigo, pois as métricas de produção utilizadas na avaliação acadêmica precisam ser normalizadas por área.

Abstract
This study aimed to identify the constructs related to customer experience that underpin e-commerce, as well as their interconnections, to develop a comprehensive conceptual model based on theories-in-use. A quantitative approach was employed through a survey of 441 respondents. Data analysis was conducted using partial least squares structural equation modeling. The research findings revealed that there are a total of 11 constructs: customer experience, customer satisfaction, customer loyalty, word-of-mouth, trust, perceived risk, security and privacy, web content, perceived price, perceived value, and service quality. Furthermore, twelve relationships were established between these constructs, which led to the development of a holistic conceptual model. The identified constructs and the relationships between them are hierarchized, which has practical implications for businesses. It allows them to concentrate on operational activities and formulate and implement strategies that are valued by consumers and supported by empirical evidence. The originality and value of this research lie in the conception and development of a comprehensive e-commerce model, which includes eleven constructs and twelve relationships. It also highlights the pivotal role of the customer experience.

Abstract
The concept of sustainable fashion is becoming more relevant in today's society. The purpose of this research is to identify the determinants of the purchase intention of sustainable fashion, and the relationship between price and the purchase of sustainable fashion. A questionnaire was administered, which made it possible to define the concept of sustainable fashion, to use PLS-SEM to identify the determinants, and to apply linear regression models and t-tests of two independent samples (two-tailed test). The concept of sustainable fashion comprises the dimensions of manufacturing with a reduced environmental impact, consuming second-hand fashion products, manufacturing in an environmentally friendly way, reusing fashion products, manufacturing to last longer, manufacturing according to fair trade principles, using recycled materials, and manufacturing from organic materials. The PLS-SEM results show that purchase intention is determined by consumer knowledge, environmental beliefs, and willingness to pay more. The research also revealed that there is a non-linear (quadratic or exponential) relationship between the price of the product and the price increase that consumers are willing to pay and that they value the dimensions of sustainable fashion differently. The purchase intention determinants of consumers and non-consumers of sustainable fashion are identical, yet the dimensions of sustainable fashion are valued differently by each group.