Abstract
São diversos os benefícios da utilização de indicadores e métricas de sustentabilidade organizacional,e referem-se à possível antecipação de condições e tendências, fornecimento de avisos de possíveis ocorrências e situações que evitem danos aos aspectos econômico, social e ambiental e auxílio nos processos de gestão. O objetivo deste estudo foi analisar as métricas de sustentabilidade organizacional, identificadas na literatura acadêmica nos últimos cinco anos. Seguindo a metodologia PRISMA, foram relacionadas sete pesquisas relevantes e enquadradas nos critérios de seleção. As principais contribuições, por meio da revisão sistemática, apontaram para estudos compostos de diferentes aspectos (empresas, cidades, regiões) ligados à sustentabilidade. Foram diversas métricas identificadas, algumas focando mais aspectos sociais da população e ou funcionários e outras mais os aspectos ambientais e seus impactos na sociedade e nas organizações. As limitações do estudo são decorrentes do método escolhido que considerou os últimos cinco anos na base Scopus e artigos completos em inglês.

Abstract
Classifying papers according to the fields of knowledge is critical to clearly understand the dynamics of scientific (sub)fields, their leading questions, and trends. Most studies rely on journal categories defined by popular databases such as WoS or Scopus, but some experts find that those categories may not correctly map the existing subfields nor identify the subfield of a specific article. This study addresses the classification problem using data from each paper (Abstract, Title, Keywords, and the KeyWords Plus) and the help of experts to identify the existing subfields and journals exclusive of each subfield. These exclusive journals are critical to obtain, through a pattern detection procedure that uses machine learning techniques (from software NVivo), a list of the frequent terms that are specific to each subfield. With that list of terms and with the help of optimization procedures, we can identify to which subfield each paper most likely belongs. This study can contribute to support scientific policy-makers, funding, and research institutions-via more accurate academic performance evaluations-, to support editors in their tasks to redefine the scopes of journals, and to support popular databases in their processes of refining categories.

Abstract
In a recent paper (10.1007/s11192-020-03386-9) we proposed a model to estimate the citations of an article in a database (Scopus/Web of Science) in which it is not indexed using the percentile rank of the database (Web of Science/Scopus) in which it is indexed. In this study we supplement the previous work with three advances: (1) by using 15 different research fields, corresponding to over 1 million papers, since we previously used only four fields; (2) by measuring the agreement between the percentile ranks in both databases using Lin's concordance correlation coefficient, since this coefficient has not been used previously to measure this agreement, but as a test with a sample of 15,400 papers to compare the actual and estimated number of citations; and (3) by using a robust data cleaning procedure. The results revealed a substantial concordance between percentile ranks of papers indexed in these two databases in all the research fields studied, and that this concordance is even stronger for high percentile values. This level of concordance suggests that we can consider the percentile of a paper in a database in which it is not indexed as being equal to the percentile of this paper in a database in which it is indexed. In other words, we increased the reliability of our previous conclusions that the percentile rank can be used as a citation database-normalization. The results of this study contribute to improve the use of citation counts in bibliometric studies, and to calculate research indicators when we need to use both bibliographic databases.

Abstract
Chatbots are website artificial intelligence-based and automated customer support tools to improve the customer experience, to reduce costs, and to improve service quality. This study aims to understand and analyze the user-technology interaction and technology-engagement success measures to assess online customer engagement with chatbots and the impact on repurchase intention, within e-commerce websites. The sample data consists of 227 online consumer responses collected through an electronic survey. Only 165 respondents, which have used a chatbot to assist the online purchase process, are included in the effective sample. This research contributes to the digital marketing literature by complementing existing research exploring human-technology interactions, assessing how consumers interact with chatbot technology and how it affects customer engagement and behavioral outcomes within e-retail contexts. The study findings provide several challenges for managers. Finally, it discusses emerging trends in the digital marketing field, offering insights for future research avenues. © 2023, IGI Global. All rights reserved.

Abstract
Social media has become a crucial point for brands to establish a connection with their consumers and potential consumers, being many times responsible for developing the need and converting it into a purchase. Thus, it is worth highlighting the role of influencers in social media that affect fashion purchase. Given the growth of sustainable fashion, it is necessary to verify the relationship between influencers and social media and the intention to purchase sustainable fashion. A conceptual model that aims to understand the effect of influencers' characteristics in the intention to purchase sustainable fashion is presented. The results show that consumer knowledge and willingness to pay more are the only factors that positively affect the purchase intention of sustainable fashion. Furthermore, the authors highlight that consumer knowledge is the construct that has a distinctly greater impact on the intention to purchase sustainable fashion. © 2023, IGI Global. All rights reserved.

Abstract
Email marketing plays a key role in business communications and is one of the most widely used applications by consumers. The literature review points to several determinants that, when applied, increase the open rate of newsletters. This research evaluates the impact of six determinants of persuasion on the opening rate of a newsletter in the hotel industry. The determinants are the day of sending, the time of sending, subject line personalization, scarcity appeal, curiosity appeal, and authority figure. The chosen methodology focused on real experiments, using a high-end luxury hotel, and the respective customer database. The newsletter was sent to the subscriber list, where one part received the control and the other part received a variant with the test version. Ten A/B tests were conducted for each determinant. The results obtained were not in line with what is indicated in the literature review. Although the literature review yielded results that showed that the application of determinants increased the open rate of newsletters, this study obtained findings to the opposite and did not confirm what was prescribed by the reviewed literature. The results of the A/B tests were conclusive and revealed that the determinants did not increase the open rate of newsletters.