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This paper aims to explore the role of the researcher’s emotions in ethnographic practice in accounting research. This paper focuses on shame as an emotion that lingers on, despite the efforts to work through those emotions.

The authors conducted a collective autoethnography to make sense of the fieldwork and after-fieldwork emotions and their consequences. This autoethnography began with the three authors discovering their shared feeling of shame.

Building on Hochschild’s theory (1979, 1983) on emotional labor, the authors demonstrate how shame emerged as a central and lingering emotion of the ethnographies beyond an emotional labor process. The authors show how a double shame appeared toward the field participants and the academic accounting community, affecting the writing and the work.

The authors demonstrate that the perception of the research community’s rules of feelings gives rise to emotions that ultimately change the work. The authors show how collective autoethnography can help accounting research to acknowledge and give room to emotions.

Organizational theorists and strategy scholars are both interested in how organizations deal with ambiguity, especially in relation to implementation. This chapter examines one source of ambiguity that organizations face, which is based on their efforts to implement moral mandates. These mandates, which are related to areas such as environmental sustainability and diversity, are inherently ambiguous, as they lack a shared understanding regarding their scope and associated practices. They are also often broad and systemic and may be unclearly aligned with an organization's strategy. Due to these challenges, in this chapter, we theorize that collective action at the field level is necessary for organizations to advance and concretize moral mandates. We examine this theorizing through the case of the implementation of sustainability in higher education. We hypothesize and find support for the idea that when an organization's members engage in collective action at the field level, those organizations have an increased likelihood of achieving sustainability implementation. To gain insight into this field-to-organization relationship, we qualitatively examine 18 years of conversations from an online forum to develop a process model of moral mandate implementation. We theorize that collective action functions as a field-configuring space, in which actors from a variety of organizations come together to (1) refine the scope of the mandate and (2) create an implementation repertoire that actors can draw on when seeking to bring sustainability to their own organizations. Overall, our study provides a model of how ambiguous moral mandates can be implemented by highlighting the important role of collective action across organizations in concretizing those mandates and providing actors with the tools for their implementation.

In past decades, artificial neural network (ANN) models have revolutionised various stock market operations due to their superior ability to deal with nonlinear data and garnered considerable attention from researchers worldwide. The present study aims to synthesize the research field concerning ANN applications in the stock market to a) systematically map the research trends, key contributors, scientific collaborations, and knowledge structure, and b) uncover the challenges and future research areas in the field.

To provide a comprehensive appraisal of the extant literature, the study adopted the mixed approach of quantitative (bibliometric analysis) and qualitative (intensive review of influential articles) assessment to analyse 1,483 articles published in the Scopus and Web of Science indexed journals during 1992–2022. The bibliographic data was processed and analysed using VOSviewer and R software.

The results revealed the proliferation of articles since 2018, with China as the dominant country, Wang J as the most prolific author, “Expert Systems with Applications” as the leading journal, “computer science” as the dominant subject area, and “stock price forecasting” as the predominantly explored research theme in the field. Furthermore, “portfolio optimization”, “sentiment analysis”, “algorithmic trading”, and “crisis prediction” are found as recently emerged research areas.

To the best of the authors’ knowledge, the current study is a novel attempt that holistically assesses the existing literature on ANN applications throughout the entire domain of stock market. The main contribution of the current study lies in discussing the challenges along with the viable methodological solutions and providing application area-wise knowledge gaps for future studies.

This study aims to capture how the association between a multichannel relational communication strategy (MRCS) and customer performance is contingent upon such customer performance (low- versus high-performance customers) and to reconcile past contradictory results in this marketing-related topic. To this end, the authors propose and validate the method of quantile regression as an unconventional, yet effective, means to proceed to that reconciliation.

This study collected data from 4,934 customers of a private pension fund firm and accounted for both firm- and customer-initiated relational communication channels (RCCs) and for customer lifetime value (CLV). This study estimated a generalized linear model and then a quantile regression model was used to account for customer performance heterogeneity.

This study finds that specific RCCs present different levels of association with performance for low- versus high-performance customers, where outcome customer performance is the dependent variable. For example, the relation between firm-initiated communication (FIC) and performance is stronger for low-CLV customers, whereas the relation between customer-initiated communication (CIC) and performance is increasingly stronger for high-CLV customers but not for low-CLV ones. This study also finds that combining different forms of FIC can result in a negative association with customer performance, especially for low-CLV customers.

The authors tested the conceptual model in one single firm in the specific context of financial services and with cross-sectional data, so there should be caution when extrapolating this study’s findings.

This study offers nuanced and precise managerial insights on recommended resource allocation along with relational communication efforts, showing how managers can benefit from adopting a differentiated-customer performance approach when designing their MRCS.

This study provides an overview of the state of the art of MRCS, proposes a contingency analysis of the relationship between MRCS and performance based on customer performance heterogeneity and suggests the quantile method to perform such analysis and help reconcile past contradictory findings. This study shows how the association between RCCs and CLV varies across the conditional quantiles of the distribution of customer performance. This study also addresses a recent call for a more holistic perspective on the relationships between independent and dependent variables.

The purpose of this paper is to offer a comprehensive overview of current research on customer behavior in the business-to-business (B2B) context and propose a research agenda for future studies. Despite being a relatively recent area of interest for academics and practitioners, a literature review that synthesizes existing knowledge into coherent topics and outlines a research agenda for future research is still lacking.

Drawing on a systematic literature review of 219 papers and using a text-mining approach based on the Latent Dirichlet Allocation algorithm, this paper enhances the existing knowledge of B2B customer behavior and provides a descriptive analysis of the literature.

From this review, ten major research topics are found and analyzed. These topics were analyzed through the lens of the Theory, Context, Characteristics and Method framework, providing a summary of key findings from prior studies. Additionally, an integrative framework was developed, offering insights into future research directions.

This study presents a novel contribution to the field of B2B by providing a systematic review of the topic of customer behavior, filling a gap in the literature and offering a valuable resource for scholars and managers seeking to advance the field.

Recent research suggests positive links between adolescents' participation in sports and the quality of their relationships with their fathers. It is unclear, however, the degree to which the gendered nature of sports, and in particular the ways sports have been used to define and express masculinity, mean that these important links between sports participation and parent–child relationships might or might not extend to relationships with mothers. Recent scholarship connects joint recreational activities to mother–child relationships, but here we extend these ideas in connection to adolescents' formal sports participation. We use the National Longitudinal Study of Adolescent to Adult Health from the United States to evaluate potential connections between adolescent sports participation and maternal relationships, focusing on the adolescent's perspective on joint activities with mother, closeness to and warmth and communication with mother, and satisfaction with the relationship with mother. We also examine whether these associations differ for boys and girls. We found that adolescents' sports participation was good for relationships with their mothers, but also that there were gender differences in how sport paid off for boys and girls. We discuss our findings in terms of contemporary shifts in gendered norms and conclude that gender may remain salient to how sports participation can promote mother–child relationships.

The scientific community shares a heritage of knowledge generated by several different fields of research. Identifying how scientific interest evolves is relevant for recording and understanding research trends and society’s demands.

This article presents SciBR-M, a novel method to identify scientific interest evolution from bibliographic material based on Formal Concept Analysis. The SciBR-M aims to describe the thematic evolution surrounding a field of research. The method begins by hierarchically organising sub-domains within the field of study to identify the themes that are more relevant. After this organisation, we apply a temporal analysis that extracts implication rules with minimal premises and a single conclusion, which are helpful to observe the evolution of scientific interest in a specific field of study. To analyse the results, we consider support, confidence, and lift metrics to evaluate the extracted implications.

The authors applied the SciBR-M method for the Educational Data Mining (EDM) field considering 23 years since the first publications. In the digital libraries context, SciBR-M allows the integration of the academy, education, and cultural memory, in relation to a study domain.

Cultural changes lead to the production of new knowledge and to the evolution of scientific interest. This knowledge is part of the scientific heritage of society and should be transmitted in a structured and organised form to future generations of scientists and the general public.

The method, based on Formal Concept Analysis, identifies the evolution of scientific interest to a field of study. SciBR-M hierarchically organises bibliographic material to different time periods and explores this hierarchy from proper implication rules. These rules permit identifying recurring themes, i.e. themes subset that received more attention from the scientific community during a specific period. Analysing these rules, it is possible to identify the temporal evolution of scientific interest in the field of study. This evolution is observed by the emergence, increase or decrease of interest in topics in the domain. The SciBR-M method can be used to register and analyse the scientific, cultural heritage of a field of study. In addition, the authors can use the method to stimulate the process of creating knowledge and innovation and encouraging the emergence of new research.

Mentoring is an essential tool for teacher education, not least because it allows knowledge and experience sharing. Research findings suggest a close relationship between mentoring and the well-being of those involved. However, little is known about this relationship or the mechanisms involved. This paper aims to discuss the aforementioned issues.

Through an integrative literature review, important links between mentor and mentee well-being and certain aspects of mentoring are explored. The results of the review are then synthesised into a theoretical framework.

The framework developed here posits that the well-being of teachers relates to the quality of mentoring. This includes teachers' perceptions of mentoring and their decision to get involved, their contributions to functional mentor–mentee relationships and the selection and use of mentoring styles that support both mentor and mentee well-being. Moreover, the framework hypothesises that the quality of mentoring received by mentees is related to their well-being, which is in turn connected to their professional development. Most of these relationships appear to be bidirectional, meaning that mentee well-being also contributes to mentoring quality and mentor well-being. Finally, it is hypothesised that the well-being of both mentors and mentees is connected to the school context in which the mentoring takes place.

This work provides a novel, comprehensive framework for future examinations of the connections between well-being and mentoring. It synthesises the prior work on this topic by integrating findings from both the mentor and mentee perspectives into a single framework.

This chapter discusses the steps taken to access and use the ACS five-year data. The format of the data is discussed pointing out the fact that there is no requirement that an ACS five-year variable holds data for the same field year to year. The development of a cross-reference table is discussed allowing the data to be accessed by a common label.

The purpose of this article is to contribute to the digital development and utilization of China’s intangible cultural heritage resources, research on the theft of intangible cultural heritage resources and knowledge integration based on linked data is proposed to promote the standardized description of intangible cultural heritage knowledge and realize the digital dissemination and development of intangible cultural heritage.

In this study, firstly, the knowledge organization theory and semantic Web technology are used to describe the intangible cultural heritage digital resource objects in metadata specifications. Secondly, the ontology theory and technical methods are used to build a conceptual model of the intangible cultural resources field and determine the concept sets and hierarchical relationships in this field. Finally, the semantic Web technology is used to establish semantic associations between intangible cultural heritage resource knowledge.

The study findings indicate that the knowledge organization of intangible cultural heritage resources constructed in this study provides a solution for the digital development of intangible cultural heritage in China. It also provides semantic retrieval with better knowledge granularity and helps to visualize the knowledge content of intangible cultural heritage.

This study summarizes and provides significant theoretical and practical value for the digital development of intangible cultural heritage and the resource description and knowledge fusion of intangible cultural heritage can help to discover the semantic relationship of intangible cultural heritage in multiple dimensions and levels.