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This paper aims to obtain the domain of the textual content generated by users of online social network (OSN) platforms. Understanding a users’ domain (s) of interest is a significant step towards addressing their domain-based trustworthiness through an accurate understanding of their content in their OSNs.

This study uses a Twitter mining approach for domain-based classification of users and their textual content. The proposed approach incorporates machine learning modules. The approach comprises two analysis phases: the time-aware semantic analysis of users’ historical content incorporating five commonly used machine learning classifiers. This framework classifies users into two main categories: politics-related and non-politics-related categories. In the second stage, the likelihood predictions obtained in the first phase will be used to predict the domain of future users’ tweets.

Experiments have been conducted to validate the mechanism proposed in the study framework, further supported by the excellent performance of the harnessed evaluation metrics. The experiments conducted verify the applicability of the framework to an effective domain-based classification for Twitter users and their content, as evident in the outstanding results of several performance evaluation metrics.

This study is limited to an on/off domain classification for content of OSNs. Hence, we have selected a politics domain because of Twitter’s popularity as an opulent source of political deliberations. Such data abundance facilitates data aggregation and improves the results of the data analysis. Furthermore, the currently implemented machine learning approaches assume that uncertainty and incompleteness do not affect the accuracy of the Twitter classification. In fact, data uncertainty and incompleteness may exist. In the future, the authors will formulate the data uncertainty and incompleteness into fuzzy numbers which can be used to address imprecise, uncertain and vague data.

This study proposes a practical framework comprising significant implications for a variety of business-related applications, such as the voice of customer/voice of market, recommendation systems, the discovery of domain-based influencers and opinion mining through tracking and simulation. In particular, the factual grasp of the domains of interest extracted at the user level or post level enhances the customer-to-business engagement. This contributes to an accurate analysis of customer reviews and opinions to improve brand loyalty, customer service, etc.

This paper fills a gap in the existing literature by presenting a consolidated framework for Twitter mining that aims to uncover the deficiency of the current state-of-the-art approaches to topic distillation and domain discovery. The overall approach is promising in the fortification of Twitter mining towards a better understanding of users’ domains of interest.

The purpose of this paper is to discuss the methodology in building an integrated domain information system with illustrations that provide proof of concept

The present work studies the usual search engine approach to information and its pitfalls. A methodology was adopted for construction of a domain‐based information system, known as Aerospace Information System (AERIS), comprising six distinct steps in identifying and sourcing, evaluating and then technically integrating resources into the information system. AERIS is an integrated gateway for resources in the domain of aerospace science and technology. AERIS is designed to provide information from varied sources such as formal publications (e.g. articles), aggregators (e.g. harvesters) and also informal resources such as blogs and discussion fora. Interaction is provided through a simple user interface.

The domain‐based information system with focussed collection and services serves patrons with more precision than general web search engines.

At present the AERIS system is populated with a limited number of resources. A fully‐fledged system may be developed based on the same model.

This original research work provides a model for a comprehensive integrated gateway to domain‐based information using open‐source tools.

This study deployed a bibliometric analysis of 604 academic articles on celebrity endorsement collected from the Scopus database from January 1960 to August 2021 (the first published article dated back to 1976). This study integrated three bibliometric analyses: timeline visualization, co-citation cluster analysis, and historical direct citation analysis. This study conducted a qualitative review to further examine the obtained quantitative results.

This study reviewed the existing research on the celebrity endorsement domain. Based on a bibliometric review of existing literature, this study aimed to provide main theoretical roots and research trajectories and propose new research avenues concerning the theory, context, characteristics, and research methodologies adopted within the marketing discipline.

The findings revealed that the existing relevant research focused on celebrity endorsement in different periods. The main theoretical roots and research trajectories identified were developed under the influence of primary articles from co-citation analysis and historical direct citation.

Based on the quantitative bibliometric analysis and a qualitative literature review, this study has provided a comprehensive overview of the current stage of this domain. The study also has underscored an abundance of celebrity endorsement literature and revealed the research topics that require further investigations to theoretically and empirically advance the understanding of celebrity endorsement.

Some topics were recommended for further research within the theory, context, characteristics, and methodology aspects. Some practical examples and suggestions are also given in the study.

This study proposed a bibliometric overview of celebrity endorsement in the marketing discipline, especially based on timeline visualization, co-citation cluster analysis, and historical direct citation analysis. Furthermore, this study offered a research agenda for further studies in the marketing discipline.

This literature review aims to synthesise the research on various sustainable product branding activities and their impact on consumer responses to sustainable products and brands.

This literature review is semi-systematic and can be classified as a domain-based review. The search strategy was systematic and well-defined.

The authors identified four themes: building brand equity, brand communication, product development and third-party labels and ratings, within the sustainable product branding activities that influence consumers' responses to sustainable products and brands. The study's findings revealed diverse, and not always favourable, types of behavioural and attitudinal responses from consumers. As for the positive consumer responses, the authors found positive attitudes towards brands, willingness to pay a premium price and positive word-of-mouth intentions. As for the negative consumer responses, the authors found perceived greenwashing, negative brand evaluations and resistance to sustainable products with unfamiliar third-party labels. Several future research propositions and implications for research and practice are discussed.

Despite the large number of studies that look at sustainable branding strategies, there is a gap in terms of synthesising the knowledge on consumer responses to sustainable product branding strategies. This paper intends to fill this gap.

In this paper the authors aim to review the state-of-the-art literature on online review systems and their impacts on consumer behavior and retailers' performance with the aim of identifying research gaps related to different design features of review systems and developing future research agenda.

The authors conducted a systematic review based on PRISMA 2020 protocol, focusing on studies published in the domains of retailing and marketing. This procedure resulted in 48 selected papers investigating the design features of retailer online review systems.

The authors identify eight design features that are controllable by retailers in an online review system. The design features have been researched independently in previous literature, with some features receiving more attention. Most selected studies focus on the design features adapted metrics and review presentations, while other features are generally neglected (e.g. rating dimensions). Previous literature argues that design features affect consumer behaviors and retailers' performance. However, the interactions among the features are still neglected in the literature, creating a relevant gap for future research.

This paper distinguishes between different types of retailer online review systems based on how they are implemented. The authors summarize the state-of-the-art of relevant literature on design features of online review systems and their effects on consumer- and retailer-related outcome variables. This systematic literature review distinguishes between online reviews provided on websites controlled by retailers (internal systems) and third-party websites (external systems).

The COVID-19 pandemic has affected educational systems worldwide, forcing them to abruptly shift from face-to-face to online teaching and learning. This case study illustrates how a traditional lecture-based activity for undergraduate students in a Management of Health Service Organizations program was transformed into an argumentation-based learning activity using the technique of digital concept mapping and was deployed in an online format during the COVID-19 lockdown.

The students were tasked with solving an ill-structured problem bearing significance for their future professional lives and connected to the contents of their course (entitled “Assimilation of service quality in health systems”). The activity was composed of two phases. In Phase 1, participants were asked to provide five arguments to establish their proposed solution to the problem by using a concept map on a digital platform (Mindomo). In Phase 2, they were asked to substantiate their arguments. Reflective journals were used to ascertain how the participants viewed the activity. Thematic analysis was used to analyze the qualitative data by searching for themes demonstrating different epistemological positions.

Six themes were inductively derived from the students' reflections: (1) transitioning from passive to active learning; (2) generating epistemic change; (3) social perspective-taking; (4) domain-based knowledge; (5) prior knowledge and experience; and (6) online collaboration with other students. Episodes, thoughts and feelings expressed by the students were reported so as to increase the reliability of the recurrent and common themes.

This study mainly shows that combining constructivist teaching and learning tools with advanced technology in an online course enables the development of lifelong learning capabilities among students in the health management professions.

The purpose of this study is to review and synthesize the literature on in-app advertising, identify gaps and propose future research directions.

The authors use a systematic literature review (SLR) approach, following the PRISMA guidelines, to investigate the current state of research in in-app advertising. The study uses 44 shortlisted articles from the Scopus and Web of Science databases. Using the Theory-Context-Characteristics-Methodology (TCCM) framework, the authors analyze the gaps in theory, context, characteristics and methods.

Using thematic analysis, the authors identify five main themes in the in-app advertising literature, namely, ad platform optimization; mobile app user psychology and behavior; ad effectiveness; ad fraud; and security, privacy and other user concerns. The findings show the need for empirical research, with a strong theoretical foundation in emerging ad formats of in-app advertising, user behavior and buy-side of in-app advertising.

This is a maiden study to conduct a domain-based SLR in the emerging field of in-app advertising using the TCCM framework. The authors highlight the key differences between in-app advertising and mobile web advertising. The authors propose theories in the advertising field that could be used in future empirical studies of in-app advertising.

El propósito de esta investigación es revisar y sintetizar la literatura sobre la publicidad en Apps, identificar lagunas y proponer futuras direcciones de investigación.

Utilizamos un enfoque de revisión sistemática de la literatura, siguiendo las directrices PRISMA, para investigar el estado actual de la investigación en publicidad en aplicaciones. El estudio utiliza 44 artículos preseleccionados de las bases de datos Scopus y Web of Science (WoS). Utilizando el marco Teoría-Contexto-Características-Metodología (TCCM), analizamos las lagunas en teoría, contexto, características y métodos.

Mediante un análisis temático, identificamos cinco temas principales en la literatura sobre publicidad en aplicaciones, a saber: optimización de plataformas publicitarias; psicología y comportamiento de los usuarios de aplicaciones móviles; eficacia publicitaria; fraude publicitario; seguridad, privacidad y otras preocupaciones de los usuarios. Nuestros hallazgos muestran la necesidad de investigación empírica, con una sólida base teórica en los formatos publicitarios emergentes de la publicidad en Apps, el comportamiento del usuario y el buy-side de la publicidad en Apps.

Se trata de un estudio pionero para realizar una revisión sistemática de la literatura basada en el dominio en el campo emergente de la publicidad en Apps utilizando el marco TCCM. Destacamos las principales diferencias entre la publicidad en aplicaciones y la publicidad en la web para móviles. Proponemos teorías en el campo de la publicidad que podrían utilizarse en futuros estudios empíricos sobre la publicidad en Apps.

本研究旨在回顾和总结有关应用内广告的文献, 找出差距并提出未来的研究方向。

我们采用系统性文献综述方法, 遵循 PRISMA 指南, 调查应用内广告的研究现状。研究使用了 Scopus 和 Web of Science (WoS) 数据库中的 44 篇入围文章。利用理论-背景-特征-方法（TCCM）框架, 我们分析了理论、背景、特征和方法方面的差距。

通过主题分析, 我们确定了应用内广告文献的五大主题, 即广告平台优化; 移动应用用户心理和行为; 广告效果; 广告欺诈; 安全、隐私和其他用户关注点。我们的研究结果表明, 有必要在应用内广告的新兴广告形式、用户行为和应用内广告买方等方面开展实证研究, 并奠定坚实的理论基础。

这是一项首次使用 TCCM 框架对新兴的应用内广告领域进行基于领域的系统性文献综述的研究。我们强调了应用内广告与移动网络广告的主要区别。我们提出了广告领域的理论, 可用于未来的应用内广告实证研究。

Although the debate about the interplay between quality management and organizational culture is long established, extant knowledge about their link is not consistent. This article attempts to fill such a gap by integrating current perspectives and insights through a literature review.

A domain-based literature review has been conducted, which followed the Scientific Procedures and Rationales for Systematic Literature Reviews. The knowledge core consisted of 76 items, which were analysed through bibliographic coupling and co-citation analysis. An interpretive approach was taken to articulate the study findings.

The current scholarly debate unfolds through four research streams, which emphasize the need for joint optimizing quality management and organizational culture embracing a longitudinal perspective. Similarly, the theoretical roots inspiring reviewed contributions are distributed in four clusters, which rely on the assumption that organizational excellence derives from the harmonization of quality management and organizational culture.

Quality management necessitates a supportive organizational culture to set the ground for excellence. At the same time, it modifies the inner traits of the organizational culture. Such cultural changes should be carefully handled to ensure a dependable quality orientation. Achieving organizational excellence involves mastering the interplay between quality management and organizational culture.

This article delivers an unprecedented systematization of the scientific literature. It identifies the main research streams through which the debate on quality management and culture evolves, shedding light on the main conceptual roots inspiring recent scholarly advancements. Alongside overcoming the fragmentation of the extant debate, this review enables the envisioning of an agenda for further developments.

A vast amount of complex data is being generated in the business environment, which enables support for decision-making through information processing and insight generation. The purpose of this study is to propose a process model for data-driven decision-making which provides an overarching methodology covering key stages of the business analytics life cycle. The model is then applied in two small enterprises using real customer/donor data to assist the strategic management of sales and fundraising.

Data science is a multi-disciplinary subject that aims to discover knowledge and insight from data while providing a bridge to data-driven decision-making across businesses. This paper starts with a review of established frameworks for data science and analytics before linking with process modelling and data-driven decision-making. A consolidated methodology is then described covering the key stages of exploring data, discovering insights and making decisions.

Representative case studies from a small manufacturing organisation and an independent hospice charity have been used to illustrate the application of the process model. Visual analytics have informed customer sales strategy and donor fundraising strategy through recommendations to the respective senior management teams.

The scope of this research has focused on customer analytics in small to medium-sized enterprise through two case studies. While the aims of these organisations are rather specific, they share a commonality of purpose for their strategic development, which is addressed by this paper.

Data science is shown to be applicable in the business environment through the proposed process model, synthesising micro- and macro-solution methodologies and allowing organisations to follow a structured procedure. Two real-world case studies have been used to highlight the value of the data-driven model in management decision-making.