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Designing effective business analytics (BA) platforms that visualise data, provide deep insights and support data-driven decision-making is a challenging task. Understanding the elements shaping BA platform design is crucial for success. The purpose of this study is to explore the impact of visualisation on usability (UI) and user experience (UX) while emphasising the importance of insights understanding in BA platform design.

This paper presents a case study following a startup’s journey as it undergoes two redesign phases for its BA platform. A combination of quantitative and qualitative methods is used to assess UX/UI and insights understanding of the platform. Indicatively this included semi-structured interviews, observations, think-aloud techniques and surveys to monitor runtime per task, number of errors, users’ emotions and users’ understanding.

Our findings suggest that modifications in aesthetics and information visualisation positively influence overall usability, UX, and understanding of platform insights – a critical aspect for the success of the startup.

Our goal is not to make a methodological contribution, but to illustrate how companies, constrained by time and pressure, navigate platform changes without meticulous design and provide learnings on important elements while designing BA platforms.

This paper concludes with suggested methods for assessing BA platforms and recommends practical practices to follow. These practices include recommendations on important elements for BA platform users, such as navigation and interactivity, user control and personalisation, visual consistency and effective visualisation.

This study contributes to practice as it presents a real-life case and offers valuable insights for practitioners.

This study develops a comprehensive taxonomy of the business analytics (BA) discipline, uncovering its intellectual core and revealing its evolution over the past 12 years.

Using stakeholder-driven identity formation theory, this study explores how organizational identity emerges through stakeholder negotiations. It investigates how top scholarly journals shape the BA discipline’s image and influence perceptions. High-quality articles from top journals listed by the Australian Business Deans Council are analyzed using latent Dirichlet allocation (LDA), a natural language processing and topic modeling method.

The study outlines key research areas identified as analytics methods, marketing, finance, operations and decision support analytics, along with 12 subareas. An analysis of the top 100 topics reveals prevalent research themes, showcasing the breadth of BA. A 12-year time-series review shows initial growth followed by maturation across most areas, except for decision support analytics, which maintained steady growth. These findings provide empirical evidence of BA’s development as a distinct discipline, highlighting its interdisciplinary nature and evolving research focus.

This study presents the first comprehensive, data-driven taxonomy of BA research, distilling the intellectual core into five key areas and 12 subareas, while identifying 100 supporting themes. It extends the stakeholders’ approach to identity development theory in the context of BA, providing empirical support for discussions on the field’s identity and diversity. The findings offer valuable insights for scholars, industries, managers and professionals, guiding curriculum development, research directions and practical applications of BA.

This paper aims to offer an integrated framework for branded apps (BAs) that highlights research gaps and points to areas for future research.

Using a systematic literature review approach, the authors analyzed more than 100 articles published between 2009 and the present. This research used databases such as SCOPUS, Web of Science, EBSCO and Elsevier’s Science Direct, with a particular focus on articles listed in the 2021 ABS index. The reviewed papers were coded and organized into four categories in terms of themes and concepts: antecedents, mechanisms, outcomes and moderators.

The study identified four types of antecedents (app benefits, personal traits, brand benefits and others) that influence outcomes via cognitive, affective and a mix of both mechanisms, which is termed multipaths. The authors classified outcomes into five areas (financial gains; app benefits; brand benefits; customer benefits; and others). Moderators were grouped into four types (customer individuality; app features; brand characteristics; and others). The authors concluded by recommending promising directions for future research. Specifically, the authors suggested an inverted U-shaped relationship between escapism and customer responses to BAs.

This paper focused exclusively on BAs, differentiating them from other mobile apps. The authors integrated nearly 100+ studies conducted over two decades. This integrated model serves as a guiding tool for understanding the past, present and future of BAs.

This study aims to investigate the Jordanian Telecommunications Company's implementation of business analytics and how it affects the caliber of its financial reporting. The staff members of Jordanian telecom businesses will receive a questionnaire. Previous research has indicated that organizational, technological, and environmental factors have a significant role in influencing the choice to use business analytics. It is also anticipated that pressure from competitors, top management backing, and cost savings would all have a significant impact on the intention to use business analytics. These financial reports have improved in quality as a result. These anticipated outcomes demonstrate how crucial it is for businesses to employ business analytics as a tool to improve their financial performance and ability to compete in the global marketplace.

Cross-cultural cognitive paradoxes have frequently broken the existing boundaries of knowledge and stimulated demands for knowledge creation (KC), and such paradoxes have triggered and will continue to trigger novel risks in the context of international business (IB). Given the nascency of relevant issues, this study aims to develop a more comprehensive understanding of KC across cultures by proposing a Yin-Yang dialectical systems theory of KC as micro-foundation to more systematically frame the risk/paradox-resolving mechanism elicited by cultural collisions.

This paper is conceptual in nature. The authors first critically review the literature to lay a broad theoretical foundation. Integrating the philosophy- and praxis-based views, the authors reposition knowledge as a Yin-Yang dialectical system of knowing, with yin representing the tacit while yang represents the explicit. Next, the authors justify the underling logic of realising KC through a contradiction-resolving process. On this basis, the authors draw upon the Yijing’s Later Heaven Sequence (LHS) as the source domain of a heuristic metaphor to reconceptualise KC as a dynamic capability in the IB context.

Using the LHS paradigm to metaphorically map the intricate patterns of interaction and interconnectivity among the involved individuals, organisations and all related stakeholders, this research identifies and theorises the overall dynamic capability of KC in the IB context, which comprises five sets of processes: contradiction, conflict, communication, compromise and conversion.

This research highlights that KC is simultaneously activated and constrained by human actions as well as by the socially constructed context in which it emerges, which helps individuals, organisations and policy makers more clearly frame the novel risks induced by cross-cultural cognitive conflicts in the IB context.

The authors synthesise Yin-Yang dialectics with the approach of collective phronesis, proposing a novel, praxis-oriented Yin-Yang dialectical systems theory of KC. It provides a deeper understanding of the epistemological paradox inherent in all knowledge, thus enabling KC to be rationalised by a sounder logical reasoning. By fusing the macro and micro perspectives on KC, the authors also enrich existing theory and future theory building in the domain of knowledge management.

While scholars agree on the complexity of knowledge management processes (KMPs), achieving a comprehensive understanding of these processes and how they integrate into the core organizational processes still proves challenging. In response to this research gap, this study presents a pioneering, inductive exploration into the views of chief knowledge officers (CKOs).

We employed an interpretative multiple-case study methodology, conducting semi-structured interviews with 28 CKOs across diverse industry sectors. Thematic analysis was utilized to analyze the data.

The CKOs’ insights reveal that the degree of “superposition and overlap” between KMPs and business processes is pivotal to the effectiveness of both knowledge management (KM) and business operations. The study introduces the concept of “transparent KM,” where KM becomes an imperceptible yet indispensable element of the organizational structure. This challenges the conventional notion of KM as an isolated discipline and highlights the dangers of artificially segregating KMPs from core business processes, which can result in employee disengagement and managerial doubts about the value of KM.

This research contributes to a novel vision of KM, advocating for the seamless integration of KMPs into organizational processes. It suggests that KM should be considered a ubiquitous force that naturally enhances organizational workflows. Scholars, practitioners and company leaders, in designing business processes, should take into consideration their KM implications and, in turn, potentially reshaping the strategic role of KM in organizations.

This study explores the intricate relationships between greenwashing (GW), negative word-of-mouth (NWoM) and brand avoidance (BA), emphasizing the pivotal roles of green perceived risk (GPR) and green trust (GT). By analyzing these dynamics, the study sheds light on the effect of GW on consumer reactions and behaviors toward brands engaging in green marketing practices.

The current study used a survey dataset of 512 customers in Saudi Arabia and applied partial least squares-structural equation modeling (PLS-SEM) to assess the paths within the proposed model.

The findings of this study indicate that consumers’ perceptions of GW can harm brands. Specifically, GW positively influences BA through both GPR and GT. Moreover, GW directly affects NWoM and indirectly via GPR.

The study provides actionable insights for practitioners, emphasizing the importance of avoiding deceptive green marketing (i.e. GW) to build consumer trust and reduce negative behaviors like BA and NWoM. By adopting transparent practices and leveraging third-party environmental certifications, brands can enhance credibility, mitigate risks and maintain customer loyalty in sustainability-focused markets.

Drawing on signaling theory and expectancy violation theory, this study builds a new framework to highlight the harmful effects of GW on brands. By integrating these theories, the framework effectively explains how GW can trigger extreme responses such as NWoM and BA, thereby contributing to research that has previously overlooked the connections between these factors.

Restaurant table booking (RTB) mobile apps are transforming how consumers reserve tables in the restaurants of their choice. This study analyses how RTB mobile apps influence brand attachment (BA) and brand commitment (BC), highlighting the moderation effect of desire for uniqueness (DU) by integrating visual content theory and social exchange theory.

Data [N = 414] were collected through the survey method from consumers having experience in using RTB mobile apps. The data were analysed through structural equation modelling using AMOS and SPSS PROCESS macro to examine moderated relationship.

The results confirm that content aesthetic quality, perceived technical interactivity and brand investments influence BA and BC in the RTB mobile app and also confirm the moderating role of the DU.

The present work is among the first to study the sources of BA in the RTB mobile app domain. Thus, it contributes to the literature on the restaurant industry to understand consumers' BA behaviour to achieve BC.

This study aims to investigate the effect of brand authenticity on consumer brand loyalty in the Pakistani frozen food industry sector in the light of the stimulus-organism-response (SOR) theory.

The quantitative approach utilized a survey questionnaire to acquire customers’ perceptions. A simple random technique was used to collect data. About 255 questionnaires were analysed, and the response rate was 72.86%. The measurement and structural model were constructed through Smart PLS-4 and fsQCA.

The findings indicated that brand authenticity positively affects brand loyalty in the Pakistani frozen food industry. Results further proved that brand involvement has a full mediation effect, fsQCA supports the same results, and customer satisfaction has a partial mediation effect. These findings offer valuable insights into the frozen food industry in Pakistan and other countries, allowing them to create successful tactics to engage customers and foster brand loyalty. The findings reveal the complexity and ever-changing nature of how consumers assess brand authenticity in the frozen food industry.

These findings also have implications for the frozen food business’s marketing and brand positioning strategies, particularly its utilization of brand authenticity to attract and retain consumers.

This is the first paper in the frozen food sector from the perspective of brand authenticity.

Brand reputation (BR) is one of the most important factors that affect the consumer–brand relationship and give businesses a competitive advantage. Businesses with a strong BR can increase their market shares and product market prices, in addition to gaining a competitive advantage. In order for businesses to have these advantages, they need to know and analyze their consumers. This study aimed to develop an alternative analysis method by using classification algorithms and regression analysis to measure and evaluate the effect of consumers' BR perceptions on their willingness to pay premium prices (WPP).

The research data were collected from 483 participants by the online survey method due to the COVID-19 pandemic. The data were first analyzed with regression analysis, and the effect of BR on WPP was found to be significant. Then, using artificial intelligence (AI) methods that were not used in previous studies, consumers' perceptions of BR and WPP were clustered and classified.

The results revealed the highest and lowest customer groups with BR and WPP and empirically demonstrated that highly accurate practical classification models can be applied to determine strategies in line with these findings.

The model proposed in this study offers an integrated approach by using AI and regression analysis together and tries to fill the gap in the literature in this field. Therefore, the novelty of this study is to quantitatively reveal and evaluate the relationship between BR and WPP by using AI classification algorithms and regression analysis together.