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Despite an enormous body of literature on conflict management, intra-group conflicts vis-à-vis team performance, there is currently no study investigating the conflict prevention approach to handling innovation-induced conflicts that may hinder smooth implementation of big data technology in project teams.

This study uses constructs from conflict theory, and team power relations to develop an explanatory framework. The study proceeded to formulate theoretical hypotheses from task-conflict, process-conflict, relationship and team power conflict. The hypotheses were tested using Partial Least Square Structural Equation Model (PLS-SEM) to understand key preventive measures that can encourage conflict prevention in project teams when implementing big data technology.

Results from the structural model validated six out of seven theoretical hypotheses and identified Relationship Conflict Prevention as the most important factor for promoting smooth implementation of Big Data Analytics technology in project teams. This is followed by power-conflict prevention, prevention of task disputes and prevention of Process conflicts respectively. Results also show that relationship and power conflicts interact on the one hand, while task and relationship conflict prevention also interact on the other hand, thus, suggesting the prevention of one of the conflicts could minimise the outbreak of the other.

The study has been conducted within the context of big data adoption in a project-based work environment and the need to prevent innovation-induced conflicts in teams. Similarly, the research participants examined are stakeholders within UK projected-based organisations.

The study urges organisations wishing to embrace big data innovation to evolve a multipronged approach for facilitating smooth implementation through prevention of conflicts among project frontlines. This study urges organisations to anticipate both subtle and overt frictions that can undermine relationships and team dynamics, effective task performance, derail processes and create unhealthy rivalry that undermines cooperation and collaboration in the team.

The study also addresses the uncertainty and disruption that big data technology presents to employees in teams and explore conflict prevention measure which can be used to mitigate such in project teams.

The study proposes a Structural Model for establishing conflict prevention strategies in project teams through a multidimensional framework that combines constructs like team power conflict, process, relationship and task conflicts; to encourage Big Data implementation.

This rich descriptive study examines auditors' client risk assessment (i.e. “key audit matters”/critical audit matters) disclosures in expanded audit reports of 328 Financial Times Stock Exchange (FTSE) 350 companies. The study compares auditor-identified client risks with corporate risk disclosures identified in audit committee reports, in terms of number and type of risks. The research also compares variation in auditor-identified client risks between individual Big 4 audit firms. In addition, the study examines auditor ranking of their client risks disclosed.

The study manually content analyses disclosures in audit reports and audit committee reports of a sample of 328 FTSE-350 companies with 2015 year-ends.

Audit committees identify more risks than auditors (23% more risks). However, auditor-identified client risks and audit-committee-identified risks are similar (80% similar), as are auditor-identified client risks between the individual Big 4 audit firms. Only ten (3%) audit reports rank the importance of auditor-identified client risks.

Sample is restricted to one year, one jurisdiction, large-listed companies and companies audited by Big 4 auditors.

The study provides important insights for regulators, auditors and users of financial statements by identifying influences on disclosure of auditor-identified client risks.

The paper mobilises institutional theory to interpret the findings. The findings suggest that auditor-identified client risks in expanded audit reports may demonstrate mimetic behaviour in terms of similarity with audit-committee-identified risks and similarity between individual Big 4 audit firms. The study provides important insights for regulators, auditors and users of financial statements by identifying influences on disclosure of auditor-identified client risks.

This paper aims to investigate how narrative is constructed to create connections with fat readers, how books function to envision spaces of fat liberation for young readers and to highlight the incredible importance of providing bigger mirrors (Bishop, 1990) for fat representation in children’s literature.

This paper analyzes and reflects on two texts that contain counternarratives of fatness: The (Other) F Word: A celebration of the fat and fierce edited by Angie Manfredi (2019) and Big by Vashti Harrison (2023) to interrogate how these two narratives intentionally disrupt anti-fat bias.

Body size and fatness are identities that need to be included in diversity efforts within education. Books like The (Other) F Word: A celebration of the fat and fierce (Manfredi, 2019) and Big (Harrison, 2023) offer positive representations of fatness, disrupt biases around body size and provide spaces that allow fat students to find joy, hope, connection and, more than anything, imagine a way toward liberation.

This paper highlights the need to include more narratives of positive fat representation within children’s literature and calls for educators to interrogate their own anti-fat biases and practices.

There is a lack of research on fat representation specifically within children and young adult literature. This paper provides an analysis of two pieces of literature with fat representation that brings attention to the need for this type of future research.

This study aims to explore the use, effectiveness, motives and obstacles of analytical procedures (APs) used by auditors in Palestine, a context characterised by a pool of small and medium enterprises (SMEs), a limited skill set, poor quality of data, political uncertainty and a community-based business culture.

The study considers the audit market in Palestine using a sequential mixed-methods approach combining a questionnaire survey and a series of in-depth interviews. A total of 129 Big-4 and non-Big-4 auditors were surveyed.

The use of APs is driven by the auditor size (Big-4 vs non-Big-4) and the client size (large vs SMEs). Even though the use of APs has increased over the past decade, audit objectives, know-how, and personal, family and social connections among auditors and clients influence the quality of the audit process.

Small firms take advantage of the lack of audit governance in Palestine. Our findings suggest that the regulators should help bridge the knowledge-sharing programmes between the small and large audit firms to help improve audit quality.

Studies on audit quality, particularly using APs, in the context of politically unstable cases such as Palestine are limited. The study has implications for the use of APs in the case of SMEs to prepare for the technological revolution that will modernise audit procedures and quality soon.

The paper aims to tackle the classification of Remote Sensing Images (RSIs), which presents a significant challenge for computer algorithms due to the inherent characteristics of clustered ground objects and noisy backgrounds. Recent research typically leverages larger volume models to achieve advanced performance. However, the operating environments of remote sensing commonly cannot provide unconstrained computational and storage resources. It requires lightweight algorithms with exceptional generalization capabilities.

This study introduces an efficient knowledge distillation (KD) method to build a lightweight yet precise convolutional neural network (CNN) classifier. This method also aims to substantially decrease the training time expenses commonly linked with traditional KD techniques. This approach entails extensive alterations to both the model training framework and the distillation process, each tailored to the unique characteristics of RSIs. In particular, this study establishes a robust ensemble teacher by independently training two CNN models using a customized, efficient training algorithm. Following this, this study modifies a KD loss function to mitigate the suppression of non-target category predictions, which are essential for capturing the inter- and intra-similarity of RSIs.

This study validated the student model, termed KD-enhanced network (KDE-Net), obtained through the KD process on three benchmark RSI data sets. The KDE-Net surpasses 42 other state-of-the-art methods in the literature published from 2020 to 2023. Compared to the top-ranked method’s performance on the challenging NWPU45 data set, KDE-Net demonstrated a noticeable 0.4% increase in overall accuracy with a significant 88% reduction in parameters. Meanwhile, this study’s reformed KD framework significantly enhances the knowledge transfer speed by at least three times.

This study illustrates that the logit-based KD technique can effectively develop lightweight CNN classifiers for RSI classification without substantial sacrifices in computation and storage costs. Compared to neural architecture search or other methods aiming to provide lightweight solutions, this study’s KDE-Net, based on the inherent characteristics of RSIs, is currently more efficient in constructing accurate yet lightweight classifiers for RSI classification.

Falsified online reviews (FORs) are the published/viewable consumer-generated online content regarding a firm (or its representatives) or its services and goods that is, to some degree, untruthful or falsified. The purpose of this study is first to explore the nature of FORs, focusing on reviewers' interpretations and refections on falsity, intent, anonymity and the target of their FOR. Secondly, the authors examine the valence and veracity dimensions of FORs and introduce a typology to differentiate their variations.

using an exploratory research design, 48 interviews were conducted with participants who post online reviews on social media about their experiences with food and beverage serving outlets.

The results show four common forms of FORs on social media. These are reviews focused on equity equalizing, friendly flattery, opinionated opportunism and malicious profiteering.

The authors provide exploratory and in-depth information via interviews, but do not analyse the content of FORs.

Firms should be aware of varieties of FORs and that these may not be limited to malicious content. This is important in terms of showing that in dealing with FORs, a one-size-fits-all approach will not work. FORs are not always entirely fabricated, and instead various levels of falseness are observed, ranging from slight alterations to complete fabrications.

Previous research explored how to identify and differentiate FORs from truthful ones, focusing on the reviews or how they are perceived by readers. However, comparatively little is known of the reviewers of FORs. Hence, this study focuses on reviewers and offers new insights into the nature of FORs by identifying and examining the main forms of FORs on social media.

This study aims to examine Big Data and the management of libraries in the era of the Fourth Industrial Revolution and its implications for policymakers in Nigeria.

A qualitative methodology was used, involving the administration of open-ended questionnaires to librarians from six selected federal universities located in Southwest Nigeria.

The findings of this research highlight that a significant proportion of librarians are well-acquainted with the relevance of big data and its potential to positively revolutionize library services. Librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

This study exclusively focuses on the Nigerian context, overlooking insights from other African countries. As a result, it may not be possible to generalize the study’s findings to the broader African library community.

To the best of the authors’ knowledge, this study is unique because the paper reported that librarians generally express favorable opinions concerning the relevance of big data, acknowledging its capacity to enhance decision-making, optimize services and deliver personalized user experiences.

This study aims to investigate why and how shared service centres (SSCs) are implemented as well as how they affect audit firm practice and audit quality.

In this qualitative study guided by the theoretical framework of institutional theory, the authors conducted 25 semi-structured interviews in seven European countries, including 16 interviews with audit partners from Big 4 firms, 6 with audit team members, 2 with interviewees from second-tier audit firms and 1 with a member of an oversight body.

The authors show that the central rationale for audit firms to implement SSCs is economic rather than external legitimacy. The authors find that SSC implementation has substantial effects on audit practices, particularly those related to standardisation, coordination and monitoring activities. The authors also highlight the potential impacts on audit quality.

By exploring the motivation for and effects of SSC implementation amongst audit firms, the authors offer insights into the best practices related to subsequent change processes and audit quality.

The purpose of this paper is to map the process of (social) valuing by people encountering built heritage in their daily environments. Value-based approaches are not well researched and formalized in Flemish policy context. New questions and issues are emerging in relation to values-based heritage management and the (adaptive) reuse of heritage within a context of spatial development and urban renewal practices. This paper firstly focus on what factors influence the process of (social) valuing, secondly on the hybrid character of the process and finally at the conflicts between the values frames of the different actors. This way it also inquires the potentials of participatory design supporting alternative regimes of care.

Within the research trajectory, the authors approached built heritage as a social construction and a social product, where there are as many stories as users. What heritage is and how heritage is dealt with, forms the basis of negotiation and valuation processes. An ethnographic approach was embarked on to get a grip on the socio-cultural significance of immovable property heritage in Flanders.

This paper describes the process of (social) valuing of by people encountering built heritage in their daily environments and offers an integrated conceptual framework for this kind of dynamic processes.

New questions and issues are emerging in relation to values-based heritage management and the (adaptive) reuse of heritage within a context of spatial development and urban renewal practices. This paper firstly focuses on what factors influence the process of (social) valuing, secondly on the hybrid character of the process and finally at the conflicts between the values frames of the different actors.