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Cloud computing promises dependable services offered through next-generation data centres based on virtualization technologies for computation, network and storage. Big Data Applications have been made viable by cloud computing technologies due to the tremendous expansion of data. Disaster management is one of the areas where big data applications are rapidly being deployed. This study looks at how big data is being used in conjunction with cloud computing to increase disaster risk reduction (DRR). This paper aims to explore and review the existing framework for big data used in disaster management and to provide an insightful view of how cloud-based big data platform toward DRR is applied.

A systematic mapping study is conducted to answer four research questions with papers related to Big Data Analytics, cloud computing and disaster management ranging from the year 2013 to 2019. A total of 26 papers were finalised after going through five steps of systematic mapping.

Findings are based on each research question.

A specific study on big data platforms on the application of disaster management, in general is still limited. The lack of study in this field is opened for further research sources.

In terms of technology, research in DRR leverage on existing big data platform is still lacking. In terms of data, many disaster data are available, but scientists still struggle to learn and listen to the data and take more proactive disaster preparedness.

This study shows that a very famous platform selected by researchers is central processing unit based processing, namely, Apache Hadoop. Apache Spark which uses memory processing requires a big capacity of memory, therefore this is less preferred in the world of research.

Big 4 professional services firms increasingly lay claim to recruiting and including staff of diverse genders, cultures, ages and sexualities. Drawing on Foucauldian insights, this study explores how LGBTIQ+ staff navigated shifting technologies of client power, at the time marriage equality was legislated in Australia.

This article explores changing experiences of LGBTIQ+ staff and allies, through 56 semi-structured interviews undertaken through 2018–2019.

Technologies of client power were central to shaping workplace experiences for LGBTIQ+ staff. However, each firm was also keen to carve unique and bold responses to changing societal attitudes regarding sexuality and gender. These progressive moves did not sit comfortably with all clients, and so this article provides insight into the limitations of client privilege within professional services firms. For staff, this increasing complexity of sometimes opaque, contradictory and shifting technologies of client and firm power, enabled agency to explore a sense of self for some, but continued to exclude others.

Little attention has been directed to exploring challenges for staff of sexual and gendered diversity within professional services firms, or to exploring how staff navigate changing perceptions of client power.

From an agency perspective, the authors investigate whether family ownership and control configurations are systematically associated with a firm's choice of auditor and audit fees. Agency theory is an economic theory that purposes the existence of a contract between two parties, principals and agents. Auditor choice and audit fees by family firms provide interesting insights given the unique nature of the agency problems faced by such firms.

The authors employ Big-4 auditors (PWC, KPMG, E&Y and Deloitte) as a proxy for high quality auditor (Big N) for the auditor choice model. For the audit fee model, the dependent variable is the natural logarithm of audit fees (LnAF). The authors use two measures for family firm as explanatory variables: (1) a dummy variable (FAM_Control), which equals one if the firm is classified as a family firm and (2) FAM_Ownership, which is an indicator variable with a value of one if a firm has family members who hold CEO position, occupy board seats, or hold at least 10% of the firm's equity. Data of Chinese listed firms from 2011 to 2021 are used. The authors adopt the Heckman (1979) two-stage model to mitigate the potential endogeneity issue involved in the selection of Big-N auditors.

The findings suggest that compared with non-family firms, Chinese family firms have a less tendency to employ Big-4 auditors due to less severe agency problems between owners and managers. Additionally, Chinese family firms sustain higher audit fees than non-family firms. Similar to the prior literature, however, Chinese family firms audited by Big-4 auditors incur lower audit fees than family firms audited by non-Big-4 auditors in this study. In contrast to young-family firms, old-family firms are less likely to pick top-tier auditors and sustain lower audit fees. Consistent and robust results are found from endogeneity tests and sensitivity analyses.

The empirical evidence provides a unique insight, for accounting practitioners, policymakers, family owners and other capital market participants concerning the diverse effects of various family ownership and control features on selecting high-quality auditors and audit fees. This study advances the understanding, showing that a lower demand for audit quality occurs in Chinese family firms as they encounter less severe Type I agency problems. However, the more severe Type II agency problems in Chinese family firms sustain higher audit fees due to higher audit risk and greater audit effort.

Existing literature has begun to identify the agonistic and contested aspects of the ongoing development of accountability systems. These “contests” are particularly important during periods of change when an accountability “deficit” has been identified, that is, when existing accountability systems are deemed inadequate and requiring revision. The purpose of this paper is to explore one such set of contests in the case of large technology and social media firms: the so-called “big tech”. The authors focus specifically on “big tech” because of increasing societal concerns about the harms associated with their products, services and business practices.

The authors analysed four US Congressional hearings, in which the CEO of Facebook was held to account for the company's alleged breaches and harms. The authors conducted a discourse analysis of the dialogue between the account giver (Mark Zuckerberg) and account holders (Members of Congress) in the oral testimony at the four hearings.

Two areas of contestation in the dialogue between the account giver and account holders are identified. “Epistemic contests” involved contestation about the “facts” concerning the harms the company had allegedly caused. “Responsibility contests” involved contestation about who (or what) should be held responsible for these harms and according to what standards or criteria.

The study advances critical dialogical accountability literature by identifying two areas of contestation during periods of change in accountability systems. In so doing, they advanced the theory by conceptualising the process of change as underpinned by discursive contests in which multiple actors construct and contest the “problem” with existing accountability systems. The outcomes of these contests are significant, the authors suggest, because they inform the development of reforms to the accountability system governing big tech firms and other industries undergoing similar periods of contestation and change.

Online social networks can bridge the gap between distant individuals by simulating online experiences that closely resemble physical interactions. While people have positive experiences, such as joy, in a physical relationship and would like to enjoy those experiences online, they also have negative experiences, such as being subject to a lie. An online social network may allow users to lie to simulate a real-world social group better. However, lying must be prevented on social networks as unethical behavior. Thus, this study aims to investigate an ethical dilemma raised due to the two abovementioned perspectives.

This paper examines different aspects of lying in social networks, using a comprehensive descriptive literature review approach and a classification scheme.

Contrary to their initial intent, social networks are disrupting the traditional notion of human interaction, either by disregarding the presence of dishonesty or by attempting to regulate relationships. In this research, the authors examine the challenges of these two perspectives by identifying enablers, consequences and control measures of lying on social networks at the individual, social and technological levels. The authors also develop a framework to facilitate investigating this dilemma.

This paper examines a controversial topic. Although lying is unethical, allowing users to lie may be considered an appealing feature of social network platforms. This paper offers a framework to propose several research directions for future studies. This study’s examination focuses on the challenges associated with deception on social networks, prompting the formulation of three crucial questions regarding the potential impact of technology on such behavior.

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.

COVID-19 has forced Big 4 firms to challenge existing management control arrangements and adapt their ways of working. Yet, we know little about how management control might be enacted in the future of the sustainable workplace. The objective of the study is to examine the patterns of management control change in the Big 4 accounting firms during the COVID-19 pandemic.

Adopting an exploratory qualitative research design, the authors draw on 42 interviews with directors and associates in the Big 4 professional services firms.

The findings reveal two pathways of management control change including alignment and displacement. The authors found that relatively minor adaptions to action and result controls were relied upon to respond to substantial cultural and personnel control changes.

The contributions are threefold: the authors take a temporal perspective to (1) unpack the changes to management control arrangements; (2) theorise the findings by developing a three-dimensional taxonomy of change pathways encompassing pace, scope and longevity of management control change and (3) contextualise management control arrangements in a hybrid work setting.

1. COVID-19 has forced Big 4 firms to challenge existing management control arrangements.

2. Literature has focused on traditional, onsite work settings and largely ignored change pathways.

3. The authors take a temporal perspective to unpack changes to management control arrangements.

4. Big 4 firms adapted to hybrid work with substantial changes to personnel and cultural controls.

5. The authors theorise the findings by developing a three-dimensional taxonomy of change pathways.

COVID-19 has forced Big 4 firms to challenge existing management control arrangements.

Literature has focused on traditional, onsite work settings and largely ignored change pathways.

The authors take a temporal perspective to unpack changes to management control arrangements.

Big 4 firms adapted to hybrid work with substantial changes to personnel and cultural controls.

The authors theorise the findings by developing a three-dimensional taxonomy of change pathways.

This study aims to examine the necessity effects of big data analytics capabilities (BDAC) on decision-making performance (DMP), particularly in the public sector.

The authors used the combined methods of partial least square structural equation modeling (PLS-SEM) and necessary condition analysis (NCA) to test the hypothesized relationships.

The findings show that the presence of all three BDAC (infrastructure, management and personnel) is significant and necessary to achieve higher levels of DMP. Specifically, the results revealed big data management capabilities to be of higher necessity to achieve the highest possible DMP. The findings provide public-sector practitioners with insights to support the development of their BDAC.

Time-sensitive domains such as the public sector require insight and quality decision-making to create public value and achieve competitive advantage. This study examined BDAC in light of the combined methods of (PLS-SEM) and NCA to test the hypothesized relationships in the public sector context.

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.