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This study aims to examine the relation between a client’s relative economic importance to its auditor and the number of key audit matters (KAMs) reported in the expanded audit report.

The authors measure a client’s economic importance at the audit firm level as well as the audit partner level using the ratio of a client’s total fees to an auditor’s total fees earned from its listed clients and the ratio of a client’s audit fees to an auditor’s total audit fees from its listed clients. The authors estimate a multivariate regression model using a sample of New Zealand-listed company-years from 2017 to 2019.

Results reveal a positive relation between client importance to auditor and the number of KAMs disclosed. Furthermore, the positive association between client importance and the number of KAMs reported is more pronounced for clients audited by the Big 4 auditors and less experienced audit partners. These findings suggest that auditors’ incentive to protect against potential losses from important client engagements outweighs any impairment to auditor independence and leads to a higher number of KAMs reported for the economically more important clients. Overall, the results suggest that auditors report KAMs strategically to mitigate engagement risks.

This study provides the first evidence on how client economic importance relates to the disclosure in the expanded audit report and contributes to the dialogue on auditors’ reporting of KAMs in the Asia-Pacific region.

Indoor environmental quality (IEQ) in buildings has an impact on people’s health, productivity and comfort. Maintaining the highest possible IEQ level in complex buildings, such as health care, is difficult due to economic and organizational constraints. This study aims to categorize the vicinities in a typical health-care facility in terms of importance and criticality in relation to the various IEQ factors, as well as to develop an IEQ assessment procedure.

A comprehensive literature review, established standards and structured interviews with industrial hygiene professionals in health-care settings were used in this study. To test the applicability of the developed IEQ assessment procedure, a pilot study was conducted in an existing health-care facility.

This study categorized health-care facilities into various vicinities and discovered three respondents group had varying IEQ perceptions (facility managers, environmental health specialists and nurses). According to the findings, indoor air quality is the most important and dominant factor influencing overall IEQ in health-care facilities. The trial application of the framework shows that much work is needed to improve the level of response and readiness of facility management and occupants to allow for the effective use of the developed procedure.

Previous research did not include a detailed categorization of vicinities in health-care buildings based on IEQ requirements. The findings of this study will help to close this knowledge gap and guide facility managers and operators in recognizing the relative importance of different IEQ factors, maintaining functional requirements and identifying priorities when developing maintenance and operational procedures and allocating resources.

The aim of this chapter is to develop a conceptual model for the analysis of sustainable development and the ranking of cities based on selected standard criteria and metrics of smart cities. The conceptual framework contains standard and measurable indicators that influence the creation and survival of smart cities that could be self-sustaining, Green Resilient. We can measure the level of smartness of cities from two perspectives, first from the point of view of the degree of automation of services, infrastructure, buildings, transport, etc. and second from the point of view of planning the further development of the city in order to raise the quality of life of its citizens. Indicators should satisfy the principles of specificity, measurability, availability, relevance and timeliness (Schomaker, 1997). Researchers in the field of smart cities define different sets of characteristics, on which they construct a system of indicators that together describe the degree of development of a smart city. It must be taken into account the fact that there is no single set of indicators that would refer to the level of smartness of the city. It is a complex phenomenon, which occurs differently depending on the conceptual framework and the goal of classifying cities according to the complex characteristics of smartness, especially if you take into account the fact that the general well-being and quality of life of citizens are more important than only indicators of the quality of city services.

Organisations and industries are often looking for technologies that can accomplish multiple tasks, providing economic benefits and an edge over their competitors. In this context, drones have the potential to change many industries by making operations more efficient, safer and more economic. Therefore, this study investigates the use of drones as the next step in smart/digital warehouse management to determine their socio-economic benefits.

The study identifies various enablers impacting drone applications to improve inventory management, intra-logistics, inspections and surveillance in smart warehouses through a literature review, a test of concordance and the fuzzy Delphi method. Further, the graph theory matrix approach (GTMA) method was applied to ranking the enablers of drone application in smart/digital warehouses. In the subsequent phase, researchers investigated the relation between the drone application's performance and the enablers of drone adoption using logistic regression analysis under the TOE framework.

This study identifies inventory man agement, intra-logistics, inspections and surveillance are three major applications of drones in the smart warehousing. Further, nine enablers are identified for the adoption of drone in warehouse management. The findings suggest that operational effectiveness, compatibility of drone integration and quality/value offered are the most impactful enablers of drone adoption in warehouses. The logistic regression findings are useful for warehouse managers who are planning to adopt drones in a warehouse for efficient operations.

This study identifies the enablers of drone adoption in the smart and digital warehouse through the literature review and fuzzy Delphi. Therefore, some enablers may be overlooked during the identification process. In addition to this, the analysis is based on the opinion of the expert which might be influenced by their field of expertise.

By considering technology-organisation-environment (TOE) framework warehousing companies identify the opportunities and challenges associated with using drones in a smart warehouse and develop strategies to integrate drones into their operations effectively.

This study proposes a TOE-based framework for the adoption of drones in warehouse management to improve the three prominent warehouse functions inventory management, intra-logistics, inspections and surveillance using the mixed-method.

This study aims to examine the impact of board characteristics on firm performance while also exploring the influential mechanisms that help Chinese listed companies establish effective boards of directors and strengthen their corporate governance mechanisms.

This paper uses machine learning methods to investigate the predictive ability of the board of directors' characteristics on firm performance based on the data from Chinese A-share listed companies on the Shanghai and Shenzhen stock exchanges in China during 2008–2021. This study further analyzes board characteristics with relatively strong predictive ability and their predictive models on firm performance.

The results show that nonlinear machine learning methods are more effective than traditional linear models in analyzing the impact of board characteristics on Chinese firm performance. Among the series characteristics of the board of directors, the contribution ratio in prediction from directors compensation, director shareholding ratio, the average age of directors and directors' educational level are significant, and these characteristics have a roughly nonlinear correlation to the prediction of firm performance; the improvement of the predictive ability of board characteristics on firm performance in state-owned enterprises in China performs better than that in private enterprises.

The findings of this study provide valuable suggestions for enriching the theory of board governance, strengthening board construction and optimizing the effectiveness of board governance. Furthermore, these impacts can serve as a valuable reference for board construction and selection, aiding in the rational selection of boards to establish an efficient and high-performing board of directors.

The study findings unequivocally demonstrate the superiority of nonlinear machine learning approaches over traditional linear models in examining the relationship between board characteristics and firm performance in China. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. Within the suite of board characteristics, director compensation, shareholding ratio, average age and educational level are particularly noteworthy, consistently demonstrating strong, nonlinear associations with firm performance. The study reveals that the predictive performance of board attributes is generally more robust for state-owned enterprises in China in comparison to their counterparts in the private sector.

This study aims to examine the determinants that influence housing prices in Dammam metropolitan area (DMA), Saudi Arabia, by using the analytic hierarchy process (AHP) model. The study considers determinants such as building age (BLD AG), building size (BLD SZ), building condition (BLD CN), access to parking (ACC PK), proximity to transport infrastructure (PRX TRS), proximity to green areas (PRX GA) and proximity to amenities (PRX AM).

The AHP decision model was used to assess the determinants of housing prices in DMA, using a pair-wise comparison matrix to determine the influence of the investigated factors on housing prices.

The study’s results revealed that building size (BLD SZ) was the most critical determinant affecting housing prices in DMA, with a weight of 0.32, trailed by proximity to transport infrastructure (PRX TRS), with a weight of 0.24 as the second most influential housing price determinant in DMA. The third most important determinant was proximity to amenities (PRX AM), with a weight of 0.18.

This study addresses a research gap by using the AHP model to assess the spatial determinants of housing prices in DMA, Saudi Arabia. Few studies have used this model in examining housing price factors, particularly in the context of Saudi Arabia. Consequently, the findings of this study provide unique insights for policymakers, housing developers and other stakeholders in understanding the importance of building size, proximity to transport infrastructure and proximity to amenities in influencing housing prices in DMA. By considering these determinants, stakeholders can make informed decisions to improve housing quality and prices in the region.

This study aims to investigate which resources and sources of support are related to employee adaptability to work-related change during the COVID-19 pandemic, with implications for human resource management (HRM).

The authors analysed a survey of 1,619 employees working in architectural practice and allied fields in Australia in 2020.

Drawing on conservation of resources (COR) theory, the authors asked whether workers would be more adaptable to change during COVID-19 if they were able to draw on a combination or bundle of supports, known as resource caravans. Hierarchical multiple regression and relative importance analysis showed that confidence in personal support networks during the pandemic was the most important predictor assisting workers to adapt to change, followed by concrete (practical, technical) organizational support for remote work. No evidence was found to corroborate this study's hypotheses that these resources provide support in bundles, challenging the notion of resource caravans in this research context.

The authors argue that COR theory has been too broadly applied to the workplace and that boundary conditions should apply to its emphasis on resource caravans. In practical terms, HRM supports to promote employee adaptability should be carefully targeted in extreme circumstances such as the COVID-19 pandemic.

This study aims to focus on the five most relevant and discursive emerging technologies in accounting (cloud computing, big data and data analytics, blockchain, artificial intelligence (AI) and robotics process automation [RPA]). It investigates the adoption and use of these technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey.

The study investigates the adoption and use of emerging technologies based on data collected from accounting professionals in a technology-developed country – Canada, through a survey. This study considers the said nature and characteristics of emerging technologies and proposes a model using the factors that have been found to be significant and most commonly investigated by existing prior technology-organization-environment (TOE)-related technology adoption studies. This survey applies the TOE framework and examines the influence of significant and most commonly known factors on Canadian firms’ intention to adopt the said emerging technologies.

Study results indicate that Canadian accounting professionals’ self-assessed knowledge (about these emerging technologies) is more theoretical than operational. Cloud computing is highly used by Canadian firms, while the use of other technologies, particularly blockchain and RPA, is reportedly low. However, firms’ intention about the future adoption of these technologies seems positive. Study results reveal that only the relative advantage and top management commitment are found to be significant considerations influencing the adoption intention.

Study findings confirm some results presented in earlier studies but provide additional insights from a new perspective, that of accounting professionals in Canada. The first limitation relates to the respondents. Although accounting professionals provided valuable insights, their responses are personal views and do not necessarily represent the views of other professionals within the same firm or the official position of their accounting departments or firms. Therefore, the exclusion of diverse viewpoints from the same firm might have negatively impacted the results of this study. Second, this study sample is limited to Canada-based firms, which means that the study reflects only the situation in that country. Third, considering the research method and the limit on the number of questions the authors could ask, respondents were only asked to rate the impact of these five technologies on the accounting field and to clarify which technologies are used.

This study’s findings confirm that the organizational intention to adopt new technology is not primarily based on the characteristics of the technology. In the case of emerging technology adoption, the decision also depends upon other factors related to the internal organization. Furthermore, although this study found no support for the effect of environmental factors, it fills a gap in the literature by including the factor of vendor support, which has received little attention in prior information technology (IT)/ information system (IS) adoption research. Moreover, in contrast to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study findings may serve as a guide for researchers, practitioners, firms and other stakeholders, particularly technology providers, interested in learning about emerging technologies’ adoption and use in Canada and/or in a relevant context. Contrary to most prior adoption studies, this study elaborates on accounting professionals’ experience and perceptions in investigating the organizational adoption and use of emerging technologies. Thus, the findings of this study are valuable, providing insights from a new perspective, that of professional accountants.

The study provides insights into the said technologies’ actual adoption and improves the awareness of firms and stakeholders to the effect of some constructs that influence the adoption of these emerging technologies in accounting.

This paper aims to review, systematize and map the extant literature on private equity (PE) and study the underlying research agenda for investment selection and value creation in portfolio firms of PE investors. The PE investment process entails the preinvestment stage, where PE investors screen the target firms, and the postinvestment stage, where PE investors monitor the funded firms. With the motive to understand both stages, this review consolidates the findings of existing literature.

This research adopts a systematic literature review approach to study the underlying themes in PE investment literature. To adequately profile the key research areas, the authors have adopted citation classics in addition to keyword search and drawn the most significant papers in this field of research based on citation metrics.

The review presents a heterogeneous set of themes by encapsulating the relevant PE literature and identifies significant and emergent themes within the broad research area of investment and performance. The foundational themes found are selection determinants for PE investments, value creation in PE investments and selection vs value-adding effect of PE investors. While the emergent themes are the relative performance of PE investments; sources of value creation; skill, luck and social capital in PE; and resource dependency vis-à-vis PE. Each theme or subtheme chalks out the underlying research agendas for future researchers.

To build an understanding of the selection determinants and value creation, this review addresses the need to synthesize and align the PE literature concerning pre and post investment stages. PE is a fertile research area that is systematically captured in this review by identifying themes, subthemes and avenues for future research.

Quality 4.0 is essential to the Industry 4.0 framework, notably in the electronics sector. It evaluates product quality in real-time using automatic process controls, quality tools and procedures. The implementation of Quality 4.0 criteria in the electronics industry is the subject of this study’s investigation and analysis. In this study, nine Customer Requirements (CRs) and 18 Design Requirements (DRs) have been defined to adopt Quality 4.0, aiming to increase yield while reducing defects. This study has developed a Quality 4.0 framework for effective implementation, incorporating the People, Process and Technology categories.

Many CRs and DRs of Quality 4.0 exhibit interdependencies. The Analytic Network Process (ANP) considers interdependencies among the criteria at various levels. Quality Function Deployment (QFD) can capture the customer’s voice, which is particularly important in Quality 4.0. Therefore, in this research, we use an integrated ANP-QFD methodology for prioritizing DRs based on the customers' needs and preferences, ultimately leading to better product and service development.

According to the research findings, the most critical consumer criteria for Quality 4.0 in the electronics sector are automatic systems, connectivity, compliance and leadership. The Intelligent Internet of Things (IIOTs) has emerged as the most significant design requirement that enables effective control in production. It is observed that robotics process automation and a workforce aligned with Quality 4.0 also play crucial roles.

Existing literature does not include studies on identifying CRs and DRs for implementing Quality 4.0 in the electronics industry. To address this gap, we propose a framework to integrate real-time quality measures into the Industry 4.0 context, thereby facilitating the implementation of Quality 4.0 in the electronics industry. This study can provide valuable insights for industry practitioners to implement Quality 4.0 effectively in their organizations.