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This paper’s objective is to provide a systematic literature review of the contextual factors affecting downward communication from supervisors to subordinates in the audit environment. In addition, this review identifies emerging research themes and directions for future research.

I accomplish this review’s objectives by leveraging communication literature to establish a framework to identify and synthesize contextual factors affecting downward communication in the audit environment. The review identifies 50 published articles in the last 20 years from leading accounting and auditing journals.

This study consolidates research findings on downward communication under two primary contextual factors: (1) message and (2) channel. Findings indicate that empirical research examining communication in audit is fragmented and limited. Studies examining the message focus heavily on its content and treatment in the areas of feedback, nonverbal cues, and fraud brainstorming, and a handful of additional studies examine the effectiveness of the channel in these areas. Additional research is needed to understand a broader set of supervisor–subordinate communication practices, including those that are computer-mediated, and their effect on subordinate auditors’ judgments and behaviors in the contemporary audit environment.

Much of the audit literature examining communication to date is topic-versus construct-based, making it difficult to see how the research findings relate to one another. This review is the first to synthesize the literature to provide academics recommendations for a way forward, and inform practitioners of communication practices whereby supervisors can be trained to improve audit quality.

This study aims to investigate how living lab (LL) activities align with responsible research and innovation (RRI) principles, particularly in artificial intelligence (AI)-driven digital transformation (DT) processes. The study seeks to define a framework termed “responsible living lab” (RLL), emphasizing transparency, stakeholder engagement, ethics and sustainability. This emerging issue paper also proposes several directions for future researchers in the field.

The research methodology involved a literature review complemented by insights from a workshop on defining RLLs. The literature review followed a concept-centric approach, searching key journals and conferences, yielding 32 relevant articles. Backward and forward citation analysis added 19 more articles. The workshop, conducted in the context of UrbanTestbeds.JR and SynAir-G projects, used a reverse brainstorming approach to explore potential ethical and responsible issues in LL activities. In total, 13 experts engaged in collaborative discussions, highlighting insights into AI’s role in promoting RRI within LL activities. The workshop facilitated knowledge sharing and a deeper understanding of RLL, particularly in the context of DT and AI.

This emerging issue paper highlights ethical considerations in LL activities, emphasizing user voluntariness, user interests and unintended participation. AI in DT introduces challenges like bias, transparency and digital divide, necessitating responsible practices. Workshop insights underscore challenges: AI bias, data privacy and transparency; opportunities: inclusive decision-making and efficient innovation. The synthesis defines RLLs as frameworks ensuring transparency, stakeholder engagement, ethical considerations and sustainability in AI-driven DT within LLs. RLLs aim to align DT with ethical values, fostering inclusivity, responsible resource use and human rights protection.

The proposed definition of RLL introduces a framework prioritizing transparency, stakeholder engagement, ethics and sustainability in LL activities, particularly those involving AI for DT. This definition aligns LL practices with RRI, addressing ethical implications of AI. The value of RLL lies in promoting inclusive and sustainable innovation, prioritizing stakeholder needs, fostering collaboration and ensuring environmental and social responsibility throughout LL activities. This concept serves as a foundational step toward a more responsible and sustainable LL approach in the era of AI-driven technologies.

The United Kingdom (UK) construction sector is transforming with increasing confidence in offsite construction (OSC) solutions following its accrued benefits. To sustain this momentum, exploring viable strategies to promote successful OSC implementation is a top priority. This paper aims to identify and establish interrelationships and logical dependencies of critical success factors (CSFs) for implementing OSC on building projects in the UK.

This study utilised a qualitative research approach. Following a critical review of extant literature, brainstorming and focus group sessions were carried out with OSC experts in the UK construction industry to identify and contextualise CSFs for OSC implementation. Interpretive structural modelling (ISM) and matrix impact cross-reference multiplication applied to a classification (MICMAC) were used to analyse and model the interrelationships between the contextualised CSFs.

The study identified eighteen CSFs for implementing OSC on projects in the UK positioned on seven hierarchical levels and clustered into dependent, linkage and independent factors. The top five CSFs established were client commitment, top management support, adequate OSC knowledge and experience, flexible leadership and flexible business models. These were located at the base of the ISM model, possessing the highest driving powers in facilitating the successful implementation of OSC on projects.

This study established a hierarchical interrelationship and the importance of the CSFs influencing the successful implementation of OSC. This would assist OSC clients and project teams in identifying and prioritising particular areas for strategic actions, which offer advantages in pursuing successful OSC project outcomes in the UK. Previous research on OSC implementation in the UK had not examined CSFs' interrelationships.

The purpose of this study is to investigate how the process of becoming an entrepreneur in the cooperation and poverty contexts takes place.

This study adopted a phenomenological approach for data collection purposes. Autoscopy, which is a methodological device of reflective nature, was herein applied to a group of interlocutors comprising seven representatives of waste pickers’ cooperatives (RC). Data analysis focused on defining the meaning of participants’ speech was conducted in compliance with Interpretative Phenomenological Analysis guidelines.

The current findings have shown that becoming a representative of cooperatives involves mobilization toward empowerment and a sense of collectively doing on behalf of community interests. Moreover, these RCs become entrepreneurs in the poverty context, as they perceive opportunities, are persistent and take risks pursuing alternatives for both the survival and improvement of theirs own living conditions, and of others.

Adopting a reflective approach associated with an ontology of becoming could have led to deeper results if the current research was a longitudinal study, rather than a cross-sectional one.

Training programs provided for waste pickers should take into consideration that their learning process is mainly based on practice.

Behaviors disclosed by participants toward fostering collective and entrepreneurial actions in the poverty context may be an inspiration for future changes.

The methodological option for adopting a reflective approach resulted in a contribution device that is barely applied to research in the management field; thus, the current investigation can introduce a new pathway for further research.

The problem of long delay and waiting time in Disabled Facilities Grants (DFG) housing adaptation has been ongoing for years. This study aimed at constructing an innovative smart solution to streamline the housing adaptation process to prevent lengthy delays for disabled and elderly people.

The Adapt-ABLE approach is suggested based on a constructive research approach, where extensive theoretical development of the Adapt-ABLE concept is developed. It consists of four integrated platforms that undergo theoretical and analogical development and validations through applicable theories, a workshop, four brainstorming sessions and a focus group.

The proposed Adapt-ABLE approach utilises process optimisation techniques through an IT system for streamlining the process. The merits of the semi-automated system include the development of a preventive measure that allows measurement of suitability index of homes for the occupants, indicative assessment that shorten the application duration, procurement and contracting platform that utilises principles based on framework agreement and call-off contract, and a platform that standardised performance management for continuous improvement.

The Adapt-ABLE solution will cut the application journey of non-qualified applicants and suggest where help can be sought. The qualified applicants' application journey will also be shortened through an online indicative assessment regime and early online resources (means) testing. Overall, the proposed system reduces the waiting time, and timely delivery improves the applicant's quality of life by living independently. It will potentially save the NHS billions of pounds used to replace hips and residential care costs due to lengthy delays in the housing adaptations process.

The lack of a proper register to store, match and display information on the adapted property has led to a waste of resources and prolonged delays in matching the disabled and elderly people with appropriate properties. This paper presents the development of a Housing Adaptations Register with user-matching functionalities for different mobility categories. The developed system accurately captures and documents adapted home information to facilitate the automated matching of disabled/aged applicants needing an adapted home with suitable property using banding, mobility and suitability index.

A theoretical review was conducted to identify parameters and develop adaptations register construct. A survey questionnaire approach to rate the 111 parameters in the register as either moderate, desirable or essential before system development and application. The system development relied on DSS modelling to support data-driven decision-making based on the decision table method to represent property information for implementing the decision process. The system is validated through a workshop, four brainstorming sessions and three focus group exercises.

Development of a choice-based system that enables the housing officers or the Housing Adaptations Register coordinators to know the level of adaptation to properties and match properties quickly with the applicants based on their mobility status. The merits of the automated system include the development of a register to capture in real-time adapted home information to facilitate the automated matching of disabled/aged applicants. A “choice-based” system that can map and suggest a property that can easily be adapted and upgraded from one mobility band to the other.

The development of a housing adaptation register helps social housing landlords to have a real-time register to match, map and upgrade properties for the most vulnerable people in our society. It saves time and money for the housing associations and the local authorities through stable tenancy for adapted homes. Potentially, it will promote the independence of aged and disabled people and can reduce their dependence on social and healthcare services.

This system provides the local authorities with objective and practical tools that may be used to assess, score, prioritise and select qualified people for appropriate accommodation based on their needs and mobility status. It will provide a record of properties adapted with their features and ensure that matching and eligibility decisions are consistent and uniform.

The use of generative artificial intelligence (genAi) language models such as ChatGPT to write assignment text is well established. This paper aims to assess to what extent genAi can be used to obtain guidance on how to avoid detection when commissioning and submitting contract-written assignments and how workable the offered solutions are.

Although ChatGPT is programmed not to provide answers that are unethical or that may cause harm to people, ChatGPT’s can be prompted to answer with inverted moral valence, thereby supplying unethical answers. The authors tasked ChatGPT to generate 30 essays that discussed the benefits of submitting contract-written undergraduate assignments and outline the best ways of avoiding detection. The authors scored the likelihood that ChatGPT’s suggestions would be successful in avoiding detection by markers when submitting contract-written work.

While the majority of suggested strategies had a low chance of escaping detection, recommendations related to obscuring plagiarism and content blending as well as techniques related to distraction have a higher probability of remaining undetected. The authors conclude that ChatGPT can be used with success as a brainstorming tool to provide cheating advice, but that its success depends on the vigilance of the assignment markers and the cheating student’s ability to distinguish between genuinely viable options and those that appear to be workable but are not.

This paper is a novel application of making ChatGPT answer with inverted moral valence, simulating queries by students who may be intent on escaping detection when committing academic misconduct.

This study reviews and discusses the accounting literature that analyzes the role of auditors and enforcers in the context of fraud.

This literature review includes both qualitative and quantitative studies, based on the idea that the findings from different research paradigms can shed light on the complex interactions between different financial reporting controls. The authors use a mixed-methods research synthesis and select 64 accounting journal articles to analyze the main proxies for fraud, the stages of the fraud process under investigation and the roles played by auditors and enforcers.

The study highlights heterogeneity with respect to the terms and concepts used to capture the fraud phenomenon, a fragmentation in terms of the measures used in quantitative studies and a low level of detail in the fraud analysis. The review also shows a limited number of case studies and a lack of focus on the interaction and interplay between enforcers and auditors.

This study outlines directions for future accounting research on fraud.

The analysis underscores the need for the academic community, policymakers and practitioners to work together to prevent the destructive economic and social consequences of fraud in an increasingly complex and interconnected environment.

This study differs from previous literature reviews that focus on a single monitoring mechanism or deal with fraud in a broadly manner by discussing how the accounting literature addresses the roles and the complex interplay between enforcers and auditors in the context of accounting fraud.

Delay in housing adaptation is a major problem, especially in assessing if homes are suitable for the occupants and in determining if the occupants are qualified for the Disabled Facilities Grant (DFG). This paper describes the development of two self-administered intelligent integrated assessment tools from the DFG Adapt-ABLE system: (1) The Home Suitability Assessment Platform, which is a preventive mechanism that allows assessment of the suitability of homes based on occupants’ mobility status and (2) an indicative assessment platform that determines if the applicants are qualified for the DFG to prevent lengthy delays.

The adopted method aligned with a development study approach: a grounded literature review, a severity measurement approach, two stakeholder engagement workshops, four brainstorming sessions and four focus group exercises. The system development relied on Entity–Relationship Diagram (ERD) technique for data structures and database systems design. It uses DFG context sensitivity with alignment with DFG guidance, interlinkages and interoperability between the assessment tools and other platforms of the integrated Adapt-ABLE system.

The assessment tools are client-level outcomes related to accessibility, usability and activity based on the assessment process. The home suitability platform shows the percentage of the suitability of a home with assessment results that suggest appropriate action plans based on individual mobility status. The indicative assessment combines the function of referral, allocation, assessment and test of resources into an integrated platform. This enables timely assessment, decision-making and case-escalation by Occupational Therapists based on needs criteria and the eligibility threshold.

These assessment tools are useful for understanding occupants’ perception of their physical housing environment in terms of accessibility, suitability and usability based on basic activities of daily living and their mobility status. The indicative self-assessment tool will substantially cut down the application journey. The developed tools have been recommended for use in the CSJ Disability Commission report and the UK government Guidance on DFGs for local authorities in England.

This study is part of a participatory design research project and aims to develop and study pedagogical frameworks and tools for integrating computational thinking (CT) concepts and data science practices into elementary school classrooms.

This paper describes a pedagogical approach that uses a data science framework the research team developed to assist teachers in providing data science instruction to elementary-aged students. Using phenomenological case study methodology, the authors use classroom observations, student focus groups, video recordings and artifacts to detail ways learners engage in data science practices and understand how they perceive their engagement during activities and learning.

Findings suggest student engagement in data science is enhanced when data problems are contextualized and connected to students’ lived experiences; data analysis and data-based decision-making is practiced in multiple ways; and students are given choices to communicate patterns, interpret graphs and tell data stories. The authors note challenges students experienced with data practices including conflict between inconsistencies in data patterns and lived experiences and focusing on data visualization appearances versus relationships between variables.

Data science instruction in elementary schools is an understudied, emerging and important area of data science education. Most elementary schools offer limited data science instruction; few elementary schools offer data science curriculum with embedded CT practices integrated across disciplines. This research assists elementary educators in fostering children's data science engagement and agency while developing their ability to reason, visualize and make decisions with data.