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The purpose of this study is to provide a detailed demonstration of how artificial intelligence (AI) can be used to potentially generate valuable insights and recommendations regarding the role of accounting in addressing key sustainability-related issues.

The study offers a novel method for leveraging AI tools to augment traditional scoping study techniques. The method was used to show how the authors can produce recommendations for potentially enhancing organisational accountability pertaining to seasonal workers.

Through the use of AI and informed by the knowledge base that the authors created, the authors have developed prescriptions that have the potential to advance the interests of seasonal workers. In doing so, the authors have focussed on developing a useful and detailed guide to assist their colleagues to apply AI to various research questions.

This study demonstrates the ability of AI to assist researchers in efficiently finding solutions to social problems. By augmenting traditional scoping study techniques with AI tools, the authors present a framework to assist future research in such areas as accounting and accountability.

Pressures from non-profit sport organizations’ (NPSOs) external environment influence governance structures and processes. Thus, this study explores the impact of external factors on NPSO board decision making.

Using a sample of six NPSO boards (two national, four provincial/territorial), data were collected via 36 observations, 18 interviews, and over 900 documents. A thematic analysis was conducted via NVivo 12.

Results identified two external factors impacting NPSO board decision making: the sport system structure and general environment conditions. External factors impacted NPSO board decision making in terms of duration, flow, interaction, and scrutiny.

Results demonstrate the need for NPSO boards to engage in boundary-spanning activities whereby external information sources from stakeholders are incorporated to make informed decisions. Practically, NPSO boards should harness virtual meetings to continue their operations while incorporating risk management analyses to assess threats and opportunities.

The purpose of this paper is to examine the contribution of big data in the transforming process of an IT firm to a learning organization.

The authors adopted a qualitative research approach to define and interpret the ideas and experiences of the IT firms’ employees and to present them to the readers directly. For this purpose, they followed a single-case study design. They researched on a small and medium enterprise operating in the IT sector in Düzce province, Turkey. This paper used a semi-structured interview and document analysis as data collecting methods. In all, eight interviews were conducted with employees. Brochures and website of the organization were used as data sources for the document analysis.

As a result of in-depth interviews and document analysis, the authors formed five main themes that describe perception of big data and learning organization concepts, methods and practices adopted in transforming process, usage areas of big data in organization and how the sample organization uses big data as a learning organization. The findings of this paper show that the sample organization is a learning IT firm that has used big data in transforming to learning organization and in maintaining the learning culture.

The findings contribute to literature as it is one of the first studies that examine the influence of big data on the transformation process of an IT firm to a learning organization. The findings reveal that IT firms benefit from the solutions of big data while learning. However, as the design of the research is single-case study, the findings may be specific to the sample organization. Future studies are required that examine the subject in different samples and by different research designs.

In literature, research on how IT firms’ managers and employees use big data in organizational learning process is limited. The authors expect that this paper will shed light on future research that examines the effect of big data on the learning process of the organization.

The authors examine whether limitations in Form 990 result in zero or understated fundraising and administrative expenses for organizations supported by related organizations. Form 990 does not consolidate financial information of legally separate related organizations, resulting in fundraising and administrative expenses being reported by supporting organizations but not by the supported organization.

The authors use the IRS Statistics of Income Sample Data Files and compare charities receiving support from related organizations (supported) to non-supported charities.

The authors find evidence that supported organizations are likely to report zero or understated fundraising expenses and zero administrative expenses. Those receiving related donations are more likely to have zero or understated fundraising expense while those receiving related compensation are more likely to have zero and understated fundraising and administrative expenses. The authors also find evidence that supported organizations receiving greater amounts of related donations and related compensation are also more likely to report zero and understated fundraising expenses as well as zero administrative expenses while greater amounts of related compensation are also associated with understated administrative expense.

Since donors and other stakeholders use Form 990 to evaluate nonprofits, its unconsolidated nature could result in a lack of comparability across organizations and misinformed resource allocation (e.g. donation) decisions. The results also have implications for researchers who use zero and understated fundraising and administrative expenses as proxies for low quality reporting or interpret them as data errors.

The paper examines the extent to which zero or understated fundraising expense reporting (i.e. the fundraising expense puzzle) is associated with supported organizations receiving financial support from related organizations. The authors also expand their examination to zero and understated administrative expenses.

Practitioners have reported a minimal and non-use of building information modelling (BIM), especially in small and medium-sized organisations and BIM infant construction industries. This development calls for a reappraisal of organisations’ strength in capabilities required for BIM uptake towards the target of global construction digitalisation. This study aims to assess the BIM Level 2 uptake capability of organisations in a BIM infant construction industry and identify the underlying interactions between the capability criteria.

The study used a multivariable analysis of fifteen descriptors identified from the people, process, policy, finance and technology domain. Data collection was done in the BIM infant construction industry in Nigeria. Verification of the descriptors and an evaluation of BIM uptake capability in organisations was done. Seventy-three responses were received within the selected context, and data analysis was done with mean weighting and exploratory factor analysis. Maximum Likelihood extraction and Direct Oblimin rotation were used.

Factor analysis revealed three factors that explained 53.28% of the total variance in the BIM Level 2 uptake capability of construction organisations. The factors are workforce capacity and continuous development, an affinity for innovation and strength in physical and operational facilities.

This study provides an overarching and insightful discussion on BIM uptake capability and construction digitalisation with evidence from a BIM-infant construction industry.

The findings of this study are a piece of valuable empirical evidence on Level 2 BIM uptake capability. This empirical situation analysis will inform the advocacy for the advancement of BIM and enhanced utilisation of building information. Evidence on the capability performance of the BIM infant industry has been revealed.

The outcome is expected to stir debate on the preparedness of organisations to further exploit the benefits of BIM in the BIM infant construction industry. Examination of the capability for a particular phase of BIM is scanty in the literature.

Business intelligence (BI) systems and tools are deemed to be a transformative source with the potential to contribute to reshaping the way different healthcare organizations’ (HCOs) services are offered and managed. However, this emerging field of research still appears underdeveloped and fragmented. Hence, this paper aims to reconciling, analyzing and synthesizing different strands of managerial-oriented literature on BI in HCOs and to enhance both theoretical and applied future contributions.

A literature-based framework was developed to establish and guide a three-stage state-of-the-art systematic literature review (SLR). The SLR was undertaken adopting a hybrid methodology that combines a bibliometric and a content analysis.

In total, 34 peer-review articles were included. Results revealed significant heterogeneity in theoretical basis and methodological strategies. Nonetheless, the knowledge structure of this research’s stream seems to be primarily composed of five clusters of interconnected topics: (1) decision-making, relevant capabilities and value creation; (2) user satisfaction and quality; (3) process management, organizational change and financial effectiveness; (4) decision-support information, dashboard and key performance indicators; and (5) performance management and organizational effectiveness.

To the authors’ knowledge, this is the first SLR providing a business and management-related state-of-the-art on the topic. Besides, the paper offers an original framework disentangling future research directions from each emerged cluster into issues pertaining to BI implementation, utilization and impact in HCOs. The paper also discusses the need of future contributions to explore possible integrations of BI with emerging data-driven technologies (e.g. artificial intelligence) in HCOs, as the role of BI in addressing sustainability challenges.

This paper aims to critically examine the accounting and information systems literature to understand the changes that are occurring in the management accounting profession. The changes the authors are interested in are linked to technology-driven innovations in managerial decision-making and in organizational structures. In addition, the paper highlights research gaps and opportunities for future research.

The authors adopted a grounded theory literature review method (Wolfswinkel et al., 2013) to achieve the study’s aims.

The authors identified four research themes that describe the changes in the management accounting profession due to technology-driven innovations: structured vs unstructured data, human vs algorithm-driven decision-making, delineated vs blurred functional boundaries and hierarchical vs platform-based organizations. The authors also identified tensions mentioned in the literature for each research theme.

Previous studies display a rather narrow focus on the role of digital technologies in accounting work and new competences that management accountants require in the digital era. By contrast, the authors focus on the broader technology-driven shifts in organizational processes and structures, which vastly change how accounting information is collected, processed and analyzed internally to support managerial decision-making. Hence, the paper focuses on how management accountants can adapt and evolve as their organizations transition toward a digital environment.

Develop a comprehensive framework for assessing the knowledge organization systems (KOSs), including the taxonomy of Wikipedia and the ontologies of Wikidata, with a specific focus on enhancing management and retrieval with a gender nonbinary perspective.

This study employs heuristic and inspection methods to assess Wikipedia’s KOS, ensuring compliance with international standards. It evaluates the efficiency of retrieving non-masculine gender-related articles using the Catalan Wikipedian category scheme, identifying limitations. Additionally, a novel assessment of Wikidata ontologies examines their structure and coverage of gender-related properties, comparing them to Wikipedia’s taxonomy for advantages and enhancements.

This study evaluates Wikipedia’s taxonomy and Wikidata’s ontologies, establishing evaluation criteria for gender-based categorization and exploring their structural effectiveness. The evaluation process suggests that Wikidata ontologies may offer a viable solution to address Wikipedia’s categorization challenges.

The assessment of Wikipedia categories (taxonomy) based on KOS standards leads to the conclusion that there is ample room for improvement, not only in matters concerning gender identity but also in the overall KOS to enhance search and retrieval for users. These findings bear relevance for the design of tools to support information retrieval on knowledge-rich websites, as they assist users in exploring topics and concepts.

This study aims to explore a rarely studied form of person–organization fit, perceptual fit, which captures the accuracy of an employee’s understanding of their organization’s culture. The managerial antecedents of perceptual fit were explored to increase understanding about how employees learn their organizational culture and the role that managers play in that process. In addition, the behavioural and attitudinal consequences of perceptual fit were examined to gain a deeper appreciation for the impact of misunderstanding one’s organizational culture on work attitudes and cognitions.

Survey tools were used to measure multiple workplace cognitions, attitudes and values from employees of three small health-care organizations. Organizational culture was measured for each organization so that perceptual fit could be ascertained, which represents an accuracy score of each individual’s comprehension of their organization’s culture. Regression analyses measured the hypothesized associations between perceptual fit and its proposed antecedents and consequences.

The results suggest that leader–member exchange (LMX) and perceived organizational support (POS) are both positively associated with perceptual fit. In terms of the outcomes of perceptual fit, the regression analyses provide support for an association between perceptual fit and psychological empowerment, job satisfaction and organizational commitment.

This study contributes to the literature by exploring how employees come to understand their organization’s culture, and the consequences of differing levels of understanding (i.e. perceptual fit). The study results suggest that managerial action such as LMX and POS can enhance the chances that an employee is able to understand their organization’s culture accurately. Furthermore, this research adds to our understanding of the individual consequences of understanding one’s organizational culture by providing evidence that psychological empowerment is associated with perceptual fit.

The purpose of this study is to develop a model for investigating the sharing of harmful messages by employees using social media using the conspiracy theory from a socio-legal perspective. This study also examines the moderating role of different demographic parameters such as age, gender and education toward sharing harmful messages using social media.

Using the conspiracy theory and social impact theory as the foundation of this study, the authors developed theoretical model and validated it using the structural equation modeling technique with 342 participants from various organizations across Europe and Asia. The study also used different statistical measures to understand the demographic impacts toward sharing harmful messages.

It was found that epistemic, existential and social motives significantly and positively influence employees’ inappropriate message-sharing and seeking behavior, which in turn influences them to share harmful messages on social media. The study also indicates that there are some moderating impacts of employee demography toward sharing harmful messages using social media platforms.

This study investigates the antecedents of sharing harmful messages using social media by employees. The present study could be useful for the organizations leaders as well as policymakers and legal fraternity. The study uses a limited number of feedback to validate the model. Also, this is a cross-sectional study which is another limitation of this study.

This study has proposed and validated a theoretical model by using the conspiracy theory as well as the social impact theory which is unique. Moreover, this study adds value to the existing literature on the harmful impacts of social media and its societal impacts. Besides, the validated model of this study has a high explanatory power which is another uniqueness of this study.