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This study aims to objectively synthesize the volume of accounting literature on financial statement fraud (FSF) using a systematic literature review research method (SLRRM). This paper analyzes the vast FSF literature based on inclusion and exclusion criteria. These criteria filter articles that are present in the accounting fraud domain and are published in peer-reviewed quality journals based on Australian Business Deans Council (ABDC) journal ranking. Lastly, a reverse search, analyzing the articles' abstracts, further narrows the search to 88 peer-reviewed articles. After examining these 88 articles, the results imply that the current literature is shifting from traditional statistical approaches towards computational methods, specifically machine learning (ML), for predicting and detecting FSF. This evolution of the literature is influenced by the impact of micro and macro variables on FSF and the inadequacy of audit procedures to detect red flags of fraud. The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper chronicles the cluster of narratives surrounding the inadequacy of current accounting and auditing practices in preventing and detecting Financial Statement Fraud. The primary objective of this study is to objectively synthesize the volume of accounting literature on financial statement fraud. More specifically, this study will conduct a systematic literature review (SLR) to examine the evolution of financial statement fraud research and the emergence of new computational techniques to detect fraud in the accounting and finance literature.

The storyline of this study illustrates how the literature has evolved from conventional fraud detection mechanisms to computational techniques such as artificial intelligence (AI) and machine learning (ML). The findings also concluded that A* peer-reviewed journals accepted articles that showed a complete picture of performance measures of computational techniques in their results. Therefore, this paper contributes to the literature by providing insights to researchers about why ML articles on fraud do not make it to top accounting journals and which computational techniques are the best algorithms for predicting and detecting FSF.

This paper contributes to the literature by providing insights to researchers about why the evolution of accounting fraud literature from traditional statistical methods to machine learning algorithms in fraud detection and prediction.

The promotion of autonomous vehicles introduces privacy and security risks, underscoring the pressing need for responsible innovation implementation. To more effectively address the societal risks posed by autonomous vehicles, considering collaborative engagement of key stakeholders is essential. This study aims to provide insights into the governance of potential privacy and security issues in the innovation of autonomous driving technology by analyzing the micro-level decision-making processes of various stakeholders.

For this study, the authors use a nuanced approach, integrating key stakeholder theory, perceived value theory and prospect theory. The study constructs a model based on evolutionary game for the privacy and security governance mechanism of autonomous vehicles, involving enterprises, governments and consumers.

The governance of privacy and security in autonomous driving technology is influenced by key stakeholders’ decision-making behaviors and pivotal factors such as perceived value factors. The study finds that the governmental is influenced to a lesser extent by the decisions of other stakeholders, and factors such as risk preference coefficient, which contribute to perceived value, have a more significant influence than appearance factors like participation costs.

This study lacks an investigation into the risk sensitivity of various stakeholders in different scenarios.

The study delineates the roles and behaviors of key stakeholders and contributes valuable insights toward addressing pertinent risk concerns within the governance of autonomous vehicles. Through the study, the practical application of Responsible Innovation theory has been enriched, addressing the shortcomings in the analysis of micro-level processes within the framework of evolutionary game.

This study uses a multi-level framework to systematically summarize and synthesize the empirical literature on determinants of sustainability disclosure.

This review study is based on 159 empirical studies examining determinants of sustainability disclosure and published in Charted Association of Business Schools (CABS) ranked journals over the last 40 years.

Companies are experiencing multi-level pressures for sustainability disclosure. Macro-level variables include political, legal, social-cultural and international pressures. Meso-level factors include customers' concerns, shareholders’ and investors' demands, industry-level variables and media coverage. Micro-level factors include the firm-level governance mechanisms, executives' reporting attitude and role of sustainability promoting institutions. Unlike in developed markets, companies in developing markets feel minimal public pressure for sustainability disclosure but rather are influenced by international NGOs, the media and international buyers. Multi-level and multitude of pressures for sustainability disclosure explains the widely observed differences between studies.

This research presents the most extensive systematic review of the extant sustainability disclosure literature and is the first study to group determinants into micro-, meso- and macro-level components using multi-level analysis.

Recent literature on customer engagement has introduced the concept of “actor engagement,” which serves as the foundation for this study. The study aims to investigate the formation of engagement and engagement's impact on the performance of sharing economy platforms in an international context.

The study analyses unstructured data from 145,434 service providers and 1,703,266 customers on Airbnb across seven countries (USA, Canada, United Kingdom, Australia, South Africa, China and Singapore). Machine learning techniques are used to measure actor engagement, and the research model is tested using structural equation modelling (SEM).

The findings suggest that actor engagement, encompassing the reciprocal relationship between customer engagement and service provider engagement, has a significant impact on platform performance. The moderator analysis highlights the role of cultural differences in the relationship between customer engagement and service provider engagement and between actor engagement and platform performance. Specifically, the study reveals that actor engagement exhibits a more pronounced impact on platform performance in Western countries (such as the USA, Australia and the UK), compared to Eastern countries (such as China and Singapore).

The analysis of the conceptual model is based on the utilisation of behavioural data obtained from the Airbnb website. Due to the nature of the available data, proxies are employed as measures for variables such as platform performance.

This research is amongst the first to provide empirical evidence for actor engagement formation and the function's role in platform performance in the sharing economy. The global nature of Airbnb as a platform facilitates the investigation of country-level factors, specifically cultural values, across seven diverse countries and highlight differences from business to customer (B2C) business models.

To cope with intensifying uncertainties coupled with the rapid advancement of information communication technology (ICT), understanding how to encourage employees' innovative workplace behavior (IWB) is imperative, with two motivational concerns: (1) the possession of critical knowledge resources characterized by intellectual capital (IC) to better reconfigure new and existing knowledge and (2) the development of career sustainability to handle ICT-enabled intricate job arrangements. The authors investigate the relationships among IC, career sustainability and IWB in Chinese cross-border e-commerce enterprises (CEEs), which are becoming increasingly prevalent and central to the global economy.

Using data collected from 417 participants employed in Chinese CEEs, the authors used regression analyses to test the authors' hypotheses.

Human capital (HC) and structural capital (SC) exerted inverted U-shaped influences on IWB, while relational capital (RC) was positively related to IWB. Perceived career sustainability positively moderated such associations between HC and IWB and between SC and IWB; perceived career sustainability negatively moderated the positive RC-IWB relationship.

Results can inform managers which components of IC and how managers are related to IWB so crucial for success of CEEs with ICT-enabled, intricate architectures of knowledge exchange. The authors' results can help global managers and policymakers to more appropriately allocate scarce knowledge resources to maximize innovative behaviors in the highly competitive international business context.

From the knowledge-based view (KBV) of firm innovation, the authors examine the differential effects of IC components on employee IWB amid coronavirus disease 2019 (COVID-19) through a novel lens of employees' perceptions of career sustainability, enriching the literature at the intersection of IC, knowledge management (KM) and career development. The authors' cross-level analysis links micro-level variables to organizational IC in the new normal.

The paper aims to investigate the practices facilitating the transformation of healthcare services, understanding the resulting outcomes in terms of well-being and uplifting changes. a systematic literature review (SLR) focusing on analyzing the healthcare sector under the transformative service research (TSR) theoretical domain is conducted to achieve this goal.

Employing a structured SLR developed based on the PRISMA protocol (Pickering and Byrne, 2014; Pickering et al., 2015) and using Scopus and WoS databases, the study identifies and analyzes 49 papers published between 2021 and 2022. Content analysis is used to classify and analyze the papers.

The SLR reveals four transformative practices (how) within the healthcare sector under the TSR domain, each linked to specific well-being outcomes (what). The analysis shows that both practices and outcomes are mainly patient-related. An integrative framework for transformative healthcare service is presented and critically examined to identify research gaps and define the trajectory for the future development of TSR in healthcare. In addition, managerial implications are provided to guide practitioners.

This research is among the first to analyze TSR literature in the context of healthcare. The study critically examines the TSR’s impact on the sector’s transformation, providing insights for future research and offering a roadmap for healthcare practitioners to facilitate uplifting changes.

The purpose of this paper is to advance the understanding of paradoxes, underlying tensions and potential management strategies when integrating digital technologies into existing lean-based production systems (LPSs), with the aim of achieving synergies and fostering the development of production systems.

This study adopts a collaborative management research (CMR) approach to identify patterns of organisational tensions and paradoxes and explore management strategies to overcome them. The data were collected through interviews and focus group interviews with experts on lean and/or digital technologies from the companies, from documents and from workshops with the in-case researchers.

The findings of this paper provide insights into the salient organisational paradoxes embraced in the integration of digital technologies in LPS by identifying different aspects of the performing, organising, learning and belonging paradoxes. Furthermore, the findings demonstrate the intricacies and relatedness between different paradoxes and their resolutions, and more specifically, how a resolution strategy adopted to manage one paradox might unintentionally generate new tensions. This, in turn, calls for either re-contextualising actions to counteract the drift or the adoption of new resolution strategies.

This paper adds perspective to operations management (OM) research through the use of paradox theory, and we (1) provide a fine-grained perspective on why integration sometimes “fails” and label the forces of internal drift as mechanisms of imbalances and (2) provide detailed insights into how different management and resolution strategies are adopted, especially by identifying re-contextualising actions as a key to rebalancing organisational paradoxes in favour of the integration of digital technologies in LPSs.

Sales organizations embrace technological innovation. However, salespeople’s willingness to use new technology influences a firm’s return on investment, representing a significant concern for the organization. These concerns highlight tensions regarding the tradeoffs associated with technology implementations. The purpose of this study is to offer insights that help reduce the complexities of sales technology (ST) by exploring the changing dynamics of contemporary business relationships.

This paper synthesizes the ST literature using the service ecosystem perspective to propose the sales techno-ecosystem (STE) framework, providing new insights into organizational decision-making related to the ongoing digital transformation of sales tasks.

This synthesis of the ST literature with the service ecosystem seeks to clarify the impact of technology within the evolving nature of buyer–seller relationships by providing four unique perspectives.

Perspective 1 reviews the sales-service ecosystem framework and develops the theoretical underpinnings and relevant terminologies. Perspective 2 summarizes critical aspects of the ST literature and provides foundations for future research in the STE. Perspective 3 offers a more granular view, explicating roles and contexts prevalent in buyer–seller–technology interactions. Perspective 4 provides a set of tenets and advances research questions related to each tenet.

The culmination of these four perspectives is the introduction of five key tenants designed to help guide strategy and research.

The paper advances Hartmann et al. (2018) service ecosystem paradigm by explicating critical aspects of its ST domain to generate insights for theory and practice.

This study aims to investigate whether social investment (SI) policies improve employment among single mothers.

This paper analyzes the potential effects of SI policies on vulnerable individuals and workers at the macro level by using the employment position of single mothers as a dependent variable. Time-series cross-national data from 18 OECD countries between 1998 and 2017 are analyzed. Multilevel model analysis is also used for robustness check.

I find that public spending on education and family support is positively associated with the employment rates of single mothers. In contrast, active labor market policy (ALMP) spending is negatively associated. ALMP’s negative effects stand out particularly with public spending on job training. Of all family support policies, family allowances are positively associated with single mothers’ employment, which runs counter to the conventional argument that family allowances are a disincentive for women’s or mothers’ employment. Paid leave (length and generosity) is also associated with higher employment for single mothers. There is also some tentative evidence that public spending on maternity leave benefits (spending level) may raise the odds of single mothers being employed, when individual-level factors are controlled for in multilevel analysis we implement for robustness check.

This paper does not analyze the effects of the qualitative properties of SI policies. Future research is necessary in this respect.

The effects of SI policies on employment among single mothers have not yet been examined in the literature. This paper seeks to be a first cut at measuring the effects.

This paper explores the role that the control system – understood as a set of financial and non-financial mechanisms – introduced by the Ministerial Decree of 15th February 1860 played in promoting the ethical tolerance of prostitution in the Kingdom of Italy.

A qualitative research method was adopted. Specifically, this study draws on literature on accounting and deviant behaviors and on Suchman's theories of legitimation (1995) to interpret empirical evidence collected from archival primary sources as well as secondary sources.

The paper highlights how the accounting mechanisms introduced by the law were molded to limit the serious consequences of prostitution from a public health standpoint and to demonstrate that the State neither profited from prostitution nor used public money to fund it. This should have stimulated ethical tolerance of the law itself and, consequently, of the prostitution that was regulated.

This paper opens a new research avenue in the field of accounting history by exploring the connection between accounting and prostitution. Moreover, unlike the extant literature on accounting and deviant behaviors, this study delves into the role played by accounting mechanisms to promote ethical tolerance rather than to activate normalization processes.