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The worldwide imposition of lockdown measures to control the 2020 coronavirus disease 2019 (COVID-19) outbreak has shifted most executive communications with external stakeholders online, resulting in quick responses from stakeholders. This study aims to understand how presentational styles exhibited in online communication induce immediate audience responses and empirically test the effectiveness of reactive impression management tactics.

The authors analyze presentational styles using MP3 files containing executive utterances during earnings call conferences held by S&P 100-listed firms after June 2020, the quarter after the World Health Organization declared the COVID-19 outbreak a pandemic on March 11, 2020. Using timestamps, the authors link each utterance to a 1-minute interval change in the ask/bid prices of the stocks that occurs a minute after the corresponding utterance begins.

Exhibiting an informational presentation style in earnings calls leads to positive and immediate audience responses. Managers tend to increase their reliance on promotional presentation styles rather than on informational ones when quarterly earnings exceed market forecasts.

Drawing on organizational genre theory, this research identifies the discrepancy between the presentation styles that audiences positively respond to and those that managers tend to exhibit in earnings calls and provides a reactive impression management typology for immediate responses from online audiences.

This paper aims to examine whether information technology (IT) managers’ virtual listening, as rated by their high-tech employees, affected turnover behaviour beyond a new constellation of variables, some of which have never been researched as antecedents of turnover behaviour, particularly during a pandemic or crisis. Namely, the main aim, among others, is to answer the research question: does IT employees’ perception of the quality of their supervisors’ virtual listening in the pandemic and crisis era, when employees and managers work remotely, will negatively affect turnover behaviour? If yes, in which constellation of antecedents the virtual listening effecting on turnover behaviour?

Logistic regression analysis was conducted to test the hypotheses via SPSS 26 and PROCESS (Model 6). The variance inflation factor was calculated to test multicollinearity. Interaction was tested using the Hayes and Preacher PROCESS macro model. The researchers also used the J-N technique test (Johnson–Neyman via process). The supplemental analysis used also PROCESS MACRO (IBM Corp., Armonk, NY, USA, 2023) Model 4 and Bootstrap test.

The findings show that perceptions of supervisors’ virtual listening quality as rated by their employees moderated the relationship between organisational deviance as a type of organisational misbehaviour (OMB) and turnover behaviour and had the strongest effect on turnover behaviour beyond other key predictors (organisational deviance as a type of misbehaviour, turnover intention, job satisfaction, embeddedness and alternatives in the labour market). Alternatives to current work moderated the association between the perception of managers’ virtual listening behaviour as rated by their employees and turnover behaviour. Specifically, when alternatives in the labour market were high or medium, the perceived quality of managers’ virtual listening reduced turnover behaviour. Finally, the perception of the IT employees supervisors’ virtual listening moderated the relationship between organisational deviance and turnover intention among high-tech employees.

Evaluating supervisor listening in the high-tech firm may have value in terms of its relationship to outcomes such as retaining employees, turnover intention and especially turnover behaviour. The effect on turnover behaviour and of that new constellation of antecedents on turnover behaviour when people work remotely was not researched yet and important for the post COVID-19 era. Additionally, in contrast to most studies of turnover, this study also focus on the positive aspects of turnover and especially turnover behaviour to organisations in general and especially to high-tech firm and not just the negative aspect as was researched until now. Another contribution is the finding that when employees perceived their managers’ virtual listening quality as high, the effect of deviance as a type of OMB on turnover behaviour was positive. Namely, the listening as a moderator and turnover assisted in making the organisation cleaner from inappropriate behaviour. Additionally, when alternatives in the labour market are high or medium, perceived quality of virtual listening of managers as rated by their employees can reduce turnover behaviour. This virtual listening–turnover relationship and the moderator of alternatives to current work had not previously been found in the turnover literature and this is also significant a contribution to the turnover and withdrawal literature.

This study aims to investigate the dynamic capabilities of Indonesia’s local government internal auditors (LGIAs). LGIAs are the functional civil apparatus that is responsible for the main task of auditing local governments at the provincial, regency and municipal levels. Meanwhile, the LGIAs are also a spearhead in identifying and analysing errors, irregularities and fraudulent actions in the finance and development of local government.

The exploratory case study methodology was used, gathering insights from 18 individuals through interviews. In addition, the authors use a critical perspective of the LGIAs’ behaviours in enhancing their capabilities in compliance with the regulations. Moreover, the authors discuss the low motivation of LGIAs in terms of achievement in knowledge acquisition, a mechanistic curriculum creating a climate of low spirit, mental models in rooted ordinariness and behavioural anxiety in hierarchical systems of expertise.

This paper infers that the LGIAs reflect inertia in terms of capabilities because its curriculum, environment and organisation have pervasively changed the culture of the work environment. Consequently, although immorally convenient and practical, the LGIAs work with professional discipline and expedient behaviours. In addition, the LGIAs behave performativity, presenting task performances with undynamic capabilities. Lastly, these behaviours imply the need to enhance the LGIAs’ dynamic capabilities by structuring local governments’ adaptive environment. Hence, this adaptive environment, in turn, could facilitate LGIAs’ further being in high spirits in enhancing knowledge-based expertise.

This study firstly implies that the research findings indicate the need for environmental-, organisational- and curriculum-made transformations to change the capabilities and competencies of LGIAs in the future, facilitating them to increase assimilation-learning abilities. Furthermore, the research shows that mental models dominate LGIAs, resulting in low spirits and reluctance to develop their dynamic capabilities. The paper recommends creating a work culture where anxiety is not dominant and changing the flexibility of the professional structure for LGIAs so that they can be promoted from functional to structural officers.

LGIAs work in a cultural environment that is always structured to fulfil what the regulations require. So, this study’s first novelty is that it underlines the ordinary job practices of LGIAs and the low incentives to enhance their dynamic capabilities. Secondly, it is highlighted that the institution’s auspices do not facilitate LGIAs to advance their dynamic capabilities because of the static competency-based development curriculum. Thirdly, the research shows that the LGIAs are a civil apparatus whose employment system in Indonesia implies a no-dismissal culture and halo effect in measuring performance.

This study aims to examine the influence of accounting professionals’ Machiavellian behavior and ethical judgments on their intention to report fraudulent acts and also to examine the moderating effect of Machiavellianism on the relationship between professionals’ ethical judgments and whistleblowing intention, as well as the mediating effect of personal responsibility, personal costs/benefits and the seriousness of the questionable act on this relationship.

The data were collected via a survey sent to 201 Tunisian accounting professionals and analyzed using the structural equation method.

The results indicate that ethical judgments support the whistleblowing intentions among Tunisian accountants. However, this relationship is affected by Machiavellian behavior that minimizes whistleblowing. Furthermore, the results show that Machiavellianism is negatively associated with whistleblowing intention and has an indirect effect on whistleblowing through perceived personal benefit and the seriousness of the questionable act.

Examining the ethical ideologies that may affect whistleblowing, including Machiavellianism and ethical judgment, in the Tunisian context contributes to the literature on the accounting profession in the Middle East and North Africa. The results of this study could raise awareness among policymakers and regulators in developing countries, particularly in Tunisia, to value whistleblowing as a mechanism for detecting and controlling organizational misconduct and enact regulations that encourage accounting professionals to report fraudulent acts while protecting them.

Drawing on the social presence theory, this study aims to explore how supplier–customer social media interactions influence supplier observers’ trust in the customers and what mechanisms contribute to variation in trust experience.

A total of 36 semi-structured interviews were conducted with Chinese suppliers using WeChat for business-to-business interactions. Data were analyzed in three steps: open coding, axial coding and selective coding.

Findings reveal that varied trust is based not only on the categories of social presence of interaction – whether social presence is embedded in informative interactions – but also on the perceived selectivity in social presence. Observer suppliers who experience selectivity during social and affective interactions create a perception of hidden information and an unhealthy relationship atmosphere, and report a sense of emotional vulnerability, thus eroding cognitive and affective trust.

The findings contribute new understandings to social presence theory by exploring the social presence of interactions in a supplier–supplier–customer triad and offer valuable insights into business-to-business social media literature by adopting a suppliers’ viewpoint to unpack the mechanisms of how social presence of interaction positively and negatively influences suppliers’ trust and behavioral responses.

The research paper aims to analyse the scholarly literature on advancing HR analytics as an intervention for attrition, a problem that lingers on organisational performance. This study aspires to provide an in-depth literature review and critically assess the knowledge gaps in HR analytics and attritions within organisational performance.

The review analyses the corpus of 196 research articles published in ostensible journals between 2011 and 2023. To identify research gaps and provide valuable insights, this study synthesises relevant studies using School of thought (S), Context (C), Methodology (M), Triggers (T), Barriers (B), Facilitators (F) and Outcomes (O) (SCM-TBFO framework). This study employs the R programming language to conduct a systematic literature review in accordance with the “preferred reporting items for systematic reviews and meta-analysis” (PRISMA) guidelines.

The emerging discipline of HR analytics encompasses the potential to manage attrition and drive organisational performance enhancements effectively. The study of SCM-TBFO encompasses a multidimensional approach, incorporating diverse perspectives and analysing its complex aspects compared to various approaches. The School of thought includes the human capital theory, expectancy theory and resource-based view. The varied research contexts entail the USA, United Kingdom, China, France, Italy and India. Further, the methodologies adopted in the studies are artificial neural networking (ANN), regression, structure equation modelling (SEM) case studies and other theoretical studies. HR analytics and attrition triggers are data mining decision systems, forecasting for firm performance and employee satisfaction. The barriers include leadership styles, cultural adaptability and lack of analytic skills, data security and organisational orientation. The facilitators were categorised into data and technology-related facilitators, human resource policies and organisational growth and performance-related facilitators. The study's primary outcomes are technology adoption, effective HR policies, HR strategies, employee satisfaction, career and organisational expansion and growth.

The primary goal of the literature review is to provide a comprehensive overview of the current state of HR analytics and its impact on organisational performance, particularly in relation to attrition. Further, the study suggests that attrition, a critical organisational concern, can be effectively managed by strategically utilising HR analytics and empowering data-driven interventions that optimise performance and enhance overall organisational outcomes.

The purpose of this paper is to investigate the relationship between CEOs' inside debt holdings (pension benefits and deferred compensation) and the operating leverage of the firms they manage, with the aim to examine whether CEO incentives play a role in corporate risk-taking.

The authors investigate the relation between CEO inside debt holdings (CIDH) (pension benefits and deferred compensation) and the operating leverage (DOL) of the firms they manage. Using a sample of 11,145 US firm-year observations over the period 2006–2017, the authors find a strong negative association between CIDH and DOL. Additional analyses reveal that the relationship between CIDH and DOL is more pronounced in firms with heightened agency issues, powerful CEOs and for CEOs with stronger professional networks. The results are robust to various sensitivity and endogeneity tests.

The authors find strong evidence confirming the expected negative association between CEO inside debt and DOL suggesting that firms with higher inside debt tend to maintain lower levels of operating leverage. These findings continue to hold with the alternative measure for the inside debt and operating leverage, and across a range of tests designed to rule out the possibility that the primary findings are in any way driven by potential endogeneity. In addition, the findings demonstrate that the presence of manager-shareholder agency conflicts can strengthen the inside debt–DOL relationship suggesting the strong role of inside debt in reducing firm risk.

Findings in this paper have implications for design of compensation structures so that corporate boards can establish incentives as a tool for risk management. A limitation of this study is that it is focused on one market, i.e. US listed companies, so the findings may not be applicable on a global scale.

To the best of the authors’ knowledge, this is the first study that links firm-level management of operating leverage through design of CEO inside debt incentives (two obvious choices for risk-reduction at the CEOs’ disposal include reducing financial risk through reduction of firm leverage and reducing operating risk through reduction of operating leverage). While use of firm leverage as an instrument of choice has been explored in the past, use of operating leverage to achieve risk reduction when CEO possess high inside holding, has received very little attention.

In the current economic scenario characterized by turbulence, innovation is a requisite for company's growth. The innovation activities are implemented through the realization of innovative project. This paper aims to prospect the promising opportunities coming from the application of Machine Learning (ML) algorithms to project risk management for organizational innovation, where a large amount of data supports the decision-making process within the companies and the organizations.

Moving from a structured literature review (SLR), a final sample of 42 papers has been analyzed through a descriptive, content and bibliographic analysis. Moreover, metrics for measuring the impact of the citation index approach and the CPY (Citations per year) have been defined. The descriptive and cluster analysis has been realized with VOSviewer, a tool for constructing and visualizing bibliometric networks and clusters.

Prospective future developments and forthcoming challenges of ML applications for managing risks in projects have been identified in the following research context: software development projects; construction industry projects; climate and environmental issues and Health and Safety projects. Insights about the impact of ML for improving organizational innovation through the project risks management are defined.

The study have some limitations regarding the choice of keywords and as well the database chosen for selecting the final sample. Another limitation regards the number of the analyzed papers.

The analysis demonstrated how much the use of ML techniques for project risk management is still new and has many unexplored areas, given the increasing trend in annual scientific publications. This evidence represents an opportunities for supporting the organizational innovation in companies engaged into complex projects whose risk management become strategic.

Machine learning (ML) techniques are increasingly important in enabling business-to-business (B2B) companies to offer personalized services to business customers. On the other hand, humans play a critical role in dealing with uncertain situations and the relationship-building aspects of a B2B business. Most existing studies advocating human-ML augmentation simply posit the concept without providing a detailed view of augmentation. Therefore, the purpose of this paper is to investigate how human involvement can practically augment ML capabilities to develop a personalized information system (PIS) for business customers.

The authors developed a research framework to create an integrated human-ML PIS for business customers. The PIS was then implemented in the energy sector. Next, the accuracy of the PIS was evaluated using customer feedback. To this end, precision, recall and F1 evaluation metrics were used.

The computed figures of precision, recall and F1 (respectively, 0.73, 0.72 and 0.72) were all above 0.5; thus, the accuracy of the model was confirmed. Finally, the study presents the research model that illustrates how human involvement can augment ML capabilities in different stages of creating the PIS including the business/market understanding, data understanding, data collection and preparation, model creation and deployment and model evaluation phases.

This paper offers novel insight into the less-known phenomenon of human-ML augmentation for marketing purposes. Furthermore, the study contributes to the B2B personalization literature by elaborating on how human experts can augment ML computing power to create a PIS for business customers.

In the rapidly evolving digital economy, businesses face formidable pressures to maintain their competitive standing, prompting a surge of interest in the intersection of artificial intelligence (AI) and digital transformation (DT). This study aims to assess the impact of AI technologies on corporate DT by scrutinizing 3,602 firm-year observations listed on the Shanghai and Shenzhen stock exchanges. The research delves into the extent to which investments in AI drive DT, while also investigating how this relationship varies based on firms' ownership structure.

To explore the influence of AI technologies on corporate DT, the research employs robust quantitative methodologies. Notably, the study employs multiple validation techniques, including two-stage least squares (2SLS), propensity score matching and an instrumental variable approach, to ensure the credibility of its primary findings.

The investigation provides clear evidence that AI technologies can accelerate the pace of corporate DT. Firms strategically investing in AI technologies experience faster DT enabled by the automation of operational processes and enhanced data-driven decision-making abilities conferred by AI. Our findings confirm that AI integration has a significant positive impact in propelling DT across the firms studied. Interestingly, the study uncovers a significant divergence in the impact of AI on DT, contingent upon firms' ownership structure. State-owned enterprises (SOEs) exhibit a lesser degree of DT following AI integration compared to privately owned non-SOEs.

This study contributes to the burgeoning literature at the nexus of AI and DT by offering empirical evidence of the nexus between AI technologies and corporate DT. The investigation’s examination of the nuanced relationship between AI implementation, ownership structure and DT outcomes provides novel insights into the implications of AI in the diverse business contexts. Moreover, the research underscores the policy significance of supporting SOEs in their DT endeavors to prevent their potential lag in the digital economy. Overall, this study accentuates the imperative for businesses to strategically embrace AI technologies as a means to bolster their competitive edge in the contemporary digital landscape.