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The purpose of this paper is to examine how and why individuals involved in executive remuneration (top pay) decision-making consider quantum as being appropriate rather than excessive, theorised under the rubric of accountability.

In-depth interviews were conducted with non-executive directors (NEDs) serving on remuneration committees (Remcos), institutional investors, their external advisers and internal HR reward experts. Transcripts were analysed using NVivo and the Gioia qualitative methodology.

Defining, measuring and applying performance conditionality in the determination of top pay quantum such that it aligns with company strategy/culture and values, as well as individual recipient motivations, is difficult. While creative approaches to setting top pay so as to attract, retain and motivate key personnel are welcomed, these risk Remco members' personal/organisational reputations. Members recognise disconnection between top pay quantum and general pay levels and how the media highlights social inequality leading to public distrust. They believe they can contribute to more socially acceptable quantum by applying their own values in top pay decision-making.

Sanctions-based, trust-based and selection/peer networks/felt-based accountability theory is used to explain decision-makers’ actions when determining top pay quantum. This paper extends felt accountability theory to encompass public/societal accountability in the context of the appropriateness of top pay quantum decisions.

New Public Management-informed pay-for-performance policies are common in public sectors internationally but can be controversial with delivery agents. More attention is needed on contingent forms of bottom-up implementation of challenging policies, in emerging market economies, for professionals who face tensions between policies and their codes of practice. Street-level bureaucrats (SLBs) mediate policy implementation through discretionary practices; health professionals have enhanced space for discretion based on autonomy derived from professional status. The authors explore policy implementation, adaptation and resistance by physicians, focusing on payments for health workers in Turkey.

The researchers conducted semi-structured qualitative interviews with 12 physicians in Turkish hospitals and thematic analysis of interview transcripts, using a blended (deductive and inductive) approach.

The policy fostered discretionary behaviours such as cherry-picking (high volume, low risk procedures) and pro-social rule-breaking (e.g. “upcoding”), highlighting clinical autonomy to navigate within policy restrictions. Respondents described damage to relationships with patients and colleagues, and dissonance between professional practice and perverse policy incentives, sometimes leading to disengagement from clinical work. Policymakers were perceived to be detached from the realities experienced by SLBs. Tensions between the policy and professional values risked alienating physicians.

This study utilises participant self-reported perceptions of discretionary behaviours. Further work may adopt alternative methods to explore the relationship between self-reporting and observed practice.

The authors contribute to research on differentiated, contingent roles of groups with high scope for discretion in bottom-up implementation, pointing to the potential for policy-professional role conflicts between top-down P4P policies, and the values and codes of practice of professional SLBs.

The article investigates the patterns of asset impairment recognition in search of signs of “big bath” earnings management practices across an internationally diversified sample of public companies. It also elucidates the incentives that may underlie such practices and explores possible safeguards embedded in the existing corporate governance mechanisms.

The article applied static panel and binary logit models to an international firm-level panel dataset of 1045 public companies observed between 2003 and 2018.

Our empirical results suggest that recognition of asset impairment has no determinate impact on earnings volatility. Investigating the possibility of “big bath” earnings management practices, the authors found no impact of asset impairment recognition on total senior executive compensation in firms, which pay performance-based remuneration. The quality of corporate governance has appeared to impact the firms’ intertemporal proclivity to recognize asset impairment with those having the more entrenched and management-controlled boards being more likely to time impairment recognition by delaying it during exceptionally good and exceptionally bad years. While generally unlikely, recognition of asset impairment in a period with a recorded negative operating performance is found to be closely associated with key executive departures.

The article corroborates the salient role of corporate governance mechanisms in shaping the intertemporal patterns of asset impairment recognition. The possible remedies to the phenomenon should be derived therefrom.

This study aims to examine talent management (TM) in the hospitality industry in Macao during COVID-19. It deploys a contingency theory perspective (Luthans and Stewart, 1977) to illuminate the heightened uncertainties and challenges talent managers faced during the pandemic and the urgent adaptations to TM practices they embraced in response.

Adopting a phenomenological approach, this study analyzed data collected through semi-structured interviews conducted with a representative sample of 20 hotel managers in Macao.

Managers reported four major categories of COVID-19-induced challenges and a corresponding set of contingent TM practices. The four contingent TM practices were found to contribute to the shaping of the next new normal in TM in hospitality and included the following: Contingent TM planning; contingent TM deployment and replacement; talent training and development under contingent arrangements; and changed “talent” attitude and practices in recruitment and retention.

The findings are limited to the geographical and industry context of the study. This study should be refined with larger samples.

This study provides a useful framework for guiding professionals on how to manage talent during turmoil periods. It also contributes toward understanding the shifting meaning of talent and TM in hospitality.

This study demonstrates the applicability of contingency theory in managing hospitality talent during turbulent times, which extends TM knowledge and enriches the contingency theory. The findings also facilitate our understanding on how contingent TM practices create processes that lead in setting the new normal.

This study investigates the current trends in CEO compensation by applying a bibliometric technique from the Scopus database.

The bibliometric analysis examines CEO compensation trends through the Scopus database. Frequency analysis is conducted using Microsoft Excel, while data visualisation is performed using VOSviewer. Finally, citation metrics are carried out using Harzing's Publish or Perish.

The results reveal that research into CEO compensation has been consistently increasing since 1976. This study identifies the most popular publication trends, the most active institutions, the top funding institutions, annual publication growth, document and source type, publishers, subject area, author co-citations, highly cited articles, top publishing countries, and keyword co-occurrences. Notably, Arizona State University in the United States (US) is the leading institution with the most prominent publications on CEO compensation. The US is the most active country involved in CEO compensation research.

The current research only derived articles from the Scopus database. Nonetheless, the findings provide an in-depth comprehension of the meaning of “CEO compensation” and present the outline of the research trends on the concept, thus significantly facilitating further studies.

The findings can assist researchers in comprehending and classifying the drivers of CEO compensation previously identified and proven in past studies. Additionally, the findings also create opportunities for new researchers to study CEO compensation.

This study is among the pioneering research investigating CEO compensation-related publications and utilising the Scopus database from an international perspective. This study also offers a historical view of CEO remuneration, a summary of the most significant nations, journals, and writers on the topic, and an outline of how CEO remuneration studies have changed over time. These contributions will enable other researchers to focus on this subject.

Digital labor platforms (DLPs) are transforming the nature of the work for an increasing number of workers, especially through extensively employing automated algorithms for performing managerial functions. In this novel working setting – characterized by algorithmic governance, and automatic matching, rewarding and punishing mechanisms – gig-workers play an essential role in providing on-demand services for final customers. Since gig-workers’ continued participation is crucial for sustainable service delivery in platform contexts, this study aims to identify and examine the antecedents of their working outcomes, including burnout and engagement.

We suggested a theoretical framework, grounded in the job demands-resources heuristic model to investigate how the interplay of job demands and resources, resulting from working in DLPs, explains gig-workers’ engagement and burnout. We further empirically tested the proposed model to understand how DLPs' working conditions, in particular their algorithmic management, impact gig-working outcomes.

Our findings indicate that job resources – algorithmic compensation, work autonomy and information sharing– have significant positive effects on gig-workers’ engagement. Furthermore, our results demonstrate that job insecurity, unsupportive algorithmic interaction (UAI) and algorithmic injustice significantly contribute to gig-workers’ burnout. Notably, we found that job resources substantially, but differently, moderate the relationship between job demands and gig-workers’ burnout.

This study contributes a theoretically accurate and empirically grounded understanding of two clusters of conditions – job demands and resources– as a result of algorithmic management practice in DLPs. We developed nuanced insights into how such conditions are evaluated by gig-workers and shape their engagement or burnout in DLP emerging work settings. We further uncovered that in gig-working context, resources do not similarly buffer against the negative effects of job demands.

A growing body of research finds that gig economy platforms use gamification to enhance managerial control. Focusing on technologically mediated forms of gamification, this literature reveals how platforms mobilize gig workers’ work effort by making the labour process resemble a game. This chapter contends that this tech-centric scholarship fails to fully capture the historical continuities between contemporary and much older occurrences of game-playing at work. Informed by interviews and participatory observations at two food delivery platforms in Amsterdam, I document how these platforms’ piece wage system gives rise to a workplace dynamic in which severely underpaid delivery couriers continuously employ game strategies to maximize their gig income. Reminiscent of observations from the early shop floor ethnographies of the manufacturing industry, I show that the game of gig income maximization operates as an indirect modality of control by (re)aligning the interests of couriers with the interests of capital and by individualizing and depoliticizing couriers’ overall low wage level. I argue that the new, algorithmic technologies expand and intensify the much older forms of gamified control by infusing the organizational activities of shift and task allocation with the logic of the piece wage game and by increasing the possibilities for interaction, direct feedback and immersion. My study contributes to the literature on gamification in the gig economy by interweaving it with the classic observations derived from the manufacturing industry and by developing a conceptualization of gamification in which both capital and labour exercise agency.

Based on stakeholder, agency and institutional theory, this study aims to examine the role of institutional ownership in the relationship between environmental, social and governance practices and CEO compensation.

Utilizing a fixed-effect panel regression analysis, this research utilized a panel data approach, analyzing data spanning from 2014 to 2021, focusing on US companies listed on the S&P500 stock market index. The dataset encompassed 219 companies, leading to a total of 1,533 observations.

The analysis identified that environmental scores significantly impact CEO equity-linked compensation, unlike social and governance scores. Additionally, it was found that institutional ownership acts as a moderating factor in the relationship between the environmental score and CEO equity-linked compensation, as well as the association between the social score and CEO equity-linked compensation. Interestingly, the direction of these moderating effects varied between the two relationships, suggesting a nuanced role of institutional ownership.

This research makes a unique contribution to the field of corporate governance by exploring the relatively understudied area of institutional ownership's influence on the ESG practices–CEO compensation nexus.

This study aims to explore the holistic context of organisational staff retention in small, medium and large organisations. It also aims to identify the factors affecting the retention of organisations of different sizes.

The study implements an empirical test of a model created during previous research with the participation of 511 employees. The responses to the online questionnaire and the modelling were analysed using the partial least squares structural equation modelling method. The models were tested for internal consistency reliability, convergent and discriminant validity, multicollinearity and model fit.

Two models were tested by organisation size, which revealed a total of 62 significant correlations between the latent variables tested. Identical correlations were present in both models in 22 cases. After testing the hypotheses, critical variables (nature of work, normative commitment, benefits, co-workers and organisational commitment) were identified that determine employees’ organisational commitment and intention to leave, regardless of the size of the organisation.

As a result of this research, the models developed are suitable for identifying differences in organisational staffing levels, but there is as yet no empirical evidence on the use of the scales for homogeneous groups of employees.

The results show that employees’ normative commitment and organisational commitment are critical factors for retention. Of the satisfaction factors examined, the nature of work, benefits and co-workers have a significant impact on retention in organisations, so organisational retention measures should focus on improving satisfaction regarding these factors.

The readers of the journal would appreciate the work, which highlights the significance of employee psychology and retention for organisational success.

The study is based on primary data and, to the best of the authors’ knowledge, is one of the few studies that take a holistic approach to organisational staff retention in the context of the moderating effect of organisational size. This study contributes to a comprehensive understanding of the phenomenon of employee retention and in contrast to previous research, examines the combined effect of several factors.

Amidst the turbulent tides of geopolitical uncertainty and pandemic-induced economic disruptions, the information technology industry grapples with alarming attrition and aggravating talent gaps, spurring a surge in demand for specialized digital proficiencies. Leveraging this imperative, firms seek to attract and retain top-tier talent through generous compensation packages. This study introduces a holistic, integrated theoretical framework integrating machine learning models to develop a compensation model, interrogating the multifaceted factors that shape pay determination.

Drawing upon a stratified sample of 2488 observations, this study determines whether compensation can be accurately predicted via constructs derived from the integrated theoretical framework, employing various cutting-edge machine learning models. This study culminates in discovering a random forest model, exhibiting 99.6% accuracy and 0.08° mean absolute error, following a series of comprehensive robustness checks.

The empirical findings of this study have revealed critical determinants of compensation, including but not limited to experience level, educational background, and specialized skill-set. The research also elucidates that gender does not play a role in pay disparity, while company size and type hold no consequential sway over individual compensation determination.

The research underscores the importance of equitable compensation to foster technological innovation and encourage the retention of top talent, emphasizing the significance of human capital. Furthermore, the model presented in this study empowers individuals to negotiate their compensation more effectively and supports enterprises in crafting targeted compensation strategies, thereby facilitating sustainable economic growth and helping to attain various Sustainable Development Goals.

The cardinal contribution of this research lies in the inception of an inclusive theoretical framework that persuasively explicates the intricacies of a machine learning-driven remuneration model, ennobled by the synthesis of diverse management theories to capture the complexity of compensation determination. However, the generalizability of the findings to other sectors is constrained as this study is exclusively limited to the IT sector.