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The purpose of the study is to conduct an in-depth study of employee performance in connection with compensation, job satisfaction and the work environment of employees at the PT Bank Rakyat Indonesia (Persero) Tbk.

This study was performed at the PT Bank Rakyat Indonesia (Persero) Tbk, which operates in Indonesia, and included all employees of the different branch offices in Sumatera, Jawa, Kalimantan, Sulawesi, Bali and Jayapura.

Compensation does not directly affect employee performance but working environment does directly influence employee performance at the PT Bank Rakyat Indonesia (Persero) Tbk. There is the power of compensation and working environment on job satisfaction and employee performance at the PT Bank Rakyat Indonesia (Persero) Tbk.

The difference between this research and previous ones is the application of compensation influence testing on employee job satisfaction and performance within one bank in Indonesia.

The main goal of this study is to determine the role of employee commitment in the relations between the compensation system and turnover intentions of employees in the Republic of Serbia, as well as to investigate whether there is a mediating effect of employee commitment in this relation.

The primary methodology implemented in the research was data gathering, obtaining theoretical research works on the proposed relations and empirical studies based on the PLS-SEM, analysed by IBM SPSS Statistics and SmartPLS data processing software. The data for the analysis was obtained from a total sample of 764 employees, collected in the Republic of Serbia via an online questionnaire.

The results indicated a positive statistically significant relationship between the formative construct (compensation system) and reflective construct (commitment), as well as a negative statistically significant relationship between the compensation system and reflective construct (turnover intentions). Employee commitment partially mediates the relationship between the compensation system and turnover intentions of employees.

The study was conducted in Serbia and is thus rooted in the specific national context which is characterized by high power distance and high uncertainty avoidance and more collectivistic society with feminine values more expressed. Most of the previous investigations related to the mentioned constructs were performed in companies from more developed countries, including Western Europe and the United States of America, whereas there has been no such research conducted in Serbia to date. The results portrayed a mismatch between the expected relations regarding the attitudes of employees to the rewards and the proposed national context. Modern companies in Serbia need to follow a modern reward mechanism to build stronger commitment and decrease turnover intentions. Moreover, in most earlier research works, compensation was examined in terms of satisfaction with rewards, while this study was based on questions related to perceptions of employees toward HR compensation practices (“The organization offers me”-type questions), not related to their satisfaction. Further, in the majority of previous research works, the compensation system was examined as a variable in combination with other HR processes (staffing, training and development, career development, employee relations, HR planning, communication, etc.), as a HPWP, while in this case the authors used only the practice of compensation (reward elements and employee performance evaluation) to investigate relations with commitment and turnover intentions.

This book aimed to conceptualise a construction workforce management model suitable for effectively managing workers in construction organisations. To this end, this chapter presents the conceptualised model, which consists of seven workforce management practices with their respective measurement variables. Drawing from existing theories, models, and practices, the chapter concludes that a construction organisation that will attain its strategic objectives in the current fourth industrial revolution era must be willing to promote effective recruitment and selection, compensation and benefits, performance management and appraisal, employee involvement and empowerment, training and development, as well as improving workers emotional intelligence and handling external environment pressure. These practices can promote proactiveness, participation, and improved skills and can lead to effective commitment, better quality, and flexibility within the organisation.

The study's objective is to estimate the association of specific perceived employer-provided benefits on employees' intention to leave in different age cohorts during coronavirus disease 2019 (COVID-19). Informed by the psychological theories of ageing, the authors propose three age-cohort-specific hypotheses in three motivational domains: security and health benefits, flexible work arrangement and education-related benefits.

The authors use a large survey of employees in Estonia (n = 7,209) conducted in 2020 and test the association of specific benefits and their interactions with age on employees' intention to leave.

The results show that older cohorts are generally less prone to leave their jobs. Benefits that employers could use during the COVID-19 crisis generally had negative associations with the intention to leave, but age-specific differences were negligible; only the perceived provision of flexible work arrangements reduced the younger cohort's intention to leave relatively more.

This study is one of the few that allows us to make inferences regarding the benefits preferences amongst the working population during an unprecedented health crisis.

This paper aims to focus on the issue of high employee turnover in the Indian tech industry. An integrative review is conducted to analyse the past and current state of literature, as well as prepare a research agenda for future studies.

A pool of 72 articles published between 2010 and 2022 is reviewed with a special focus on Indian tech employees. This study elucidates the extent and impact of employee retention strategies through content analysis.

Two broad perspectives have been established in the literature: the reasons for quitting and the explanations for staying. By means of a comprehensive review, this paper combines these two aspects of literature and suggests factors under organization’s control to retain competent tech employees.

The study is designed to integrate the two theoretical viewpoints of employee turnover literature by consolidating the reasons behind quitting behaviour and staying intention. Codes combining the two aspects are presented as a valuable resource to retain tech talent.

Previous research suggests that the compensation offered to customers after a service failure has to be substantial to make customer satisfaction surpass that of an error-free service. However, with the right service recovery strategy, it might be possible to reduce compensation size while maintaining happy customers. The aim of the current study is to test whether an anchoring technique can be used to achieve this goal.

After experiencing a service failure, participants were told that there is a standard size of the compensation for service failures. The size of this standard was different depending on condition. Thereafter, participants were asked how much they would demand to be satisfied with their customer experience.

The compensation demand was relatively high on average (1,000–1,400 SEK, ≈ $120). However, telling the participants that customers typically receive 200 SEK as compensation reduced their demand to about 800 SEK (Experiment 1)—an anchoring effect. Moreover, a precise anchoring point (a typical compensation of 247 SEK) generated a lower demand than rounded anchoring points, even when the rounded anchoring point was lower (200 SEK) than the precise counterpart (Experiment 2)—a precision effect.

Setting a low compensation standard—yet allowing customers to actually receive compensations above the standard—can make customers more satisfied while also saving resources in demand-what-you-want service recovery situations, in particular when the compensation standard is a precise value.

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.

This paper aims to review the latest management developments across the globe and pinpoint practical implications from cutting-edge research and case studies.

This briefing is prepared by an independent writer who adds their own impartial comments and places the articles in context.

Tracking survey data from millennial manufacturing employees in Indonesia, the conceptual model proposed concentrates on linking employee satisfaction and turnover intention, by unpacking the causation of employee satisfaction into four strands: competency development, compensation and benefits, work-life balance, and meaningful work. The results showed that every strand boosted satisfaction, except the compensation and benefits strand in this manufacturing case. Compensation and benefits packages should be made malleable enough to let employees self-tailor them to a diverse-enough range of life priorities. Doing so, while investing in their broad-minded learning and development, should get companies closer to supplying meaningful work more regularly.

The briefing saves busy executives, strategists and researchers hours of reading time by selecting only the very best, most pertinent information and presenting it in a condensed and easy-to-digest format.

This research aims to study the effects of information (on salary, salary reductions and the pandemic's impact on the organization) on the salary satisfaction of workers whose salary had been cut during the coronavirus disease 2019 (COVID-19) pandemic, analyzing the mediating role of salary equity in this relationship.

Information was acquired with a structured questionnaire sent by email in May 2021 from 251 employees in Spain during the “third wave” of COVID-19. The model was estimated using the weighted least squares mean and variance adjusted (WLSMV).

Results collected reveal that workers' perceptions of equity fully mediated the relationship between salary information, information on salary cuts and salary satisfaction.

Learning more about the effects of information on salary satisfaction can contribute to communication policies that reduce the negative impact of sensitive salary decisions, practical implications for employees, organizations and policymakers.

This study examines the central role of organizational information as a mechanism for managing problems arising from the pandemic-induced unfavorable working conditions. This study analyzes how this information affects workers' attitudes, highlighting the role of equity as a mediator in this process.

Esta investigación pretende estudiar los efectos de la información (sobre el salario, las reducciones salariales y el impacto de la pandemia en la organización) en la satisfacción salarial de los trabajadores que sufrieron reducciones salariales durante la pandemia de COVID-19, analizando el papel mediador de la equidad salarial en esta relación.

La información se obtuvo mediante un cuestionario estructurado enviado por correo electrónico en mayo de 2021 a 251 empleados en Espa durante la “tercera ola” de COVID-19. El modelo se estimó utilizando la media ponderada de mínimos cuadrados, y varianza ajustada (WLSMV).

Los resultados recogidos revelan que la percepción de equidad de los trabajadores media totalmente la relación entre la información salarial y la información de recortes salariales sobre la satisfacción salarial.

Aprender más sobre los efectos de la información en la satisfacción salarial puede contribuir a políticas de comunicación que reduzcan el impacto negativo de decisiones salariales delicadas, implicaciones prácticas para empleados, organizaciones y responsables políticos.

Este estudio examina el papel central de la información organizativa como mecanismo de gestión de los problemas derivados de las condiciones laborales desfavorables inducidas por la pandemia. Analiza cómo esta información afecta a las actitudes de los trabajadores, destacando el papel de la equidad como mediador en este proceso.

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.