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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.

In this “Info-plosion” era, recommendation systems (or recommenders) play a significant role in finding interesting items in the surge of online digital activity and e-commerce. The purpose of this paper is to model users' preference evolution to recommend potential items which users may be interested in.

A novel recommendation system, namely evolution-learning recommendation (ELR), is developed to precisely predict user interest for making recommendations. Differing from prior related methods, the authors integrate the matrix factorization (MF) and recurrent neural network (RNN) to effectively describe the variation of user preferences over time.

A novel cumulative factorization technique is proposed to efficiently decompose a rating matrix for discovering latent user preferences. Compared to traditional MF-based methods, the cumulative MF could reduce the utilization of computation resources. Furthermore, the authors depict the significance of long- and short-term effects in the memory cell of RNN for evolution patterns. With the context awareness, a learning model, V-LSTM, is developed to dynamically capture the evolution pattern of user interests. By using a well-trained learning model, the authors predict future user preferences and recommend related items.

Based on the relations among users and items for recommendation, the authors introduce a novel concept, virtual communication, to effectively learn and estimate the correlation among users and items. By incorporating the discovered latent features of users and items in an evolved manner, the proposed ELR model could promote “right” things to “right” users at the “right” time. In addition, several extensive experiments are performed on real datasets and are discussed. Empirical results show that ELR significantly outperforms the prior recommendation models. The proposed ELR exhibits great generalization and robustness in real datasets, including e-commerce, industrial retail and streaming service, with all discussed metrics.

The purpose of this study to improve the efficiency of customer acquisition and retention through the design of salary information disclosure mechanism.

This study develops a stylized game-theoretic model of delegating customer acquisition and retention, focusing on how firms choose delegation and wage information disclosure strategy.

The results confirm the necessity for enterprises to disclose salary information. When sales agents are risk neutral, firms should choose multi-agent (MA) delegation and disclose their wages. However, when agents are risk averse, firms may disclose the wages of acquisition agents or both agents in MA delegation, depending on the uncertainty of the retention market.

This paper contributes to the literature on delegation of customer acquisition and retention and demonstrates that salary disclosure can be used as a supplement to the incentive mechanism.

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 study aims to examine the relationship between TQM practices and teachers' job satisfaction in Qatar, visualizing this relationship through a path causal model.

A cross-sectional survey from different schools in Qatar was conducted, using a questionnaire administered to 359 teachers. Factor analysis was used to establish the construct validity of the questionnaire, using two statistical tests: Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy, and Bartlett's test of sphericity.

The TQM practices measured were information, professional development, teachers' involvement in decision-making, teamwork and salary. Regression analyses showed that only four of the five constructs were significant in predicting teachers' job satisfaction. The path causal model's results revealed that each explanatory variable's direct effect was strengthened via the effect of the other independent variables.

Teachers who are highly satisfied with their jobs are willing to give their best. This study proposes a conceptual causal model for TQM adoption in the Qatar educational system. The proposed causal model will help policymakers and decision-makers in Qatari schools to draw strategies based on the antecedents and consequences of teachers' involvement in decision-making.

Empirically, this article has employed the concepts of TQM and job satisfaction to construct a causal model, demonstrating the effect of TQM practices on teachers' job satisfaction in schools in Qatar, thus bridging the gap between the two fields. To the best of the researcher's knowledge, no prior studies have examined this relationship within Qatari schools.

This study aims to identify and explain a possible gender pay gap in the creative industry. By using the salary information of Hollywood actors, this paper restricts the analysis to a relatively homogenous group of workers. In addition, actors' human capital endowments and past performance can be measured precisely. The factors that impact the salaries of movie stars are likely to influence the pay of other high-wage employees, such as athletes and executives.

This paper uses a rich panel data set including 178 female and male actors in 973 movies released between 1980 and 2019. Using a random-effects model and the Blinder–Oaxaca decomposition approach, this paper distinguishes between a fraction of the gender pay gap that can be explained and another fraction that cannot be explained. Hence, only the unexplained residual typically obtained by estimating two standard Mincer-type earnings functions is due to discriminatory pay practices.

This study reveals a pay difference between female and male actors. Gender-specific representation in leading roles and systematic differences in performance measures can explain this pay difference. While female actors' underrepresentation in leading roles reflects consumer tastes and, therefore, reflects discriminatory attitudes, no evidence can be found for direct pay discrimination in Hollywood's movie business.

To the best of the authors’ knowledge, this is the first Hollywood study to relying on a rich panel data set that includes various measures of the human capital characteristics of the different individual actors. This paper's theoretical contribution lies in applying classic labor economics reasoning to explain pay determination in Hollywood's movie business.

Little research is devoted to how salary allocation processes interfere with gender inequality in talent development in universities. Administrative data from a university indicated a substantial salary gap between men and women academics, which partially could be explained by the unequal distribution of men and women in the academic job levels after acquiring a PhD, from lecturer to full professor, with men being overrepresented in the higher job levels, as well as in the more senior positions within each job level. We demonstrated how a lack of transparency, consistency and accountability can disqualify apparent fair, merit-based salary decisions and result in biased gender differences in job and salary levels. This chapter reflects on how salary decisions matter for the recognition of talent and should be an integral part of talent management.

The study aims to examine the digital competence of young employees (under 30 years of age) who graduated from the technical university. Self-assessment of selected digital competencies was examined along with the determination of a self-efficacy level in the area of using digital competencies.

Quantitative research was conducted using the computer-assisted web interview method on a sample of 4532 respondents.

Young employees' self-assessment of digital competencies and self-efficacy in the area of using them is high, and it can be assumed that they perceive themselves as digitally competent. Both digital self-efficacy and assessed digital competencies have a positive impact on satisfaction with the university.

The research sample consisted only of employees who graduated from the technical university, but the results may provide feedback on the demand for digital competencies sought in the labor market and constitute valuable information useful in university curriculum development and in vocational education and training.

This is the first study that focuses on the Kozanoglu and Abedin approach to the concept of digital literacy in the context of research on self-assessment and self-efficacy in using digital competencies among technical university graduates, adapting the creative self-efficacy scale by Tierney and Farmer, for measuring digital self-efficacy.

1. Young employees' digital competencies self-assessment is high.

2. Young employees' self-efficacy of using digital competencies is high.

3. Graduating from a DT-focused department has a positive impact on satisfaction.

4. Digital self-efficacy has a positive impact on satisfaction with the university.

5. Assessed digital competencies have a positive impact on satisfaction.

Young employees' digital competencies self-assessment is high.

Young employees' self-efficacy of using digital competencies is high.

Graduating from a DT-focused department has a positive impact on satisfaction.

Digital self-efficacy has a positive impact on satisfaction with the university.

Assessed digital competencies have a positive impact on satisfaction.

The aim of the paper is to examine whether there really is a shortage of VET teachers, and if so, whether there are links to the salary offered and to the qualifications required.

The paper uses three main approaches to examine the narrative of a shortage of VET teachers in Australia.

There was no documented evidence of a VET teacher shortage, beyond a general perception of shortage in line with other occupations due to the post-COVID economic recovery. Salaries for VET teachers were found to compare well with other education occupations and other jobs in the economy. There was no evidence of the required qualifications deterring entry. The main concern appears to be whether VET can adequately train workers for other sectors in shortage.

The research did not include empirical survey work and suggests that this needs to be carried out urgently.

The research provides evidence that will challenge current assumptions and help in the recruitment of VET teachers.

It argues for a recognition of the importance of the VET sector beyond its function of serving industry.

It highlights ways to make VET teaching a more attractive proposition and to better promote its advantages.

Research suggests that engaging in networking behaviors can affect individual work outcomes. However, relatively less is known about how internal versus external networking behaviors influence work outcomes, and whether gender moderates these relationships. Drawing on social capital theory and social role theory, the authors propose a positive relationship between employees' internal and external networking behaviors and their work outcomes (job commitment and career success), and the moderating effect of gender. The authors also explore employee preference in networking.

Based on a sequential mixed-method research design with a four-month time lag, Study 1 data on networking behaviors and employee outcomes were collected via a survey of middle managers and their supervisors from 10 private sector organizations in Sri Lanka. Study 2 data were collected via interviews from a sample of those middle managers and their supervisors.

Study 1 findings indicate a positive relationship between internal networking behaviors and job commitment, and external networking behaviors and career success. The authors also found that internal networking behaviors enhance job commitment. Study 2 findings indicate men and women network differently and benefit differently from that networking but achieve equitable workplace benefits.

This study provides pioneering evidence that internal networking behaviors enhance job commitment among women. It appears that past research did not test the moderating effect of gender for internal versus external networking behaviors separately. Moreover, this study refines the evidence that internal and external networking behaviors differentially impact employee outcomes and explains the processes through a qualitative inquiry.