Job Salary Research Articles

Assessment of Employee Turnover on an Organisations Efficiency In Post Covid Scenario

The study found out that the organization was experiencing high cases of employee turnover. Most respondents indicated that lack of retention strategies affected organization productivity to a great extent. Most respondents felt that the organization had employed various measures to manage employee turnover. High rate of employee’s turnover impacted negatively on organization productivity since most of the experienced and highly productive staffs were lost during COVID pandemic and it took a long time before the newly recruited staff. Lack of staff training denied the employees with an opportunity for skills development and this encouraged most of the employees to leave the organization and seek jobs in organization that offered career development opportunities. Organization management was not commitment to Employee skills development and this hampered exposure of employees. The study concluded that causes of employees turnover that impacted negatively on an organisation’s productivity included; lack of employees retention strategies, low level of employee motivation, lack of career development opportunities and poor work environment. The study recommended that the organization human resource management should employ strategic strategies such as job security, salaries and remuneration, providing recognition, and individual growth opportunities. The organization human resource management should provide open communication, offer employee reward program, offer recreation facilities as well as various gifts. Key Words: covid, unite nations, career, employees, organization, turnover

Salary Estimator using Big Data

This paper aims to present a salary prediction system. This system use the economic liberalization of Indian markets in early 90s boosted the economic growth of the nation in various sectors over the next two decades. One such sector that has seen a massive growth in this time is Information Technology (IT). The IT industry has played a very crucial role in transforming India from a slow moving economy to one of the largest exporters of IT services. This growth created a huge demand in the labour markets for skilled labour, which in turn made engineering one of the top choices of study after high school over the years. In addition, the earning potential and an opportunity to contribute to technology advancements after engineering, makes it a popular choice of study. These growth dynamics along with the diversified education and labor markets demands gives insight into the factors affecting the employment outcomes of engineering students job postings from job recruiting websites. The growth dynamics along with the employment outcomes of engineering Using big data techniques .Techniques like lasso and random forest are made in use to optimize the API Keywords— Feature Selection, Hypothesis Testing, Job Salary, Prediction engine, Random Forest, Regression, Salary Predictors, Support Vector Machines, Salary Predictor

Fine-Grained Job Salary Benchmarking with a Nonparametric Dirichlet Process–Based Latent Factor Model

As a key decision-making process in compensation and benefits (C&B) in human resource management, job salary benchmarking (JSB) plays an indispensable role in attracting, motivating, and retaining talent. Whereas the existing research mainly focuses on revealing the essential impacts of personal and organizational characteristics and economic factors on labor costs (e.g., C&B), few studies target optimizing JSB from a practical, data-driven perspective. Traditional approaches suffer from issues that result from using small and sparse data as well as from the limitations of linear statistical models in practice. Furthermore, there are also important technical issues that need to be addressed in the small number of machine learning–based JSB approaches, such as “cold start” issues when considering a brand-new type of company or job or model interpretability issues. To this end, we propose to address the JSB problem with data-driven techniques from a fine-grained perspective by modeling large-scale, real-world online recruitment data. Specifically, we develop a nonparametric Dirichlet process–based latent factor model (NDP-JSB) to jointly model the latent representations of both company and job position and then apply the model to predict salaries based on company and position information. Our model strengthens the usage of data-driven approaches in JSB optimization by addressing the aforementioned issues in existing models. For evaluation, extensive experiments are conducted on two large-scale, real-world data sets. Our results validate the effectiveness of the NDP-JSB and demonstrate its strength in providing interpretable salary benchmarking to benefit complex decision-making processes in talent management.Summary of Contribution: This paper bridges the cutting-edge machine learning techniques to their implementation in a practical operation research problem in human resources. We focus on optimizing the salary-matching work to help the companies to seek reasonable salaries for their positions by proposing a data-driven approach to capture hidden patterns from user and company profiles. The contributions of this work reside in both operation research and computing. We (1) formulate the JSB optimization problem and (2) solve it by developing a data-driven method along with an effective algorithm optimization. Moreover, the proposed methodology has strengths in addressing the issues of data sparseness and result interpretability.

Impact of Herzberg Two-Factor Theory on Teachers’ Job Satisfaction: An Implication to the Private Universities of Bangladesh

This paper examines to identify the responsible factors for increasing academician’s job satisfaction of private universities in the northern part of Bangladesh. This study seeks to investigate the suitability of Herzberg Two Factor theory by using five point Likert scale for data collection. To measure these, the researcher has applied descriptive statistics including frequency analysis, mean and standard deviation. The results have been conducted and analyzed of 92 respondents that show the teachers are less satisfied with the working conditions and the research opportunities in their workplace. Furthermore, the salary and fringe benefits as well as the quality of working life (Job security) might have a strong tendency to create job resentment among the teachers. The findings of this study are emphasizing that the hygiene factors, including the Job security, salary and fringe benefits, physical working conditions, research potentials are the most responsible factors causing job dissatisfaction along with some motivational factors such as job autonomy, the way of recognizing teachers' achievement. The researcher ended up that the authority should put high emphasis on faculty job satisfaction by taking care of the hygiene factors as well as the job dissatisfaction avoidance issues (Motivational factors) for a favorable workplace.

Is there a happiness premium for working in the public sector? Evidence from Italy

Is there a happiness premium for working in the public sector? We empirically explore this question using a large sample of about 15,000 Italian employees, from 2004 to 2016. We find that happiness increases with economic conditions, defined as either wealth, job salary, total income or as a factor combining these three pieces of information. Moreover, public employees are on average happier than private employees. This effect, however, holds only for individuals in relatively more deprived economic conditions. For better off individuals, there is no difference in happiness between public and private employees. We conclude that there is a happiness premium for working in the public sector, but only among individuals living in low economic conditions. In particular, their happiness gain is able to compensate the gap these individuals face with respect to private employees with medium economic conditions. Our findings add to the relatively scant empirical literature on psychological well-being and public employment.

Hitting where it hurts most: COVID-19 and low-income urban college students

Using data from a rich online student survey collected at an urban college during the summer of 2020, I estimate the causal impact of the pandemic on students' current and expected outcomes. I find that the COVID-19 disruptions on students’ lives were significant. Because of the pandemic, between 14% and 34% of the students considered dropping a class during spring 2020, 30% modified their graduation plans, and the freshman fall retention rate dropped by 26%. The pandemic also deprived 39% of the students of their jobs and reduced the earnings of 35% and the expected household income of 64%. The economic consequences are grimmer for Pell recipients as they were 20% more likely to lose a job due to the pandemic and 17% more likely to experience earning losses than never Pell recipients. Despite being 36% more likely to receive financial support from the CARES Act than never Pell recipients, Pell recipients were 65% more likely to have faced food and shelter insecurity, and 15% more likely to expect lower annual household income. In contrast with economic outcomes, the only educational differential effect between the two groups is Pell recipients’ 41% greater likelihood to consider dropping a course mostly because of concerns that their grade would jeopardize their financial assistance. Other vulnerable students, such as first-generation students and transfer students, were relatively harder hit. To the extent that they seem to rely less on financial aid and more on income from wage and salary jobs, both their educational and employment outcomes were more negatively impacted by the pandemic relative to students whose parents also attended college or those who began college as freshmen.

Personality and Job Performance of Frontline Employees: A Meta-Analytic Review

Trends in personnel management of frontline employees’ (FLEs) imply that “soft skills” related to personality may be hardest to replace by technological advancements and, thus, become increasingly important. Building on the five-factor model (FFM) of personality, the present research therefore aimed at clarifying meta-analytically the role of personality for explaining FLEs’ job performance. Analyses covered 31 to 55 studies per FFM dimension (N = 6,514 to 10,139). It was found that all five dimensions showed moderate and generalizable relations either to subjectively, or to objectively, measured performance in sales jobs, whereas results were more mixed in non-sales jobs. We also found some evidence of positive time trends of validities. Theoretical and managerial implications include shifting the focus to (1) narrower and more job-related traits, (2) identifying more homogeneous clusters of non-sales jobs, (3) studying more complex personality performance relations, and (4) further monitoring time trends related to technological changes.

Motivation and job satisfaction among hospital nurses in Bulgaria: A cross-sectional study

Introduction/Objective. The competitive healthcare market is focused on quality health services and the search for effective methods to improve the quality of these services represents a continuing challenge for healthcare managers. It has been found that satisfaction with the work of nurses directly affects the quality of care and patient satisfaction. The aim of this study was to examine the factors influencing the motivation and job satisfaction of hospital nurses. Methods. A cross-sectional study in private and public hospitals of Plovdiv region (second largest region in Bulgaria), established as training and teaching bases for nurses was conducted. The sample comprised of nurses employed in internal wards, surgical wards, intensive care units, and neurology ward settings. Results. Most of the participants 55 (67.1%) are working in public hospitals and 27 (32.9%) in private ones. All of the respondents were women with a mean age of 50.57 ? 11.6 years. Only 40.3% of nurses were satisfied with their job and employees in public hospitals were generally more dissatisfied, although both sectors have identified ?payment? and ?working conditions? as being an important source of dissatisfaction. Conclusion. Motivation and job satisfaction studies play an important role in providing appropriate medical care in the healthcare sector. The results of this study demonstrate the importance of good job salary, good working conditions, and co-workers? support for job satisfaction.

Job satisfaction of women employees of the public sector of Afghanistan

Purpose This paper focuses on job satisfaction of women employees in the public sector of Afghanistan and identifies factors and challenges influencing women's job satisfaction in their workplace. Design/methodology/approach The survey data were gathered from 92 employees working at the Ministry of Finance at different position levels. Findings The findings indicate that women employees highly prioritize salary increment and job promotion as their main job satisfaction factors while mentioning low salary, delay in salary payment and unsuitable workplace as the biggest challenges. Among recommendations, the research suggests to launch workshops for male employees to improve their behavior with women employees in the workplace, to promote employees based on their merit regardless of gender, to standardize salary scales, to develop a chart of female rights highlighting how they should be treated in their workplace and to support the female employees by eliminating gender discrimination and providing a secure work environment free of gender bias. Social implications The findings and recommendations may help public sector organizations as well as the private sector of Afghanistan to improve women employees' job satisfaction. Originality/value This article represents an added value for the literature which lacks references about the satisfaction of women working in the public sector of Afghanistan.

Work, stress, and well-being of healthcare and human service professionals during outbreak of COVID-19

Objective: This study explored the level of occupational stress experienced by healthcare and human service professionals during COVID-19 pandemic and assessed if their personal characteristics, occupational stressors, job satisfaction, and their satisfaction with diversity of staff composition, salary, and compensation influenced their perceived stress, and their physical and psychological well-being.Methods: A total of 227 healthcare and human service professionals participated in an online survey from March to August 2020. Participants provided background and job-related information and completed several measures to explore their perceived stress, job experiences, occupational stressors, as well as their physical and psychological problems. Bivariate analyses were used to assess the relationships between perceived stress, occupational stressors, satisfaction with job salary and compensation, satisfaction with diversity of staff composition, overall job satisfaction, and physical and psychological problems. Stepwise multiple regression analyses were performed to identify predictors of perceived stress and physical and psychological problems.Results: The study found a significant correlation between level of job satisfaction, satisfaction with diversity of staff composition, and satisfaction with job salary and compensation. Perceived stress was related positively with occupational stressors and physical and psychological problems, but negatively with overall job satisfaction, satisfaction with diversity of staff composition, and satisfaction with job salary and compensation. The findings found occupational stressors and being younger as significant predicators of perceived stress. Occupational stressors and female gender were significant predicators of experience of physical and psychological problems.Conclusions: This study provides understanding on critical factors that have impacted healthcare and human service professionals’ stress and wellbeing during outbreak of COVID-19 pandemic. These factors should be further investigated to inform public policy and interventions that mitigate health and mental health problems among these professionals during this and future outbreaks.

Propensity to Selling Scale

Sales occupation is one of the most frequent in the job market, and selection of successful sales people is typically among the highest priorities of their companies. Research aimed at explaining sales performance shows that traditional psychometric predictors are limited in achieving this goal. Common constructs that are typically related to work behaviour, such as abilities or personality traits, typically show non-significant or low relations with sales performance. Taking that into an account, we developed a new measure for assessing one’s propensity for selling, based on motivational constructs that underlie successful sales job. In the first study, we developed an initial set of items and assessed its content validity using a sample of sales professionals. In the second study, we assessed the scale’s dimensionality, divergent and predictive validity. A sample of 99 contact centre agents were asked to describe themselves using newly developed items and measures of personality and explicit motives. Besides psychometric measures, the data on agents’ objective sales performance was provided by their employer. First, a unidimensional, three-item solution was shown to be the most appropriate in the exploratory factor analysis of initially developed items. Second, an aggregated result of these three items, representing a total scale score, showed to be largely independent of personality and explicit motives measures. Third, propensity to selling, compared to personality and motives measures, showed to be the most important predictor in explaining the variance of objective sales performance. The scale was labelled Propensity to Selling Scale, and its theoretical and practical implications were further discussed.

ACADEMIC WORKLOADS: INPUTS TO INSTRUCTIONAL LEADERS’ PRODUCTIVITY AND JOB SATISFACTION

This study was conducted to determine the significant effect of academic workloads to productivity and job satisfaction of elementary teachers in selected schools in Liliw District, Laguna. It is important to value the teachers’ productivity and job satisfaction because the researcher believed that these influences teachers’ turnover and quality of teaching. The independent variables included the academic workloads of elementary teachers. On the other hand, teachers’ productivity and job satisfaction are used as an indicator for dependent variables. It aimed to answer the questions such as the mean level of respondent’s academic workloads in terms of: Teaching Load Allocation, Working Hours, Preparation Time, Coaching and Mentoring and Ancillary Function. Also, the mean level of instructional leaders’ productivity in terms of Community services and linkages, Research, Professional Development and Awards and Recognition as well as the mean level of instructional leaders’ job satisfaction in terms of Work Condition, Job Security, Salaries and Benefits, Working Environment; and Social Satisfaction. Presented the summary of findings, ancillary function had a significant effect to instructional leaders’ productivity as to research and job satisfaction as to Job Security, Salaries and Benefits. Preparation time had a significant effect to teachers’ job satisfaction as to work condition and social satisfaction. Ancillary function and preparation time had significant effect to teachers’ productivity as to community services and linkages and professional development. Therefore, the null hypothesis that academic workloads have no significant effect on instructional leaders’ productivity and job satisfaction among selected elementary schools in Liliw, Laguna at 0.05 level of significance was partially accepted. Based on the drawn conclusions resulted to the following recommendations: Rebalance the workload on a regular basis, it may be recommended that automating faculty workload to ensure faculties in institutions optimally spend their time and align with the interests of the institution to maximize efficiency and effectiveness in all areas of operations. Faculty workload management system can help administrators to determine how best to divide the work. Furthermore, creating an action plan based on evaluation scores to enable faculty members to attend workshops, courses and conferences that promote the development of skills for both teaching and research can also be an option for the Academic Workloads of teachers to be improved.

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UNIQUE APPLICATION OF SALES-ORIENTATION CUSTOMER-ORIENTATION (SOCO) SCALE AS A BEHAVIORAL ASSESSMENT TOOL TO PREDICT FUTURE ORIENTATION OF STUDENTS: A STUDY

ABSTRACT Sales management students carry certain misconceptions about sales jobs, which often create confusion in their minds about the nature of the sales job- should they be customer-oriented or sales-oriented? To excel in the initial years of their careers as effective salespersons, students might emphasize sales-orientation or target achievement over customer-orientation. This might force them to choose manipulative practices in their professional lives. The orientation also depends upon the gender and prior sales experience of the students. Thus, if the instructors could assess the students’ orientation, i.e., sales-orientation or customer-orientation, which they would practice during the job in advance, they could mentor them with proper inputs. The present study is an attempt to predict such orientations of the students by using a modified version of the SOCO scale. The findings suggest that gender and prior sales experience play a significant role in predicting the students’ orientation in some cases.

Keep On Moving: Rural University Graduates as Sales Workers in South and Central China

Between 1978 and 2018 the percentage of the Chinese workforce in the service sector rose from 12.2 to 46.3. A large share of this workforce is in sales, selling products ranging from household goods, insurance, advertising space, and education, to various other services. The proliferation of salespeople in China is facilitated by the dramatic increase in the number of university graduates. Personnel in sales jobs, which are particularly popular among graduates from rural backgrounds with degrees from universities with indifferent reputations, experience an extraordinarily high level of mobility. They typically change jobs every few months, either because they are fired or they pursue better opportunities. Based on one year of fieldwork undertaken between 2015 and 2017, this article shows how the rapid expansion of China's higher education subjects students from rural backgrounds to new inequalities, which, in turn, reconfigure the rural-urban divide into multiple intersecting hierarchies. Building on the concept of complexed development, this article analyzes how salespeople experience contradictory mobilities in a web of intersecting hierarchies. It shows how they achieve upward status mobility by breaking away from agricultural and manual labour and becoming university graduates and white-collar workers; but also, how they sometimes experience downward mobility in terms of income in comparison to previous generations of migrants and their less-educated peers.

Market-oriented job skill valuation with cooperative composition neural network

The value assessment of job skills is important for companies to select and retain the right talent. However, there are few quantitative ways available for this assessment. Therefore, we propose a data-driven solution to assess skill value from a market-oriented perspective. Specifically, we formulate the task of job skill value assessment as a Salary-Skill Value Composition Problem, where each job position is regarded as the composition of a set of required skills attached with the contextual information of jobs, and the job salary is assumed to be jointly influenced by the context-aware value of these skills. Then, we propose an enhanced neural network with cooperative structure, namely Salary-Skill Composition Network (SSCN), to separate the job skills and measure their value based on the massive job postings. Experiments show that SSCN can not only assign meaningful value to job skills, but also outperforms benchmark models for job salary prediction.

Business Income Dynamics and Labor Market Fluidity

Abstract The share of the U.S. population that receives business income has increased substantially in recent decades. At the same time, worker hire and separation rates declined, with worrying implications for productivity and wage growth. In this paper, we explore the relationship between business income (BI) receipt and labor reallocation. We show that BI recipients are largely excluded from existing measures of labor reallocation. Including BI recipients reduces the measured decline from 1994 to 2014 in the hire and separation rates by 8.3–8.7%, respectively, primarily among jobs that were secondary sources of income or short in duration. We present evidence that worker transitions between wage and salary jobs and BI represent labor reallocation, as opposed to reclassification of employees as independent contractors.

On Aggregating Salaries of Occupations From Job Post and Review Data

The popularity of job websites has significantly changed the way people learn about different occupations. Among the insights offered by these websites are the statistics of occupation salaries which are useful information for job seekers, career coaches, graduating students, and labor related government agencies. Such statistics include the distribution of job salaries of each occupation, such as average or quantiles. However, significant variability in salary (and review salary) can be found among jobs of the same occupation as we gather job post and review data from job websites. Such variability shows the existence of biases, including salary competitiveness in job posts and salary inflation in job reviews. Based on the observation, we aim at developing an approach to derive occupation salary for a job market, named unbiased salary, by aggregating offer salaries from job posts and review salaries from review data and at the same time removing their biases. To achieve this goal, we proposed COC-model to learn unbiased salaries of occupations, competitiveness of companies and inflation of companies efficiently. COC here is an abbreviation of “Company, Occupation, Company”, which represents two different connections between companies and occupations from job posting site and job review site. COC-model represents the dependency of salary information between companies and occupations in job post data and job review data. It begins with defining three latent variables, say competitiveness, inflation, and unbiased salary, based on their dependencies. Instead of computing these variables iteratively, we formulate the interaction among these three latent variables into a matrix form so that these values could be then efficiently learned in a unified way by a series of matrix operations. Extensive experiments are conducted, including empirical studies about competitiveness and inflation of companies using real dataset and performance testing by synthetic dataset. The experimental results show that COC-model can not only derive unbiased salaries effectively but also help us to understand latent biases in job post and job review data.

Evaluating Nursing Students’ Academic Motivation through Academic Motivational Scale: A Cross-Sectional Study of Two Colleges

Background: Learning is an ongoing process. To achieve desired learning outcomes of the academic journey, students must possess motivation, resilience, and effective communication skills. The positive motivation regarding the academic journey increase students' motivation for learning. This will benefit students to achieve desired results without major obstacles. Objective: To identify the nursing students’ motivation towards their academic journey. Methods: This was a cross-sectional study. Nursing students of first & second year were invited to participate voluntarily. Informed consent was employed before data collection. Two Nursing Colleges affiliated with Peoples University of Medical and Health Sciences for Women Nawabshah were selected as a study site and the duration was from 16th February to 28th February 2021. The convenience sampling technique was used to collect data through a structured, 28-item Academic Motivational Scale. Results: The response rate was of the survey was 100% as all the approached participants responded and completed the survey. The results showed that nursing students were extrinsically motivated (x̅=3.78 & SD =1.192) than internally motivated (x̅ =3.41 & SD=1.128). The main reasons for their extrinsic motivation were to seek a good salary job and live a good life. Conclusion: Students were extrinsically motivated therefore the intrinsic motivation needs to be enhanced through improving the image of the profession among students, making them autonomous, self-directed, and listening to them for understanding their life situations.

Inelastic Nature of Labour Market Needs a Progressive Wage Structure to Equilibrate Skills and Salary Compensation

Due to various externalities, a labour market never operates in perfect competition mode. One such externality is the inelasticity in wages introduced due to personal fulfilment and satisfaction that led to personal job preference. This meant that salary is not the sole determinant of one’s career choice, and thereby, remove one important factor that could equilibrate one’s skills and his/her salary compensation. But, there are other externalities at play. Inefficient transmission of external economic indicators into the labour market ranks as another method in which salary could be out of sync with economic fundamentals. Protected industries or career in emerging fields are examples in which salary are usually higher than the norm. Such realities in the labour market as well as the presence of externalities difficult to unwound thus presents particular challenges to national governments seeking to pull the labour market towards a better equilibrium between skills qualifications and salary compensation. Being fairer, such a labour market is the foundation on which income inequality can be ameliorated, and meritocracy could work its magic in assigning higher salary jobs to those with the necessary qualifications. More importantly, a labour market that assign appropriate value to particular skills qualifications provide a roadmap for individuals to learn new skills, and upgrade to more competitive and better paying jobs. The key question is how do we get there? One approach is to introduce a nationally certified mechanism in which a minimum salary is associated with particular skills qualifications. This mechanism assigns a higher salary to higher educational and skills qualifications, and is not restricted to traditional correlation between salary and educational qualifications. Emphasis on skills qualification is important as individuals should constantly learn and pick up new upgraded skills through continuous learning throughout their careers. Naturally, this should be compensated. Implemented across all sectors of the labour market, such a skill centred salary compensation system would collectively move the entire labour market to a better equilibrium position between skills qualifications and salary compensation. Such a system also reaps other sociological benefits in the wider society, principally in the high value placed on education, as well as charting a continuous path towards skills upgrading for the less education inclined. But, one caveat to the skill centred salary compensation scheme is the need for calibration with a nationally agreed yardstick. One option in this endeavour would be conducting surveys across and within industries to put a price on various educational and skills qualifications. Collectively, a labour market is hampered by various externalities, and is never in perfect competition mode. This meant that there may be disequilibrium in skills qualifications and salary compensation. Implementing a national skills-centred salary compensation system where salary moves in lockstep with skills qualification may be one way to achieving better income equality and seeding a learning and skills upgrading culture in a country.