Job Postings Research Articles

CareerConnector

Abstract: Career Connector is an innovative online platform designed to facilitate efficient job searching and recruitment processes, connecting job seekers with potential employers. Powered by a robust technology stack, with .Net serving as the backend language, CareerConnector offers a seamless user experience for both job seekers and employers. Key functionalities encompass user registration and profile creation, advanced job search and filtering, streamlined job posting and application processes, user notifications, and an array of administrative tools for platform management. Additionally, the system incorporates advanced features such as resume upload and parsing, applicant tracking, machine learning-driven job recommendations, and user feedback and review systems. CareerConnector places paramount importance on data privacy and security, adhering to pertinent data protection laws while implementing stringent encryption measures. Scalability and performance optimization are integral to ensuring a smooth and responsive user experience, even as the platform expands. By embracing. Net as the backend language, CareerConnector benefits from its reputation for reliability, scalability, and a wealth of community support. .Net , including React.js, provide the essential infrastructure for handling HTTP requests and database interactions. The ultimate aim of CareerConnector is to create a dynamic, user-centric job portal that effectively bridges the gap between job seekers and employers. By streamlining the job search and recruitment process, it contributes to a more efficient and vibrant

Most Sought-After Professional Competencies in Leading Research Teams of the Ural Federal District

At the current stage of socio-economic development, one of the key tasks is to ensure that education quality matches labour market expectations, and the industry of science and technology is no exception. Nowadays, there is no systemic evaluation and due regard of research staffing needs and competencies required in this field. Hence, the gap between the current level of human capital development and its necessary level is ever increasing. This study focuses on leading research teams working in the area of advanced manufacturing technologies. The main research methods are the following: publication activity analysis for organizations in the Ural Federal District (henceforth UFD) in the field of advanced manufacturing, bibliometric mapping for identifying research teams, a series of in-depth interviews with research team leaders, job postings analysis using HeadHunter website database. Key findings: 1) we developed a methodology to identify leading research teams in the UFD that possess unique research and technology competencies in the field of advances manufacturing technologies; such teams and their leaders were identified; 2) in-depth interviews with research team leaders allowed to determine the most sought-after competencies for young researchers; 3) we compared the results of qualitative analysis (the in-depth interviews) with the final list of required competencies obtained in the process of analyzing job postings in the area of advanced technology in the UFD using the HeadHunter website. Thus, we identified the pools of the most sought-after competencies for the research and manufacturing sectors in the field of advanced manufacturing technologies. Identifying the most sought-after and in-demand competencies in the UFD leading research teams can inform decision-making on updating university study programmes to ensure that student training matches the needs of the industry of science and technology in the UFD.

Analysis of Skills and Qualifications Required in Data Scientist Job Postings Based on the Pareto Analysis Perspective Using Text Mining

Analysis of Skills and Qualifications Required in Data Scientist Job Postings Based on the Pareto Analysis Perspective Using Text Mining

JOB AVAILABILITY FOR OLDER WORKERS IN A COMMUNITY: ANALYSIS ON JOB POSTINGS

Abstract Objectives This study examined the current job availability in a local job market for older workers and investigated the required skills the older workers to be competitive. Background Most studies approached older workers’ employment transition from the supply side of the labor market, examining individual-level factors for a successful employment transition. However, there is a lack of knowledge on the demand side, such as job opportunities, regarding older workers’ employment transition. Methods The study uses combined data with job postings collected in the 4th quarter of 2021 from three engines and the O*NET database with occupational information to identify job opportunities and required skills. Additionally, the 2020 and 2021 American Community Survey were used to explore the characteristics of the older workforce in the community. Results A total of 5,160 job postings divided into 468 occupations were found in the community. The most frequently available jobs were healthcare (14%), transportation and material moving (13 %), and sales (13%) occupations, which required some work experience needed. The older labor force mostly had a college or associate degree (45.8%) and was in educational (16%), office (11%), and sales (11%) occupations. All occupations require technological skills. Conclusion The study found a mismatch between the available jobs and the actual older labor force, and those who are in employment transition, even downward movement, would be required some related experience. These suggest that a pre-employment transition program providing job training and age-friendly employment support services would be helpful for older workers in all occupational classes.

Which skills are the most prized? Analysing monetary value of geographers’ skills on the labour market in six European countries

The objective of the study is to identify those skills that are actually needed by the labour market and allow university graduates to achieve the highest remuneration. To achieve this objective, the authors monitored, for 18 months, online job postings from six countries addressed to geography graduates. Online job postings are the most up-to-date and reliable source of data about the salaries that employers are willing to offer for specific skills or skillsets. A total of 17,397 advertisements were collected, out of which 7,407 included information about the offered salary. Applying text mining and regression tree (classification and regression tree [CART]) analyses, the authors identified skills that significantly differentiate annual salaries. The group of competences associated with higher earnings includes highly specialised geographic information system (GIS), statistical and geological skills. Lower salaries were linked to some general skills such as communicating in a native language as well as some specialised skills, but only to those related to teaching and conducting scientific research.

Sequential job posting and equilibrium wage dispersion with bunching

In a model where new jobs cannot start until some time in the future, we show that firms post vacancies in advance when the match surplus is high, and they post more vacancies but lower wages as the job starting time gets closer. The number of vacancies increases over time because firms prefer to pay the vacancy cost later rather than sooner. Wages decrease over time because vacancies posted early have to compete with a larger number of vacancies posted later. An equilibrium wage distribution with both a continuous component and a mass point exists even with identical and rational agents on both sides of the market. Wage dispersion is generated by the inter-temporal competition between vacancies posted at different times, and a mass point emerges due to the lack of wage competition among vacancies posted at the same time. Consistent with the model, we find college students who graduate in May are more likely to receive an offer in April than March, and the distribution of wage offers received in March first-order stochastically dominates the distribution of wage offers received in April.

Personal Taxes and Firm Skill Hiring: Evidence from 27 Million Job Postings

Using big data on U.S. job postings, we show that firms increase skill requirements when hiring workers in states that cut personal income taxes. We trace a significant driver of this effect to companies’ reallocation of skilled job postings across states based on tax differentials. The tax-induced upskilling is observed within occupations and is more pronounced for high-skill positions within firms. It is accompanied and amplified by concurrent increases in information technology expenditures at local-level establishments. In characterizing the mechanism at play, we show that job upskilling is triggered by tax changes affecting middle- and upper middle-class workers. It is pronounced for high-growth firms, for firms in tradable industries, and in urban areas, but it is mitigated among profitable firms. A narrative-based analysis helps us establish causal inferences. This paper was accepted by Victoria Ivashina, finance. Supplemental Material: The data files and online appendix are available at https://doi.org/10.1287/mnsc.2022.01211 .

Refining the activities of genetic assistants: Development of task statements applicable across practice settings.

Although genetic (counseling) assistants (GAs) have been implemented in many institutions, their roles vary widely. Therefore, this study aimed to refine our knowledge of GA tasks across work settings and specialties. Tasks performed by GAs were extracted from peer-reviewed articles, publicly available theses, and job postings, then analyzed using directed content analysis. Briefly, task statements were coded using broad categories from previous studies, with new categories added as emergent. Coded tasks were combined and condensed to produce a final task list, which was reviewed by subject matter experts. Sixty-one task statements were extracted from previous studies and 335 task statements were extracted from job descriptions. Directed content analysis produced a list of 40 unique tasks under 10 categories (8 from original research and 2 from the data). This study design resulted in a refined list of GA tasks that may be applicable across work settings and specialties, which is an essential step towards defining the scope of GA work. Beyond the human resource applications of the refined task list, this work may also benefit genetics services by reducing role overlap, improving efficiencies, improving employee satisfaction, and informing the development/improvement of training and other educational materials.

Ambiguity in advertised compensation: Recruiting implications of nominal compliance with pay transparency legislation.

Pursuant to legislative mandates the proportion of job postings that include wage and salary information has rapidly increased. However, many organizations comply by advertising very broad salary ranges. Here, we examine how the width of a pay range influences prospective applicants' perceptions. Although in other contexts people often exhibit a preference for vaguely specified gains, we draw from decision and signaling theories to hypothesize negative reactions to highly ambiguous pay ranges and test them in three preregistered experiments. In Study 1, business students evaluate a job posting with the width of the salary range manipulated between subjects. Study 2 tests for moderating effects of ambiguity explanations using a within-subjects manipulation of pay range width counterbalanced across two job postings and a sample of college graduates with relevant work experience. In Study 3, a diverse sample of recent job seekers predict a salary offer for a hiring vignette in which both the extent of ambiguity in the advertised pay range and the chosen candidate's qualifications are manipulated; their qualitative impressions of the organization are also analyzed. Results provide converging evidence for modal aversion to high ambiguity resulting from negative effects on perceived organizational trustworthiness and skewed predictions of salary offers. Practical implications of this aspect of pay transparency are discussed, as well as broader theoretical implications for understanding outcome ambiguity effects in domains where decision makers vary in their beliefs about underlying reasons for vagueness in communicated information. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Hunting for talent: Firm‐driven labor market search in the United States

AbstractResearch SummaryWe analyze firm‐driven labor market search, where firms “hunt” for talent rather than rely on workers to apply for vacancies. We leverage three approaches. We develop a model of firm‐driven search and derive equilibrium conditions under which firms use this channel. We test our model's predictions using two data sources. Data from a nationally representative survey of 10,000 workers shows that the percentage hired through recruiting has increased from 4.9% in 1991 to 14.3% in 2022. This share is larger for higher‐skilled workers and those with online profiles on LinkedIn. We complement this analysis with data on the near universe of online job postings from 2010 through 2020. Consistent with our model and worker survey evidence, we find firms that demand higher‐skilled workers or operate in labor markets with heavy LinkedIn use are more likely to “hunt for talent.”Managerial SummaryWe study the phenomenon of “hunting” for talent, where firms fill open positions by searching for workers and inviting them to a recruiting process, rather than relying on workers to apply directly. We find that the percentage of workers hired through hunting has increased from 4.9% in 1991 to 14.3% in 2022. We propose that firms that rely more on high‐skilled workers and/or operate within industries with a higher share of available candidates with online profiles are more likely to hunt for their talent. We find support for this conjecture using two data sets, documenting the worker and firm side of the labor market. Data from a nationally representative survey of 10,000 workers shows they are more likely to have been “hunted” by their employer if they work in an occupation that requires more skills, or if their industry has more candidates with online profiles. Moreover, data on US‐wide job postings over the past decade shows that firms in need of highly skilled workers are more likely to invest in outbound recruiting capabilities.

Ready or Not

AbstractDebates about the best means of preparing archaeologists continue. This article reviews data from 674 archaeological job postings to assess in-demand archaeological knowledge, skills, and abilities. The needs assessment reveals American archaeology's demand for dynamic, highly skilled professionals capable of identifying, preserving, and protecting the past. The skills demanded in archaeology job postings are the skills necessary to not only succeed as an archaeologist in any sector but also meet the challenges faced by the discipline more generally.

İNSAN KAYNAKLARI DEPARTMANLARININ VERDİKLERİ İŞ İLANLARININ ÇOK BOYUTLU ANALİZİ

In today’s business world, job postings are an important part of the recruitment process used to attract candidates with the qualifications desired by organizations. Job postings are not only a recruiting tool, but also a tool that indicates the experience, skills, and qualifications the industry demands from candidates. The analysis of job postings, on the other hand, provides a general framework regarding the qualifications, skills and experiences that the sector expects from candidates, and provides guidance for sector stakeholders (candidates, educational institutions and the sector). In this context, it is aimed to analyze the job advertisements given by the human resources departments in terms of various categories. Although there are studies on the analysis of job postings for various sectors and professions, this study is the first to analyze human resources job postings. In the study, document/document scanning and examination technique, which is one of the qualitative survey methods, was used as a data collection method. The data were collected from various job posting sites on the internet and frequency analysis was performed using the SPSS program. According to the findings of the research, it has been determined that job postings are given by almost all sectors, more common job postings are given for 23 job positions, foreign language, computer knowledge and software program knowledge is important, gender equality is ensured in job postings, the duration of experience varies according to job positions, job postings 74 different skills and 54 different experience topics.

Entry-level career paths in the life sciences: generic skills in Dutch job postings

ABSTRACT The importance of generic skills for life scientists is commonly recognised by employers, graduates, and higher education institutes. As it remains unclear which generic skills are relevant for different life sciences career paths, this study aims to give an overview to inform and inspire universities and students, by analysing 179 Dutch entry-level job postings. We deductively coded nine career paths, namely: life sciences industry, PhD-student, quality compliance, research-related, sales & business, communication/education, information technology, consultancy, and policy. We coded generic skills using an adapted categorisation consisting of 46 generic skills within four categories, which were: self, others, information, and tasks. The descriptive statistics and cluster analysis results showed that although language, communication, and collaboration were the most requested skills, differences in requested generic skills between career paths and cluster composition were observed as well. We concluded that although some generic skills are important in general, other generic skills are relevant for specific life sciences career paths. To educate skilled life scientists, universities should consider the flexible integration of these generic skills in their life sciences programmes.

Deep Learning Approaches for Big Data-Driven Metadata Extraction in Online Job Postings

This article presents a study on the multi-class classification of job postings using machine learning algorithms. With the growth of online job platforms, there has been an influx of labor market data. Machine learning, particularly NLP, is increasingly used to analyze and classify job postings. However, the effectiveness of these algorithms largely hinges on the quality and volume of the training data. In our study, we propose a multi-class classification methodology for job postings, drawing on AI models such as text-davinci-003 and the quantized versions of Falcon 7b (Falcon), Wizardlm 7B (Wizardlm), and Vicuna 7B (Vicuna) to generate synthetic datasets. These synthetic data are employed in two use-case scenarios: (a) exclusively as training datasets composed of synthetic job postings (situations where no real data is available) and (b) as an augmentation method to bolster underrepresented job title categories. To evaluate our proposed method, we relied on two well-established approaches: the feedforward neural network (FFNN) and the BERT model. Both the use cases and training methods were assessed against a genuine job posting dataset to gauge classification accuracy. Our experiments substantiated the benefits of using synthetic data to enhance job posting classification. In the first scenario, the models’ performance matched, and occasionally exceeded, that of the real data. In the second scenario, the augmented classes consistently outperformed in most instances. This research confirms that AI-generated datasets can enhance the efficacy of NLP algorithms, especially in the domain of multi-class classification job postings. While data augmentation can boost model generalization, its impact varies. It is especially beneficial for simpler models like FNN. BERT, due to its context-aware architecture, also benefits from augmentation but sees limited improvement. Selecting the right type and amount of augmentation is essential.

The Demand for Internal Auditors following Accounting and Operational Failures

ABSTRACT Using a comprehensive database of U.S. internal auditor job postings, we find that firms are about 10 percent more likely to post an internal auditor job after the revelation of accounting and operational failures. Also, the demand for internal auditors is stronger when a failure is more severe. Among firms posting internal auditor jobs, firms demand higher-quality internal auditors in response to a failure compared with when there has not been a recent failure. We find evidence of internal audit demand spillovers through connected directors, which helps mitigate concerns that the primary results are due to replacing internal auditors that recently left or due to endogenous links between hiring internal auditors and failure revelations. Overall, our evidence suggests that firms demand internal auditors to help ensure high-quality financial reporting and effective operations. JEL Classifications: G34, J23, M41, M42.

How open innovation specialists contribute to corporate sustainability and responsibility: A latent Dirichlet allocation approach

AbstractThis study examines the job postings for open innovation (OI) specialists to determine a universal archetype of what competencies and tasks are requested from said professionals and their implications for corporate sustainability and responsibility. This research uses Bayesian statistics and latent Dirichlet allocation (LDA) topic modeling to measure multiple dimensions of the 341 sampled job postings. Our empirical findings unveil the pivotal role that OI specialists have in engaging with stakeholders and monitoring OI dynamics. Multiple dimensions are expected from OI specialists, addressing a multitude of concerns, such as the environment and technologies. Moreover, this study underlines the need for OI specialists to comprehend both internal and external stakeholders' needs. This research contributes to the literature as follows. First, it underlines the value of topic modeling analysis in job profiling research. Second, it bridges existing knowledge gaps on OI specialists' competencies and roles with empirical evidence obtained from a global dataset. Third, it outlines the current market expectations and requirements for OI specialists, which is useful to both candidates and companies.

Countervailing Claims: Pro-Diversity Responses to Stigma by Association Following the Unite the Right Rally

Why do firms take positions on divisive social issues? In this article, I draw on theories of stigma by association to explain why firms’ mere proximity to controversial political actors may lead stakeholders to presume that firms silent on social issues are misaligned with the stakeholders’ sociopolitical preferences. Firms, in turn, countervail these presumptions of misalignment by eschewing silence and claiming sociopolitical positions. Substantiating this theory in the context of employee recruitment following the 2017 Unite the Right White supremacist rally in Charlottesville, Virginia, I show that Charlottesville’s employers combated presumptions that they shared demonstrators’ anti-diversity positions by making countervailing pro-diversity claims in their online job postings. In supplementary analysis, I show that the rally was associated with a newfound wage premium in job postings by Charlottesville’s employers but that this premium was lower when employers made pro-diversity claims. This study advances understanding of strategic sociopolitical positioning whereby firms make calculated appeals to stakeholders. It contrasts with related research showing that firms use social claims to combat negative evaluations resulting from their own actions or to differentiate from competitors. In doing so, it suggests opportunities for further research investigating, for example, additional motivations for firms’ sociopolitical positioning, how positioning might evolve in the context of growing political polarization, and how positioning might relate to workplace inequality and diversity.

Expectations of employers in the United States for entry-level public health job skills with a bachelor's degree: an analysis of the positions advertised in an online job portal.

To analyze the current public health labor market for bachelor's-level graduates. Public health-related job postings (N = 365) from across the United States were collected from an online job portal, Indeed.com, from November 7-14, 2022. Job titles, organization type, degree requirements, work experience, job location, and preferred skills for bachelor's-level public health positions were analyzed. Thirty-one job titles were identified. Approximately one-third (32.33%) of postings were from the Northeastern US; 23.56% were from the Southeastern region. Thirty-five job skill categories were identified. Most jobs (92.33%) required oral and written communication skills, and 85.21% specified educational skills for public health promotion. Cultural competency, project management, and case management abilities were also highly sought. This study revealed the needs of the public health workforce and bolstered the case that public health degree-seekers should be equipped with a set of strategic skills applicable to a range of multisectoral and multidisciplinary public health jobs. Given the rapid changes in the field of public health, ongoing analysis of the labor market benefits educators, employers, and policymakers alike.

THE ECONOMIC IMPACTS OF COVID-19: EVIDENCE FROM A NEW PUBLIC DATABASE BUILT USING PRIVATE SECTOR DATA.

We build a publicly available database that tracks economic activity in the United States at a granular level in real time using anonymized data from private companies. We report weekly statistics on consumer spending, business revenues, job postings, and employment rates disaggregated by county, sector, and income group. Using the publicly available data, we show how the COVID-19 pandemic affected the economy by analyzing heterogeneity in its effects across subgroups. High-income individuals reduced spending sharply in March 2020, particularly in sectors that require in-person interaction. This reduction in spending greatly reduced the revenues of small businesses in affluent, dense areas. Those businesses laid off many of their employees, leading to widespread job losses, especially among low-wage workers in such areas. High-wage workers experienced a V-shaped recession that lasted a few weeks, whereas low-wage workers experienced much larger, more persistent job losses. Even though consumer spending and job postings had recovered fully by December 2021, employment rates in low-wage jobs remained depressed in areas that were initially hard hit, indicating that the temporary fall in labor demand led to a persistent reduction in labor supply. Building on this diagnostic analysis, we evaluate the effects of fiscal stimulus policies designed to stem the downward spiral in economic activity. Cash stimulus payments led to sharp increases in spending early in the pandemic, but much smaller responses later in the pandemic, especially for high-income households. Real-time estimates of marginal propensities to consume provided better forecasts of the impacts of subsequent rounds of stimulus payments than historical estimates. Overall, our findings suggest that fiscal policies can stem secondary declines in consumer spending and job losses, but cannot restore full employment when the initial shock to consumer spending arises from health concerns. More broadly, our analysis demonstrates how public statistics constructed from private sector data can support many research and real-time policy analyses, providing a new tool for empirical macroeconomics.

Benden sosyal medya uzmanı olur mu? Türkiye’de yayınlanan iş ilanlarındaki gerekli beceri ve nitelikler üzerine betimsel bir içerik analizi

The increase in the demand for digital skills has attracted attention in job postings published in the communication sector in recent years. The aim of this study is to reveal the frequently demanded skills and qualifications for the position of social media specialist, which is directly related to digital skills, in the context of Türkiye. For this purpose, descriptive content analysis was employed on 244 job postings published on Bigumigu.com and Mediacat.com, which publish the job postings of agencies in Türkiye. As a result of the analysis, it is possible to say that the most dominant demand of the job postings is experience in terms of years. Having agency experience, being fluent in English, being able to work in a team and having high communication skills are among the most demanded qualifications. Digital content management, digital advertising management, data analytics, design, reporting, and presentation skills are also among the most frequently requested skills. The most surprising result of the research is that agencies do not require a university education. It is important for universities to revise their curricula on the basis of these demands to respond to the needs of the sector and to train qualified graduates.