Job Postings Research Articles

Auditor distraction: The case of outside job opportunities for external auditors and audit quality

AbstractPublic accountants are in high demand by non‐accounting firms. While this demand attracts high‐quality accountants to public accounting, it can negatively impact audit quality by distracting auditors. We find that the number of metropolitan statistical area–level busy season job postings for public accountants by non‐accounting firms is positively associated with misstatements. Results are most pronounced (1) when outside job opportunities are from non–publicly traded companies, which likely provide better work‐life balance, and (2) when auditors are under a heavier workload, as captured by higher audit fee‐to‐auditor ratios and increased job postings by audit offices leading into the busy season. Results also suggest that accounting firms that provide large pay increases before the busy season can mitigate the negative audit‐quality effects of busy season job postings for public accountants. These results suggest that accounting firms are not immune to negative effects of auditor distraction from outside job opportunities despite accounting firms knowing that their auditors are highly sought after by non‐accounting firms.

WHAT SKILLS DO EMPLOYERS WANT FROM RECENT COLLEGE GRADUATES?

Currently, it is not enough for university graduates to acquire only occupation-specific academic knowledge to find a job. Graduates are also expected to possess an additional set of skills called employability skills. In this study, job vacancies were analyzed to determine the skills employers want from new graduates. In this study, 178 job posts for new graduates on an online job search platform (Kariyer. net) were analyzed using content analysis. According to the findings of the study, fewer hard skills and more soft skills were demanded by recent university graduates. The most demanded skills for both associate degree and bachelor's degree graduates were skills in social and communication groups. When examined in detail, the highest-demanded soft skills include "strong communication skills,” "predisposition to teamwork,” "planning and organization skills,” "effective written and oral communication skills.” In addition, "mastery of MS Office applications, knowledge of foreign languages and "knowledge of computer programs related to the field" are among the technical skills that graduates require. This research is expected to guide new graduates in terms of which skills they should develop and educational institutions in terms of updating their curricula in line with the demand for skills.

Auditor Skill Demands and Audit Quality: Evidence from Job Postings

This study empirically examines the relation between audit quality and auditors’ cognitive and social skills. Using a novel data set of online job postings by accounting firms, we document substantial variation in the stated demand for auditors’ cognitive and social skills, suggesting that audit offices are not homogeneous in their preferences for such skills. We find a positive relation between audit quality and the prevalence of cognitive and social skills within an audit office’s job postings. This association is stronger for audit engagements that are more complex or require greater coordination, suggesting that cognitive and social skills are particularly important in engagements where effective communication and knowledge transfer, as well as sound professional judgment and skepticism, are needed. The association is also stronger for audit offices with greater investments in new technology, consistent with the complementary relation between cognitive and social skills and the use of technology. Overall, our study offers empirical evidence linking specific auditor skills to audit quality. This paper was accepted by Suraj Srinivasan, accounting. Funding: C. Ham acknowledges financial support from the Blanche “Peg” Philpott Faculty Fellowship. R. N. Hann acknowledges financial support from KPMG. W. Wang acknowledges the financial support from the Hong Kong Research Grant Council [Grant 11503720]. Supplemental Material: The online appendix and data files are available at https://doi.org/10.1287/mnsc.2022.01640 .

Emerging landscapes of “alternative-academic” careers in library and information science: Evolutionary patterns and prospects in the Chinese context

This study investigated the emerging landscape of alternative-academic careers in the field of library and information science in China using text mining techniques on a dataset of 7832 job postings from 334 institutions between 2016 and 2023. The findings revealed that alternative-academic positions are widely distributed across academic, cultural, governmental, and commercial institutions, with a growing presence in interdisciplinary and applied research domains. The results highlight the emergence of four distinct functional types: resource construction, academic services, intelligence research, and social functions. Alternative-academic roles have evolved towards greater professionalization, specialization, and collaboration, reflecting the shifting demands of the digital information landscape.

Employer Demand and Desired Skills for Public Health Graduates: Evidence From Job Postings.

Objectives. To determine whether job postings from employers seeking master of public health (MPH) graduates require skills aligning with Council on Education in Public Health (CEPH) competencies. Methods. I analyzed a data set of 70 343 job postings in the United States for MPH graduates from Lightcast, a data vendor that collects, cleans, and analyzes millions of job postings per year. I contrasted skills from the postings with CEPH competencies. Results. Most postings were from for-profit industry, academia and research, or hospitals and health care, with only 12% from government. The skills from job postings aligned well with CEPH competencies, but some CEPH competencies did not appear in the top skills in job postings. Conclusions. Although accredited public health degree programs provide key competencies demanded by employers, they can improve graduate employability by ensuring that their graduates also obtain specific technical skills listed in job postings. (Am J Public Health. Published online ahead of print October 3, 2024:e1-e6. https://doi.org/10.2105/AJPH.2024.307834).

Chutes and Ladders? Job Opportunities for Generation Covid

Focusing on jobs for youth, this study analyzes the development of job postings in Norway during the first and second waves of the COVID-19 pandemic in 2020. Jobs for youth are defined by the top 20 three-digit occupations for young workers, and postings for these occupations took a heavier hit than other jobs during the pandemic. We also identify the top 20 occupations for entrants immediately after completing their highest education to reveal that, during the pandemic, entry jobs for young people with lower education declined the most. Using 2018 and 2019 as reference years, we show that the decline started before ‘lockdown’ policies were in place but worsened during the lockdown. As the economy reopened, job posting rates improved but did not reach the 2018 and 2019 levels.

Machine Learning-based Human Resource Management Information Retrieval and Classification Algorithm

Efficient human resource management (HRM) is essential for company achievement in today’s fast-paced corporate world. Businesses must find effective ways to retrieve and categorise the ever-growing amount of HR-related knowledge. This work presents a new method for retrieving and classifying HRM data using machine learning. Modern natural language processing (NLP) and CNN methods are used by the algorithm we developed to handle unorganized human resources (HR) information, including worker records, job postings, and certificates. HR decision-making is facilitated by the system’s ability to derive insightful information from the information using sophisticated text mining and machine learning algorithms.The two main parts of the method are classification and data extraction. HR workers can more easily obtain the required knowledge thanks to information retrieval, which makes it possible to search HR data quickly and accurately. Contrarily, categorisation optimises the division of human resources information into pertinent classifications, including job positions, competencies, and achievement grades. We assess our algorithm’s effectiveness on various datasets from actual HR datasets. The outcomes show how well our strategy works to streamline HRM procedures, cut down on manual labour, and increase the precision of decisions. Furthermore, our technology is compatible with corporate human resources offices and educational settings because it complies with worldwide university requirements.This study belongs to the growing body of knowledge in HRM. It provides a useful tool for businesses looking to improve employee relations, simplify HR procedures, and attract and retain talent. The suggested method is a valuable resource for academics and businesses alike because of its versatility and compliance with global educational norms.

Client restatement announcement, audit office human capital investment, and audit quality improvements

This paper examines audit offices’ human capital investment in response to client restatement announcements and the resulting effects on audit quality and audit office client base. We find that audit offices attempt to acquire human capital and talent by posting more audit-related job positions just after a client announces a restatement. The increase in job postings follows restatements with more negative announcement returns and restatements of annual financial statements, and is concentrated among more senior and experienced positions. Importantly, the increased job postings are not driven by replacement hiring due to individual auditor departures and reflect more auditors joining the office. These human capital investments reduce future client misstatements and losses in client portfolios, indicating improvements in actual and perceived audit quality. Audit offices are also more likely to replace audit managing partners and prevent the signing partners of the misstated financial statements from signing new audit reports after restatement announcements.

How to Hire Top Talent

This article provides guidance to organizations on developing an effective hiring process to attract and recruit top talent. It outlines six key phases of the hiring lifecycle: crafting job postings, sourcing candidates, screening applicants, conducting interviews, making a final selection, and onboarding new hires. For each phase, research-backed best practices are presented to help motivate top performers and identify the right cultural fit. The article stresses understanding what factors drive high-potential candidates like meaningful work, career growth, autonomy, competitive compensation, and strong company culture. It then provides tips for each step, from promoting these motivators in postings to assessing cultural fit thoroughly during interviews to ensuring new hires are set up for long-term success through customized onboarding plans. Overall, the article aims to help companies optimize their talent acquisition strategy.

A cluster approach to matching the competences of data specialists with skills in demand on the labour market

This paper addresses the challenge of aligning the competences of data specialists with skills in demand on the labour market in the rapidly evolving field of data science. Using an open dataset of 3,744 IT job postings, the study applies K-means clustering to identify key skill groupings for data specialist positions. The optimal number of clusters is determined using the elbow method, resulting in four distinct clusters: Data Analyst & Engineer, Data Platform Engineer, Data Science & Engineering Specialist, and Cloud Data Engineer. The research methodology employs unsupervised learning techniques, specifically K-means clustering, to analyze the distribution of skills across job postings. The clusters are visualized using t-distributed Stochastic Neighbor Embedding (t-SNE), providing insights into the relationships between different skill sets. The study reveals that job titles do not always unambiguously define the required skills, emphasizing the importance of focusing on specific skill sets rather than job titles alone. To bridge the gap between specific subject competences academic programs and industry requirements, the paper proposes a novel approach for comparing the proportion of skills in job clusters with the proportion of professional competencies in academic programs. This method is demonstrated using the Information Systems and Technologies Master's program at Kherson State University as a case study. The chi-square test is applied to confirm the statistical similarity between the skill structure of the Data Science & Engineering Specialist cluster and the competency structure of the academic program. The findings highlight the importance of continuous adaptation of profile of academic program to meet evolving industry needs. The proposed approach provides a data-driven framework for universities to align their programs with labor market demands, potentially improving graduate employability in the data science field. The study also underscores the need for personalized learning paths that can be tailored to individual career goals and skill gaps. Future research directions include the development of an artificial intelligence system to form individualized educational trajectories based on the skills required for specific job clusters. This could further enhance the alignment between education and industry needs, preparing students more effectively for the dynamic data science job market.

Abstract B175: Addressing the urgent demand for clinical research professionals through a novel training initiative

Abstract Training and retaining diverse, qualified clinical research professionals that reflect the demographics of the community is pivotal to design inclusive clinical protocols, recruit underrepresented populations, and increase generalizability of scientific advancements. The University of Chicago's Comprehensive Cancer Center (UCCCC) and the Professional Education (UCPE) office job market analysis found an urgent and growing—and chronically unmet—demand for clinical research professionals across the United States. Nearly 6,930 employers nationwide had active clinical trials job postings from May 2023-2024. Illinois is among the top ten states with unique clinical research job postings. Further, internal UChicago analysis revealed high turnover in entry-level clinical research positions, highlighting a competitive job market for qualified individuals. As 60% of all clinical research activities at UChicago are cancer-focused, the UCCCC pursued novel strategies to diversify, grow, and retain the clinical research workforce. The overarching goal is to optimize pathways from undergraduate programs to clinical research careers. City Colleges of Chicago (CCC) and the UCCCC’s Clinical Trials Support Office (CTSO), Office of Diversity, Equity, and Inclusion, and Office of Education are collaborating on a three-module Cancer Clinical Research Professionals (CCRP) Program to create new pathways into clinical research careers. The yearlong CCRP Program provides hands-on training and development opportunities to community college students interested in biomedicine via a 6-week summer internship, monthly academic year engagements, and a semester-long apprenticeship. The program expands CCC’s capacity to combine classroom learning with practical experience and professional opportunities, which are critical components of students’ education. It promotes career awareness, specialized skill development, and employment in cancer clinical research among CCC students, a diverse and highly motivated talent pool. The internship attracted 49 applicants in its first year. Out of 22 qualified applicants, 6 interns were selected and will begin their training in June 2024. Detailed findings from the internship evaluation will be available in September 2024. We expect the CCRP Program to be most students’ first experience with clinical research careers, greatly expanding their access to opportunities. Our evaluation will present lessons learned during the first year of the CCRP and plans to modify program components. Findings will also inform related training initiatives such as developing an Associate Degree in Clinical Research. We are confident that our forthcoming data will be of interest to other cancer centers and academic medical centers working to enhance their cancer clinical research workforce, which is essential for inclusive research and cancer health equity. Citation Format: Camilla Frost-Brewer, Aspen Ward, Lauren Wall, Megan Mekinda, Eileen Dolan, Jasmine Tiro, Matt Cohn. Addressing the urgent demand for clinical research professionals through a novel training initiative [abstract]. In: Proceedings of the 17th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2024 Sep 21-24; Los Angeles, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2024;33(9 Suppl):Abstract nr B175.

Analytics: What Do Business Majors Need and Where Do They Get It?

Analytical skills are important for all business majors. Because of the statistical underpinnings, statisticians are a natural fit for the delivery of these skills. Unfortunately, there is a lack of common understanding of what skills and competencies are needed. This article has two primary objectives: determine how business analytics course offerings delineate course content (i.e., where statistical and analytical topics are currently offered in business disciplines); and determine the industry analytical needs of various business domains. We performed two phases of analysis. First, we collected course listings and descriptions from the top thirty undergraduate and graduate business programs in the United States to determine what analytics courses are currently offered. Second, we collected industry data to determine what skills are needed across business disciplines based on job postings that identify analytics. Our results indicate there is some overlap of content between current courses. We also find that there are varying analytical skills and competencies needed in other business domains based on job postings. These results can help guide the structure of analytics offerings in business schools.

Identifying skills required of new epidemiologists: a content analysis of Canadian job postings and master's programs.

The rise of emerging public health threats has increased the need for qualified epidemiologists in Canada. Our study aimed to identify the knowledge, skills, and abilities (KSAs) required of epidemiologists entering the workforce and determine whether these align with those taught in graduate epidemiology programs. An inductive content analysis of Canadian job postings from May to December 2023 containing the keyword "epidemiology" and requiring master's degrees in epidemiology or related fields was conducted to identify the KSAs required in the workforce. Inductive content analysis of Master of Science (MSc) program descriptions and core course descriptions was completed to discern skills gained through Canadian graduate epidemiology and public health programs. Based on the 295 job postings analyzed, five KSA categories were identified: communication skills (n = 268, 90.8%), analytical skills (n = 267, 90.5%), soft skills (n = 254, 86.1%), research methodology (n = 217, 73.6%), and knowledge of epidemiological concepts (n = 170, 57.6%). Analysis of 18 MSc programs found that that all of them described analytical skills, research methodology, and epidemiological concepts within their curriculum. Communication skills were described in 94.4% (n = 17) of programs, while soft skills were mentioned in 50.0% (n = 9). However, only 66.7% (n = 12) of programs outlined learning objectives or specified the skills acquired from their programs in their descriptions. There was alignment between the needs of the Canadian epidemiology job market and MSc programs, particularly in analytical skills and research methodology. However, development of soft skills should be emphasized within graduate epidemiology programs to better prepare graduates for the job market. Future research should aim to develop competency statements for epidemiologists in training to ensure consistency across graduate programs and promote career readiness.

Current status of lung cancer care in Germany in the context of treatment centralization and lack of personnel

Lung cancer is the malignancy with the highest mortality rate worldwide. In January 2025, the German public healthcare system will introduce a new regulation according to which a centre can offer surgery for lung cancer only if it carries out a minimum number of lung resections. The purpose of this directive is to reduce the number of centres offering surgical treatment for primary lung cancer, thus centralising and improving lung cancer care. It is expected that the introduction of this regulation will lead to a significant shift in the staffing of thoracic units. The purpose of this survey was to examine the current occupational structures behind the units of thoracic surgery and respiratory medicine. We performed an online survey through the German Society for Thoracic Surgery and the Association of Respiratory Physicians. The responding centres were divided in two groups, centres that were certified by the German Cancer Society or the Society for Thoracic Surgery and centres which were not certified. The response rate was 29.3% (respiratory physicians) and 31.9% (thoracic surgeons); 67% of the participating colleagues answered that their unit was an independent department. The majority of the participants reported having to share the on-call duty of the trainees with other departments in order to be able to cover the required shifts. 35% of the respiratory physicians and 57% of the thoracic surgeons reported having vacant job posts in their units. The introduction of the minimum quantity regulation will have significant consequences for the treatment of lung cancer in Germany. The current staff shortage in healthcare will lead to both medical and nursing staff needing to be redistributed in order to meet the needs that will arise in 2025. Operating lists, theatre days, and operative equipment will need to be redistributed as well, not only within hospitals but probably on a nationwide level. A negative impact of the new regulation is to be expected on research and academic activities since most university hospitals are not expected to reach the minimum number of lung resections that is required in order keep performing lung cancer surgery.

Tempus Fugit: Unraveling Temporal Occurrence and Display Order Effects of Online Information on Employer Impressions

ABSTRACT As social media readily enables users to traverse a targets’ posted content across time, the present research explores the effects of two types of temporality – occurrence and display order – on offline perceptions. Using the context of employers’ impression formation of job applicants, N = 200 human resource personnel were exposed to a job posting and an applicant’s resume and supplemental social media posts in a fully crossed 2 (occurrence order: posts becoming either more or less positive over a 4-year period) and display order (most-recent posts presented either first or last), and a one-condition offset in which all posts were made 2 years ago and displayed in a random order. Findings support the main effect of temporal occurrence so that more recently posted information more strongly influenced resultant perceptions of the applicant’s employability, person-organization fit, and starting salary; but neither primacy or recency effects of display order were detected. Findings are discussed with respect to warranting theory, primacy/recency effects, and the hiring process.

Seductive Language for Narcissists in Job Postings

Seductive Language for Narcissists in Job Postings

Psycho-semantic analysis of job advertisements as a communicative tool of educational marketing

Introduction. The relevance of the study of job advertisements for teachers and psychologists is associated with the need to find tools for regulating communication within the modern educational environment with dynamic, constantly changing working conditions. The publication of employer requirements sets the direction for changing the criteria for the success of the specialist, which changes the entire educational environment. The purpose of the study: to identify the categorical semantic structure of job advertisements for teachers (using the example of the "Infrastructure of Scientific Research Data" platform). Materials and methods. The object of the study was a corpus of teacher job vacancies from the "Infrastructure of Scientific Research Data" platform, published in 2023 in 83 regions of Russia (5561 vacancies). The job postings included descriptions of candidate requirements, information about the offered salary, and the region in which the vacancy was available. As a comparison group, a corpus of psychologist job vacancies (2076 vacancies) was considered. The following methods were used in the study: 1) Latent Dirichlet Allocation (LDA) method for identifying and analyzing the structure of requirements presented in teacher and psychologist job vacancies; 2) Term Frequency-Inverse Document Frequency (TF-IDF) method for categorical semantic analysis of the structure of teacher and psychologist job vacancies and description of the semantic framework (frame) of the job description; 3) Descriptive statistical methods for analyzing the needs of professionals in helping professions in different regions of Russia and the conditions offered to them. The results of the study. The regions of the Russian Federation with the greatest need for teachers and psychologists have been identified. Based on the statistical significance in the collection of text documents, the most demanded skills of teachers by employers are identified: methodological development and design of an individual educational route (0.167), work with children with disabilities (0.144), organization of the educational process (0.089). For vacancies of psychologists, the most significant were: work on investigative actions (0.319), methodical work in an educational organization (0.187), psychological and pedagogical support for successful development and training (0.129). The main meanings governing professional pedagogical activity are more focused on meta-skills based on the values of inclusion and continuous improvement of education, as well as on flexible skills (Soft skills) that increase competitiveness in various fields of pedagogical activity. In the vacancies of psychologists, professional skills (Hard skills) are relevant, applicable in specific areas, which somewhat narrows the scope of professional implementation. Conclusion. The results of the empirical study allow for considering job vacancy advertisements as one of the communicative tools of educational marketing. Analyzing the significant professional skills from the employer's perspective will enable the development of recommendations for the development of professional communication for teachers, which can be considered in the system of continuous professional education, as well as in regulating interaction within the educational environment. Automated analysis of job vacancies can become a successful interactive diagnostic tool for educational marketing, necessary for the development of the educational space and the improvement of the competitiveness of educational institutions.

An example of the application of artificial intelligence models in human resources processes

Creating job postings and selecting suitable candidates among these job postings is a challenging process. This process increases the workload of human resources and causes the process to proceed slowly. It is of great importance for human resources departments to utilize information processing technologies to create job postings effectively and to evaluate the CVs of applicants to these postings. This study introduces and analyzes two different technologies that can help human resources. In the process of preparing job advertisements in the field of IT, in the first stage, the word cloud method is used to decide which keywords should be emphasized in the advertisement texts. In the second stage, the resumes of the applicants are analyzed using three different deep learning models such as CNN (Convolutional Neural Network), GRU (Gated Recurrent Unit), and LSTM (Long Short-Term Memory) for classification purposes. While the performance of these models is evaluated using metrics such as accuracy, MCC, F_1 score, and MSE, the decision-making processes of the models with explainable artificial intelligence are also analyzed. In this context, the GRU model, which achieved an accuracy of 99%, provided the most superior result in this study and the literature. This research shows that deep learning models provide high accuracy rates and efficiency in human resources resume classification and candidate matching processes. It also explains that using the word cloud method, the most appropriate keywords can be identified, and advertisements can be created.

Embracing artificial intelligence in the labour market: the case of statistics

In an era marked by rapid advancements in artificial intelligence (AI), the dynamics of the labour market are undergoing significant transformation. A common concern amidst these changes is the potential obsolescence of traditional disciplines due to AI-driven productivity enhancements. This study delves into the evolving role and resilience of these disciplines within the AI-influenced labour market. Focusing on statistics as a representative field, we investigate its integration with AI and its interplay with other disciplines. Analyzing 279.87 million online job postings in the United States from 2010 to 2022, we observed a remarkable 31-fold increase in the demand for AI-specialized statistical talent, diversifying into 932 distinct AI-related job roles. Additionally, our research identified four major interdisciplinary clusters, encompassing 190 disciplines with a statistical focus. The findings also highlight a growing emphasis on specific hard skills within these AI roles and the differences in demand for AI talent in statistics across economic sectors and regions. Contrary to the pessimistic view of traditional disciplines’ survival in the AI age, our study suggests a more optimistic outlook. We recommend that professionals and organizations proactively adapt to AI advancements. Governments and academic institutions should collaborate to foster interdisciplinary skill development and evaluation for AI talents, thereby enhancing the employability of individuals from traditional disciplines and contributing to broader economic growth.

Economic policy uncertainty and the demand for labor: Evidence from the online job postings of Chinese firms

This paper examines the impact of economic policy uncertainty (EPU) on labor demand. Using data from a Chinese online job posting site, this study empirically investigates how EPU affects firms' hiring behavior. The results suggest that EPU has overall negative effects. Firms tend to reduce job postings in times of increasing policy uncertainty. More particularly, the demand for skills such as teamwork, personnel management, project management, and customer service declines, while individual qualities become more important to enterprises. The study also reveals that there is a positive relationship between EPU and the educational background required in firms' job ads. Further analysis indicates that non-state-owned enterprises, those with poor internal control quality, smaller scale, greater industry competitiveness, and those in non-high-tech industries are more significantly affected by EPU in hiring. This research provides empirical support and policy recommendations for the government to maintain employment stability and stimulate enterprise labor demand.