Job Advertisements Research Articles

Analytical skills for accounting students in a data-driven job market: Australian evidence

Purpose The purpose of this study is to investigate the essential analytical skills required by accounting students to succeed in a rapidly evolving data-driven job market. Specifically, the study explores the role of data analytics, visualisation and software proficiency (e.g. Excel, Power BI) in the contemporary Australian accounting industry. The scope extends to providing recommendations for academia, professional bodies and employers on how accounting education can better align with the dynamic needs of the business environment by integrating these skills into curricula and professional development programmes. Design/methodology/approach Data was collected from Australian job listings incorporating accounting and data analytics tasks from popular job advertisement websites such as Seek, Indeed and Monster. Using the keyword “Data Analyst”, information was gathered on skills demanded, technology proficiency, industry sectors, professional qualifications and salary expectations. The data set comprised 73 observations across various job requirements and characteristics variables. Findings Critical analytical skills sought by accounting professionals in the current job market include extracting insights from big data, solving complex business problems, effective communication and data visualisation. Proficiency in tools like Microsoft Excel, SQL and Power BI is paramount. Originality/value This study enriches the literature by providing comprehensive insights into the contemporary demands for accounting analytics skills. It highlights the importance of integrating technology into accounting education and the varying skill requirements across industries. Additionally, it offers implications for professional qualifications and underscores the necessity for continuous monitoring and adaptation of accounting curricula to meet evolving industry needs.

Labor Market of Regular Workers in Japan: A Perspective from Job Advertisement Data

We present an analysis of wages and labor market tightness for regular workers (full-time permanent workers) in Japan, utilizing a novel dataset of online job advertisements spanning the period from 2015 to 2022. Despite the importance of online job advertisements for the labor market, little has been studied for the case of Japan. Our study documents labor market conditions reflected in online job advertisement data and investigates how posted wages are related to the labor market tightness, and how they affect actual wages of existing workers. The results uncover several aspects of the labor market which are not captured by official statistics. First, we find that posted wages for regular workers increased at a pace faster than wages for existing regular workers in the sample period, with some heterogeneity across industries and skill requirements. Second, we find that the estimated job-filling rate observed from the dataset declined in recent years, which suggests difficulties that firms faced in hiring workers, and that this was associated with an increase in posted wages. Third, we find that an increase in posted wages positively affects the wages of existing regular workers after some time lag. Our empirical findings suggest that spillovers are driven by underlying mechanisms such as retention of existing workers, and fairness norms to maintain a balance in wages between newly hired workers and existing workers.

The Most In-Demand Soft Skills for QA Professionals in Brazil

Background: Software quality assurance (QA) is carried out in tandem with software development. Essentially, QA activities are conducted in hopes of assessing the extent to which a software product aligns with predefined requirements. Although QA includes highly technical tasks, much like software development, it remains largely a human-centered endeavor. Consequently, soft skills can play a significant role in contributing to the success of a project and product quality, as well as boosting the productivity of QA professionals. Aim: Our objective is to investigate: (i) the most sought-after soft skills for QA professionals, (ii) potential correlations among these in-demand soft skills, (iii) variations in soft skill requirements based on the seniority level of positions, and (iv) potential differences in soft skills expectations according to the size of the hiring companies. Our analysis is centered around organizations in Brazil. Method: We looked for soft skills in 2,164 job advertisements from Brazilian companies. Our data extraction process followed an inductive, data-driven approach that included both manual and automated steps. Results: approximately 91% of the job advertisements list at least one soft skill. We identified 32 soft skills in our study, with five soft skills standing out as the most sought-after among them: communication-related skills, planning, innovation, collaboration, and written communication. Notably, companies of various sizes consistently prioritize communication-related and planning skills, deeming them crucial for QA professionals. Conclusions: Our findings underscore the critical importance of five soft skills: communication-related skills, planning, innovation, collaboration, and written communication. The results of our study hold potential value for QA professionals in Brazil seeking to enhance their employability and provide insights to those tasked with staffing, curriculum design, and professional development.

Valtiotieteilijöiden menettelytapatietämys, metakognitio ja näiden vastaavuus työpaikkailmoitusten vaatimusten kanssa

Social scientists’ procedural knowledge, metacognition, and the correspondence of these to the requirements of job advertisements The study examines the alignment between university students’ reported skills, particularly focusing on procedural knowledge and metacognition, and the skill requirements outlined in job advertisements within the field of social sciences. Data were gathered from career portfolios of 261 social science students, compiled during the 2020-21 academic year, and 179 job advertisements sourced from the Finnish TE Office webpages, collected between 2021 and 2022. The research draws upon a qualitative content analysis of these documents. The results reveal that procedural knowledge and metacognition constitute a category rarely mentioned in the job advertisements. Employers prefer a different type of procedural knowledge from what is discerned in the portfolios. Metacognition skills are highly valued in both the advertisements and portfolios, but collective regulative knowledge is more pronounced in the portfolios.

Re-imagining Librarianship: An Observation of Job Advertisements for Librarian Positions in the US

In the current artificial intelligence (AI) and post-pandemic era, libraries are compelled to accelerate digitalization and automation (Nugroho et al., 2023; Pressreader Team, 2023). Revisiting the core values of librarianship is critical to understanding the opportunities and challenges for libraries and librarians in this trend. Advertisements define, convey, and uphold ideologies by including specific ideas and excluding others (McIntosh & Cuklanz, 2014). Job advertisements for librarian positions, therefore, are designed to convey the values of librarianship in the United States. The study aims to identify the values by answering the following research questions: (1) How do libraries describe themselves in job advertisements? (2) How do libraries describe ideal librarians in job advertisements? Between February 15 and March 15, 2023, we collected job advertisements for librarian positions in the US on ALA JobLIST and Indeed. We will use a qualitative research design to analyze the data. The codes are generated from the core values of librarianship, including sustainability, service, intellectual freedom, literacy and learning, equity of access, privacy, democracy, and public good (American Library Association [ALA], 2024; Gorman, 2015). By investigating the values embedded in library job advertisements, we reflect on what core values of librarianship affirm professionalization in social transformation and whether new principles need to be added to the core values. The study also responds to the burnt-out among librarians by emphasizing the boundaries of librarianship. Additionally, it offers insights into Master of Library and Information Science (MLIS) programs on how to prepare future librarians for the job market.

The Role of Recruitment Practises in Enabling Workforce Diversity in County Governments in Kenya

Workforce diversity in public sector organizations in sub-Saharan Africa is supported by legal statutes and mandates as opposed to organizational policy initiatives. HR audits indicate a skewed distribution of specific ethnic groups and an aged workforce with redundant skills due to recruitment practices. Due to the dearth of studies on workforce diversity in sub-national governments in Sub-Saharan Africa, the study examined the role of recruitment practices in enabling workforce diversity in the County Government of Trans- Nzoia. The study was guided by the social identity theory and adopted a descriptive design that was cross-sectional in the time dimension. The study censused senior employees of the County Government and employed a questionnaire as the main research instrument The study carried out data analysis through descriptive analysis and used regression analysis using Statistical Package for Social Sciences (SPSS) software version 20.0 and the output presented in the form of graphs, Charts, and tables. The descriptive statistics indicated the county government values employee qualifications and uses both internal and external job advertisements, with a skewed but consistent selection process. Use of interviews with little application of the psychometric test of candidates as a screening criteria. Workforce diversity significantly correlated with the recruitment practices; with job advertisements (r = 0.781, p< 0.05), and screening process (r = 0.679, p< 0.05), The study concluded that the recruitment practices have a positive effect on workforce diversity. Based on the findings, the study recommends that the county government support competitive recruitment procedures to improve workforce diversity. The study implications are that sector organizations can promote workforce diversity through efficient practices. The study calls for the HR professional to critically examine the different aspects of HRM in public sector organizations. The study findings are beneficial to sub-national governments, policymakers/legislators, and other scholars in Kenya

Analysis of Relationships Between Business Domains and Technical-Skill Requirements for Data Analysts

As growth of the data analytics field continues, more and more academic departments and professional training programs are offering skill training to potential data analysts. However, not all business domains require their data analysts to possess the same sets of technical skills. Based on over 2,500 data-analyst job advertisements posted on LinkedIn and utilizing subject analysis, cross-tabulation analysis, heat map, Kruskal-Wallis test, and Kappa test, this study examined relationships between various business domains and the technical skills required for data analysts within the respective business domains. Among many findings, the study discovered noteworthy disparities among the business domains concerning their requirements of technical-skill sets for data analysts. The findings of this study offer valuable insights to educators and potential data analysts.

Taken for granted or wilfully ignored? Seeking legitimacy for the entrepreneurship educator

PurposeThis study offers insights into how the entrepreneurship educator (EE) is legitimised in higher education.Design/methodology/approachThis exploratory study is based on content analysis of 73 university programme specifications, 61 university strategies and 35 job advertisements. The study uses Suchman’s (1995) conceptualisation of organisational legitimacy to assist in categorising the results according to type of legitimacy.FindingsConnections are made between the legitimacy of the EE and wider societal discourses surrounding the legitimacy of enterprise/entrepreneurship as expressed in university strategies. Attempts to legitimise the EE specifically, as opposed to “the educator” more broadly understood, are quite limited. Programme specifications mainly offer a cognitive form of legitimacy relating to teaching, with elements of pragmatic legitimacy arising from educators’ links to industry and research prowess. Job descriptions are more focused on the educator’s research as a form of legitimation.Research limitations/implicationsThe study creates a baseline of knowledge surrounding the legitimacy of the EE, which raises important questions as to how the educator is supposed to add value in relation to different stakeholders.Originality/valueThe concept of legitimacy, despite widespread application in other disciplines, has found very limited application in the study of EE. Using three sources of data, the paper offers a first application of Suchman’s (1995) conceptualisation of legitimacy to entrepreneurship education. It thereby offers a critical perspective on the role of the EE as shaped by institutional norms.

Discrimination in the Automated Targeting of Job Advertising: The role of the General Data Protection Regulation

Recently, companies have increasingly been using AI to attract potential candidates through targeted job advertising, whose delivery is then algorithmically optimised. By excluding certain groups from job opportunities, these practices can discriminate in access to work, in relation to grounds protected by EU equality law. This article investigates the possible role of GDPR (Reg. n. 2016/679) in litigating discrimination in targeted and optimised job advertising. It firstly analyses whether and how the data access right under Art. 15(1)(h) can be exercised to gather the prima facie discrimination evidence necessary to bring a discrimination claim against the employer. It then deepens the potential use of Art. 80(2) to address the challenges relating to litigating these discriminatory practices, particularly the victims’ lack of awareness and their difficulty in coordinating.

Beauty pays, but not under all circumstances: Evidence on gendered hiring discrimination from a novel experimental treatment using deepfakes

Using deepfaked job application videos as a novel experimental treatment, this study analyses the effects of physical attractiveness for men and women on their hypothetical hiring chances. Based on status construction theory, we argue that whether gendered expectations through physical attractiveness translate into better hiring chances depends on the social context. To test this theoretical claim, we conducted a 2×2×2 factorial survey experiment among respondents with personnel responsibilities (N = 493). Using deep-learning techniques, we swap the faces of fictitious male and female candidates in application videos, thus varying gender and physical attractiveness while holding everything else constant. Additionally, we manipulate the occupational context with job advertisements for a male-typed and a female-typed job. Results show that attractive applicants score higher in competence ratings and are more likely to be invited for a job interview than less attractive candidates. However, only men consistently profit from their looks, while women benefit from a beauty premium in the female-typed, but not in the male-typed job. These results strongly support the idea that physical attractiveness works as a status characteristic, triggers gendered expectations, and leads to beauty-based treatment differences. This study suggests that the use of deepfakes is a promising avenue to move inequality research forward.

What Are The Qualifications For An Exercise Professional? A Content-Analysis Of Canadian Job Advertisements

What Are The Qualifications For An Exercise Professional? A Content-Analysis Of Canadian Job Advertisements

Apskaitos specialisto kompetencijų formavimas: keliami reikalavimai ir iššūkiai

Accounting specialists play an essential role in ensuring the company's financial stability and legality, so their level of competence directly affects the efficiency and success of the company's operations. In this labor market, accounting specialists must have mastered not only technical knowledge, such as preparation of financial reports and tax calculations, but also be familiar with the latest technologies and information systems. Analytical skills, problem-solving ability, and adherence to ethical behavior are also emphasized. The challenges in the labor market are the continuous improvement of technology, so accounting specialists must adapt to automation processes and be able to effectively use new digital tools. In addition, as the legal environment changes and regulations become more stringent, it is necessary to constantly update knowledge. In this context, continuous training and professional development become especially important in order to ensure a high level of professionalism. This work analyzes how accounting specialists can shape their competence in a way that meets the needs of today's market, what requirements are placed on them, and what challenges they face in order to remain competitive and professional in their field. The purpose of the study was to determine the most important competencies and requirements, problems, and challenges of accounting specialists. Research methods: the analysis of scientific literature used for the work, the method of analyzing job advertisements, expert interviews, information comparison, systematization, and summarization.

The graduate employability cycle of learning: Preparation, practice, and presentation

Change in the workplace is inevitable, intensified by the rapid development of global markets and demand for highly skilled and adaptable employees. One response to this demand is for higher degree students to immerse in workplace experiences aligned to their course discipline to build their employability. In consideration of higher education and industry practices in Australia, our paper examined the phases of student learning and development before, during and after workplace experiences that contribute to graduate employability and signalling capability. Three progressive methodological approaches were adopted: a job advertisement audit, semi-structured interviews, and an online employability survey. Deductive and inductive coding was applied to organise themes from interview transcripts and survey data, using non-parametric statistics to analyse data. Findings revealed a three-phased Graduate Employability Cycle of Learning. The Pre-Condition Phase 1 encourages student exploration of the industry discipline and self against defined awareness factors to prepare for practical experiences. Phase 2 comprises the Experiential Learning Cycle (Kolb, 1984) to validate the process of learning through practical experience. The Observed Signals Phase 3 identifies the experiential learning gained from practical experience and subsequent conversion into transferable graduate employability signals. Combined, the three-phased cycle guides theoretical knowledge and practical application of the employability signals, to assist job recruitment and selection, where employers can observe and recognise employable graduates who demonstrate their point of difference in the job market.

Employers most desirable attributes in early-career physiotherapists: a content analysis of job advertisements

BackgroundEnsuring a sufficient, appropriately qualified health workforce is of global concern. Understanding the attributes that employers seek is critical in recruitment, retention, and educational design. In physiotherapy, there is a dearth of evidence on desirable attributes that employers seek from early-career physiotherapists. This study directly addresses this gap. The aims of this study were to identify the characteristics of the jobs advertised for early-career physiotherapists in Australia; determine which attributes were most desired when employing an early-career physiotherapist; and identify if there were differences in the attributes required based upon workplace location.MethodsNew graduate and early-career physiotherapy job advertisements were collected for six months from 1st October 2020 until 31st March 2021 from SEEK.com.au, a large online employment marketplace that operates across ten countries in the Asia Pacific and Latin America. Job advertisements needed to specify new graduate or early-career physiotherapist eligibility and be located within Australia. Data extraction were completed using QuestionPro®. The Modified Monash Model was used to classify rurality of job location. Job advertisements were analysed descriptively and using content analysis to identify attributes.ResultsThe search yielded 578 job advertisements with the greatest number collected in October 2020 (25.3%). Of the advertisements, 428 (74.0%) were in metropolitan locations (Modified Monash 1), 47 (8.1%) were in regional (Modified Monash 2), 99 (17.1%) were in rural locations (Modified Monash 3–5), and 4 (0.8%) were in remote locations (Modified Monash 6–7). Most roles were in private practice (63.3%) or aged care (21.7%). The top five attributes requested by employers were client focus, communication and interpersonal skills, team player, willingness to learn, and being able to build rapport, relationships, and networks. Academic results, resilience, and empathy were the least requested attributes. Differences in requested employability attributes increased with rurality.ConclusionsThis study addresses the current knowledge about attributes sought by employers for early-career physiotherapists. The most prevalent attributes requested were client focus and communication and interpersonal skills. This exploration of attributes can help to better prepare graduates for their first roles, align expectations, and increase understanding of priorities for entry level university programs, as well as identify priorities for support during transition to practice. Desired attributes should be clearly defined by employers in recruitment and retention processes.

Do women only apply when they are 100% qualified, whereas men already apply when they are 60% qualified?

AbstractWe tested the popular claim that women only apply for jobs when they are 100% qualified, whereas men apply already with as little as a 60% qualification fit. In Study 1, we presented a job advertisement and a CV with different levels of qualification fit. Participants were asked to imagine that the presented CV was their own and to indicate whether they would apply for the advertised job. No gender difference emerged in participants’ application intentions, neither at 60% nor at 100% qualification fit. To enhance personal involvement, in Studies 2–4 we presented a job advertisement and asked participants to indicate whether they themselves would apply for the advertised job. Afterwards, participants indicated for every qualification criterion listed in the job advertisement whether they fulfilled it or not. We found a significant, but not robust gender difference in the predicted direction in the relationship between application intention and qualification fit. In addition, when asking how much women and men wanted to be prepared in application situations, women robustly indicated a higher desire for preparedness than men. Overall, our results indicate that for women psychological hurdles (i.e., desire for preparedness, fears and other gender‐relevant indicators assessed) are higher in application situations than for men. However, these do not seem to translate reliably into differential application intentions in the experimental paradigms used in our studies. We discuss the theoretical and practical implications of our findings.

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.

Enhancing taxonomy-based extraction: Leveraging information from online community platforms for digital skills demand identification in job ads

The rapid technological changes have revolutionised how we function, including how we search for work and what skills we need to be equipped with to perform the tasks at the workplace. As employers more often recruit using online job advertisements, their content becomes a natural source of information for analytical purposes on the skills demanded in the labour market, especially for analysing emerging skills like digital. There are still some challenges with the extraction of information from online content. However, the extraction improvements go hand in hand with new technological developments like natural language processing techniques. This article presents the experimental method of updating the classification of digital skills to keep it up to date for information extraction applied to online job advertisements. The evaluation proved this method successfully identified terms related to programming skills but failed to identify terms associated with artificial intelligence sufficiently. The latter is related to the fact that the AI field is among the fastest developing areas of technology advancement, and new terms (e.g. Chatgpt) always appear.

The architecture of the system of intelligent analysis of competencies for updating university educational programs

The problem of updating educational programs and educational content is closely related to the need to adapt them to the changing conditions of regional labor markets. The solution to the problem is achieved through the collection and analysis of data on the competence requirements of employers for the qualifications of specialists (the data itself can be extracted from job advertisements on open resources on the Internet). The article presents a method of using search robots and text data processing modules to obtain formalized descriptions of competence requirements and compare them by degree of similarity with competence descriptions from educational programs. For a comparative analysis of competency requirements, a clustering method was developed using fuzzy logic and a neural network. The architecture of the collection and intelligent analysis system includes search crawlers, a module for parsing text data with cleaning from information noise, a data consolidation module, a keyword dictionary generation module, a module for synthesizing competency vectors, a clustering module, a distributed registry of formalized descriptions of competencies, etc. The results of the comparative analysis are crucial for assessing the compliance of competencies of specialists trained in regional universities with the requirements of employers in the regions. The assessment allows to develop recommendations for updating educational programs and educational content of an educational institution, as well as to carry out adaptive adjustment of information and educational environment components of higher educational institutions.

Effects of gender sensitive language in job listings: A study on real-life user interaction.

The possible impact of gender-sensitive language on readers is among the most controversially debated issues in linguistics and beyond. Previous studies have suggested that there is an effect of gender-sensitive language on mental representations, based on data gathered in laboratory settings with small groups of participants. We add a new perspective by examining correlations of authentic language use with authentic user interaction on a recruitment website. Drawing upon a large dataset provided by the recruitment platform StepStone, we evaluate whether job advertisements using certain kinds of gender-sensitive language in their titles correlate with higher proportions of views by female users. Our results indicate that there are differing effects depending on the type of gender-sensitive language that is used. Overall, the strongest correlation can be found with terms that include the feminine suffix -in.