Online Job Search Research Articles

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.

Використання великих даних для інформаційного забезпечення ринку праці

The challenges of collecting current labor market data amidst global changes and geopolitical fluctuations increasingly necessitate new approaches and alternative methods of data collection and analysis. This highlights the relevance of research aimed at developing and adapting labor market information provision methods to contemporary challenges. A promising approach in this context is the use of Big Data for labor market assessment, which involves collecting information from sources such as online job search and vacancy portals. This method allows for a deeper analysis of market trends and provides a more accurate and timely assessment of labor market needs and opportunities. The aim of this article is to discuss approaches to developing labor market information systems using Big Data, particularly online data from job vacancy websites. It examines the use of Big Data in labor market analysis based on a database containing over four million job vacancies posted on Ukrainian job search portals over the last five years, provided by the European Training Foundation (ETF). The effectiveness of these approaches in facilitating job search for all interested parties is evaluated, particularly through providing insights into the dynamics of supply and demand in the labor market based on data from these portals. The opportunities and limitations of using Big Data in this context are analyzed, including their impact on employment policy development and labor market planning. The potential benefits of Big Data in providing deeper and more accurate market condition analyses are outlined, along with technical aspects and challenges associated with their processing and interpretation. The article examines methodological approaches to data collection and analytical processing in the context of accelerated transformations, volatility, and limited access to traditional information resources. The scientific novelty of the article lies in the substantiation of the feasibility and appropriateness of using open data from online job portals for labor market information provision under current conditions. In conducting the research, methods of analysis, synthesis, and generalization were applied to identify the main contemporary issues of labor market information provision in Ukraine. The effectiveness of data collection methods based on web scraping and parsing techniques was evaluated, as well as the use of the integrated Snowflake platform to identify key trends and patterns in the labor market. The conclusions summarize the main points and substantiate directions for further research, highlighting the significance of Big Data in developing employment strategies and optimizing the labor market.

A Study on Perception of Job Seeker on Recruitment through Job Portals

This study investigates the perceptions of job seekers regarding the effectiveness and reliability of job portals as a recruitment platform. With the proliferation of online job search platforms, understanding job seekers' perspectives is crucial for both employers and job portal operators. Through a mixed-method approach involving surveys and interviews, this research delves into the preferences, concerns, and experiences of job seekers utilizing job portals. Initial findings suggest a mixed perception among job seekers, highlighting factors such as platform usability, trustworthiness of job listings, and the relevance of job matches. The study aims to provide insights for improving job portal functionalities and enhancing the overall recruitment experience for both job seekers and employers.

Large-scale online job search behaviors reveal labor market shifts amid COVID-19

Large-scale online job search behaviors reveal labor market shifts amid COVID-19

Which Occupations Do Unemployed Workers Target? Insights from Online Job Search Profiles

Which Occupations Do Unemployed Workers Target? Insights from Online Job Search Profiles

ДОСЛІДЖЕННЯ ПРОБЛЕМИ ДЕФІЦИТУ КАДРІВ НА РИНКУ ПРАЦІ НА ПРИКЛАДІ МЕБЛЕВОЇ ГАЛУЗІ

Modern russian-Ukrainian war deepened in February 2022 drastically reshaped the labour market, causing emigration and internal people displacement and as a consequence the significant workforce shortage for all industries, especially in manufacturing. Solving this problem is crucial for resolving several major challenges, including defence procurements. The relevance of this topic lies in on-date quantitative and qualitative analysis of labour market deficiencies during martial law. The aim of this article is to evaluate and analyse the labour market imbalance and workforce shortages in production industries, with a focus on the furniture industry, and to seek solutions to these problems. Observation disclosed that official statistical data is overdue and does not fully show the volume of the shortages. This article presents findings from the authors’ own research, scientific inquiries, reviews, surveys, and labour market monitoring by business communities and donor organizations. A survey of furniture industry enterprise representatives identified the distribution of personnel needs in production specialties across Ukrainian regions. In-depth interviews with industry experts provided diagnostic insights into the current state and prospects of the industry. The article also examines the trend of labour shortages across Ukraine’s labour market from the early months of the invasion to the present, using data from online job search portals. The increasing workforce shortage is illustrated through the furniture industry, with diagnostic conclusions about the industry’s state and prospects. The article develops recommendations for advancing the furniture industry and training new personnel for vacant production positions. Three options to address the labour market shortage are proposed: utilizing artificial intelligence and radical business process automation, attracting labour migrants from poorer countries, and establishing training and retraining centres. The initial results of testing the latter option for furniture companies demonstrate the approach’s potential. The article underscores the importance of addressing the personnel shortage issue for businesses and the state budget both now and in the coming years. The proposed measures can help overcome the labour market crisis, contribute to economic stabilization, and provide the necessary resources for the country’s recovery.

Exploring the Influence of Sociodemographic Backgrounds on Money Mule Recruitment Types in South Korea: An Analysis of Probabilities from Machine Learning Classifiers

ABSTRACT This study explores the influence of socio-demographic characteristics on money mule recruitment types in South Korea. Analyzing data from 543 apprehended money mules, probabilities were calculated for each group’s involvement in recruitment types. Using class membership probability estimates from six machine learning methods, the research investigates the probability relationship between socio-demographic characteristics and recruitment types. Findings indicate that unemployed individuals in their 20s with intermediate education levels are more likely to be recruited through social media, while offline recruitment is prevalent among unemployed teenagers with low education levels and men over 50s with criminal records. Highly educated unemployed individuals in their 20s and 30s show a higher probability of using online job search channels. The study provides valuable insights into the complex interplay between sociodemographic factors and money mule recruitment, offering potential implications for law enforcement agencies in developing effective crime prevention strategies. Further analysis will shed light on the underlying reasons behind these results.

Online job search discouragement: How employment platforms and digital exclusion shape the experience of low‐qualified job seekers?

AbstractHow do people experience the platform‐mediated job search process? We explore this question based on a sample of in‐depth interviews (n = 20) with low‐qualified, unemployed Spanish job seekers. Our main finding shows that the ways they use Information and Communication Technologies negatively impact their engagement in online job search activities. Based on our findings, we develop a framework of online job search discouragement revolving around crafting online profiles, applying for jobs, reviewing application statuses and integrating the tensions these activities carry for the experience and the outcome of the platform‐mediated job search.

What Influences Older Urban Poor’s Attitude towards Online Job Search? Implications for Smart Cities Development

There is an increasing number of older adults being encouraged to come back to the workforce in search of better financial security in their later years. At the same time, the job market nowadays has increasingly depended on technology to recruit new workers, especially in Smart Cities, a concept that has been recently introduced to developing countries. As a result, the use of the Internet for job searches has become increasingly important for older adults living in urban environments, especially those with limited resources. However, there has not been an in-depth paper exploring the various factors that may affect the older population’s ability to use this new development to their advantage. This study offered a closer look at the social and economic factors that influence acceptance of using the Internet to look for a job among older urban poor in Thailand. By understanding the influences that shape their attitudes and behaviors towards online job searches, it is then possible to guide the development of Smart Cities and offer better assistance to older adults who wish to use the Internet for employment opportunities. We applied a logit regression model on data collected from individuals aged pre-retirement and retirement (n = 1505) in two Thai cities with significantly different economic development levels. The results showed that gender, religion, family arrangement, and income had a significant impact on older adults’ online job search activities, especially when it came to women, people of the Islamic faith, people living with partners, and high-income individuals. Urban planners are recommended to take these aforementioned factors into account while formulating the Smart Cities development plan.

Who Considers Leaving a Job in a Pandemic?: Determinants of Online Job Search Behavior in COVID-19

Drawing from the unfolding model of voluntary turnover and behavioral immune system theory, we proposed and tested a theoretical model of how the perceived severity of a pandemic affects employees’ turnover intention as well as their virtual job-search behaviors. In an analysis of matched survey and mobile application usage data, we found that the perceived severity of COVID-19 is positively related to employees’ turnover intention, which is, in turn, positively related to the usage of mobile job-search apps. Our findings further disclosed that these relationships were weakened when employees perceived their organizations as more adaptive to COVID-19. When employees perceived their coworkers as more supportive in coping with COVID-19, however, the relationships were strengthened. Theoretical and practical implications of these findings are discussed.

Schumpeter Lecture 2022: Job Search in the 21St Century

Abstract Formal job search has undergone massive transformations in the last two decades with the move to online platforms. This makes more stages of the job search process observable, and allows researchers to intervene in this market and improve the design of the job search process and the information available in it. This paper showcases studies that illustrate the potential of analyzing online job search data and of intervening in the online job search process. It presents the current insights and some open questions and highlights conditions under which some of the recent interventions are likely to improve market outcomes overall, rather than improving only the outcomes for the treated individuals.

Modelling online job search and choices of dentists in the Australian job market: Staged sequential DCEs and FIML econometric methods

Workforce participation decisions involve multiple stages: search, screening and offer evaluation. Standard econometric practice focusses on these stages in isolation. We conceptualize the focal behaviours as separate sequential decision stages, and provide a stated preference measurement framework for online job search and choice with a behaviourally consistent modelling approach. We demonstrate this approach in an empirical application of 275 dentists who completed an online survey including two Discrete Choice Experiments: the first mimicked an online job search site in which dentists decided which jobs they would apply to and the second presented dentists with a job offer which they accepted or rejected. Modelling these tasks requires a two-stage econometric model that incorporates the likelihood of application (first stage) into the job offer choice (second stage). The model detects differences in preferences (hence behaviours) across stages, facilitating the differentiation of policy aimed at search and job choice behaviours. Job screening occurs during search and the marginal propensity to apply for a job-type differs from the offer stage. We suggest that the approach presented provides a valuable way to investigate how dentists particularly, and perhaps the health workforce more generally, respond at different stages of workforce participation decisions and discuss practical implications.

A Quantitative Study of User Perception of Credibility of Jobs Posted on Online Job Search Portals

Purpose: This study aims to study the factors which influence user perception of credibility of jobs posted on online job search portalsDesign/Methodology/Approach: A quantitative research methodology was used and 240 responses received, via a web-based survey, were analysed. These responses covered user perception across more than 10 leading online job portals.Findings: Credibility perception of jobs posted on online job search portals differs across users belonging to different categories with respect to years of work experience, job application response, and number of jobs changed. Number of responses received on their online job applications and the proportion of jobs they get via the online portals emerged as significant predictors of users’ credibility perception of the jobs posted on such portals.Practical Implications: Marketers of online job search portals must collaborate with their recruitment partners to focus on driving response rate and actual job seeking success rate for users on their portals.Originality/Value: This study bridges a key gap in current literature regarding a limited understanding of how users perceive the usefulness of online job search portals.

Do the Long-Term Unemployed Benefit from Automated Occupational Advice During Online Job Search?

Do the Long-Term Unemployed Benefit from Automated Occupational Advice During Online Job Search?

The Direct and Indirect Effects of Online Job Search Advice

The Direct and Indirect Effects of Online Job Search Advice

РИНОК ПРАЦІ ТА ЗАЙНЯТІСТЬ УКРАЇНИ В УМОВАХ ВІЙНИ

The article analyzes the state of the labor market of Ukraine, which functions in conditions of war. It was substantiated that the majority of enterprises were not ready for the worst scenario of the development of events despite the formation of a threatening situation and military escalation near the Ukrainian borders. Quite a large share of such enterprises slowed down or suspended their activities. The companies of the IT sector, as well as those that were able to organize remote work and in which the relocation is not connected with the movement of significant production capacities, received a smaller shock. It was determined that during the first month of the war, the Ukrainian economy halved, which caused changes in the labor market. According to the survey results, on average, 53% of the surveyed respondents lost their jobs due to hostilities in the country (a total of 1000 respondents were surveyed). The biggest problem is in the east, where this indicator reaches 74%. In the first weeks after the start of the war, all online job search platforms saw a significant decrease in the number of open vacancies and resumes posted on them. In Ukraine, the number of resumes has critically decreased. There have been changes in internal migration, as well as population migration abroad. According to UN data, more than 4 million Ukrainians are seeking asylum in neighboring countries. The mass movement of the population to the western regions of Ukraine has led to a sharp increase in the shortage of personnel in the vitally necessary areas of the market in the areas covered by hostilities. The shock period on the labor market did not last long, and already in the second half of March there were signs of its gradual adaptation to the conditions of the new socio-economic reality. It was found that the most in demand on the modern labor market are specialists in the fields of agriculture, transport and logistics, as well as sales (salespeople, cashiers, etc.). The demand for medical workers and pharmacists has also increased. The fact that the RussianUkrainian war will significantly change not only the domestic, but also the global labor market is indisputable. One of the industries that can become a driver of further recovery and development of the domestic economy can be the IT industry. In addition, further development of various formats of remote work should be expect. Also, the need to restore the housing stock, rebuild domestic enterprises and infrastructure facilities creates favorable conditions for the intensive development of the construction industry. Undoubtedly, professions related to the security and defense sector, medicine, psychology, energy, logistics, etc. will be in demand.

Does the Internet Reduce Gender Gaps? The Case of Jordan

This article investigates the link between digital technologies and female labour outcomes in a country with one of the lowest female labour force participation (LFP) rates. It exploits the massive roll-out of mobile broadband technology in Jordan between 2010 and 2016 to identify the effect of internet adoption on LFP, internet job search, employment and unemployment. Using panel data at the individual level and an instrumental variable strategy, the article finds that internet adoption increases female LFP and that the effect is driven by women who were not married in 2010, who also experience declines in marriage and fertility rates in response to internet adoption. An increase in online job search explains some – but not all – of the total increase in female LFP. Only women who are older and have higher levels of education experience an increase in employment in response to gaining internet access. The internet reduces the prevalence of traditional social norms among married women, but this channel does not explain the increase in female LFP.

Skilled immigrant women's career trajectories during the COVID-19 pandemic in Canada

PurposeDespite immigrant-receiving countries' need for skilled professionals to meet labour demands, research suggests that many skilled migrants undergo deskilling, downward career mobility, underemployment, unemployment and talent waste, finding themselves in low-skilled occupations that are not commensurate to their education and experience. Skilled immigrant women face additional gendered disadvantages, including a disproportionate domestic burden, interrupted careers and gender segmentation in occupations and organizations. This study explores how the ongoing COVID-19 pandemic impacted skilled newcomer women's labour market outcomes and work experiences.Design/methodology/approachThe authors draw on 50 in-depth questionnaires with skilled women to elaborate on their work experiences during the ongoing COVID-19 pandemic.FindingsThe pandemic pushed skilled immigrant women towards unemployment, lower-skilled or less stable employment. Most study participants had their career trajectory delayed, interrupted or reversed due to layoffs, decreased job opportunities and increased domestic burden. The pandemic's gendered nature and the reliance on work-from-home arrangements and online job search heightened immigrant women's challenges due to limited social support and increased family responsibilities.Originality/valueThis paper adds to the conversation of increased integration challenges under pandemic conditions by contextualizing the pre-pandemic literature on immigrant work integration to the pandemic environment. Also, this paper contributes a better understanding of the gender dynamics informing the COVID-19 socio-economic climate.

Unemployment Insurance and Job Search Behavior

AbstractHow does unemployment insurance (UI) affect unemployed workers’ search behavior? Search models predict that until benefit exhaustion, UI depresses job search effort and increases reservation wages. Over an unemployment spell, search effort should increase up to benefit exhaustion and stay high thereafter. Meanwhile, reservation wages should decrease up to benefit exhaustion and stay low thereafter. To test these predictions, we link administrative registers to data on job search behavior from a major online job search platform in France. We follow over 400,000 workers, as long as they remain unemployed. We analyze the changes in search behavior around benefits exhaustion and take two steps to isolate the individual response to unemployment benefits. First, our longitudinal data allows us to correct for changes in sample composition over the spell. Second, we exploit data on workers eligible for 12–24 months of UI as well as workers ineligible for UI, to control for behavior changes over the unemployment spell that are independent of UI. Our results confirm the predictions of search models. We find that search effort (the number of job applications) increases by at least 50% during the year preceding benefits exhaustion and remains high thereafter. The target monthly wage decreases by at least 2.4% during the year preceding benefits exhaustion and remains low thereafter. In addition, we provide evidence for duration dependence: workers decrease the wage they target by 1.5% over each year of unemployment, irrespective of their UI status.

Search design and online job search – new avenues for applied and experimental research

Online job search opens new avenues to experimentally alter the search process, and to engage in “search design”. It also offers an unprecedented channel to collect data on how job seekers search for jobs and how firms search for employees. This paper discusses the research possibilities that this generates and reviews some of the recent developments in this area.