Academic literature on the topic 'Job Matching'

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Journal articles on the topic "Job Matching"

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Holzer, Harry J. "Job-Matching." Brookings Review 14, no. 1 (1996): 2. http://dx.doi.org/10.2307/20080609.

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Hall, Robert E., and Sam Schulhofer-Wohl. "Measuring Job-Finding Rates and Matching Efficiency with Heterogeneous Job-Seekers." American Economic Journal: Macroeconomics 10, no. 1 (January 1, 2018): 1–32. http://dx.doi.org/10.1257/mac.20170061.

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Matching efficiency is the productivity of the process for matching job-seekers to available jobs. Job-finding is the output; vacant jobs and active job-seekers are the inputs.We develop a framework for measuring matching productivity when the population of job-seekers is heterogeneous. We find that overall matching efficiency declined smoothly over the period from 2001 through 2013. Measures of matching efficiency that neglect heterogeneity among the unemployed and also neglect job-seekers other than the unemployed suggest a large 28 percent decline in efficiency between 2007 and 2009. Most of this apparent decline results from changes in the composition of job-seekers. (JEL E24, J22, J23, J24, J41, J63)
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Haeringer, Guillaume, and Myrna Wooders. "Decentralized job matching." International Journal of Game Theory 40, no. 1 (January 13, 2010): 1–28. http://dx.doi.org/10.1007/s00182-009-0218-x.

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Fujita, Shigeru, and Garey Ramey. "Job matching and propagation." Journal of Economic Dynamics and Control 31, no. 11 (November 2007): 3671–98. http://dx.doi.org/10.1016/j.jedc.2006.12.008.

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Kojima, Fuhito, Ning Sun, and Ning Neil Yu. "Job Matching under Constraints." American Economic Review 110, no. 9 (September 1, 2020): 2935–47. http://dx.doi.org/10.1257/aer.20190780.

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Studying job matching in a Kelso-Crawford framework, we consider arbitrary constraints imposed on sets of doctors that a hospital can hire. We characterize all constraints that preserve the substitutes condition (for all revenue functions that satisfy the substitutes condition), a critical condition on hospitals’ revenue functions for well-behaved competitive equilibria. A constraint preserves the substitutes condition if and only if it is a “generalized interval constraint,” which specifies the minimum and maximum numbers of hired doctors, forces some hires, and forbids others. Additionally, “generalized polyhedral constraints” are precisely those that preserve the substitutes condition for all “group separable” revenue functions. (JEL C78, D47, I11, J23, J41, J44)
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Barron, John M., Dan A. Black, and Mark A. Loewenstein. "Job Matching and On-the-Job Training." Journal of Labor Economics 7, no. 1 (January 1989): 1–19. http://dx.doi.org/10.1086/298196.

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Chala, Sisay Adugna, Fazel Ansari, Madjid Fathi, and Kea Tijdens. "Semantic matching of job seeker to vacancy: a bidirectional approach." International Journal of Manpower 39, no. 8 (November 5, 2018): 1047–63. http://dx.doi.org/10.1108/ijm-10-2018-0331.

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Purpose The purpose of this paper is to propose a framework of an automatic bidirectional matching system that measures the degree of semantic similarity of job-seeker qualifications and skills, against the vacancy provided by employers or job-agents. Design/methodology/approach The paper presents a framework of bidirectional jobseeker-to-vacancy matching system. Using occupational data from various sources such as the WageIndicator web survey, International Standard Classification of Occupations, European Skills, Competences, Qualifications, and Occupations as well as vacancy data from various open access internet sources and job seekers information from social networking sites, the authors apply machine learning techniques for bidirectional matching of job vacancies and occupational standards to enhance the contents of job vacancies and job seekers profiles. The authors also apply bidirectional matching of job seeker profiles and vacancies, i.e., semantic matching vacancies to job seekers and vice versa in the individual level. Moreover, data from occupational standards and social networks were utilized to enhance the relevance (i.e. degree of similarity) of job vacancies and job seekers, respectively. Findings The paper provides empirical insights of increase in job vacancy advertisements on the selected jobs – Internet of Things – with respect to other job vacancies, and identifies the evolution of job profiles and its effect on job vacancies announcements in the era of Industry 4.0. In addition, the paper shows the gap between job seeker interests and available jobs in the selected job area. Research limitations/implications Due to limited data about jobseekers, the research results may not guarantee high quality of recommendation and maturity of matching results. Therefore, further research is required to test if the proposed system works for other domains as well as more diverse data sets. Originality/value The paper demonstrates how online jobseeker-to-vacancy matching can be improved by use of semantic technology and the integration of occupational standards, web survey data, and social networking data into user profile collection and matching.
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Brown, Alessio, Christian Merkl, and Dennis Snower. "AN INCENTIVE THEORY OF MATCHING." Macroeconomic Dynamics 19, no. 3 (October 23, 2013): 643–68. http://dx.doi.org/10.1017/s1365100513000527.

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This paper presents a theory of the labor market matching process in terms of incentive-based, two-sided search among heterogeneous agents. The matching process is decomposed into its two component stages: the contact stage, in which job searchers make contact with employers, and the selection stage, in which they decide whether to match. We construct a theoretical model explaining two-sided selection through microeconomic incentives. Firms face adjustment costs in responding to heterogeneous variations in the characteristics of workers and jobs. Matches and separations are described through firms' job offer and firing decisions and workers' job acceptance and quit decisions. Our calibrated model for the United States can account for important empirical regularities, such as the large volatilities of labor market variables, that the conventional matching model cannot.
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Zenou, Yves. "Endogenous job destruction and job matching in cities." Journal of Urban Economics 65, no. 3 (May 2009): 323–36. http://dx.doi.org/10.1016/j.jue.2009.02.002.

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Song, Kyungho, Hyun Kim, Jisoo Cha, and Taedong Lee. "Matching and Mismatching of Green Jobs: A Big Data Analysis of Job Recruiting and Searching." Sustainability 13, no. 7 (April 6, 2021): 4074. http://dx.doi.org/10.3390/su13074074.

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Creating green jobs tackles two crises: the economic downturn and environmental degradation. Responding to the economic downturn, some governments have declared a “green new deal” to remedy unemployment and the economic crisis. Job creation has been suggested as a driving force for sustainable economic development and climate change action. However, the question of how many and what types of green jobs are required has not been systematically examined. Are green job openings and searches matching each other in terms of timing, sectors, regions, and salary? This study aims to explore the degree of matching between green job supply and demand using a big data analysis (BDA) of online job market recruiting services in South Korea from 2009 to 2020. The BDA of the Ecojob website reveals that green jobs are concentrated in Seoul and Gyeounggi-do metropolitan areas. The number of water- and air-quality-related jobs is high within these sectors. Job searches in the water quality sector outnumbered job openings. The findings imply that green job creation policy should reflect timing, regional, and sectoral demand and supply data. Creating and matching green jobs is expected to reduce environmental harm, enhance environmental quality, and reduce unemployment.
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Dissertations / Theses on the topic "Job Matching"

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Corrêa, Márcio. "Essays on job-matching theory." Doctoral thesis, Instituto Superior de Economia e Gestão, 2007. http://hdl.handle.net/10400.5/8763.

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Doutoramento em Economia
O objectivo principal da Job Matching Theiry é o de explicar os efeitos dos custos de mobilidade sobre o equilíbrio no mercado de trabalho. A ideia por trás deste tipo de modelo é a de que antes do início da actividade produtiva, tanto as firmas como os trabalhadores têm que despender tempo e recursos de forma a encontrar seu parceiro de produção.Nesta dissertação, nosso objectivo é o desenvolver t`rês artigos, todos desenvolvidos no mesmo ambiente, com o intuito de responder três questões distintas. No primeiro capítulo - Job Matching, Technological Progress. and Worker-Provided on-the job Training - nosso objectivo é o de estudar os efeitos do investimento em treinamento pagos pelo trabalhador empregado sobre o mercado de trabalho caracterizado por dois tipos distintos de progresso tecnólógico: destruição criativa e renovação. No segundo capítulo - Technological Progress and Average Job Matching Quality - nosso objectivo é o de estudar, também em um cenário caracterizado por search frictions, os efeitos da taxa de progresso tecnológico: destruição criativa e renovação. No segundo capítulo - Tecnhonological Progress and Average Job Matching Quality - nooso objectivo é o de estudar, tanbém em um cenário caracterizado por search frictions, os efeitos da taxa de progresso tecnológico sobre a qualidade média das parcerias proodutivas. No terceiro e último capítulo - Job Matching, Unexpected Obligations and Retirement Decisions - nosso objectivo é o de investigar os efeitos de variações não antecipadas no nível das obrigações dos trabalhadores sobre a sua regra óptima de entrada na reforma.
The main objective of the Job Matching Theory is to explain the effects of mobility costs over the labor market equilibrium. The basic idea behind these models is that before the production begins, firms and workers have to spend resources in order to find their production partner. In this dissertation, our main objective is to develop three essays, all carried out in the same environment - that of Job Matching Theory - with the aim of answering three distinct questions. In the first chapter - Job Matching Technological Progress, and Worker-Provided On-the-job Training - the objective is to study the effects of the worker-provided on-the-job training investments on a labor market characterized by technological progress of the creative destruction type and the renovative type. In the second chapter of the dissertation - Technological Progress and Average Job Matching Quality - our objective is to study, also a labor market characterized by search frictions, the effects of technological progress on the average quality of the job matches. In the third and final chapter of the thesis - Job Matching, Unexpected Obligations and Retirement Decisions - our objective is to investigate the effects of unexpected changes in the worker's obligations on the decision to retire.
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Persch, Andrew Charles. "The Model of Systematic Job Matching." The Ohio State University, 2014. http://rave.ohiolink.edu/etdc/view?acc_num=osu1405612722.

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Rama, Apoorva. "Essays on Higher Education and Job Matching." The Ohio State University, 2019. http://rave.ohiolink.edu/etdc/view?acc_num=osu1574248733672506.

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Hall, Julie. "Correspondence of Job-Preference and Job-Matching Assessment with Job Performance and Satisfaction among Youth with Developmental Disabilities." DigitalCommons@USU, 2010. https://digitalcommons.usu.edu/etd/771.

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This study investigated the effects of job preference and job match on job performance among four 19-to 20-year-old young adults with developmental disabilities placed in community-based job conditions. Prior studies have examined the effects of job preference on community-based job performance without the job-matching component. The researcher identified high-preference, high-match and low-preference, low-match job conditions and tasks using a video web-based assessment program. Each participant was subsequently placed in a randomized sequence of 30-min sessions on one high-preference, high-match job condition performing a preferred task and one low-preference, low-match job performing a non preferred task. Job coaches instructed and prompted participants throughout the study, teaching job tasks based on criteria specified by the employer or industry standard. Data collectors recorded data on (a) on-task performance, (b) productivity, (c) quality and quantity of work, (d) job satisfaction as measured through participant judgment of preferred and well-matched jobs, and (e) an independent observer's judgment of well-matched jobs. The researcher found higher productivity, accuracy, and job satisfaction across all participants on the high-preference, high-match jobs as well as higher quantity of work completed for three of the four participants. On- task levels remained high in both job conditions for three of the four participants. Results are discussed in terms of variables in and limitations to this study as well as suggestions for future research.
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Thun, Anton. "Matching Job Applicants to Free Text Job Ads Using Semantic Networks and Natural Language Inference." Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-281250.

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Automated e-recruitment systems have been a focus for research in the past decade due to the amount of work required to screen suitable applicants to a job post, whose resumés and job ads are commonly submitted as free text. While recruitment organizations have data concerning applicant resumés and job ad descriptions, resumés are often confidential, limiting the use of direct deep learning methods. This presents an issue where traditional data-agnostic methods have greater potential to achieve good results in determining applicant suitability for a given job post. However, with the advent of transfer learning methods, it is possible to train language models independently of the task at hand, and thus independently of the available data. In this report, a language model fine-tuned on Natural Language Inference (NLI) via cross-lingual transfer learning is used for the job matching task. This is compared to a semantic method using Swedish taxonomies to construct networks with hierarchical and synonymy relations. As NLI may apply to arbitrary sentence pairs, the use of text segmentation to enhance the methods’ performance is also examined. The results show that the NLI approach is significantly better than a random suitability classifier, but is outperformed by the semantic method that achieved 34% better performance on the used dataset. The use of text segmentation had negligible effect on overall performance, but was shown to improve ranking of the top-most suitable applicants in relation to manual expert relevance scores.
Automatiserade e-rekryteringssystem har varit ett forskningsfokus det senaste årtioendet på grund av hur mycket arbete som krävs för att sålla passande jobbsökande till en jobbpost, vars CV och jobbannons vanligen skickas som fritext. Medan rekryteringsorganisationer har data omfattande sökandes CV:n och jobbannonsbeskrivningar, är CV:n oftast konfidentiella, vilket begränsar direktanvändande av djupinlärningsmetoder. Detta leder till ett problem där traditionella data-agnostiska metoder har större potential att uppnå bra resultat i att bestämma hur lämplig en jobbsökande är för en given jobbpost. Dock är det möjligt att träna språkmodeller oberoende av det faktiska problemet– och därav oberoende av tillgänglig data – med tillkomsten av inlärningsöverföring. I den här rapporten används en språkmodell som finjusterats på naturlig språkinferens (NSI) via tvärspråklig inlärningsöverföring för jobbmatchningsproblemet. Den jämförs mot en semantisk metod som använder svenska taxonomier för att konstruera nätverk med hierarki- och synonymrelationer. Då NSI kan appliceras på godtyckliga meningspar, undersöks även textsegmentering för att förbättra metodernas prestanda. Resultaten visar att NSI-metoden är signifikant bättre än en slumpmässig lämplighetsklassificerare, men överträffas av den semantiska metoden som hade 34% bättre prestanda på datasetet som användes. Användandet av textsegmentering hade försumbar effekt för den samlade prestandan, men visades uppnå bättre rankning av de mest lämpande jobbsökande relativt expertbedömning av deras relevans.
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Chala, Sisay Adugna [Verfasser]. "Bidirectional job matching through unsupervised feature learning / Sisay Adugna Chala." Siegen : Universitätsbibliothek der Universität Siegen, 2018. http://d-nb.info/1154308588/34.

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Gonard, François. "Cold-start recommendation : from Algorithm Portfolios to Job Applicant Matching." Thesis, Université Paris-Saclay (ComUE), 2018. http://www.theses.fr/2018SACLS121/document.

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La quantité d'informations, de produits et de relations potentielles dans les réseaux sociaux a rendu indispensable la mise à disposition de recommandations personnalisées. L'activité d'un utilisateur est enregistrée et utilisée par des systèmes de recommandation pour apprendre ses centres d'intérêt. Les recommandations sont également utiles lorsqu'estimer la pertinence d'un objet est complexe et repose sur l'expérience. L'apprentissage automatique offre d'excellents moyens de simuler l'expérience par l'emploi de grandes quantités de données.Cette thèse examine le démarrage à froid en recommandation, situation dans laquelle soit un tout nouvel utilisateur désire des recommandations, soit un tout nouvel objet est proposé à la recommandation. En l'absence de données d'intéraction, les recommandations reposent sur des descriptions externes. Deux problèmes de recommandation de ce type sont étudiés ici, pour lesquels des systèmes de recommandation spécialisés pour le démarrage à froid sont présentés.En optimisation, il est possible d'aborder le choix d'algorithme dans un portfolio d'algorithmes comme un problème de recommandation. Notre première contribution concerne un système à deux composants, un sélecteur et un ordonnanceur d'algorithmes, qui vise à réduire le coût de l'optimisation d'une nouvelle instance d'optimisation tout en limitant le risque d'un échec de l'optimisation. Les deux composants sont entrainés sur les données du passé afin de simuler l'expérience, et sont alternativement optimisés afin de les faire coopérer. Ce système a remporté l'Open Algorithm Selection Challenge 2017.L'appariement automatique de chercheurs d'emploi et d'offres est un problème de recommandation très suivi par les plateformes de recrutement en ligne. Une seconde contribution concerne le développement de techniques spécifiques pour la modélisation du langage naturel et leur combinaison avec des techniques de recommandation classiques afin de tirer profit à la fois des intéractions passées des utilisateurs et des descriptions textuelles des annonces. Le problème d'appariement d'offres et de chercheurs d'emploi est étudié à travers le prisme du langage naturel et de la recommandation sur deux jeux de données tirés de contextes réels. Une discussion sur la pertinence des différents systèmes de recommandations pour des applications similaires est proposée
The need for personalized recommendations is motivated by the overabundance of online information, products, social connections. This typically tackled by recommender systems (RS) that learn users interests from past recorded activities. Another context where recommendation is desirable is when estimating the relevance of an item requires complex reasoning based on experience. Machine learning techniques are good candidates to simulate experience with large amounts of data.The present thesis focuses on the cold-start context in recommendation, i.e. the situation where either a new user desires recommendations or a brand-new item is to be recommended. Since no past interaction is available, RSs have to base their reasoning on side descriptions to form recommendations. Two of such recommendation problems are investigated in this work. Recommender systems designed for the cold-start context are designed.The problem of choosing an optimization algorithm in a portfolio can be cast as a recommendation problem. We propose a two components system combining a per-instance algorithm selector and a sequential scheduler to reduce the optimization cost of a brand-new problem instance and mitigate the risk of optimization failure. Both components are trained with past data to simulate experience, and alternatively optimized to enforce their cooperation. The final system won the Open Algorithm Challenge 2017.Automatic job-applicant matching (JAM) has recently received considerable attention in the recommendation community for applications in online recruitment platforms. We develop specific natural language (NL) modeling techniques and combine them with standard recommendation procedures to leverage past user interactions and the textual descriptions of job positions. The NL and recommendation aspects of the JAM problem are studied on two real-world datasets. The appropriateness of various RSs on applications similar to the JAM problem are discussed
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Elm, Emilia. "Comparison of methods applied to job matching based on soft skills." Thesis, Uppsala universitet, Institutionen för informationsteknologi, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:uu:diva-420374.

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The expression ''Hire for attitude, train for skills'' is used as a motive to create a matching program where companies and job seekers' soft qualities are measured and compared against each other. Are there better or worse methods for this purpose, and how do they compare with each other? By associating soft qualities with companies and job seekers, it is possible to generate a value for how well they match. Therefore, data has been collected on several companies and job seekers. Their associated qualities are then translated into numerical vectors that can be used for matching purposes, where vectors closer together are more equal than vectors with greater distances. When it comes to analyzing and comparing the qualities, several methods have been used and compared with a subsequent discussion about their suitability. One consequence of the lack of a proper standard for presenting the qualities of companies and job seekers is that the data is messy and varied. An expected conclusion from the result is that the most flexible method is the one that generates the most accurate results.
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Wesley, S. Scott. "Background data subgroups and career outcomes : some developmental influences on person job-matching." Diss., Georgia Institute of Technology, 1989. http://hdl.handle.net/1853/31065.

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Petrongolo, Barbara. "Job matching and unemployment : applications to the UK labour market and international comparisons." Thesis, London School of Economics and Political Science (University of London), 1998. http://etheses.lse.ac.uk/1501/.

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This thesis studies different aspects of job matching, mismatch, and their relationship with aggregate unemployment. The first part addresses the question of the structural rise in the unemployment rate in OECD countries by looking at the link between sectoral shocks and aggregate performance in an economy with heterogeneous labour. The type of sectoral shock considered in chapter 2 is the introduction of skill-biased technologies, that increase the relative demand for skilled labour at the expenses of the less-skilled. Unless the supply of skills adjusts accordingly to the increased demand, and/or relative wages are perfectly flexible, this shock has permanent effects on the aggregate unemployment rate, as shown in a non-competitive labour market model with skilled and unskilled workers. The calibration of this model predicts that a relevant proportion of the recent rise in British unemployment can be attributed to an unbalanced evolution in the demand and the supply of skills, while in continental Europe skill imbalances do not seem responsible for serious labour market problems. Finally, the impact of skill mismatch on US unemployment was limited in magnitude and almost completely offset by counteracting forces. The second part of the work uses a job-search approach to investigate the technical characteristics of the matching process between vacancies and unemployed job-seekers. Chapter 3 reviews the empirical search literature that has estimated hiring functions, concluding that recent work has successfully established the existence of a labour market matching function, in which both vacancies and unemployed workers contribute significantly to job formation. Chapter 4 considers a plausible alternative to a random meeting technology between employers and job-seekers, based on the existence of cheap information channels that save all traders the effort of locating matching partners. When combined with a proper handling of timing in the matching technology, this set-up provides novel results on the recent performance of the British labour market. In particular, it seems that the claimed deterioration of the search effectiveness of the unemployed cannot be explained by a lack of search effort per se, but by stronger competition that the registered unemployed face by other labour market segments. Chapter 5 provides an analysis of the matching process at the micro level, using individual duration data obtained from a British sample of unemployment entrants. The determinants of re-employment probabilities are here related to a search model in which transitions into employment depend on the probability of receiving a job offer and that of accepting a job offer. The analysis shows that the hypothesis of constant returns to scale in the matching technology, embodied in most bilateral search models, is not rejected by the data. Individual re-employment probabilities respond in fact to local labour market tightness, and are unaffected by its size.
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Books on the topic "Job Matching"

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Attfield, C. L. F. A model of job matching and job competition. Bristol: University of Bristol, Department of Economics, 1992.

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A, Pissarides Christopher, Tatsiramos Konstantinos, and Zimmermann Klaus F, eds. Job matching, wage dispersion, and unemployment. Oxford: Oxford University Press, 2011.

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Botterbusch, Karl F. A comparison of computerized job matching systems. Menomonie, Wis: Materials Development Center, Stout Vocational Rehabilitation Institute, School of Education and Human Services, University of Wisconsin-Stout, 1986.

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Blanchard, Olivier. The aggregate matching function. Cambridge, MA: National Bureau of Economic Research, 1989.

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Hanushek, Eric A. Constrained job matching: Does teacher job search harm disadvantaged urban schools? Cambridge, MA: National Bureau of Economic Research, 2010.

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Haan, Wouter J. Den. Shocks and institutions in a job matching model. Cambridge, MA: National Bureau of Economic Research, 2001.

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Felli, Leonardo. Job matching, learning and the distribution of surplus. London: Suntory-Toyota International Centre for Economics and Related Disciplines, 1994.

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Fernandez, Richard L. Setting enlistment standards and matching recruits to jobs using job performance criteria. Santa Monica, CA: Rand, 1985.

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Lancaster, Tony. Residuals, tests and plots with a job matching illustration. Hull: University of Hull, 1985.

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Linden, Bruno Van der. Equilibrium evaluation of active labor market programmes enhancing matching effectiveness. Bonn, Germany: IZA, 2005.

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Book chapters on the topic "Job Matching"

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Lancaster, Tony, Guido Imbens, and Peter Dolton. "Job separations and job matching." In International Studies in Economics and Econometrics, 31–43. Dordrecht: Springer Netherlands, 1987. http://dx.doi.org/10.1007/978-94-009-3591-4_3.

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Berglund, Tomas, and Ingrid Esser. "Matching Work Values With Job Qualities for Job Satisfaction." In Work Orientations, 219–38. New York, NY : Routledge, 2020. | Series: Routledge studies in management, organizations and society: Routledge, 2019. http://dx.doi.org/10.4324/9781351121149-10.

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McHenry, Jeffrey J. "Pinpointing: Matching Job Assignments to Employees." In Experience-Driven Leader Development, 69–75. San Francisco: John Wiley & Sons, Inc., 2014. http://dx.doi.org/10.1002/9781118918838.ch11.

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Shai, Ohad, Edi Shmueli, and Dror G. Feitelson. "Heuristics for Resource Matching in Intel’s Compute Farm." In Job Scheduling Strategies for Parallel Processing, 116–35. Berlin, Heidelberg: Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-662-43779-7_7.

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Xu, Peng, and Denilson Barbosa. "Matching Résumés to Job Descriptions with Stacked Models." In Advances in Artificial Intelligence, 304–9. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-89656-4_31.

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Ichiishi, Tatsuro, and Semih Koray. "Job matching: a multi-principal, multi-agent model." In Advances in Mathematical Economics, 41–66. Tokyo: Springer Japan, 2000. http://dx.doi.org/10.1007/978-4-431-67909-7_3.

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Heggo, Islam A., and Nashwa Abdelbaki. "Behaviorally-Based Textual Similarity Engine for Matching Job-Seekers with Jobs." In The International Conference on Advanced Machine Learning Technologies and Applications (AMLTA2018), 564–74. Cham: Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74690-6_55.

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Livingstone, D. W. "Chapter Two. Prior Empirical Research on Education-Job Matching." In Education and Jobs, edited by D. W. Livingstone, 33–50. Toronto: University of Toronto Press, 2009. http://dx.doi.org/10.3138/9781442686410-006.

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Nguyen, Cuong Duc, Khoi Duy Vo, and Dung Tien Nguyen. "Supporting Career Counseling with User Modeling and Job Matching." In Advanced Computational Methods for Knowledge Engineering, 281–92. Heidelberg: Springer International Publishing, 2013. http://dx.doi.org/10.1007/978-3-319-00293-4_21.

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Yamada, Hiroshi, Kaoru Shinkawa, Atsushi Hiyama, Masato Yamaguchi, Masatomo Kobayashi, and Michitaka Hirose. "Interactive Searching Interface for Job Matching of Elderly Workers." In Universal Access in Human-Computer Interaction. Users and Context Diversity, 436–45. Cham: Springer International Publishing, 2016. http://dx.doi.org/10.1007/978-3-319-40238-3_42.

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Conference papers on the topic "Job Matching"

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Vega, José. "Semantic matching between job offers and job search requests." In the 13th conference. Morristown, NJ, USA: Association for Computational Linguistics, 1990. http://dx.doi.org/10.3115/992507.992520.

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Rodriguez, Leah G., and Enrico P. Chavez. "Feature Selection for Job Matching Application using Profile Matching Model." In 2019 IEEE 4th International Conference on Computer and Communication Systems (ICCCS). IEEE, 2019. http://dx.doi.org/10.1109/ccoms.2019.8821682.

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Chala, Sisay Adugna, Fazel Ansari, and Madjid Fathi. "A Framework for Enriching Job Vacancies and Job Descriptions Through Bidirectional Matching." In 12th International Conference on Web Information Systems and Technologies. SCITEPRESS - Science and and Technology Publications, 2016. http://dx.doi.org/10.5220/0005806502190226.

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Zhao, Tianhua, Cheng Wuyu, and Chen Zhixiang. "Summer Job Selection Model Based on Job Matching and Comprehensive Evaluation Algorithm." In ICAIIS 2021: 2021 2nd International Conference on Artificial Intelligence and Information Systems. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3469213.3470394.

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Bollinger, Jacob, David Hardtke, and Ben Martin. "Using social data for resume job matching." In the 2012 workshop. New York, New York, USA: ACM Press, 2012. http://dx.doi.org/10.1145/2390131.2390143.

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Guo -Ding Liao, Miao-Zhu You, and Guo-Cheng Wang. "Experimental economic research for matching job positions." In 2015 International Conference on Behavioral, Economic and Socio-cultural Computing (BESC). IEEE, 2015. http://dx.doi.org/10.1109/besc.2015.7365965.

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Hauff, Claudia, and Georgios Gousios. "Matching GitHub Developer Profiles to Job Advertisements." In 2015 IEEE/ACM 12th Working Conference on Mining Software Repositories (MSR). IEEE, 2015. http://dx.doi.org/10.1109/msr.2015.41.

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Mine, Tsunenori, Tomoyuki Kakuta, and Akira Ono. "Reciprocal Recommendation for Job Matching with Bidirectional Feedback." In 2013 IIAI International Conference on Advanced Applied Informatics (IIAIAAI). IEEE, 2013. http://dx.doi.org/10.1109/iiai-aai.2013.91.

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Bills, Joseph, and Yiu-kai Dennis Ng. "Looking for Jobs? Matching Adults with Autism with Potential Employers for Job Opportunities." In IDEAS 2021: 25th International Database Engineering & Applications Symposium. New York, NY, USA: ACM, 2021. http://dx.doi.org/10.1145/3472163.3472270.

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Chala, Sisay, Scott Harrison, and Madjid Fathi. "Knowledge extraction from online vacancies for effective job matching." In 2017 IEEE 30th Canadian Conference on Electrical and Computer Engineering (CCECE). IEEE, 2017. http://dx.doi.org/10.1109/ccece.2017.7946793.

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Reports on the topic "Job Matching"

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Hanushek, Eric, and Steven Rivkin. Constrained Job Matching: Does Teacher Job Search Harm Disadvantaged Urban Schools? Cambridge, MA: National Bureau of Economic Research, March 2010. http://dx.doi.org/10.3386/w15816.

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Haan, Wouter Den, Christian Haefke, and Garey Ramey. Shocks and Institutions in a Job Matching Model. Cambridge, MA: National Bureau of Economic Research, September 2001. http://dx.doi.org/10.3386/w8463.

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Hall, Robert, and Sam Schulhofer-Wohl. Measuring Job-Finding Rates and Matching Efficiency with Heterogeneous Jobseekers. Cambridge, MA: National Bureau of Economic Research, February 2015. http://dx.doi.org/10.3386/w20939.

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Jiang, Yi, Liming Chen, and Eugenia Go. Accessibility Analysis of the South Commuter Railway Project of the Philippines. Asian Development Bank, August 2021. http://dx.doi.org/10.22617/brf2101314-2.

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This brief outlines findings on how the 54.6 km South Commuter Railway (SCR) to be built between Metro Manila and Laguna province in the Philippines is expected to improve access to jobs. A quantitative analysis estimates that residents of cities and municipalities with an SCR station will be able to reach an average of 300,000 extra jobs within a 1-hour commute—an increase of 15.3% in the south and 8.5% in Metro Manila. This could lead to better labor market matching, higher income for workers and more job opportunities for low-income households. The study contributes to efforts to quantify the wider economic benefits of infrastructure projects, especially efficient urban transport systems.
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Raei, Lamia. Exploring the Links: Youth participation and employment opportunities in Jordan. Oxfam IBIS, August 2021. http://dx.doi.org/10.21201/2021.7981.

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Oxfam partners with the Jordanian Hashemite Fund for Human Development (JOHUD) through its Youth Participation and Employment (YPE) programme in order to connect with communities and train local community-based organizations (CBOs). JOHUD’s aim is to build the job-seeking capacity of youth in four governorates in Jordan. The programme organizes informal activities involving peer-to-peer education to help young people engage in the community as volunteers, and links them to various governmental and non-governmental institutions. COVID-19 and the associated lockdowns have altered the organization’s operations, with most projects shifting online. JOHUD has adopted a youth-led initiative aimed at matching young people’s skills with labour-market demand in each governorate where the programme operates. This case study presents examples of how the programme has helped young people transform into professionals, and how youth-led employment centres can contribute to youth development activities.
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Lightfoot, Mary A., and Peter F. Ramsberger. Matching Recruits to Jobs: The Enlisted Personnel Allocation System. Fort Belvoir, VA: Defense Technical Information Center, August 2000. http://dx.doi.org/10.21236/ada382909.

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Johnson, Cecil D., and Joseph Zeidner. Classification Utility: Measuring and Improving Benefits in Matching Personnel to Jobs. Fort Belvoir, VA: Defense Technical Information Center, April 1990. http://dx.doi.org/10.21236/ada228386.

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Durand-Lasserve, Olivier. Policies to Nationalize the Private Sector Labor Force in a Matching Model with Public Jobs and Quotas. King Abdullah Petroleum Studies and Research Center, March 2021. http://dx.doi.org/10.30573/ks--2021-dp05.

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Gulf Cooperation Council (GCC) countries aim to employ more of their nationals in the private sector to absorb the inflow of new entrants into the labor force. They have put in place workforce nationalization policies to revert two peculiar features of their labor markets: the preference of nationals for public sector careers, and the crowding out of nationals by expatriate workers in the private sector.
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Boyd, Donald, Hamilton Lankford, Susanna Loeb, and James Wyckoff. Analyzing the Determinants of the Matching Public School Teachers to Jobs: Estimating Compensating Differentials in Imperfect Labor Markets. Cambridge, MA: National Bureau of Economic Research, August 2003. http://dx.doi.org/10.3386/w9878.

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