Salience and Market-aware Skill Extraction for Job Targeting

At LinkedIn, we want to create economic opportunity for everyone in the global workforce. To make this happen, LinkedIn offers a reactive Job Search system, and a proactive Jobs You May Be Interested In (JYMBII) system to match the best candidates with their dream jobs. One of the most challenging tasks for developing these systems is to properly extract important skill entities from job postings and then target members with matched attributes. In this work, we show that the commonly used text-based \emph{salience and market-agnostic} skill extraction approach is sub-optimal because it only considers skill mention and ignores the salient level of a skill and its market dynamics, i.e., the market supply and demand influence on the importance of skills. To address the above drawbacks, we present \model, our deployed \emph{salience and market-aware} skill extraction system. The proposed \model ~shows promising results in improving the online performance of job recommendation (JYMBII) ($+1.92\%$ job apply) and skill suggestions for job posters ($-37\%$ suggestion rejection rate). Lastly, we present case studies to show interesting insights that contrast traditional skill recognition method and the proposed \model~from occupation, industry, country, and individual skill levels. Based on the above promising results, we deployed the \model ~online to extract job targeting skills for all $20$M job postings served at LinkedIn.Comment: 9 pages, to appear in KDD202

Recruitment Methodology based on a "Reskilling" and "Upskilling" Strategy

Dissertation presented as the partial requirement for obtaining a Master's degree in Information Management, specialization in Information Systems and Technologies ManagementIn the era of “Digital Transformation”, new technologies have emerged in recent years, which have provided organizations with the opportunity to efficiently evolve their operations, transform their business models or even create new ones. The possibilities are enormous, but for this digital transformation process to happen, digital skills are essential, particularly highly qualified ICT professionals capable of implementing new technologies. The demand for these professionals is high, especially in Europe, and the scarcity is increasing. To face this shortage and respond to organisations’ needs, a reskilling and upskilling strategy can be a solution to bring more qualified professionals to the ICT labour market with these new technologies. However, hiring professionals to be trained in new technologies is challenging and risky to succeed. Therefore, the recruitment process needs to be more precise to select and validate candidates who can quickly and successfully acquire new technological skills. This research intends to create a method that can help in this process, applying a systematic approach to selecting and validating candidates with the most adequate technical and interpersonal skills for their requalification in new technologies. With the application of this method, a competency model is created for the target job, candidates are evaluated, and gaps are identified. In case of the feasibility of requalifying the candidate, a training plan is developed to acquire new technological skills

Toward a process theory of entrepreneurship: revisiting opportunity identification and entrepreneurial actions

This dissertation studies the early development of new ventures and small business and the entrepreneurship process from initial ideas to viable ventures. I unpack the micro-foundations of entrepreneurial actions and new ventures’ investor communications through quality signals to finance their growth path. This dissertation includes two qualitative papers and one quantitative study. The qualitative papers employ an inductive multiple-case approach and include seven medical equipment manufacturers (new ventures) in a nascent market context (the mobile health industry) across six U.S. states and a secondary data analysis to understand the emergence of opportunities and the early development of new ventures. The quantitative research chapter includes 770 IPOs in the manufacturing industries in the U.S. and investigates the legitimation strategies of young ventures to gain resources from targeted resource-holders.Open Acces

Crime and Work

Crime and legal work are not mutually exclusive choices but represent a continuum of legal and illegal income-generating activities. The links between crime and legal work involve trade-offs among crime returns, punishment costs, legal work opportunity costs, and tastes and preferences regarding both types of work. Rising crime rates in the 1980s in the face of rising incarceration rates suggest that the threat of punishment is not the dominant cost of crime. Crime rates are inversely related to expected legal wages, particularly among young males with limited job skills or prospects. Recent ethnographic research shows that involvement in illegal work often is motivated by low wages and harsh conditions in legal work. Many criminal offenders double up in both legal work and crime, either concurrently or sequentially. This overlap suggests a fluid and dynamic interaction between legal and illegal work. Market wages and job opportunities interact with social and legal pressures to influence decisions to abandon crime for legal work. Explanations of the patterns of legal and illegal work should be informed by econometric, social structural, and labeling theories. The continuity of legal and illegal work suggests the importance of illegal wages in research and theory on criminal decision making

The Phillips curve and long-term unemployment

This paper studies the role of long-term unemployment in the determination of prices and wages. Labor market theories such as insider-outsider models predict that this type of unemployed are less relevant in the wage formation process than the newly unemployed. This paper looks for evidence of this behavior in a set of OECD countries. For this purpose, I propose a new specification of the Phillips Curve that contains different unemployment lengths in a time-varying NAIRU setting. This is done by constructing an index of unemployment that assigns different weights to the unemployed based on the length of their spell. The results show that unemployment duration matters in the determination of prices and wages, and that a smaller weight ought to be given to the long-term unemployed. This modified model has important implications for the policy maker: It produces more accurate forecasts of inflation and more precise estimates of the NAIRU. JEL Classification: C22, E31, E50, J64Kalman filter, Long-term unemployment, NAIRU, Phillips curve

Redirecting research efforts on the diversification-performance linkage: The search for synergy

We review the literature on the diversification-performance (D-P) relationship to a) propose that the time is ripe for a renewed attack on understanding the relationship between diversification and firm performance, and b) outline a new approach to attacking the question. Our paper makes four main contributions. First, through a review of the literature we establish the inherent complexities in the D-P relationship and the methodological challenges confronted by the literature in reaching its current conclusion of a non-linear relationship between diversification and performance. Second, we argue that to better guide managers the literature needs to develop along a complementary path – whereas past research has often focused on answering the big question of does diversification affect firm performance, this second path would focus more on identifying the precise micro-mechanisms through which diversification adds or subtracts value. Third, we outline a new approach to the investigation of this topic, based on (a) identifying the precise underlying mechanisms through which diversification affects performance; (b) identifying performance outcomes that are “proximate” to the mechanism that the researcher is studying, and (c) identifying an appropriate research design that can enable a causal claim. Finally, we outline a set of directions for future research

Estimating Fungibility Between Skills by Combining Skill Similarities Obtained from Multiple Data Sources

Abstract This paper proposes an approach to estimating fungibility between skills given multiple information sources of those skills. An estimate of skill adjacency or fungibility or substitutability is critical for effective capacity planning, analytics and optimization in the face of changing skill requirements of an organization. The proposed approach is based on computing a similarity measure between skills, using each available data source, and combining these similarities into a measure of fungibility. We present both supervised and unsupervised integration methods and demonstrate that these produce improved outcomes, compared to using any single skill similarity source alone, using data from a large IT organization. The skills’ fungibility matrix created using this approach has been deployed by the organization for demand forecasting across groups of skills. We discuss how the fungibility matrix is deployed to generate skill clusters and present a forecasting algorithm that additionally incorporates past/future engagements and a mechanism to quantify uncertainty in the forecast. A possible extension of this work is to use the fungibility measure to cluster skills and develop a skill-centric representation of an organization to enable strategic assessments and planning

Impact Evaluations and Development: Nonie Guidance on Impact Evaluation

In international development, impact evaluation is principally concerned with final results of interventions (programs, projects, policy measures, reforms) on the welfare of communities, households, and individuals, including taxpayers and voters. Impact evaluation is one tool within the larger toolkit of monitoring and evaluation (including broad program evaluations, process evaluations, ex ante studies, etc.).The Network of Networks for Impact Evaluation (NONIE) was established in 2006 to foster more and better impact evaluations by its membership -- the evaluation networks of bilateral and multilateral organizations focusing on development issues, as well as networks of developing country evaluators. NONIE's member networks conduct a broad set of evaluations, examining issues such as project and strategy performance, institutional development, and aid effectiveness. By sharing methodological approaches and promoting learning by doing on impact evaluations, NONIE aims to promote the use of this more specific approach by its members within their larger portfolio of evaluations. This document, by Frans Leeuw and Jos Vaessen, has been developed to support this focus.For development practitioners, impact evaluations play a keyrole in the drive for better evidence on results and development effectiveness. They are particularly well suited to answer important questions about whether development interventions do or do not work, whether they make a difference, and how cost-effective they are. Consequently, they can help ensure that scarce resources are allocated where they can have the most developmental impact

Tourism in peripheral areas: the use of causal networks and lesson drawing as analytical methods.

The thesis sets out to evaluate the use of Causal Networks as a methodology and as a means of highlighting the problems associated with tourism in peripheral areas. Once these problems were identified through this process, the research findings are related to established literature and Lesson Drawing is evaluated as a means of comparative analysis. In attempting to utilise both Causal Networks and Lesson Drawing, three regions within Scotland were chosen as case studies. It was hoped that the selection of three regions within the same geographical propinquity would allow for Lessons to be both, imported and exported, from within the regions. The three regions chosen were Grampian; Inverness and Nairn; and Ross and Cromarty. An extensive literature search was conducted in an attempt to establish facts salient to the regions and primary research was carried out in all three regions. The primary research involved the use of an interview questionnaire. The respondents were all involved in tourism provision in one of the three case study regions. The interview data was collated and input onto conceptually clustered matrices. Causal Networks were constructed and analysed for each individual interview and for cognate groups and regions. Some tentative conclusions were drawn as a result of constructing the Causal Networks. These Causal Networks segmented the respondents into representative groups based on their functions or locations, for example commercial and non-commercial sector respondents or Grampian and Aberdeen City regional sector respondents. Using the Causal Networks opportunities for drawing lessons between the regions were highlighted. Finally, the effectiveness of both Casual Networks and Lesson Drawing methodologies were assessed in terms of their applicability for tourism provision in peripheral areas