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

Investigating effort prediction of web-based applications using CBR on the ISBSG dataset

As web-based applications become more popular and more sophisticated, so does the requirement for early accurate estimates of the effort required to build such systems. Case-based reasoning (CBR) has been shown to be a reasonably effective estimation strategy, although it has not been widely explored in the context of web applications. This paper reports on a study carried out on a subset of the ISBSG dataset to examine the optimal number of analogies that should be used in making a prediction. The results show that it is not possible to select such a value with confidence, and that, in common with other findings in different domains, the effectiveness of CBR is hampered by other factors including the characteristics of the underlying dataset (such as the spread of data and presence of outliers) and the calculation employed to evaluate the distance function (in particular, the treatment of numeric and categorical data)

Rivals’ Reactions to Mergers and Acquisitions

Mergers and acquisitions research has principally focused on attributes of the acquiring firm and post-acquisition outcomes. To extend our knowledge, we focus on external factors, in particular rival responses, and explore when and how rivals respond to their competitor’s acquisitions. Leveraging the awareness–motivation–capability framework, we predict and find evidence that a rival’s dependence on markets in common with the acquirer, resource similarity between rival and acquirer, and a rival’s organizational slack increase the volume and, in some cases, also the complexity of a rival’s competitive actions following an acquisition. Furthermore, the type of acquisition positively moderates some of these relationships. The results extend our understanding of the influence of mergers and acquisitions on competitive dynamics in the marketplace

Definition, Measurement and Determinants of the Consumer's Willingness to Pay: a Critical Synthesis and Directions for Further Research

Differentiated prices, bundling, Web auctions : firms' pricing practices are evolving. When there is no market or for customised pricing, the willingness-to-pay concept seems to be interesting. This article aims at presenting a synthesis of the marketing research stream relative to willingness to pay. First, a definition of the concept is given and compared to other similar concepts, notably reference price and acceptable price. Then the methods of measurement are presented, compared to those used to measure elasticity and criticized. Furthermore, the research on external determinants of willingness to pay is commented. Finally, numerous directions for further research are proposed.willingness to pay, price elasticity, reference price, acceptable price, conjoint analysis, contingent valuation, Vickrey auctions, BDM lottery, prices

Transaction Costs and Profitability in UK Manufacturing

This paper explores the impact of transaction costs on performance at firm and industry levels using a sample of 7350 UK manufacturing firms. This is achieved by estimating a profit function with estimated transaction costs as a right hand side variable. The discussion has two specific objectives. (1) To show how firm and average industry transaction costs can be estimated using a stochastic frontier method. (2) To examine a central claim of transaction cost theory that links these costs to performance. In addition the different impacts of static and dynamic transaction costs are emphasised, with the different impacts being respectively negative and positive on profitability. Broadly speaking it is shown that such costs do impact on performance in a way consistent with both static and dynamic costs, in different industries, and that the impacts hold after a series of robustness checks. In addition it is shown that the impacts can depend on monopoly power, firm scale, and firm growth

Fit for planning? An evaluation of the application of development viability appraisal models in the UK planning system

The aim of this paper is to critically examine the application of development appraisal to viability assessment in the planning system. This evaluation is of development appraisal models in general and also their use in particular applications associated with estimating planning obligation capacity. The paper is organised into four themes: · The context and conceptual basis for development viability appraisal · A review of development viability appraisal methods · A discussion of selected key inputs into a development viability appraisal · A discussion of the applications of development viability appraisals in the planning system It is assumed that readers are familiar with the basic models and information needs of development viability appraisal rather than at the cutting edge of practice and/or academ

Non-Linearity in the Determinants of Capital Structure: Evidence from UK Firms

We develop a model of the firm’s maximization programme in which the firm’s capital structure is a non linear function of a vector of costs including asymmetric information costs and is subject to a debt ceiling. Using conditional quantile regression methods, we test for the existence of such a non- linearity in a heterogeneous sample of UK firms and demonstrate that, by exploiting more fully the distribution of leverage, this technique yields new insights into the choice of leverage ratio. Not only is the estimated effect of the explanatory variables different at different quantiles of the distribution, we find evidence that the effect of a variable changes sign between low leveraged and high leveraged firms

Predicting human preferences using the block structure of complex social networks

With ever-increasing available data, predicting individuals' preferences and helping them locate the most relevant information has become a pressing need. Understanding and predicting preferences is also important from a fundamental point of view, as part of what has been called a "new" computational social science. Here, we propose a novel approach based on stochastic block models, which have been developed by sociologists as plausible models of complex networks of social interactions. Our model is in the spirit of predicting individuals' preferences based on the preferences of others but, rather than fitting a particular model, we rely on a Bayesian approach that samples over the ensemble of all possible models. We show that our approach is considerably more accurate than leading recommender algorithms, with major relative improvements between 38% and 99% over industry-level algorithms. Besides, our approach sheds light on decision-making processes by identifying groups of individuals that have consistently similar preferences, and enabling the analysis of the characteristics of those groups