Experimental Evidence of Discrimination in the Hiring of First‐ and Second‐generation Immigrants

Previous field experiments that study ethnic discrimination in the labour market are extended in this paper, which outlines a study comparing discrimination of first‐ and second‐generation immigrants. Qualitatively identical resumes, belonging to first‐ and second‐generation immigrants from the Middle East, were sent to employers in Sweden that had advertised for labour. The findings suggest, somewhat unexpectedly, that first‐ and second‐generation immigrants have essentially the same probability of being invited to a job interview, which in turn is significantly lower than the probability of invitation to interview for natives.     

Discrimination and Resistance to Low‐skilled Immigration

Abstract. This paper shows that the immigration of some low‐skilled workers can be of advantage for low‐skilled natives when the host economy suffers from unemployment due to the presence of trade unions and an unemployment insurance scheme. This benefit arises if trade unions have appropriate bargaining power and preferences for members’ income, labor market discrimination against immigrants is strong enough and the unemployment tax rate is low.     

Unionization and Labour‐market Discrimination: A Closer Look at Non‐unionized Workers

This paper introduces a model that examines the effects of unions on pay and hiring gaps between non‐unionized men and women in the context of imperfect competition. Although the model does not question the advantages unions obtain for their members, it does show that (1) unions increase wage and occupational discrimination for non‐unionized workers; (2) the non‐unionized sector does not constitute a good comparison group for use in analysing the impact of unions on gender discrimination; and (3) public policies targeting gender differences in occupational sorting can also have a positive impact on gender wage differentials.     

Hiring, engaging and retaining the A-team

It takes more than an occasional pat on the back to retain your star players. And don't think that money is the prime motivating factor to keep the A-team happy. Family matters and professional challenges are key.     

Foreign Participation and Hiring Patterns after Privatization

Critics of globalization claim that foreign ownership of privatized firms is linked to negative post‐privatization labor outcomes, such as more firing and less hiring. This paper uses new firm‐level data for a cross‐section of countries to test this idea and provides evidence that foreign purchasers of state‐owned enterprises tend to acquire firms that were already better restructured before privatization. Additionally, this paper does not find evidence that foreign participation in privatized firms is linked to negative labor outcomes.     

Firm‐level Evidence on Gender Wage Discrimination in the Belgian Private Economy

In this paper we explore a matched employer–employee data set to investigate the presence of gender wage discrimination in the Belgian private economy labour market. Contrary to many existing papers, we analyse gender wage discrimination using an independent productivity measure. Using firm‐level data, we are able to compare direct estimates of a gender productivity differential with those of a gender wage differential. We take advantage of the panel structure to identify gender‐related differences from within‐firm variation. Moreover, inspired by recent developments in the production function estimation literature, we address the problem of endogeneity of the gender mix using a structural production function estimator alongside instrumental variable‐general method of moments (IV‐GMM) methods where lagged value of labour inputs are used as instruments. Our results suggest that there is no gender wage discrimination inside private firms located in Belgium, on the contrary.     

Equity‐Based Incentives and Supply Chain Buy‐Back Contracts*

We analyze the effect of equity‐based incentives in a supply chain with a downstream firm and an upstream supplier. By using the operational decision as a signal to influence external investors’ beliefs, the downstream firm's manager intends to maximize a convex combination of the interim share price and the terminal cash flows. We show that equity‐based incentives create a side effect. Specifically, with a universal buy‐back contract, the deadweight loss of signaling induced by equity‐based incentives could spread throughout the supply chain and cause chain‐wide damages. To mitigate such undesirable consequences, we propose a new mechanism to eliminate the inefficiency. We derive the optimal mechanism that maximizes the downstream firm's profits subject to the constraint that the supply chain efficiency is not undermined. In contrast to the full‐information benchmark, this mechanism gives positive surplus to the supplier. [Submitted: January 5, 2011. Revisions received: June 20, 2011; December 11, 2011. Accepted: December 22, 2011.]     

Context‐Specific,Scenario‐Based Risk Scales

Reacting to an emergency requires quick decisions under stressful and dynamic conditions. To react effectively, responders need to know the right actions to take given the risks posed by the emergency. While existing research on risk scales focuses primarily on decision making in static environments with known risks, these scales may be inappropriate for conditions where the decision maker's time and mental resources are limited and may be infeasible if the actual risk probabilities are unknown. In this article, we propose a method to develop context‐specific, scenario‐based risk scales designed for emergency response training. Emergency scenarios are used as scale points, reducing our dependence on known probabilities; these are drawn from the targeted emergency context, reducing the mental resources required to interpret the scale. The scale is developed by asking trainers/trainees to rank order a range of risk scenarios and then aggregating these orderings using a Kemeny ranking. We propose measures to assess this aggregated scale's internal consistency, reliability, and validity, and we discuss how to use the scale effectively. We demonstrate our process by developing a risk scale for subsurface coal mine emergencies and test the reliability of the scale by repeating the process, with some methodological variations, several months later.     

Optimal Per‐Use Rentals and Sales of Durable Products and Their Distinct Roles in Price Discrimination

We consider a setting in which consumers experience distinct instances of need for a durable product at random intervals. Each instance of need is associated with a random utility and the consumers are differentiated according to the frequency with which they experience such instances of need. We use our model of consumer utility to characterize the firm's optimal strategy of whether to sell, rent, or do a combination of both in terms of the transaction costs and consumers' usage characteristics. We find that the two modes of operation serve different roles in allowing the firm to price discriminate. While sales allow the firm to discriminate among consumers of different usage frequencies, rentals allow it to discriminate according to consumers' realized valuations. Consequently, even when transaction costs are negligible, it is often optimal for the firm to simultaneously rent and sell its product. In addition, we find that although sales and rentals are substitutes and that the offering of sales weakly increases rental prices, it is possible that the introduction of rentals to a pure selling operation can either increase or decrease the optimal sales prices.     

Agent‐Based Simulation for Human‐Induced Hazard Analysis

Terrorism could be treated as a hazard for design purposes. For instance, the terrorist hazard could be analyzed in a manner similar to the way that seismic hazard is handled. No matter how terrorism is dealt with in the design of systems, the need for predictions of the frequency and magnitude of the hazard will be required. And, if the human‐induced hazard is to be designed for in a manner analogous to natural hazards, then the predictions should be probabilistic in nature. The model described in this article is a prototype model that used agent‐based modeling (ABM) to analyze terrorist attacks. The basic approach in this article of using ABM to model human‐induced hazards has been preliminarily validated in the sense that the attack magnitudes seem to be power‐law distributed and attacks occur mostly in regions where high levels of wealth pass through, such as transit routes and markets. The model developed in this study indicates that ABM is a viable approach to modeling socioeconomic‐based infrastructure systems for engineering design to deal with human‐induced hazards.     

Hiring and firing: the right and legal way.

Is any decision higher risk than hiring a new employee? You're betting your time and the organization's dollars, effectiveness, and reputation on your decision. No wonder people want to have candidates CAT scanned! There are ways to reduce the risk of a wrong decision (or, if that happens, to correct it), all within current legal guidelines. We talked with Fred R. Kimmel, a partner with the law firm of Arvey, Hodes, Costello & Burman, Chicago, and a specialist in labor and employment law, about both effectiveness and legality. This article reports on a plan for hiring and firing the right way.     

Information‐Based Relative Consumption Effects

Preferences exhibit relative consumption effects if a person's satisfaction with their own consumption appears to depend upon how much others are consuming. This paper examines a model of an evolutionary environment in which Nature optimally builds relative consumption effects into preferences in order to compensate for incomplete environmental information.     

A Reliability‐Based Capability Approach

This article proposes a rigorous mathematical approach, named a reliability‐based capability approach (RCA), to quantify the societal impact of a hazard. The starting point of the RCA is a capability approach in which capabilities refer to the genuine opportunities open to individuals to achieve valuable doings and beings (such as being mobile and being sheltered) called functionings. Capabilities depend on what individuals have and what they can do with what they have. The article develops probabilistic predictive models that relate the value of each functioning to a set of easily predictable or measurable quantities (regressors) in the aftermath of a hazard. The predicted values of selected functionings for an individual collectively determine the impact of a hazard on his/her state of well‐being. The proposed RCA integrates the predictive models of functionings into a system reliability problem to determine the probability that the state of well‐being is acceptable, tolerable, or intolerable. Importance measures are defined to quantify the contribution of each functioning to the state of well‐being. The information from the importance measures can inform decisions on optimal allocation of limited resources for risk mitigation and management.     

Panel Size and Overbooking Decisions for Appointment‐Based Services under Patient No‐Shows

Many service systems that work with appointments, particularly those in healthcare, suffer from high no‐show rates. While there are many reasons why patients become no‐shows, empirical studies found that the probability of a patient being a no‐show typically increases with the patient's appointment delay, i.e., the time between the call for the appointment and the appointment date. This paper investigates how demand and capacity control decisions should be made while taking this relationship into account. We use stylized single server queueing models to model the appointments scheduled for a provider, and consider two different problems. In the first problem, the service capacity is fixed and the decision variable is the panel size; in the second problem, both the panel size and the service capacity (i.e., overbooking level) are decision variables. The objective in both cases is to maximize some net reward function, which reduces to system throughput for the first problem. We give partial or complete characterizations for the optimal decisions, and use these characterizations to provide insights into how optimal decisions depend on patient's no‐show behavior in regards to their appointment delay. These insights especially provide guidance to service providers who are already engaged in or considering interventions such as sending reminders in order to decrease no‐show probabilities. We find that in addition to the magnitudes of patient show‐up probabilities, patients' sensitivity to incremental delays is an important determinant of how demand and capacity decisions should be adjusted in response to anticipated changes in patients' no‐show behavior.     

Profitability of Service‐Level‐Based Price Differentiation with Inventory Rationing

In this paper, we study the profitability of service‐level‐based price differentiation (SLBPD) in an inventory‐rationing context. SLBPD implies that a company offers several combinations of prices and guaranteed service levels, from which customers self‐select; different customers choose different offerings because they incur different shortage costs if an order is not fulfilled immediately. We develop an analytical model for SLBPD and explore if and when such a service differentiation strategy yields higher profits than a single undifferentiated offering. The results of our analyses suggest that SLBPD is profitable only if a company faces pricing restrictions, e.g., because of competitive pressure or regulatory restrictions. We develop necessary and sufficient conditions under which a specific and relevant form of SLBPD (called “service‐level‐based upselling”) is profitable, and provide an algorithm to compute the optimal parameters of such a policy. Based on this algorithm we carry out numerical analyses that allow us to characterize the profit increment of service‐level‐based upselling. We derive managerial insights into the attractiveness of SLBPD and explain how our basic analytical framework can be extended to account for more complex practical features.     

Investigating the Level of End‐User Development and Involvement Among Time‐Based Competitors

As global markets and technology change, time‐based competitors create product development and manufacturing practices that reduce response time and enhance customization capabilities. These practices require an information‐rich internal environment that is capable of flexible resource deployment and direct and continuous feedback. To build this environment, time‐based competitors are developing end‐user capabilities and involving them in information systems (IS) activities. Data collected from 265 manufacturers were used to determine if firms with high levels of time‐based product development and time‐based manufacturing practices also have high levels of end‐user involvement in IS‐related activities, end‐user training effectiveness, and end‐user computing skills. The results of this study support that contention.     

Fuzzy‐Logic‐Based Safety Verification Framework for Nuclear Power Plants

This article presents a practical implementation of a safety verification framework for nuclear power plants (NPPs) based on fuzzy logic where hazard scenarios are identified in view of safety and control limits in different plant process values. Risk is estimated quantitatively and compared with safety limits in real time so that safety verification can be achieved. Fuzzy logic is used to define safety rules that map hazard condition with required safety protection in view of risk estimate. Case studies are analyzed from NPP to realize the proposed real‐time safety verification framework. An automated system is developed to demonstrate the safety limit for different hazard scenarios.     

Capacity Planning and Allocation for Web‐Based Applications

Motivated by the technology division of a financial services firm, we study the problem of capacity planning and allocation for Web‐based applications. The steady growth in Web traffic has affected the quality of service (QoS) as measured by response time (RT), for numerous e‐businesses. In addition, the lack of understanding of system interactions and availability of proper planning tools has impeded effective capacity management. Managers typically make decisions to add server capacity on an ad hoc basis when systems reach critical response levels. Very often this turns out to be too late and results in extremely long response times and the system crashes. We present an analytical model to understand system interactions with the goal of making better server capacity decisions based on the results. The model studies the relationships and important interactions between the various components of a Web‐based application using a continuous time Markov chain embedded in a queuing network as the basic framework. We use several structured aggregation schemes to appropriately represent a complex system, and demonstrate how the model can be used to quickly predict system performance, which facilitates effective capacity allocation decision making. Using simulation as a benchmark, we show that our model produces results within 5% accuracy at a fraction of the time of simulation, even at high traffic intensities. This knowledge helps managers quickly analyze the performance of the system and better plan server capacity to maintain desirable levels of QoS. We also demonstrate how to utilize a combination of dedicated and shared resources to achieve QoS using fewer servers.     

Usage‐Based Pricing and Demand for Residential Broadband

We estimate demand for residential broadband using high‐frequency data from subscribers facing a three‐part tariff. The three‐part tariff makes data usage during the billing cycle a dynamic problem, thus generating variation in the (shadow) price of usage. We provide evidence that subscribers respond to this variation, and we use their dynamic decisions to estimate a flexible distribution of willingness to pay for different plan characteristics. Using the estimates, we simulate demand under alternative pricing and find that usage‐based pricing eliminates low‐value traffic. Furthermore, we show that the costs associated with investment in fiber‐optic networks are likely recoverable in some markets, but that there is a large gap between social and private incentives to invest.