Breaking Bad: Comparing Gambling Harms Among Gamblers and Affected Others

This article examines gambling harms from both gamblers and affected others’ perspectives. Participants (3076 gamblers and 2129 affected others) completed a retrospective survey that elicited information on harms they experienced from gambling across their lifetime. Their responses were analyzed through testing measurement invariance, estimating item-response theoretic parameters, calculating percentages, confidence intervals, and correlations, as well as regressions. The results indicated large commonalities in the experience of harms reported by gamblers and affected others. Further, gamblers appeared to ‘export’ about half of the harms they experienced to those around them. The findings also provided detailed profiles of evolving harms as problem gambling severity varies.     

Blunders in international marketing: Fact or fiction

Popular literature on international marketing gives the impression that U.S. firms are insensitive, lack understanding of the unique socio-political, cultural and trade environments of foreign markets, and are probably blundering all the time. Is this really so? To find an answer to this question, this article reports the results of the study that was conducted to verify some of the more publicized blunders in international marketing.     

Growth and Heat Resistance Kinetic Variation Among Various Isolates of Salmonella and its Application to Risk Assessment

The abilities of cells of a particular type of bacteria to leave lag phase and begin the process of dividing or surviving heat treatment can depend on the serotypes or strains of the bacteria. This article reports an investigation of serotype-specific differences in growth and heat resistance kinetics of clinical and food isolates of Salmonella. Growth kinetics at 19 degrees C and 37 degrees C were examined in brain heart infusion broth and heat resistance kinetics for 60 degrees C were examined in beef gravy using a submerged coil heating apparatus. Estimates of the parameters of the growth curves suggests a small between-serotype variance of the growth kinetics. However, for inactivation, the results suggest a significant between-serotype effect on the asymptotic D-values, with an estimated between-serotype CV of about 20%. In microbial risk assessment, predictive microbiology is used to estimate growth and inactivation of pathogens. Often the data used for estimating the growth or inactivation kinetics are based on measurements on a cocktail--a mixture of approximately equal proportions of several serotypes or strains of the pathogen being studied. The expected growth or inactivation rates derived from data using cocktails are biased, reflecting the characteristics of the fastest growing or most heat resistant serotype of the cocktail. In this article, an adjustment to decrease this possible bias in a risk assessment is offered. The article also presents discussion of the effect on estimating growth when stochastic assumptions are incorporated in the model. In particular, equations describing the variation of relative growth are derived, accounting for the stochastic variations of the division of cells. For small numbers of cells, the expected value of the relative growth is not an appropriate "representative" value for actual relative growths that might occur.     

A simulation analysis of the impact of family configuration on virtual cellular manufacturing

Past research has shown that it is possible to simultaneously achieve the setup efficiencies of traditional cellular manufacturing systems and the routeing flexibility of a job shop by viewing cells not as permanent, physical structures, but as temporary, 'virtual' entities. This research demonstrates that the advantages of virtual manufacturing cells can be obtained over a range of part family configurations. In particular, virtual cellular manufacturing is robust to changes in the number and size of families being processed. Further, the research shows that the benefits can be obtained under setup conditions impartial to a family-oriented part environment.     

Multiobjective Decision-Tree Analysis1

Single-objective-based decision-tree analysis has been extensively and successfully used in numerous decision-making problems since its formal introduction by Howard Raiffa more than two decades ago. This paper extends the traditional methodology to incorporate multiple noncommensurate objective functions and use of the conditional expected value of the risk of extreme and catastrophic events. The proposed methodology considers the cases where (a) a finite number of actions are available at each decision node and (b) discrete or continuous states of nature can be presented at each chance node. The proposed extension of decision-tree analysis is introduced through an example problem that leads the reader step-by-step into the methodological procedure. The example problem builds on flood warning systems. Two noncommensurate objectives—the loss of lives and the loss of property (including monetary costs of the flood warning system)–are incorporated into the decision tree. In addition, two risk measures—the common expected value and the conditional expected value of extreme and catastrophic events—are quantified and are also incorporated into the decision-making process. Theoretical difficulties associated with the stage-wise calculation of conditional expected values are identified and certain simplifying assumptions are made for computational tractibility. In particular, it is revealed that decisions concerning experimentation have a very interesting impact on the noninferior solution set of options—a phenomenon that has no equivalence in the single-objective case.     

UNBIASED ESTIMATION OF PARAMETRIC FUNCTIONS IN SAMPLING FROM TWO ONE-TRUNCATION PARAMETER FAMILIES

We consider the problem of minimum variance unbiased estimation of a U-estimable function of two unknown truncation parameters based on independent random samples from two one-truncation parameter families. In particular, we obtain the UMVU estimator of the probability that Y > X.     

A comparative analysis of school-to-work transitions in the European Union1

The present paper describes some aspects of ‘school-to-work’ transition by analyzing the employment situation of individuals as a function of the time elapsed since the completion of education or training. Our perspective is interdisciplinary, comparative and dynamic, with special focus on the patterns in southern European countries. In the literature, most of the studies have had the basic approach of constructing indicators based on retrospective information on the time of first leaving continuous education, and current information on status and characteristics of the person's economic activity – expressing the status of activity as a function of the time elapsed since leaving continuous education. In this approach, essentially cross-sectional (though in part retrospective) information is interpreted as if it pertains to real cohorts. Much of this comparative analysis of school-to-work transitions in EU countries has been based on the EU Labour Force Survey, the 2000 round of which incorporated a special module to collect information on the subject. Our basic approach is to use the longitudinal data from the European Community Household Panel to identify, at the time of each wave, the person's most recently completed education and training, and study this in relation to the person's current employment situation and other characteristics as a function of the time elapsed since that completion. Hence, in form at least, our approach is similar to that of earlier studies based on the LFS, though there are considerable differences in substantive content and statistical methodology resulting from the use of different types of data. We also demonstrate how data from a panel survey may be cumulated over time to obtain a more adequate sample size.     

Intelligent Procedures for Intra‐Day Updating of Call Center Agent Schedules

For nearly all call centers, agent schedules are typically created several days or weeks before the time that agents report to work. After schedules are created, call center resource managers receive additional information that can affect forecasted workload and resource availability. In particular, there is significant evidence, both among practitioners and in the research literature, suggesting that actual call arrival volumes early in a scheduling period (typically an individual day or week) can provide valuable information about the call arrival pattern later in the same scheduling period. In this paper, we develop a flexible and powerful heuristic framework for managers to make intra‐day resource adjustment decisions that take into account updated call forecasts, updated agent requirements, existing agent schedules, agents' schedule flexibility, and associated incremental labor costs. We demonstrate the value of this methodology in managing the trade‐off between labor costs and service levels to best meet variable rates of demand for service, using data from an actual call center.     

The state and civil society in disaster response: post-tsunami experiences in Tamil Nadu

This paper, based on the report "The State and Civil Society in Disaster Response: An Analysis of the Tamil Nadu Tsunami Experience," (Srinivasan, Nagaraj, & Venkatesh, 2005) is essentially an empirical analysis of state and civil society responses in Tamil Nadu (India) to the tsunami of December 26, 2004. It examines interventions by state and non-state agencies, as well as people's experiences in the relief and rehabilitation phases to identify factors influencing both positive and negative outcomes of the tsunami response. Issues related to vulnerability and exclusion, equity, transparency and accountability in different sectors of disaster intervention are explored to highlight themes revolving around reach and efficacy of relief and recovery processes. These analyses bring out some interesting lessons with regard to the importance of institutional autonomy, non-politicized decision-making, and synergetic state-civil society interfaces in fostering inclusive, transparent and accountable rehabilitation processes. The roles played by institutional responsiveness and flexibility in shaping an effective disaster response also emerge very clearly from this study of the Tamil Nadu experience. Another crucial finding points to the need for detailed, reliable and disaggregated geo-demographic and socioeconomic records as a resource base for informing relief and rehabilitation interventions. The study draws extensively from the experiences and insights of people affected by, and involved in tsunami response, and from secondary knowledge resources available on the disaster.     

The white native speaker and inequality regimes in the private English language school

Private English language schools market the language as a tool that helps one connect with others from different cultures. Despite their promotion of English aiding in intercultural communication, these institutions may believe that only the white native speaker is the ideal teacher of the language. This valuing of the white native speaker can consequently act as an organisational inequality regime that marginalises nonwhite teachers. Using qualitative interviews with 10 nonwhite instructors working in schools in Toronto, Canada, this article investigates the ways in which these teachers experience the inequality regime of the white native speaker at work. The findings indicate that the teachers experience this inequality regime as a series of microaggressions that involve space, competence and customer desire. The article concludes with suggestions to dismantle inequality regimes in private institutions.