Primary Integration and Political Involvement

An attempt is made to establish primary integration as a major variable in explaining citizen involvement in political life. It is argued that a convincing case requires a demonstration that the variable is both empirically important and theoretically meaningful. The former is examined through data from a sample survey of an English city. Theoretical meaning is established through focussing upon the idea of sociable talk as a key factor in reality construction, including the construction of political events as a proximate world available for the interest and participation by the individual.     

DIRECT THREAT AND POLITICAL TOLERANCE AN EXPERIMENTAL ANALYSIS OF THE TOLERANCE OF BLACKS TOWARD RACISTS

Using the NORC General Social Surveys from 1972 to 1984, weconstruct a question wording experiment that tests whether questionsconcerning the rights of a threatening group affect a respondent'swillingness to extend the same rights to other unrelated groups.Our findings suggest that a threatening stimulus in fact reducesa respondent's tolerance toward unrelated groups to a considerabledegree, although the effect is smaller for more highly educatedrespondents. We conclude by discussing some potential explanationsfor this interaction effect.     

EXPERIMENTAL STUDIES OF CONSUMER DEMAND BEHAVIOR USING LABORATORY ANIMALS*

Using laboratory animals as subjects, two series of experimental studies of consumer demand behavior are reported. The experiments show that laboratory animals will change consumption patterns in response to changes in the budget set, consuming more of the lower priced commodities and less of the higher priced commodities. Large rotations in the budget line for essential commodities resulted in severe disruption of consumer behavior. The experiments demonstrate the feasibility of using non-human subjects in laboratory studies of economic behavior.     

AN IMPROVED HEURISTIC FOR STAFFING TELEPHONE CALL CENTERS WITH LIMITED OPERATING HOURS

Many telephone call centers that experience cyclic and random customer demand adjust their staffing over the day in an attempt to provide a consistent target level of customer service. The standard and widely used staffing method, which we call the stationary independent period by period (SIPP) approach, divides the workday into planning periods and uses a series of stationary independent Erlang‐c queuing models—one for each planning period—to estimate minimum staffing needs. Our research evaluates and improves upon this commonly used heuristic for those telephone call centers with limited hours of operation during the workday. We show that the SIPP approach often suggests staffing that is substantially too low to achieve the targeted customer service levels (probability of customer delay) during critical periods. The major reasons for SIPP‘ s shortfall are as follows: (1) SIPP's failure to account for the time lag between the peak in customer demand and when system congestion actually peaks; and (2) SIPP’ s use of the planning period average arrival rate, thereby assuming that the arrival rate is constant during the period. We identify specific domains for which SIPP tends to suggest inadequate staffing. Based on an analysis of the factors that influence the magnitude of the lag in infinite server systems that start empty and idle, we propose and test two simple “lagged” SIPP modifications that, in most situations, consistently achieve the service target with only modest increases in staffing.     

INSIGHTS ON SERVICE SYSTEM DESIGN FROM A NORMAL APPROXIMATION TO ERLANG'S DELAY FORMULA

We show how a simple normal approximation to Erlang's delay formula can be used to analyze capacity and staffing problems in service systems that can be modeled as M/M/s queues. The numbers of servers, s, needed in an M/M/s queueing system to assure a probability of delay of, at most, p can be well approximated by s ≅ p + z_***I-p+, where z_1-p, is the (1 - p)th percentile of the standard normal distribution and ρ, the presented load on the system, is the ratio of Λ, the customer arrival rate, to μ, the service rate. We examine the accuracy of this approximation over a set of parameters typical of service operations ranging from police patrol, through telemarketing to automatic teller machines, and we demonstrate that it tends to slightly underestimate the number of servers actually needed to hit the delay probability target—adding one server to the number suggested by the above formula typically gives the exact result. More importantly, the structure of the approximation promotes operational insight by explicitly linking the number of servers with server utilization and the customer service level. Using a scenario based on an actual teleservicing operation, we show how operations managers and designers can quickly obtain insights about the trade-offs between system size, system utilization and customer service. We argue that this little used approach deserves a prominent role in the operations analyst's and operations manager's toolbags.     

SCHOOL QUALITY AND INFORMATION DISCLOSURE: EVIDENCE FROM THE HOUSING MARKET

In this article, we investigate the relationship between school quality and information disclosure in housing markets. When presented with the option of identifying their local public school in a real estate listing, we find that sellers with homes assigned to higher‐performing schools are more likely to provide this information. We find more evidence of selective disclosure in 2001–2002 than in 2006–2007, when the costs of gathering and disclosing information on school assignments and quality were lower. Furthermore, we find more evidence of strategic behavior among sellers of large single‐family units that presumably appeal to families with children. After controlling for school quality, information disclosure does not appear to affect housing prices. Taken together, our results support the findings of the education literature on the importance of school quality capitalization in residential real estate and they provide the first evidence of strategic information disclosure in housing markets. (JEL L15, I20, R31)     

The Ipsative Process to Reduce Response Set Bias

Researchers who gather data from several different groups arefrequently faced with the problem of response set bias. Thispaper discusses the ipsative process, a technique which canreduce systematic response bias which exists between groupsin a study. The usefulness of the ipsative process is illustratedon cross-cultural research findings gathered in four countries     

The Impact of "No Opinion" Response Options on Data Quality: Non-Attitude Reduction or an Invitation to Satisfice?

According to many seasoned survey researchers, offering a no-opinionoption should reduce the pressure to give substantive responsesfelt by respondents who have no true opinions. By contrast,the survey satisficing perspective suggests that no-opinionoptions may discourage some respondents from doing the cognitivework necessary to report the true opinions they do have. Weaddress these arguments using data from nine experiments carriedout in three household surveys. Attraction to no-opinion optionswas found to be greatest among respondents lowest in cognitiveskills (as measured by educational attainment), among respondentsanswering secretly instead of orally, for questions asked laterin a survey, and among respondents who devoted little effortto the reporting process. The quality of attitude reports obtained(as measured by over-time consistency and responsiveness toa question manipulation) was not compromised by the omissionof no-opinion options. These results suggest that inclusionof no-opinion options in attitude measures may not enhance dataquality and instead may preclude measurement of some meaningfulopinions.