Manufacturing Resistance: Rationalizing the Irrationality of Managerial Control on the Shop Floor in a US Medical Electronics Factory

Juravich (1985) asserts that the organization of US industrial manufacturing is irrational as well as appearing chaotic from the workers’ viewpoint because of management’s refusal to integrate the workers’ knowledge into the production process. Because of this, Juravich argues, if and when the workers’ knowledge is integrated into the production system, the workers no longer will experience “chaos on the shop floor.” Extending Devinatz’s (1993) analysis in response to Juravich, this article argues that workers use resistance as a logical strategy for rationalizing what they perceive to be the irrationality of the shop floor. Utilizing Kusterer’s (1978) work, I argue that the use of many, but not all, resistance strategies constitutes a type of “survival knowledge” acquired and used by workers in response to managerial control. I maintain that these strategies constitute a special type of workplace resistance which I refer to as “pure and simple resistance.”     

Corporate borrowing and growth option value: The limited liability effect

A firm issues bonds before undertaking a risky continuous investment project that is costly to later either expand or contract. The firm’s existing debt load causes it to install a smaller capacity because equity has limited liability. This lowers debt value, but such a cost should be borne by equityholders because debtholders will rationally anticipate equityholders’ future behavior. The firm’s choice of debt levels balances this agency cost against the tax shield benefit. As the firm incurs higher costs to later expand capacity, its growth option value becomes lower. The simulation results of this article are in line with Myers’ conjecture (1977), which states that a firm’s debt capacity is inversely related to its growth option value.     

Workplace Bullying: Application of Novak’s (1998) Learning Theory and Implications for Training

This paper applies Novak’s (1998) theory of learning to the problem of workplace bullying. Novak’s theory offers an understanding of how actions of bullying and responses to bullying can be seen as deriving from individualized conceptualizations of workplace bullying by those involved. Further, Novak’s theory suggests that training involving Ausubel’s concept of meaningful learning (Ausubel Educational Theory 11(1): 15–25, 1961; Ausubel et al. 1978) which attends to learners’ pre-existing knowledge and allows for new meaning to be constructed regarding workplace bullying can lead to new actions related to workplace bullying. Ideally, these new actions can involve both a reduction in workplace bullying prevalence, and responses to workplace bullying which recognize and are informed by the negative consequences of this workplace dynamic.     

Estimating sensitive proportions from Warner’s randomized responses in alternative ways restricting to only distinct units sampled

Warner’s (J Am Stat Assoc 60:63–69, 1965) pioneering ‘randomized response’ (RR) technique (RRT), useful in unbiasedly estimating the proportion of people bearing a sensitive characteristic, is based exclusively on simple random sampling (SRS) with replacement (WR). Numerous developments that follow from it also use SRSWR and employ in estimation the mean of the RR’s yielded by each person everytime he/she is drawn in the sample. We examine how the accuracy in estimation alters when instead we use the mean of the RR’s from each distinct person sampled and also alternatively if the Horvitz and Thompson’s (HT, J Am Stat Assoc 47:663–685, 1952) method is employed for an SRSWR eliciting only, a single RR from each. Arnab’s (1999) approach of using repeated RR’s from each distinct person sampled is not taken up here to avoid algebraic complexity. Pathak’s (Sánkhya 24:287–302, 1962) results for direct response (DR) from SRSWR are modified with the use of such RR’s. Through simulations we present relative levels in accuracy in estimation by the above three alternative methods.     

Resolving the conflict between clients’ privacy rights and employees’ equal employment opportunity rights

It is unlawful under Title VII of the Civil Rights Act for employers to discriminate against applicants or employees because of their sex unless sex is a bona fide occupational qualification (BFOQ). During the past two decades, a number of courts were asked to decide whether sex is a BFOQ for the purpose of protecting clients’ privacy rights (i.e., whether employers could insist that employees be of the same sex as their clients for those jobs which required employees to touch or view clients’ bodies in various stages of undress). This investigation examined relevant judicial opinions rendered throughout the United States to determine how the courts resolved this conflict between clients’ privacy rights and employees’ equal employment opportunity rights.     

Measuring opinion distributions

In this study it will be argued that the perceived distribution of opinions among others is important for opinion research. Three different ways of measuring the perception of opinion distributions in survey research are compared: (a) by means of a questionwhat most people think about an issue, (b) by means of a questionhow many people are perceived to agree with an issue-statement, (c) by means of ‘line-production-boxes’, a special version ofmagnitude estimation. The results indicate that ‘line-production-boxes’ can improve data quality, but have also some drawbacks which will have to be dealt with. ‘Line-production-boxes’ give a wealth of information about individual differences in the forms of perceived opinion distributions. Although the normal distribution is used often, many other distribution forms are also used. The method of ‘line-production-boxes’ is compared with the method of estimating percentage points. Although high correlations suggest a good concurrent validity, some systematic differences do exist. New research directions are suggested.     

Some things couples always wanted to know about stable matchings (but were afraid to ask)

In this note we study the National Resident Matching Program (NRMP) algorithm in the US market for physicians. We report on two problems that concern the presence of couples, a feature explicitly incorporated in the new NRMP algorithm (cf. Roth and Peranson in Am Econ Rev 89:748–780, 1999). First, we show that the new NRMP algorithm may not find an existing stable matching, even when couples’ preferences are ‘responsive’, i.e., when Gale and Shapley’s (Am Math Monthly 69:9–15, 1962) deferred acceptance algorithm (on which the old NRMP algorithm is based) is applicable. Second, we demonstrate that the new NRMP algorithm may also be anipulated by couples acting as singles.      

GenD An Evolutionary System for Resampling in Survey Research

The paper is a preliminary research report and presents a method for generating new records using an evolutionary algorithm (close to but different from a genetic algorithm). This method, called Pseudo-Inverse Function (in short P-I Function), was designed and implemented at Semeion Research Centre (Rome). P-I Function is a method to generate new (virtual) data from a small set of observed data. P-I Function can be of aid when budget constraints limit the number of interviewees, or in case of a population that shows some sociologically interesting trait, but whose small size can seriously affect the reliability of estimates, or in case of secondary analysis on small samples. The applicative ground is given by research design with one or more dependent and a set of independent variables. The estimation of new cases takes place according to the maximization of a fitness function and outcomes a number as large as needed of ‘virtual’ cases, which reproduce the statistical traits of the original population. The algorithm used by P-I Function is known as Genetic Doping Algorithm (GenD), designed and implemented by Semeion Research Centre; among its features there is an innovative crossover procedure, which tends to select individuals with average fitness values, rather than those who show best values at each ‘generation’. A particularly thorough research design has been put on: (1) the observed sample is half-split to obtain a training and a testing set, which are analysed by means of a back propagation neural network; (2) testing is performed to find out how good the parameter estimates are; (3) a 10% sample is randomly extracted from the training set and used as a reduced training set; (4) on this narrow basis, GenD calculates the pseudo-inverse of the estimated parameter matrix; (5) ‘virtual’ data are tested against the testing data set (which has never been used for training). The algorithm has been proved on a particularly difficult ground, since the data set used as a basis for generating ‘virtual’ cases counts only 44 respondents, randomly sampled from a broader data set taken from the General Social Survey 2002. The major result is that networks trained on the ‘virtual’ resample show a model fit as good as the one of the observed data, though ‘virtual’ and observed data differ on some features. It can be seen that GenD ‘refills’ the joint distribution of the independent variables, conditioned by the dependent one. This paper is the result of deep collaboration among all authors. Cinzia Meraviglia wrote § 1, 3, 4, 6, 7 and 8; Giulia Massini wrote §5; Daria Croce performed some elaborations with neural networks and linear regression; Massimo Buscema wrote §2.     

On the performance of voting systems in spatial voting simulations

We study the performance of voting systems in terms of minimizing the overall social disutility of making a collective choice in an univariate voting space with ideological voting and perfect information. In order to obtain a distribution of the performance indicator for each of the 12 systems chosen for this study—Baldwin’s Method, Black’s Method, The Borda Count, Bucklin’s Grand Junction System, Coombs’ Method, Dodgson’s System, Instant Run-Off Voting, Plurality, Simpson’s MinMax, Tideman’s Ranked Pairs, Schulze’s Beatpath Method, and Two-Round Majority—we simulate elections using an Agent-Based Computational approach under several different distributions for voters and candidates positioning, with up to 15 available candidates. At each iteration, voters generate complete and strict ordinal utility functions over the set of available candidates, based on which each voting system computes a winner. We define the performance of a system in terms of its capability of choosing among the available candidates the one that minimizes aggregate voter disutility. As expected, the results show an overall dominance of Condorcet completion methods over the traditional and more widely used voting systems, regardless of the distributions of voter and candidate positions.     

Social Distance,Respondent Cooperation and Item Nonresponse in Sex Survey

This paper examines the ways in which the number of item nonresponses is determined by social distance and/or interview rapport, with a focus on responses of “refusal” and “don’t know”, implying the respondent’s lack of willingness and ability to provide substantive responses to sensitive questions. The data analyzed were from 39 self- administered questions concerning sexual attitudes and behaviors in the 2002 Taiwan Social Change Survey for module “Family and Changing Gender Role”. Poisson Regression in 2-level Hierarchical Linear Model was employed to enhance the accuracy of the analysis of the accumulation of “don’t know” and “refusal” responses. The results showed that respondent cooperation significantly decreased the number of both “don’t know” and “refusal” replies. The decrease was not conditioned by any kind of social distance. Age and education distances have respectively negative and positive effect on the number of “don’t know” and “refusal” answers. The married–married interview produced more “don’t know” and “refusal” than other paired interview types. The larger the ethnicity distance is, the more “refusal” appears. The substantial findings imply that the effects of social-distance and rapport (respondent cooperation) on the number of item nonresponses deserve more attention in research on survey methodology. The divergent findings on gender-distance effect and marital-status effect, however, call for replication studies in the future.     

Taking ‘Don’t Knows’ as Valid Responses: A Multiple Complete Random Imputation of Missing Data

Incomplete data is a common problem of survey research. Recent work on multiple imputation techniques has increased analysts’ awareness of the biasing effects of missing data and has also provided a convenient solution. Imputation methods replace non-response with estimates of the unobserved scores. In many instances, however, non-response to a stimulus does not result from measurement problems that inhibit accurate surveying of empirical reality, but from the inapplicability of the survey question. In such cases, existing imputation techniques replace valid non-response with counterfactual estimates of a situation in which the stimulus is applicable to all respondents. This paper suggests an alternative imputation procedure for incomplete data for which no true score exists: multiple complete random imputation, which overcomes the biasing effects of missing data and allows analysts to model respondents’ valid ‘I don’t know’ answers.     

Impact of investor’s varying risk aversion on the dynamics of asset price fluctuations

While investors’ responses to price changes and their price forecast have been identified as one of the major factors contributing to large price fluctuations in financial markets, our study shows that investors’ heterogeneous and dynamic risk aversion (DRA) preferences may play a more critical role in understanding the dynamics of asset price fluctuations. We allow an agent specific and time-dependent risk aversion index in a popular power utility function with constant relative risk aversion to construct our DRA model in which we made two key contributions. We developed an approximated closed-form price setting equation, providing a necessary framework for exploring the impact of various agents’ behaviors on the price dynamics. The dynamics of each agent’s risk aversion index is modeled by a bounded random walk with a constant variance, and such dynamics is incorporated in the price formula to form our DRA model. We show numerically that our model reproduces most of the “stylized” facts observed in the real data, suggesting that dynamic risk aversion is an important mechanism for understanding the dynamics of the financial market and the resultant financial time series.     

“Rulers ruled by women”: an economic analysis of the rise and fall of women’s rights in ancient Sparta

Until modern times, most women possessed relatively few formal rights. The women of ancient Sparta were a striking exception. Although they could not vote, Spartan women reportedly owned 40 percent of Sparta’s agricultural land, and enjoyed other rights that were equally extraordinary. We offer a simple economic explanation for the Spartan anomaly. The defining moment for Sparta was its conquest of a neighboring land and people, which fundamentally changed the marginal products of Spartan men’s and Spartan women’s labor. To exploit the potential gains from a reallocation of labor—specifically, to provide the appropriate incentives and the proper human capital formation—men granted women property (and other) rights. Consistent with our explanation for the rise of women’s rights, when Sparta lost the conquered land several centuries later, the rights for women disappeared. Two conclusions emerge that may help explain why women’s rights have been so rare for most of history. First, in contrast to the historical norm, the optimal (from the men’s perspective) division of labor among Spartans involved women in work that was not easily monitored by men. Second, the rights held by Spartan women may have been part of an unstable equilibrium, which contained the seeds of its own destruction. For helpful comments, we thank Yoram Barzel, Paul Cartledge, Beth Davenport, Dino Falaschetti, Nancy Folbre, Barbara Hanssen, Ron Johnson, Lea Kosnik, Francine Lafontaine, Dean Lueck, Sarah Pomeroy, Mark Ramseyer, Randy Rucker, Wendy Stock, Chris Stoddard, Werner Troesken, Doug Young, and seminar participants at Colby College, George Mason University, Montana State University, the Property and Environment Research Center, the University of Virginia, Wabash College, the 2006 meetings of the Economic History Association, and the 2007 meetings of the American Economic Association.     

An alternative formulation of Neyman’s smooth goodness of fit tests under composite alternatives

Summary We propose a natural extension of Neyman’s smooth goodness of fit tests under composite hypotheses. The components of our smooth tests are immediate analogues of the corresponding components in the completely specified null case. We show that, when testing for univariate normality, one of our smooth tests is similar to D’Agostino and Pearson’s (1973) statistic; when testing for multivariate normality, our smooth test for skewness is identical to Mardia’s (1970) measure of multivariate skewness; and, when testing for exponentiality, our simplest smooth test is equivalent to Greenwood’s (1946) statistic.     

The origins of the mean-variance approach in finance: revisiting de Finetti 65 years later

Abstract In a recent critical review of de Finetti’s paper “Il problema dei pieni’’, the Nobel Prize winner Harry Markowitz recognized the primacy of de Finetti in applying the mean-variance approach to finance, but pointed out that de Finetti did not solve the problem for the general case of correlated risks. We argue in this paper that a more fair sentence would be: de Finetti did solve the general problem but under an implicit hypothesis of regularity which is not always satisfied. Moreover, a natural extension of de Finetti’s procedure to non-regular cases offers a general solution for the correlation case and shows that de Finetti anticipated a modern mathematical programming approach to mean-variance problems. Mathematics Subject Classification (2000): 91B30, 90C20 Journal of Economic Literature Classification: G11, C61, B23, D81, G22     

Towards a framework for the elicitation of dilemmas

This paper covers the main findings of the doctoral research that was concerned with seeking to extend aspects of dilemma theory. In professional practice, the Trompenaars Hampden-Turner Dilemma Reconciliation Process^TM is a vehicle delivering dilemma theory in application. It informs a manager or leader on how to explore the dilemmas they face, how to reconcile the tensions that result, and how to structure the action steps for implementing the reconciled solutions. This vehicle forms the professional practice of the author who seeks to bring more rigor to consulting practice and thereby also contribute to theory development in the domain. The critical review of dilemma theory reveals that previous authors are inconsistent and variously invalid in their use of the terms ‘dilemma theory,’ ‘dilemma methodology,’ ‘dilemma process,’ ‘dilemma reconciliation,’ etc., and therefore an attempt is made to resolve these inconsistencies by considering whether ‘dilemmaism’ at the meta-level might be positioned as a new paradigm of inquiry for (management) research that embodies ontological, epistemological, and methodical premises that frame an approach to the resolution of real world business problems in (multi) disciplinary; (multi) functional and (multi) cultural business environments. This research offers contributions to knowledge, professional practice and theory development from the exploration of the SPID model as a way to make the elicitation of dilemmas more rigorous and structured and in the broader context of exploring ‘dilemmaism’ as a new paradigm of inquiry.     

On the Sub-optimality of Entry Fees in Auctions With Entry

We study a variation of Myerson’s (1981) model in which we allow for uncertainty about the number of bidders. In our set-up, an appropriate reserve price in a standard auction maximizes the auctioneer’s expected revenue. However, entry fees can be optimal only under some special conditions. Basically, there must be some homogeneity in bidders’ beliefs about the number of bidders and the auctioneer must know, to some extent, these beliefs.     

Analysis of Korean IT startups’ initial public offering and their post-IPO performance

Since the financial crisis in Korea, by focusing on core technology, IT startups have played an important role in the recovery of Korea’s economy through innovating technologies and creating new jobs. Even though there are many startups, it is not very common to reach the point of the initial public offering (IPO) and the post-IPO performance of the firms is mostly declining. Since it is rather difficult to apply conventional performance measures to very young firms, IPO has been used as a tool for performance evaluation. This study adopts the IPO as an early-stage measure for the performance of high technology startups. It is important to find out whether an earlier IPO of firms leads to a better performance and capability of firms. We investigate the relationship between the time to IPO of firms and their post-IPO performance for 3 years after their IPO by adopting samples of 79 information technology hardware firms founded after 1996 and listed between 2000 and 2004 in the KOSDAQ. Four determinant factors, including entrepreneurs’ experience, venture capital investment, startups’ technology sourcing, and technology portfolios which determine the firm’s time lag to getting to the IPO, are identified. The findings contain several results. First, the patent has positive effects on the firms’ performance after an IPO and on the firms’ growth before the IPO. Second, a faster technology acquisition via technology alliance has a positive influence on the firms’ IPO regardless of internal technologies. Third, concentrating on core technology, instead of diversifying can mature the startup firms faster. These indicate that a startup’s efficient initial strategy is critical for its performance and it enhances the credit and confidence of the market.     

The cost of Corporate Social Responsibility: the case of the Community Reinvestment Act

A Data Envelopment Analysis (DEA) cost minimization model is employed to estimate the cost to thrift institutions of achieving a rating of ‘outstanding’ under the anti-redlining Community Reinvestment Act, which is viewed as an act of voluntary Corporate Social Responsibility (CSR). There is no difference in overall cost efficiency between ‘outstanding’ and minimally compliant ‘satisfactory’ thrifts. However, the sources of cost inefficiency do differ, and an ‘outstanding’ rating involves annual extra cost of $6.547 million or, 1.2% of total costs. This added cost is the shadow price of CSR since it is not an explicit output or input in the DEA cost model. Before and after-tax rates of return are the same for the ‘outstanding’ and ‘satisfactory’ thrifts, which implies a recoupment of the extra cost. The findings are consistent with CSR as a management choice based on balancing marginal cost and marginal revenue. An incidental finding is that larger thrifts are less efficient.