APPLICATIONS OF SPECTRAL ANALYSIS

The basic concepts and application of spectral analysis are explained. Stationary time series and autocorrelation are first defined. Autocorrelation is related to the familiar concepts of variance and covariance. The use of autocorrelation analysis is explained in estimating the interdependent relationship of a time series over discrete time lags. In order to measure the behavior of the time series using autocorrelation, it would be necessary to examine a very large number of autocorrelation lags. Alternatively, the technique of Fourier analysis can be used to transform the autocorrelation function of the time series into a continuous function, termed a spectrum. The spectrum has a one to one correspondence to the autocorrelation for the time series and has the advantage of representing all possible autocorrelations over the discrete time lags. The spectrum can then be examined as a measure of the behavior of the time series. Spectral analysis indicates the reliability of the analysis of autocorrelated variables when familiar statistical techniques such as sample means and variances are used. The application of spectral analysis to management science problems in three general areas is illustrated: (1) inventory demand, (2) transportation simulation, and (3) stock market price behavior. Spectral analysis was used to detect cycles and trends in the data. Analyses were focused on the spectrum which provides a measure of the relative contribution of cycles in a band of frequencies to the total variance of the data.     

USING DUMMY VARIABLES TO CHECK FOR ROUNDING ERROR IN COMPUTERIZED REGRESSION PROGRAMS*

After a brief review of the role of dummy variables in regression analysis and the current state-of-the art in rounding/truncation error detection in computerized least squares programs, this paper presents a theorem that can be used to detect this type of error whenever an analyst is running a regression program that has one (or more) dummy variables as independent variables.     

EXPLORING MARKET PRICING STRATEGIES VIA DYNAMIC PROGRAMMING

Price determinants as well as strategies can be studies by use of simulation, particularly if cost and price relationships can be related to market activity [1] [9] [11]. But, through the use of dynamic programming, given the market conditions, one can extend the analysis to include an optimal strategy. This paper describes a dynamic programming approach to studying price strategy. A model is developed to show that in a market characterized by cost/volume and price/volume relationships, profitability can be extended beyond that resulting from a dominant market strategy to an optimal maximizing strategy. Extension of the model is suggested for studying (a) sensitivity of a strategy (solution) to price level and cost changes, (b) optimal timing of withdrawal, and (c) present value analysis.     

DETERMINING OPTIMAL SHIFT SCHEDULES FOR TELEPHONE TRAFFIC EXCHANGE OPERATORS

A branch and bound algorithm is presented for determining the minimum number of telephone operators, and their shift schedules, required to meet demand that varies over a 24 hour operating period. An integer linear programming formulation is used, and the algorithm is described in terms of its separation, relaxation, fathoming, and branching procedures. Computational results are provided, using actual operating data. The results indicate that practical sized problems can be solved by the algorithm, involving as many as 100 different shift type variables and demand profiles typical of those encountered in many telephone traffic exchanges.     

Differentiated leader–member exchange,justice climate,and performance: Main and interactive effects

Leaders form different quality leader–member exchange (LMX) relationships with their subordinates. This variable treatment termed LMX differentiation can have negative effects on individuals' behavior and attitudes. In this study, we examined the cross-level main effect of justice climate on task performance and the moderating role of justice climate on the relationship between LMX differentiation and task performance. We tested these two hypotheses using a field study of 90 subordinates nested under 27 supervisors. Procedural justice climate, not distributive justice climate, was found to positively influence subordinate task performance. Further, distributive justice climate, not procedural justice climate, was found to moderate the LMX differentiation–task performance relationship; such that the relationship was positive when distributive justice climate was high and negative when distributive justice climate was low. Findings and future directions are discussed.     

Ambidextrous Organizational Culture,Contextual Ambidexterity and New Product Innovation: A Comparative Study of UK and Chinese High‐tech Firms

Contextual ambidexterity is of paramount importance for new product innovation and organizational success, particularly in high‐tech firms operating in a dynamic environment. Whilst it is recognized that contextual ambidexterity is grounded in organizational culture, existing research has not crystallized what kind of organizational culture enables contextual ambidexterity and consequently new product innovation. In this paper, drawing on data from 150 UK and 242 Chinese high‐tech firms, we conceptualize ambidextrous organizational culture as a higher‐order construct consisting of organizational diversity and shared vision, and examine its impacts on contextual ambidexterity and consequently on new product innovation outcomes. Using structural equation modelling, we find significant relationships between ambidextrous organizational culture, contextual ambidexterity and new product innovation outcomes; contextual ambidexterity mediates the relationship between ambidextrous organizational culture and new product innovation outcomes. Our findings also suggest that the above relationships are robust in the UK–China comparative research context, and that contextual ambidexterity and new product innovation outcomes are dependent on business unit level heterogeneity (i.e. ambidextrous organizational culture and research and development strength) rather than industry or cross‐cultural differences.     

A Diversity Index for Model Space Selection in the Estimation of Benchmark and Infectious Doses via Model Averaging

In chemical and microbial risk assessments, risk assessors fit dose‐response models to high‐dose data and extrapolate downward to risk levels in the range of 1–10%. Although multiple dose‐response models may be able to fit the data adequately in the experimental range, the estimated effective dose (ED) corresponding to an extremely small risk can be substantially different from model to model. In this respect, model averaging (MA) provides more robustness than a single dose‐response model in the point and interval estimation of an ED. In MA, accounting for both data uncertainty and model uncertainty is crucial, but addressing model uncertainty is not achieved simply by increasing the number of models in a model space. A plausible set of models for MA can be characterized by goodness of fit and diversity surrounding the truth. We propose a diversity index (DI) to balance between these two characteristics in model space selection. It addresses a collective property of a model space rather than individual performance of each model. Tuning parameters in the DI control the size of the model space for MA.     

Work as a cure for mental illnesses? Opportunism and seeking ways in psychology and psychiatry in the first decades of state socialism in Hungary

ABSTRACT

In Hungary, until the end of the 1940s, there were two main established methods of occupying the mentally ill who were fit for work. From the end of the nineteenth century, a lesser number of patients underwent work therapy in mental asylums, whereas the others were treated with so-called family therapy (otherwise known as the heterofamilial system), exploiting the capacities of families in the countryside. As an important part of this, the mentally ill helped in housekeeping and agricultural work. However, following the political and ideological turn of 1948, the latter form of treatment became debated, and then it was gradually superseded. Parallel to this process, work therapy came to be the most popular type of treatment for mental illnesses, as work formed the basis of the ideology of the communist state, and thus, healing through work harmonized with the general tendencies of the era. This article examines texts related to work therapy published in neurological–psychiatric and psychological journals and monographs between 1954 and 1964. However, although work therapy appeared to be the “handmaiden of ideology,” and even though it was supposed to fulfil a particular role, in reality, the role and perception of work therapy were a lot more complicated.