The goal of this seminar is to introduce you to the use of computers in textual analysis. This involves three things. First, we will spend time talking about how to acquire textual material in such a way that it can be made computer readable. We will talk about gathering textual material from web-pages, on-line chat rooms, CD-ROMS, as well as other paper-based sources that can be scanned. Here our goal will be to think about the range of materials that might be investigated in this manner and to discuss the ways in which computer assisted analysis of these data would facilitate the research process. Second, we will talk about how to use the computer to manage this information. For example, we will look very closely at a variety of approaches to content analysis, including recent developments in syntactic grammar analysis. As part of this effort, we will focus on learning how to use the statistical analysis software SAS as a basic tool for content analysis of textual data.
 Third, we will discuss some of the ways in which textual data can be formally analyzed in order to measure and visualize basic structures of meaning which operate in discourse. This part of the course will lead us to explore questions such as what is meaning and how does interpretation operate? We will also focus here on a range of methods that can be used to study the relational patterns that are embedded within textual material. Included here are techniques such as factor analysis, multidimensional scaling, correspondence analysis, network analysis, lattice analysis and Boolean algebras.

Measuring Meaning Structures

In this paper we present an empirical analysis to test whether organisation configurations and management accounting systems change simultaneously. Using the original application of the fuzzy logic methodology, we analyse the level of development and implementation of the management accounting system and the organisational configuration on a sample of 501 Italian firms. Even though we employ a cross-sectional approach, the results may be interpreted according to the life cycle model. Our findings show that the evolution of the organisational configurations is not always coherent with the relevance assumed by management accounting systems. In particular, we find a large group of companies with a simple organisational configuration and a well-developed management accounting system. We interpret the presence of this cluster dynamically as an intermediate stage of growth towards more complex forms of organisation.

Management accounting systems and organisational structure

This paper uses a non-linear fuzzy logic procedure to empirically investigate the links between the real interest rate and aggregate investments in Sweden from 1950 to 1990. The economic environment is characterized by multivalued logic and an indicator for the economy-wide investment climate is derived strictly from the interest rate. It turns out that the fuzzy logic approach may reveal some empirical regularities that are not recognized by conventional linear regressions.

A fuzzy design of the willingness to invest in Sweden

The theory of approximate prices: analytical foundations of experimental cost-benefit analysis in a fuzzy-decision space

Most profit maximizing firms are aware that the boundary of the feasible set of technological opportunities is fuzzy. The neoclassical theory of the firm assumes that the boundary of the feasible set of technological opportunities is well-defined. We use a spheroidal neighborhood of a neoclassical profit maximizing equilibrium as a suitable approximation of a fuzzy input demand correspondence. Using trigonometric functions this spheroidal neighborhood is parameterized and a fuzzy cost function is generated. We use Nerlove's (1963) famous electric utility data to estimate a generalized Leontief cost function, with and without inclusion of a fuzz factor. The concept of fuzz used here seems to be in accord wi th Popper's (1973) notion of "plastic control" and Simon's notion of "bounded rationality". For concreteness we plot a fuzzy isoquant for Nerlove's data. We also report numerical estimates of scale elasticity, marginal cost, Hessian matrix, etc . .L. Introduction The traditional neoclassical theory of the firm generally accepts that firms maximize their objective function in a precisely defined technological environment. It is usually assumed that the producer kriows without any vagueness the boundary of his feasible set of technological opportunities. Technological uncertainty is treated in terms of the producer's rational expectations about the objective probability distribution of the random shock driving the technology. Actually, all producing agents cannot be expected to be well versed in probability theory when they make their production and sales decisions. It is now recognized in the literature that the observed behavior of agents can be imprecise or fuzzy. The fundamental premise of fuzzy set theory arises from a value-loaded description of the environment. According to the Paretian notion, tech-

Cost Analysis and Estimating

On fuzzy quantity and fuzzy isoquant

On the properties of fuzzy production correspondence

Input price, isocost and maximum output under fuzziness

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On fuzzy quantity and fuzzy isoquant

On the properties of fuzzy production correspondence

Input price, isocost and maximum output under fuzziness