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Measures of personality and organizational climate were subjected to three different analytical methods that extract patterns from data: Discriminant, Classification and Regression Trees, and neural network classification analysis. Risk, openness, rewards, and neuroticism (rather than conscientiousness) emerged as key variables in differentiating among three similar work groups. Results of the analyses support the central hypothesis of ASA theory of greater variance in personality across compared to within organizations and an interactionist paradigm between person and environment. Implications for ASA theory and for personnel selection are discussed.

Many attempts have been made to integrate communication with other properties of organisations. Frameworks and models have been developed by Galbraith (1977, 1973), Tushman (1979), Tushman and Nadler (1978), and Penley (1982). This study proposes to continue the line of research by considering additional aspects of the organisational environment in addition to various communication variables.

Uses qualitative response models of occupational choice to investigate differences in the occupational structures of minority workers relative to white men. Compares the accuracy of multinomial logit and multiple discriminant analyses in predicting occupational distributions. Further, investigates whether these models yield consistent estimates of the level of occupational segregation of minority workers. The results suggest that logit and discriminant analysis are equally accurate and stable methods for comparing occupational structures across groups of workers.

An attempt is made in this paper to discriminate among four groups of transfer pricing methods namely: market price, cost, negotiation, and other methods, according to the transfer pricing objectives and other environmental issues (i.e. transfer pricing determinants). Discrimination is attempted on the data collected in the study of UK companies described in the earlier paper “A Survey of UK Transfer Pricing Practice — Some Preliminary Findings”. The aim of the discrimination is to evaluate the relationship between the transfer pricing method and transfer pricing determinants. This evaluation enables the prediction of transfer pricing method for new cases according to the company's perception of the relative importance of the transfer pricing determinants.

Like all other natural fibers, the physical properties of cotton also vary owing to changes in the related genetic and environmental factors, which ultimately affect both the mechanics involved in yarn spinning and the quality of the yarn produced. However, information is lacking about the degree of influence that those properties impart on the spinnability of cotton fiber and the strength of the final yarn. This paper aims to discuss this issue.

This paper proposes the application of discriminant analysis as a multivariate regression tool to develop the causal relationships between six cotton fiber properties, i.e. fiber strength (FS), fiber fineness (FF), upper half mean length (UHML), uniformity index (UI), reflectance degree and yellowness and spinning consistency index (SCI) and yarn strength (YS) along with the determination of the respective contributive roles of those fiber properties on the considered dependent variables.

Based on the developed discriminant function, it can be revealed that FS, UI, FF and reflectance degree are responsible for higher YS. On the other hand, with increasing values of UHML and fiber yellowness, YS would tend to decrease. Similarly, SCI would increase with higher values of FS, UHML, UI and reflectance degree, and its value would decrease with increasing FF and yellowness.

The discriminant functions can effectively envisage the contributive role of each of the considered cotton fiber properties on SCI and YS. The discriminant analysis can also be adopted as an efficient tool for investigating the effects of various physical properties of other natural fibers on the corresponding yarn characteristics.

The purpose of this paper is to develop a model for assessing the audit evidence of the going-concern (GC) assumptions underlying the preparation of financial statements.

This research analyses 678 audit opinions of Italian listed firms from 2007 to 2016 and uses a multiple linear discriminant analysis to create a GC score, which includes variables suggested by the international standards on auditing (ISA) 570 and by literature on GC.

The model provides three cut-off scores which can orient auditors towards issuing the most appropriate GC audit opinions (unmodified opinion, unmodified opinion, which includes emphases of matter, qualified opinion or disclaimer of opinion).

The development of the model is mainly based on public data and does not assess confidential information that is not disclosed in audit opinions.

This model can enable auditors to identify the most appropriate GC opinion and align auditor’s opinions in similar circumstances, thereby reducing their reliance on discretion and increasing the reliability of their judgement with a higher degree of accuracy. Moreover, this research lists additional events or conditions that may individually or collectively cast significant doubt on GC assumptions.

This study goes beyond the traditional decision-making process, apparently binary in nature, between “continuity” and “failure” or between “unmodified” and “modified” opinions. It is conceived to detect the different degrees of uncertainty that affect GC evaluations to orient auditors’ professional judgements.

The purpose of this paper is to examine whether differences in the characteristics, financial knowledge and financial attitudes of a migrant group exert significant influence on the likelihood of their financial literacy level.

A multiple discriminant analysis incorporating post-estimation analyses is employed, where the financial literacy level is used to identify a priori clusters.

The results showed that a significant discriminant function could be estimated to classify the study cohort into three financial literacy groupings. The paper concludes with recommendations for future research to address financial literacy, taking into account differences in characteristics, financial attitudes and financial knowledge of different cohort groups.

Although the research targets Vietnamese migrants, no claims can be made regarding the representation of other migrant groups as a whole. The research has implications with respect to programs to improve financial literacy levels of those most at need. This paper provides recommendations for future research in this area.

The paper provides one of the few studies of an Australian migrant cohort with respect to financial literacy. The study utilises a multiple discriminant analysis incorporating post-estimation analysis to examine, and compare, the factors that influence a person’s financial literacy level.

As they operate in complex schools principals must allocate their attention to numerous responsibilities. This paper seeks to ask three questions: how do principals allocate their attention across major realms of responsibility; to what extent do principals in different contexts emphasize different realms of responsibility; and to what extent do individual attributes affect how principals allocate their attention across realms?

A cluster analysis is applied to data from a daily log of principal practices to identify principals who allocate their attention across major realms of responsibility in similar ways. With the three groups identified in the cluster analysis a discriminant analysis is then used to examine the individual attributes of the principals and the contexts within which these groups work to identify those individual characteristics and contextual conditions that best predict each principal's cluster membership.

The data from the log indicate that principals are not as fragmented across numerous realms of responsibility as previous research suggests. Some principals do spend considerable time on instructional leadership. The cluster analysis revealed three groups: “Eclectic” Leaders (their activities are distributed more evenly across different activities); Instructional Leaders (they focused most on Instructional Leadership); and Student Leaders (they emphasized student affairs). In the paper's discriminant analyses no individual attributes distinguished amongst the three types of principals; only contextual conditions predicted membership.

The results point to the influence that context plays on school principals' practice; principals appear to prioritize and focus their actions under more challenging contextual conditions. The next step in the analysis is to determine how the leadership clusters and principal practices relate to important school outcomes.

The paper provides useful information on influences on school principals' practice.

How the application of multivariate analysis can aid charities in improving their fund raising appeals is demonstrated. Using a major UK charity as an example and analysing the socio‐demographic, awareness and psychographic profiles of nearly 500 respondents, the scope for market segmentation and a priori identification of potential donors is explored.

As marketing knowledge and market competition increase, so too does the need for better segmentation. Psychographics can offer greater insights into customer behaviour, but the procedures for identifying psychographic segments are complicated and this may be inhibiting its use. Explores the process of identifying psychographic risk segments in purchasers of consultancy services by taking the reader stepwise through the necessary statistical procedures. Part 1 considers factor and cluster analysis, while Part 2 looks at multiple discriminant analysis. The analysis shows that three potential risk segments exist which differ demographically and in their risk perceptions.