Advances in Doctoral Research in Management

The following sections are included:

• Aims and Scope

• CONTENTS

• ACKNOWLEDGMENTS

• Editorial Board

• ABOUT THE EDITORS

• LIST OF CONTRIBUTORS

• EDITORIAL

Despite organisational romance being heralded as an important managerial issue 30 years ago by Quinn (1977) there remains a lack of academic research exploring non-platonic workplace relationships. In light of this discrepancy, this chapter seeks to move organisational romance away from the managerialist rhetoric which adopts a rationalist, prescriptive approach, and towards the sexuality and organisation literature. Workplace romance can be thus viewed as an integral workplace dynamic, imbued with issues of power and politics at both a macro and local level. To explore how this may be played out in practice, data from 48 interviews were subjected to a number of narrative analysis techniques to demonstrate how organisational romance is discussed, negotiated, and played out in a workplace.

Extreme value theory (EVT) methods are used to investigate the asymptotic distri-bution/s of the extreme minima and maxima of the Athens Stock Exchange daily returns over the period 1976–2001. Innovative aspects of this study include: (1) the generalised extreme value and generalised logistic distributions are considered, (2) L-moments ratio diagrams are used to identify the distribution/s most likely to fit the extreme daily returns adequately, (3) the probability weighted moments method is used to estimate the parameters of the distribution/s, and (4) the Anderson–Darling goodness of fit test is employed to test the adequacy of fit. The generalised logistic distribution is found to provide adequate descriptions of the behaviour of both the extreme minima and maxima over the period studied; however, the asymptotic distributions of extremes appear to become less fat-tailed over time, implying that the probability of a large daily return occurring is decreasing.

This study examines the effectiveness of the Naïve Bayes Rule relative to that of five other popular algorithms in constructing scorecards that correctly discriminate between good-risk and bad-risk credit applicants. Scorecard performance is assessed on a real-world data sample by both the percentage of correctly classified cases and the more relevant criterion of bad rate among accepts. Naive Bayes is found to produce the worst-performing scorecard under both measures used.

Making the most of the industrial network to reduce management costs and increase competitiveness has gained a lot of attention among enterprises lately. In traditional market research methods, the approach has always been to put the emphasis on the data of a single value without considering the complexity of human thoughts. Thus, it is the purpose of this paper to first define fuzzy mode, fuzzy expect value and fuzzy χ² test. Then, a new market survey is proposed to develop a more efficient survey analysis to examine the characteristics of the fuzzy questionnaire and sample material. A comparison between the fuzzy χ² test and traditional χ² test will be carried on at the end.

This study examines the determinants of likelihood of consideration of counterfeit branded luxury handbags in the context of nondeceptive counterfeiting. The effects of consumer-perceived brand personality, benefits, product attributes, perceived risks, and consumer demographic variables are anticipated and explored. Focus groups are used to generate criteria which consumers used to evaluate studied brands, and an interview survey is used to collect data for the main study. SPSS and R software are used to analyze data. Generalised linear model analyses reveal that the brand personality is the dominant factor in determining the likelihood of the consideration of the counterfeit branded luxury products. In general, the perceived risks and the demographic variables do not appear to be significantly influential on the formation of the consideration set in the context of nondeceptive counterfeiting. In addition, factor analysis results provide empirical evidence on Plummer's (2000, 1985). Brand image components notion and further suggest that the perceived risks shall not be regarded as part of the benefit/consequence component of brand image concept.

The main objective of this chapter is to examine the invariance of Richins and Dawson's (1992) previously validated three-factor materialism model scale across different cultural groups of respondents and to analyse and estimate the presence of materialistic values among Europeans, more precisely in samples from Germany, Spain, and Portugal. Through Richins and Dawson's (1992) materialism values scale, we checked and cross-examined the materialistic dimensions among the young people of the countries referred to using Structural Equation Modeling. There are different levels and sort of materialism among the three European countries.

This study develops a pricing framework that focuses on relationship-building — a factor that has been largely ignored in the pricing literature. First, a case-study method has been employed to better understand how a production-oriented company sets prices for its products. Then a framework has been developed which incorporates the service component in the pricing equation. The results of this research suggest that factoring in the price for services offered can enhance relationship management, thus having a positive impact on the company's business performance.

Statistical inference on the parameters of regression models requires special precautions when the error term is heteroskedastic and/or non-normal. In this case, although conventional test statistics do not follow t and F distributions, simulation methods can be used to draw inferences. We discuss two methods: the wild bootstrap and the generalised lambda distribution. By employing both artificial and real-world data from the National Footbal League, we show that these methods may prove particularly useful in hypothesis testing.

The objective of this chapter is to illustrate the method of DNA computing and based on this understanding, to explain the application to group controlling of elevators.

Many non-deterministic polynomial time (NP) complete problems are solved using heuristic and approximate methods instead of providing a complete solution or mathematical optimal approaches. The central reason comes from the huge computation time needed to solve such combinatorial problems by means of a conventional silicon computer based on von Neumann's architecture. To solve such NP complete problems, this chapter provides an alternative and innovative method based on nano size of DNA to obtain infinitively in a life such as silicon. This chapter is an introductory explanation.

The group management is treated as an example of its application. Inefficient situations have been encountered such that all elevators are moving in the same direction or that all elevators arrive at the same floor even during rush hours in the morning. To resolve such situations all elevators should be controlled to assign the best elevator to passengers according to time-to-time change of passengers. The group control system is employed in selection of driving patterns according to the change of traffic volumes or driving management in accidents. Such a group control realises comfortable, safe, and economical management of elevators. The objective of this chapter is to apply DNA computing to calculate complex and huge combinatorial problems of a group of elevators and huge number of floors. The optimal solution will be presented to the group control of elevators on the basis of the DNA computing.

The following sections are included:

• INDEX