“Entrepreneurial management” as a strategic choice in firm behavior : linking it with performance

Establishing the core principals of “entrepreneurial management” within an organization describes a certain strategic choice that affects a company in six dimensions, according to Stevenson (1983). Our aim is to empirically measure entrepreneurial management (it’s existence and degree) and to link this measured strategic choice (for or against) entrepreneurial management with firm performance. Our argument here is that companies that follow core principals of entrepreneurial management should outperform other more administrative firms in certain measures of strategic performance. This paper builds on an empirical investigation published by Brown, Davidson & Wiklund (2001), who have developed and tested a reliable measurement instrument for Stevenson’s definition of “entrepreneurial management” (Stevenson 1983, Stevenson & Jarillo 1990). In the first part of our paper we aim to replicate and to some extent improve this study. In the second part we link the measured degree of “entrepreneurial management” with firm performance. To our knowledge, even so Stevenson’s definition of entrepreneurial management is commonly acknowledged and Brown et al. (2001) developed a reliable instrument to empirically capture this behavioral approach to management, the construct of entrepreneurial management never before has been linked to firm performance in an empirical study. Since most papers on corporate entrepreneurship and firm performance are based on Covin & Slevin’s (1991) or Miller’s (1983) concept of entrepreneurial orientation, we contribute to the literature on corporate entrepreneurship in a novel way, given the fact that the entrepreneurial management dimensions measured in our study can theoretically and empirically be clearly distinguished from the construct of entrepreneurial orientation as defined by Covin & Selvin (1991).

Is a mango just a mango? Testing within-fruit oviposition site choice and larval performance of a highly polyphagous fruit fly

For fruit flies, fully ripe fruit is preferred for adult oviposition and is superior for offspring performance over unripe or ripening fruit. Because not all parts of a single fruit ripen simultaneously, the opportunity exists for adult fruit flies to selectively choose riper parts of a fruit for oviposition and such selection, if it occurs, could positively influence offspring performance. Such fine scale host variation is rarely considered in fruit fly ecology, however, especially for polyphagous species which are, by definition, considered to be generalist host users. Here we study the adult oviposition preference/larval performance relationship of the Oriental fruit fly, Bactrocera dorsalis (Hendel) (Diptera: Tephritidae), a highly polyphagous pest species, at the “within-fruit” level to see if such a host use pattern occurs. We recorded the number of oviposition attempts that female flies made into three fruit portions (top, middle and bottom), and larval behavior and development within different fruit portions for ripening (color change) and fully-ripe mango, Mangifera indica L. (Anacardiaceae). Results indicate that female B. dorsalis do not oviposit uniformly across a mango fruit, but lay most often in the top (i.e., stalk end) of fruit and least in the bottom portion, regardless of ripening stage. There was no evidence of larval feeding site preference or performance (development time, pupal weight, percent pupation) being influenced by fruit portion, within or across the fruit ripening stages. There was, however, a very significant effect on adult emergence rate from pupae, with adult emergence rate from pupae from the bottom of ripening mango being approximately only 50% of the adult emergence rate from the top of ripening fruit, or from both the top and bottom of fully-ripe fruit. Differences in mechanical (firmness) and chemical (total soluble solids, titratable acidity, total non-structural carbohydrates) traits between different fruit portions were correlated with adult fruit utilisation. Our results support a positive adult preference/offspring performance relationship at within-fruit level for B. dorsalis. The fine level of host discrimination exhibited by B. dorsalis is at odds with the general perception that, as a polyphagous herbivore, the fly should show very little discrimination in its host use behavior.

Assessing the impact of transit and personal characteristics on mode choice of TOD users

Comparison are required to understand transport benefits of Transit Oriented Developments (TODs). Mode shares of TOD users need to be understood. Accurate travel demand models for TODs are needed.

Corrupt police networks : uncovering hidden relationship patterns, functions and roles

This article applies social network analysis techniques to a case study of police corruption in order to produce findings which will assist in corruption prevention and investigation. Police corruption is commonly studied but rarely are sophisticated tools of analyse engaged to add rigour to the field of study. This article analyses the ‘First Joke’ a systemic and long lasting corruption network in the Queensland Police Force, a state police agency in Australia. It uses the data obtained from a commission of inquiry which exposed the network and develops hypotheses as to the nature of the networks structure based on existing literature into dark networks and criminal networks. These hypotheses are tested by entering the data into UCINET and analysing the outcomes through social network analysis measures of average path distance, centrality and density. The conclusions reached show that the network has characteristics not predicted by the literature.

Multiscale analysis of protein functions and stochastic modelling of gene transcriptional regulatory networks

Genomic and proteomic analyses have attracted a great deal of interests in biological research in recent years. Many methods have been applied to discover useful information contained in the enormous databases of genomic sequences and amino acid sequences. The results of these investigations inspire further research in biological fields in return. These biological sequences, which may be considered as multiscale sequences, have some specific features which need further efforts to characterise using more refined methods. This project aims to study some of these biological challenges with multiscale analysis methods and stochastic modelling approach. The first part of the thesis aims to cluster some unknown proteins, and classify their families as well as their structural classes. A development in proteomic analysis is concerned with the determination of protein functions. The first step in this development is to classify proteins and predict their families. This motives us to study some unknown proteins from specific families, and to cluster them into families and structural classes. We select a large number of proteins from the same families or superfamilies, and link them to simulate some unknown large proteins from these families. We use multifractal analysis and the wavelet method to capture the characteristics of these linked proteins. The simulation results show that the method is valid for the classification of large proteins. The second part of the thesis aims to explore the relationship of proteins based on a layered comparison with their components. Many methods are based on homology of proteins because the resemblance at the protein sequence level normally indicates the similarity of functions and structures. However, some proteins may have similar functions with low sequential identity. We consider protein sequences at detail level to investigate the problem of comparison of proteins. The comparison is based on the empirical mode decomposition (EMD), and protein sequences are detected with the intrinsic mode functions. A measure of similarity is introduced with a new cross-correlation formula. The similarity results show that the EMD is useful for detection of functional relationships of proteins. The third part of the thesis aims to investigate the transcriptional regulatory network of yeast cell cycle via stochastic differential equations. As the investigation of genome-wide gene expressions has become a focus in genomic analysis, researchers have tried to understand the mechanisms of the yeast genome for many years. How cells control gene expressions still needs further investigation. We use a stochastic differential equation to model the expression profile of a target gene. We modify the model with a Gaussian membership function. For each target gene, a transcriptional rate is obtained, and the estimated transcriptional rate is also calculated with the information from five possible transcriptional regulators. Some regulators of these target genes are verified with the related references. With these results, we construct a transcriptional regulatory network for the genes from the yeast Saccharomyces cerevisiae. The construction of transcriptional regulatory network is useful for detecting more mechanisms of the yeast cell cycle.

Attribute exclusion strategies in airline choice : accounting for exogenous information on decision maker processing strategies in models of discrete choice

We examine the impact of individual-specific information processing strategies (IPSs) on the inclusion/exclusion of attributes on the parameter estimates and behavioural outputs of models of discrete choice. Current practice assumes that individuals employ a homogenous IPS with regards to how they process attributes of stated choice (SC) experiments. We show how information collected exogenous of the SC experiment on whether respondents either ignored or considered each attribute may be used in the estimation process, and how such information provides outputs that are IPS segment specific. We contend that accounting the inclusion/exclusion of attributes will result in behaviourally richer population parameter estimates.

Framework for assessing financial literacy and superannuation investment choice decisions

There is a worldwide trend towards rapidly growing defined contribution pension funds in terms of assets and membership, and the choices available to individuals. This has shifted the decisionmaking responsibility to fund members for managing the investment of their retirement savings. This change has given rise to a phenomenon where most superannuation fund members are responsible for either actively choosing or passively relying on their funds’ default investment options. Prior research identifies that deficiencies in financial literacy is one of the causes of inertia in financial decision-making and findings from international and Australian studies show that financial illiteracy is wide-spread. Given the potential significant economic and social consequences of poor financial decision-making in superannuation matters, this paper proposes a framework by which the various demographic, social and contextual factors that influence fund members’ financial literacy and its association with investment choice decisions are explored. Enhanced theoretical and empirical understanding of the factors that are associated with active/passive investment choice decisions would enable development of well-targeted financial education programs.

Sustainable assessment for large science classes : non-multiple choice, randomised assignments through a Learning Management System

This paper reports on the development of a tool that generates randomised, non-multiple choice assessment within the BlackBoard Learning Management System interface. An accepted weakness of multiple-choice assessment is that it cannot elicit learning outcomes from upper levels of Biggs’ SOLO taxonomy. However, written assessment items require extensive resources for marking, and are susceptible to copying as well as marking inconsistencies for large classes. This project developed an assessment tool which is valid, reliable and sustainable and that addresses the issues identified above. The tool provides each student with an assignment assessing the same learning outcomes, but containing different questions, with responses in the form of words or numbers. Practice questions are available, enabling students to obtain feedback on their approach before submitting their assignment. Thus, the tool incorporates automatic marking (essential for large classes), randomised tasks to each student (reducing copying), the capacity to give credit for working (feedback on the application of theory), and the capacity to target higher order learning outcomes by requiring students to derive their answers rather than choosing them. Results and feedback from students are presented, along with technical implementation details.

Design of experiments for bivariate binary responses modelled by Copula functions

Optimal design for generalized linear models has primarily focused on univariate data. Often experiments are performed that have multiple dependent responses described by regression type models, and it is of interest and of value to design the experiment for all these responses. This requires a multivariate distribution underlying a pre-chosen model for the data. Here, we consider the design of experiments for bivariate binary data which are dependent. We explore Copula functions which provide a rich and flexible class of structures to derive joint distributions for bivariate binary data. We present methods for deriving optimal experimental designs for dependent bivariate binary data using Copulas, and demonstrate that, by including the dependence between responses in the design process, more efficient parameter estimates are obtained than by the usual practice of simply designing for a single variable only. Further, we investigate the robustness of designs with respect to initial parameter estimates and Copula function, and also show the performance of compound criteria within this bivariate binary setting.

The impact of taxes on optimal portfolio choice : an Australian study

Taxes are an important component of investing that is commonly overlooked in both the literature and in practice. For example, many understand that taxes will reduce an investment’s return, but less understood is the risk-sharing nature of taxes that also reduces the investment’s risk. This thesis examines how taxes affect the optimal asset allocation and asset location decision in an Australian environment. It advances the model of Horan & Al Zaman (2008), improving the method by which the present value of tax liabilities are calculated, by using an after-tax risk-free discount rate, and incorporating any new or reduced tax liabilities generated into its expected risk and return estimates. The asset allocation problem is examined for a range of different scenarios using Australian parameters, including different risk aversion levels, personal marginal tax rates, investment horizons, borrowing premiums, high or low inflation environments, and different starting cost bases. The findings support the Horan & Al Zaman (2008) conclusion that equities should be held in the taxable account. In fact, these findings are strengthened with most of the efficient frontier maximising equity holdings in the taxable account instead of only half. Furthermore, these findings transfer to the Australian case, where it is found that taxed Australian investors should always invest into equities first through the taxable account before investing in super. However, untaxed Australian investors should invest their equity first through superannuation. With borrowings allowed in the taxable account (no borrowing premium), Australian taxed investors should hold 100% of the superannuation account in the risk-free asset, while undertaking leverage in the taxable account to achieve the desired risk-return. Introducing a borrowing premium decreases the likelihood of holding 100% of super in the risk-free asset for taxable investors. The findings also suggest that the higher the marginal tax rate, the higher the borrowing premium in order to overcome this effect. Finally, as the investor’s marginal tax rate increases, the overall allocation to equities should increase due to the increased risk and return sharing caused by taxation, and in order to achieve the same risk/return level as the lower taxation level, the investor must take on more equity exposure. The investment horizon has a minimal impact on the optimal allocation decision in the absence of factors such as mean reversion and human capital.