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Social exchange theory literature posits that a relationship is dependent on the strength of its social interactions and is clear upon the role of trust, power and commitment within that relationship as a means of value creation. However, an understanding of the nature of experiences, expectations, motivations and perceptions as components of the value derivation process are missing. SET literature does not identify these components as antecedents to value creation but central to value derived. This research builds upon that premise to give understanding into how value is derived from arts sponsorships.

A qualitative exploratory approach is used to research arts sponsorships in New Zealand of differing size, duration and profile.

This research gives understanding into the nature of experiences, expectations, motivations and perceptions as components parts of value derivation and their interactions resulting in the creation of an iterative value derivation model of the life cycle of an arts sponsorship relationship from a business perspective.

This research has relevance for both academics and marketing managers involved in arts sponsorship. The findings from this research can be used as an analytical tool to help businesses when evaluating their arts sponsorship.

Companies are increasingly bringing personnel together into teams from different countries, physically and/or electronically, to develop products for multiple or worldwide markets. Called global new product teams (GNPTs), these groups face significant challenges, including cultural diversity. Differing cultural values can lead to conflict, misunderstanding, and inefficient work styles on the one hand, and strong idea generation and creative problem solving on the other. A study was conducted to identify team compositions that would optimize the effects of national culture so that product development outcomes are favorable. This began by developing a theoretical framework describing the impact of national culture on product development tasks. The framework was then translated into several mathematical models using analytical derivations and comparative statics. The models identify the levels and variances of culture values that maximize product development success by simultaneously considering four relevant dimensions of GNPT performance. Next, the utility of these models was tested by means of numerical simulations for a range of team scenarios. Concludes by drawing implications of the findings for managers and researchers.

The US Department of Agriculture (USDA), Soil Conservation Services (SCS) rainfall-runoff model has been applied worldwide since 1954 and adopted by Malaysian government agencies. Malaysia does not have regional specific curve numbers (CN) available for the use in rainfall-runoff modelling, and therefore a SCS-CN practitioner has no option but to adopt its guideline and handbook values which are specific to the US region. The selection of CN to represent a watershed becomes subjective and even inconsistent to represent similar land cover area. In recent decades, hydrologists argue about the accuracy of the predicted runoff results from the model and challenge the validity of the key parameter, initial abstraction ratio coefficient (λ) and the use of CN. Unlike the conventional SCS-CN technique, the proposed calibration methodology in this chapter discarded the use of CN as input to the SCS model and derived statistically significant CN value of a specific region through rainfall-runoff events directly under the guide of inferential statistics. Between July and October of 2004, the derived λ was 0.015, while λ = 0.20 was rejected at alpha = 0.01 level at Melana watershed in Johor, Malaysia. Optimum CN of 88.9 was derived from the 99% confidence interval range from 87.4 to 96.6 at Melana watershed. Residual sum of square (RSS) was reduced by 79% while the runoff model of Nash–Sutcliffe was improved by 233%. The SCS rainfall-runoff model can be calibrated quickly to address urban runoff prediction challenge under rapid land use and land cover changes.

The purpose of this paper is to present a methodology based on the transactional asset pricing approach (TAPA) and to illustrate the application of TAPA within the context of professional property valuation.

The TAPA is a novel analytical valuation methodology recasting the traditional derivations of the income approach techniques, including DCF, from a transactional perspective based on the principle of inter-temporal transactional equity, instead of the conventional investor-specific view originating from I. Fisher (1907, 1930).

The authors present DCF analysis as a specific case of a more general TAPA approach to valuation under the income method. This also leads to novel analytical derivations of the Direct income capitalization, Gordon, Inwood, Hoskold and Ring models. Based on the TAPA framework, the authors also research the value-enhancing effects of benchmark market volatility on the subject property value and conclude that such effects can be statistically significant depending on the DCF analysis period.

The research has a direct bearing on time-variable discount rate forecasting capabilities, as it uses a time-variant structure for the discount rates.

Using the US Case-Shiller and BLS rental indices as a valuation benchmark, the paper contains an example of applying the general TAPA framework to value a notional property under a TAPA’s DCF version. Such property valuations can be easily replicated in practice – especially in the context of equitable/fair value determination under the International Valuation Standards Council valuation standards.

TAPA is a deductive principles-based theory of asset valuation especially fit for the transactional and illiquid asset valuation contexts – thus enabling a more efficient pricing for such assets in a sense of reflecting the transactional interests of the parties more closely than achievable under the conventional valuation methods.

TAPA is an original filiation of research with roots going as far back as Aristotelian Catallactics. It contains analytical formalizations of certain transactional equity principles.

We derive marginal conditions of optimality (i.e., Euler equations) for a general class of Dynamic Discrete Choice (DDC) structural models. These conditions can be used to estimate structural parameters in these models without having to solve for approximate value functions. This result extends to discrete choice models the GMM-Euler equation approach proposed by Hansen and Singleton (1982) for the estimation of dynamic continuous decision models. We first show that DDC models can be represented as models of continuous choice where the decision variable is a vector of choice probabilities. We then prove that the marginal conditions of optimality and the envelope conditions required to construct Euler equations are also satisfied in DDC models. The GMM estimation of these Euler equations avoids the curse of dimensionality associated to the computation of value functions and the explicit integration over the space of state variables. We present an empirical application and compare estimates using the GMM-Euler equations method with those from maximum likelihood and two-step methods.

The purpose of this research is to provide information about derivative bibliographic relationships in the online catalogue COBIB, to investigate size and complexity of bibliographic families and to determine whether bibliographic characteristics are associated with the extent of derivations.

A bibliographic entity consisting of a work and item is represented by bibliographic records. A random sample of records is converted into a sample of progenitor works and bibliographic families for each progenitor are constructed.

25.75 per cent of progenitor works are derivative; successive derivations with 67.02 per cent appear most frequently. The size of bibliographic families ranges from 1 to 16; older progenitors have larger families. The majority of families have one type of relationship; there is one case with four types. A large proportion, 59.06 per cent, of derivative relationships is not expressed explicitly by catalogue.

Research of bibliographic records representing more than one work is needed. It is also important to find out what catalogue users are looking for: a work or an item?

A model for COBIB is suggested; it enables an equal identification of works, items and relationships. A cataloguer must create an authority record for each work and link it with corresponding bibliographic records for items.

Information about relationships should be incorporated into the catalogue and corresponding records linked. Explicit control of derivative relationships would be of great help to catalogue users and would make information retrieval improved and more precise; it would also allow more efficient use of knowledge and library materials.

Several lessons learnt from a Bayesian analysis of basic macroeconomic time-series models are presented for the situation where some model parameters have substantial posterior probability near the boundary of the parameter region. This feature refers to near-instability within dynamic models, to forecasting with near-random walk models and to clustering of several economic series in a small number of groups within a data panel. Two canonical models are used: a linear regression model with autocorrelation and a simple variance components model. Several well-known time-series models like unit root and error correction models and further state space and panel data models are shown to be simple generalizations of these two canonical models for the purpose of posterior inference. A Bayesian model averaging procedure is presented in order to deal with models with substantial probability both near and at the boundary of the parameter region. Analytical, graphical, and empirical results using U.S. macroeconomic data, in particular on GDP growth, are presented.

A large‐strain/high‐deformation rate model for clay‐free sand recently proposed and validated in our work [1,2], has been extended to sand containing relatively small (< 15vol.%) of clay and having various levels of saturation with water. The model includes an equation of state which represents the material response under hydrostatic pressure, a strength model which captures material behavior under elastic‐plastic conditions and a failure model which defines conditions and laws for the initiation and evolution of damage/failure in the material. The model was validated by comparing the computational results associated with detonation of a landmine in clayey sand (at different levels of saturation with water) with their computational counterparts.