Reputation performance: a portfolio selection approach

This paper introduces a normative view on corporate reputation strategic management. Reputation performance is conceptualised as the outcome of complex processes and social interactions and the lack of a holistic reputation performance management framework is identified. In an attempt to fill this gap, a portfolio-based approach is put forward. Drawing on the foundations of modern portfolio theory we create a portfolio-based reputation management algorithmic model where reputation components and priorities are weighted by decision makers and shape organisational change in an attempt to formulate a corporate reputation strategy. The rationale of this paper is based on the foundational consideration of organisations as choosing he optimal strategy by seeking to maximise their reputation performance while maintaining organisational stability and minimising organisational risk.

Reputation Performance: a portfolio selection approach

This paper introduces a normative view on corporate reputation management; an algorithmic model for reputation-driven strategic decision making is proposed and corporate reputation is conceptualized as influenced by a selection among organizational priorities. A portfolio-based approach is put forward; we draw on the foundations of portfolio theory and we create a portfolio-based reputation management model where reputation components and priorities are weighted by decision makers and shape organizational change in an attempt to formulate a corporate reputation strategy. The rationale of this paper is based on the foundational consideration of organizations as choosing the optimal strategy by seeking to maximize performance on corporate reputation capital while maintaining organizational stability and minimizing organizational risk.

Higher-order moments in the theory of diversifying and portfolio composition

This paper examines the role of higher-order moments in portfolio choice within an expected-utility framework. We consider two-, three-, four- and five-parameter density functions for portfolio returns and derive exact conditions under which investors would all be optimally plungers rather than diversifiers. Through comparative statics we show the importance of higher-order risk preference properties, such as riskiness, prudence and temperance, in determining plunging behaviour. Empirical estimates for the S&P500 provide evidence for the optimality of diversification.

Language standardization in sociolinguistics and international business: Theory and practice across the table

This chapter addresses the issue of language standardization from two perspectives, bringing together a theoretical perspective offered by the discipline of sociolinguistics with a practical example from international business. We introduce the broad concept of standardization and embed the study of language standardization in the wider discussion of standards as a means of control across society. We analyse the language policy and practice of the Danish multinational, Grundfos, and use it as a “sociolinguistic laboratory” to “test” the theory of language standardization initially elaborated by Einar Haugen to explain the history of modern Norwegian. The table is then turned and a model from International Business by Piekkari, Welch and Welch is used to illuminate recent Norwegian language planning. It is found that the Grundfos case works well with the Haugen model, and the International Business model provides a valuable practical lesson for national language planners, both showing that a “comparative standardology” is a valuable undertaking. More voices “at the table” will allow both theory and practice to be further refined and for the role of standards across society to be better understood.

Multivariate Appoximations to Portfolio Return Distribution

This article proposes a three-step procedure to estimate portfolio return distributions under the multivariate Gram-Charlier (MGC) distribution. The method combines quasi maximum likelihood (QML) estimation for conditional means and variances and the method of moments (MM) estimation for the rest of the density parameters, including the correlation coefficients. The procedure involves consistent estimates even under density misspecification and solves the so-called ‘curse of dimensionality’ of multivariate modelling. Furthermore, the use of a MGC distribution represents a flexible and general approximation to the true distribution of portfolio returns and accounts for all its empirical regularities. An application of such procedure is performed for a portfolio composed of three European indices as an illustration. The MM estimation of the MGC (MGC-MM) is compared with the traditional maximum likelihood of both the MGC and multivariate Student’s t (benchmark) densities. A simulation on Value-at-Risk (VaR) performance for an equally weighted portfolio at 1% and 5% confidence indicates that the MGC-MM method provides reasonable approximations to the true empirical VaR. Therefore, the procedure seems to be a useful tool for risk managers and practitioners.