Managing impressions using distorted graphs of income and earnings per share: The role of memory

This study investigates the role that memory plays in interpreting and using distorted graphs that mislead the user of the financial information. It draws upon the literatures concerning memory, impression management and effective graph design. In order to examine whether reliance on memory for distorted graphs leads to different impressions of the data, we conduct an experiment in which we manipulate the type of graph distortion and whether memory of the graph is required by the decision. We present evidence that individuals receiving misleading graphs are more likely to misinterpret underlying data trends and that memory moderates the effect depending upon the type of distortion used to mislead the individual. The resulting data interpretation errors lead to more positive judgments and investment decisions than would otherwise be warranted. Thus our findings suggest that graph distortions mislead users into incorrect conclusions about the underlying data and that these interpretation errors persist in memory and affect judgments and investment decisions. We extend the prior literature, which has not considered the direct effects of graph interpretation or the effects of memory, and provide a baseline for investigating the effects of memory on impression management.     

The Open2-Innova8ion Tool—A software tool for rating organisational innovation performance

The Open2-Innova8ion Tool is an interactive, multi-media, web-based software tool for rating organisational innovation performance. This tool was designed for organisations to use as an adaptation of the European Commission's work on developing empirical measures of national innovation performance with the Summary Innovation Index (SII). It is designed for users with experience of employment in an organisation, from senior managers to all types of employees, with an interest in rating the innovation performance of their organisation. The Tool is quick and intuitive to use, and provides textual feedback, together with graphic ratings using Google meters. Feedback is based on user perceptions of organisational indicators of Innovation Enablers, Activities, and Outputs to provide an overall rating of innovation performance; this can be compared with a self-rating of innovativeness to allow some interpretation of the congruence between the user and their organisation. This prototype Tool was trialled and evaluated during a workshop on low carbon vehicle innovation, with participants (innovators) representing organisations from the surface transport industry as part of the U-STIR programme with EU Framework 7 funding. This publically available web-tool has applications to education, training, and research http://design.open.ac.uk/itool/.     

Defining the Product in Social Marketing: An Analysis of Published Research

Social marketing, a discipline rooted in marketing principles, lacks consensus on the conceptual and operational definition of product. The purpose of this article was to explore how social marketing researchers have conceptualized the product and how this definition has influenced strategy development. A systematic review of 10 years of peer-reviewed literature resulted in 92 intervention-based articles. Nearly all studies focused on health-related behavior change. Few studies used marketing language and the three product level classification. One-third of studies provided a tangible product while communication was the only strategy in over half of the studies. The focus on behavior as the product and using communication as the primary or sole strategy may limit social marketing's effectiveness as the approach resembles other social change strategies. If social marketing research aims to advance its position as a social change strategy, a starting point should be to reexamine the definition of product.     

Externalities of public firm presence: Evidence from private firms' investment decisions

Public firms provide a large amount of information through their disclosures. In addition, information intermediaries publicly analyze, discuss, and disseminate these disclosures. Thus, greater public firm presence in an industry should reduce uncertainty in that industry. Following the theoretical prediction of investment under uncertainty, we hypothesize and find that private firms are more responsive to their investment opportunities when they operate in industries with greater public firm presence. Further, we find that the effect of public firm presence is greater in industries with better information quality and in industries characterized by a greater degree of investment irreversibility. Our results suggest that public firms generate positive externalities by reducing industry uncertainty and facilitating more efficient private firm investment.     

A flexible approach to parametric inference in nonlinear and time varying time series models

Many structural break and regime-switching models have been used with macroeconomic and financial data. In this paper, we develop an extremely flexible modeling approach which can accommodate virtually any of these specifications. We build on earlier work showing the relationship between flexible functional forms and random variation in parameters. Our contribution is based around the use of priors on the time variation that is developed from considering a hypothetical reordering of the data and distance between neighboring (reordered) observations. The range of priors produced in this way can accommodate a wide variety of nonlinear time series models, including those with regime-switching and structural breaks. By allowing the amount of random variation in parameters to depend on the distance between (reordered) observations, the parameters can evolve in a wide variety of ways, allowing for everything from models exhibiting abrupt change (e.g. threshold autoregressive models or standard structural break models) to those which allow for a gradual evolution of parameters (e.g. smooth transition autoregressive models or time varying parameter models). Bayesian econometric methods for inference are developed for estimating the distance function and types of hypothetical reordering. Conditional on a hypothetical reordering and distance function, a simple reordering of the actual data allows us to estimate our models with standard state space methods by a simple adjustment to the measurement equation. We use artificial data to show the advantages of our approach, before providing two empirical illustrations involving the modeling of real GDP growth.     

Consolidation in a wildlife tourism industry: the changing impact of whale shark tourist expenditure in the Ningaloo coast region

In this paper, we examine the expenditure of whale shark tour participants at Ningaloo Marine Park, Western Australia; the location of the world's first whale shark tourism industry, established in 1989. We demonstrate that in 2006, participants' expenditure in the region was $894 per trip, total expenditure was $6.0 million (all figures are in Australian dollars), and between $2.4 and $4.6 million would have been lost to the region if whale shark tourism did not exist. Our measure of participants' expenditure is substantially lower than the calculation of $2370 per participant from a previous study of whale shark tourists using data collected in 1995. We argue that this is consistent with a change in the types of wildlife tourists that participate in an activity as the industry reaches the point of consolidation. Our results also suggest that using old data to forecast wildlife tourists' expenditure needs to take into account the industry's stage of development. Copyright © 2009 John Wiley & Sons, Ltd.     

An exploratory study into airport choice factors for European low-cost airlines

Low-cost carriers are an increasingly important part of the European aviation industry. Airport choice is a crucial factor in determining their success or failure. While research has been conducted into airport choice factors, their relative rankings have not previously been investigated. This paper addresses this through an exploratory survey of eight European low-cost airlines. The paper finds that demand for low-cost services is the most important choice factor, with aeronautical charges ranked fourth. Further analysis reveals different requirements depending upon airline characteristics. This implies that airport managers need to tailor their service offering to individual low-cost airlines rather than treating the sector uniformly.     

Forecasting annual excess stock returns via an adaptive network‐based fuzzy inference system

In this study, an adaptive network‐based fuzzy inference system (ANFIS) and a neural network were tested for the ability of these techniques to forecast the annual excess returns of three large publicly traded companies from a time series of said returns. The predictive ability of these techniques was compared with that of an autoregressive moving average (ARMA) model. The Fair–Shiller test was used in the comparisons in order to obtain results that were not subjective and so that conclusions could be made regarding the information used by the techniques in the generation of their forecasts. Since predictive ability does not translate to profitability, a simple trading strategy was used to determine the ability to generate profits from trading upon the forecasts of the respective techniques. As hypothesized, the ANFIS and neural network techniques are able to generate forecasts with significant predictive ability. However, neither technique dominates the other or the ARMA model. In tests of the ability of the techniques to generate profits from their forecasts, a simple trading strategy was used (trading on the predicted sign of the return). The ANFIS and the neural network generated profits in all of the trading scenarios. However, neither technique dominated the other, nor did they consistently outperform the traditional and naive models (strategies). The mixed results in the predictive ability tests and the profitability tests indicate that the conclusions from the study differ based upon the context in which the forecasts are used. Copyright © 2005 John Wiley & Sons, Ltd.