Conducting Measurement Validation with Experimental Data: Cautions and Recommendations

In this paper, the authors highlight several problems associated with conducting measurement validation using pooled experimental data. Beginning with a simple two-variable data set, the authors illustrate that pooling data can bias correlation and alpha coefficients, even when the data exhibit homogeneous covariance structures across treatment cells. They then introduce a data set that includes multiple measures for three latent constructs and extend the examination to include the effect of pooling bias on exploratory and confirmatory factor analysis. Three alternative approaches to conducting measurement validation that control for pooling bias are examined.     

A Comment on the Relationship between Coefficient Alpha and Scale Characteristics

To date, three major articles have analyzed the use of coefficient alpha on scales published in the marketing literature. These studies have improved our understanding of the scale development process and the behavior of coefficient alpha. One consistent result is that coefficient alpha produces an R-square of approximately .10 when regressed against scale length. In the most recent of these three meta-analyses, Peterson (1994) suggested that alpha does not behave as suggested by theory. We reexamine the behavior of alpha in relation to scale length, scale width, and response centrality. Our results suggest different conclusions from those previously reached.     

Developing an eService Strategy

"How do I justify investment in eCommerce to a group of senior managers that get their secretaries to print their emails?" was how one manager interviewed for this study summarised his eCommerce problem. This article is about how firms can develop a systematic strategy for delivering service on the web – eService. It starts with the result of a survey of responsiveness to customers in web-based service delivery, part of a study which also includes case studies of companies seeking to justify such investments. It then focuses on understanding the challenge of eService, developing a strategy and making the case for investment. It concludes with suggestions for implementation, including metrics for assessing eService quality.     

How does a Brand Ally Affect Consumer Evaluations of a Focal Brand?

Published research has shown that an alliance with a well‐known, reputable brand can improve quality perceptions of a previously unknown focal brand. Much of this research is based on signaling theory's bonding hypothesis. However, customers face information search costs when evaluating brands with which they may be unfamiliar. The authors contend that, since consumers are self‐interested, they will prefer to realize cost savings for themselves relative to a future conditional opportunity to punish a false signal sender. Three studies show that the effect of brand ally information on quality perceptions of an unfamiliar brand is mediated by perceived risk reduction due to lower information search costs.     

Beschaffung in China

Ohne Zusammenfassung Dr. Peter Voss ist Gesch?ftsführer der Sinoto GmbH, Offenbergstr. 31, 48151 Münster, und war bis 2008 Supply Chain Manager Asia Pacific für Checkpoint Systems in Shanghai, Volksrepublik China.     

The Role of Users in the Development of Applications Software

Meeting the needs of users has always been the goal of product developers. Recently, however, the important role of users as developers of new products has become more fully recognized. In many industries, it seems, users are actually a dominant part in the innovation process. To discover the part played by users in developing new computer software, Chris Voss traces the development path of a large number of software applications. He finds some particular circumstances where users lead the development of new products. This article and another that follows provide another view of software innovation to go with the preceding article by Glenn Bacon.     

Zur Geschichte der Versicherungsmathematik an der TU Dresden bis 1945

In 1919 the chair for Insurance Mathematics has been founded at the TH Dresden.Paul Eugen Boehmer was the first professor at this chair. For a long time this was the only chair in whole Germany which has been completely dedicated to the Insurance Mathematics. It has been preceded by a Seminar on Insurance Mathematics which has been founded in 1896 and has been chaired byGeorg Helm, the professor for Applied Mathematics. The seminar was based on Dresden’s long tradition in Mathematical Statistics and Theory of Probability, National Economy and Insurance Matters. This tradition is connected with the names of the professorsSchloemilch, Huels-se, Zeuner, andBoehmert. The background was the development of Insurance Matters in the economically strong Saxonia.     

Is Canada an optimal currency area? An inflation targeting perspective

We propose a method, based on the currency union model of Galí and Monacelli ( 2008 ), to determine whether a region within an existing currency area belongs in the currency union. The method involves assessing the predictability of regional inflation rates at medium term horizons. We apply the method to the Canadian provinces and find that for all but Alberta there is little evidence of costs in terms of inflation arising from national monetary policy. For Alberta, the evidence suggests that they are not as well served by the inflation targeting framework and that a more flexible policy environment might improve inflation outcomes.     

Elektroautos in einer von erneuerbaren Energien geprägten Energiewirtschaft

The German Federal Government wants to establish Germany as a leading market for electric mobility. Potential environmental benefits and changes in the economic framework conditions of the energy sector are described in this paper. In order to quantify the electricity split which is actually used for charging electric vehicles, two economic models for the energy sector, a model for the market penetration of electric vehicles, a vehicle model and an LCA model are brought together. Based on an assumed dynamic increase of electric vehicles to 12 million in 2030, an additional electricity demand of about 18 TWh is calculated. If the vehicles are charged directly after their last daily trip, the peak load increases by 12%—despite the small increase in electricity demand. First model calculations for the development of the European power generation system show that the direct impact on the construction of new power plants remains low even until 2030. An impact of electric mobility on CO₂ certificate prices can only be seen from 2025 onwards and is limited to an increase in certificate prices by a maximum of 8 % in 2030. An optimisation is possible with intelligent charging strategies: The peak load without demand side management can be reduced by 5 GW and about 600 GWh of additional wind energy can used which would otherwise have been throttled due to feed-in management—about 3.5 % of the total electricity demand of electric vehicles. On the other hand, demand side management leads to more coal power plants instead of gas power plants being used to meet the additional electricity demand. If additional renewable sources are installed along with demand side management, the electricity for electric vehicles is almost carbon free. This is also reflected in the life cycle balance of electric vehicles which also includes vehicle and battery production: With today’s average electricity split in Germany, the greenhouse gas emissions of electric vehicles are about comparable to vehicles with conventional combustion engines. However, the electricity split in 2030 or the use of additional renewable energy sources lead to a significant advantage in the greenhouse gas balance.     

Flexible inflation forecast targeting: Evidence from Canada

We test whether the Bank of Canada pursues a flexible inflation forecast target, one that weights output growth as well as inflation. For the period 1996–2007, we find evidence that the Bank did effectively pursue such a target over the forecast horizon of 12 to 18 months. We find the relative weight that the Bank gives to output growth in its target to be positive and statistically significant within the range of 0.2 to 0.4.