Classical conditioning and celebrity endorsers: An examination of belongingness and resistance to extinction

Three studies attempt to better explain how celebrities are used effectively as conditioned stimuli in the associative learning process. Study 1 establishes that direct affect transfer can occur using celebrities via conditioning. Study 2 suggests that celebrity conditioning will be more effective when there is an appropriate fit (belongingness) between the celebrity and the product endorsed—also known as the match‐up hypothesis. Finally, Study 3 examines whether attitudes toward brands paired with celebrities are resistant to efforts to extinguish them using extinction procedures. The findings suggest that conditioning with celebrities yields brand attitudes that are robust and enduring. © 2008 Wiley Periodicals, Inc.     

Valuing water level changes in reservoirs using two stated preference approaches: An exploration of validity

The combination of travel cost (TCM) and contingent behaviour (CB) methods is a relatively new research avenue in the recreational valuation community. Contrary to simple TCM applications, TCM-CB facilitates the ex ante valuation of marginal welfare effects resulting from environmental quality or quantity changes, similar to the contingent valuation method (CV). Even though TCM-CB is highly policy relevant, i.e. to inform changes in management regimes at recreational sites, the validity of estimates has hardly received any attention and little is known about the performance of TCM-CB compared to CV. In this paper, TCM-CB and CV are explored with respect to several validity tests in a case study on the recreational effects of water level changes in a reservoir. Overall, the findings reveal that TCM-CB and CV perform equally well in terms of theoretical validity, but that the marginal recreational value varies significantly between the two methods. We also observe that both methods face similar internal difficulties with respect to the stability of values when the order of a set of valuation questions is changed.     

What is the best Lévy model for stock indices? A comparative study with a view to time consistency

Financial Markets and Portfolio Management - Lévy models are frequently used for asset log-returns. An important criterion is the distributional assumption on the increments. Candidates...     

Blockchain Applications in Supply Chain Transactions

Blockchains, a disruptive technology with potentially many applications in modern‐day supply chain (SC) transactions, have not been adequately reflected by theory. Researchers and business managers must understand where and when blockchains’ application may be expected and investigated. The present study clarifies the discussion about blockchain application areas (BAAs) in SC transactions and their relevance for businesses. This study combines the findings from three methodological approaches: an extant literature review, a Delphi study, and a survey of 151 German machinery and equipment sector business managers. The results further our understanding of blockchains’ business opportunities among SC transactions and verify and extend Iansiti and Lakhani’s (Harvard Business Review 2017; 95: 118) blockchain adoption framework. Verified customer reviews and product quality certification are identified as the most relevant blockchain usages in SC transactions. Interestingly, we anticipate the least likely adoption of blockchains to occur for document‐signing processes despite arguments within the literature that suggest otherwise. Two newly identified BAAs—logistics and delivery systems—and token‐curated registries rank among the top four most relevant. The present study’s valuation of BAAs advances theory and will likely affect business strategies by indicating where, when, and why businesses should participate in blockchain networks.     

Pay-what-you-want in groups – evidence from a field experiment

Pay-what-you-want (PWYW) mechanisms are a specific form of voluntary market payment. While a large number of recent studies have considered their design options, the aspect of group behaviour in PWYW situations has not been investigated, although a substantial part of payment decisions occur in group constellations. We provide initial evidence by running a field experiment implementing a PWYW mechanism in a cinema characterized by group attendance, finding that groups chose to pay similar amounts as individuals. Group payments can be increased by a prosocial framing of the decision, while an increase in group size and repeated participation reduce voluntary payments. We thus show that group payment decisions in PWYW situations are characterized by altruism concerns rather than in-group egoism.     

Using past experience to optimize audit sampling design

Optimal sampling designs for audit, minimizing the mean squared error of the estimated amount of the misstatement, are proposed. They are derived from a general statistical model that describes the error process with the help of available auxiliary information. We show that, if the model is adequate, these optimal designs based on balanced sampling with unequal probabilities are more efficient than monetary unit sampling. We discuss how to implement the optimal designs in practice. Monte Carlo simulations based on audit data from the Swiss hospital billing system confirms the benefits of the proposed method.     

Big Data

“Big data” describes technologies that promise to fulfill a fundamental tenet of research in information systems, which is to provide the right information to the right receiver in the right volume and quality at the right time. For information systems research as an application-oriented research discipline, opportunities, and risks arise from using big data. Risks arise primarily from the considerable number of resources used for the explanation and design of fads. Opportunities arise because these resources lead to substantial knowledge gains, which support scientific progress within the discipline and are of relevance to practice as well. From the authors’ perspective, information systems research is ideally positioned to support big data critically and use the knowledge gained to explain and design innovative information systems in business and administration – regardless of whether big data is in reality a disruptive technology or a cursory fad. The continuing development and adoption of big data will ultimately provide clarity on whether big data is a fad or if it represents substantial progress in information systems research. Three theses also show how future technological developments can be used to advance the discipline of information systems. Technological progress should be used for a cumulative supplement of existing models, tools, and methods. By contrast, scientific revolutions are independent of technological progress.     

A Sealed‐bid Double Auction Experiment on German Milk Quota Exchanges

Standard double auctions perfectly mimic the neoclassical idea about the functioning of markets. The efficiency of the market outcome and speed of adjustment towards equilibrium have been studied in the literature to validate economic expectations. However, only a few real world examples outside the financial sector exist. In 2000, Germany implemented a sealed‐bid double auction mechanism for trading milk quota. The two main features of this mechanism are: (1) a sealed‐bid double auction that produces excess demands that are covered by state reserves free of charge, and (2) a variable price band that is used to exclude price bids above a certain range. To study these regulations a sealed‐bid double auction experiment is simulated and run with students. It is shown that the regulations lead to significant losses in welfare that are caused by direct effects and by an imperfect adjustment of individual bidding behaviour. Further, learning effects throughout the experiments appear to be very limited. Thus, complex auction mechanisms may need to be thoroughly tested before being introduced in the real world.