The five-factor model (FFM) of personality has been used to great effect in management and psychology research to predict attitudes, cognitions, and behaviors, but has largely been ignored in the IS field. We demonstrate the potential utility of incorporating this model into IS research by using the FFM personality factors in the context of technology acceptance. We propose a dispositional perspective to understanding user attitudes and beliefs, and examine the effect of user personality—captured using the FFM's big five factors—on both the perceived usefulness of and subjective norms toward the acceptance and use of technology. Using logged usage data from 180 new users of a collaborative technology, we found general support for our hypotheses that the FFM personality dimensions can be useful predictors of users' attitudes and beliefs. We also found strong support for the relationships between intention to use and system use.

Abidding strategy commonly observed in Internet auctions is that of “jump bidding,” or entering a bid larger than what is necessary to be a currently winning bidder. In this paper, we argue that the cost associated with entering online bids and the uncertainty about future entry—both of which distinguish Internet from live auctions—can explain this behavior. We present a simple theoretical model that includes the preceding characteristics, and derive the conditions under which jump bidding arises in a format commonly used for online trading, the ascending-price auction. We also present evidence, recorded from hundreds of Internet auctions, that is consistent with some of the basic predictions from our model. We find that jump bidding is more likely earlier in an auction, when jumping has a larger strategic value, and that the incentives to jump bid increase as competition increases. Our results also indicate that jump bidding is effective: Jump bidders place fewer bids overall, and increased early jump bidding deters entry later in the auction. We also discuss possible means of reducing bidding costs and evidence that Internet auctioneers are pursuing this goal.

Unlike advertising in traditional media, a mobile platform's in‐app advertising market exhibits two unique features—split structure of the mobile platform with a platform owner and an app developer jointly provisioning in‐app advertising, and agency pricing for app sales. We develop a two‐sided market model to analyze the role of these two unique features in determining the platform owner's optimal advertising revenue‐sharing contract. Our results reveal an interesting N‐shaped dynamic regarding the platform owner's optimal choice of her ad revenue share with respect to the overall advertisers’ valuation of in‐app ads. We identify a between‐agent subsidization strategy for the platform owner, where she finds it optimal to subsidize the developer via the advertising channel, leading to greater profits for both of them. We find that the advertising revenue‐sharing contract under agency pricing for app sales leads to a higher app price than would be offered by the integrated platform found in traditional advertising. However, the ad price is coordinated under the platform owner's optimal choice of ad revenue share when she obtains revenue from both the advertising and app sales channels, leading to an alignment of her interest with the app developer's on ad level.

The current conflict between the recording industry and a portion of its customers who are involved in illicit copying of music files arose from innovations involving the compression and electronic distribution of files over the internet. This paper briefly describes some of the challenges faced by the recording industry, and examines some of the ethical issues that arise in various industry and consumer responses to the opportunities and threats presented by these innovations. The paper concludes by highlighting the risks associated with responses that threaten further innovation, ultimately reducing the chances of finding solutions that hold appeal for all parties.

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