Gamification, an application of game design elements to non-gaming contexts, is proposed as a way to add engagement in technology-mediated training programs. Yet there is hardly any information on how to adapt game design elements to improve learning outcomes and promote learner engagement. To address this issue, we focus on a popular game design element, competition, and specifically examine the effects of different competitive structures, i.e., whether a person faces a higher-skilled, lower-skilled or equally-skilled competitor, on learning and engagement. We study a gamified training design for databases, where trainees play a trivia-based mini-game with a competitor after each e-training module. Trainees who faced a lower-skilled competitor reported higher self-efficacy beliefs and better learning outcomes, supporting the effect of peer appraisal, a less examined aspect of social cognitive theory. Yet trainees who faced equally-skilled competitors reported higher levels of engagement, supporting the balance principle of flow theory. Our study findings indicate that no one competitive structure can simultaneously address learning and engagement outcomes. The choice of competitive structures depends on the priority of the outcomes in training. Our findings provide one explanation for the mixed findings on the effect of competitive gamification designs in technology mediated training.
This paper investigates how friendship relationships act as pipes, prisms, and herding signals in a large online, peer-to-peer (P2P) lending site. By analyzing decisions of lenders, we find that friends of the borrower, especially close offline friends, act as financial pipes by lending money to the borrower. On the other hand, the prism effect of friends' endorsements via bidding on a loan negatively affects subsequent bids by third parties. However, when offline friends of a potential lender, especially close friends, place a bid, a relational herding effect occurs as potential lenders are likely to follow their offline friends with a bid.
Because digital games are fun, engaging, and popular, organizations are attempting to integrate them within organizational activities as serious components, with the anticipation that they can improve employees' motivation and performance. But in order to do so and to obtain the intended outcomes, it is necessary to first obtain an understanding of how different digital game designs impact players' behaviors and emotional responses. Hence, in this study, we address one key element of popular game designs: competition. Using extant research on tournaments and intrinsic motivation, we model competitive games as a skill-based tournament and conduct an experimental study to understand player behaviors and emotional responses under different competition conditions. When players compete with players of similar skill levels, they apply more effort as indicated by more games played and longer duration of play. But when players compete with players of lower skill levels, they report higher levels of enjoyment and lower levels of arousal after game-playing. We discuss the implications for organizations seeking to introduce games premised on competition and provide a framework to guide information system researchers to embark on a study of games.
Keyword advertising, including sponsored links and contextual advertising, powers many of today's online information services such as search engines and Internet-based emails. This paper examines the design of keyword auctions, a novel mechanism that keyword advertising providers such as Google and Yahoo! use to allocate advertising slots. In our keyword auction model, advertisers bid their willingness-to-pay per click on their advertisements, and the advertising provider can weight advertisers' bids differently and require different minimum bids based on advertisers' click-generating potential. We study the impact and design of such weighting schemes and minimum-bid policies. We find that weighting scheme determines how advertisers with different click-generating potential match in equilibrium. Minimum bids exclude low-valuation advertisers and at the same time may distort the equilibrium matching. The efficient design of keyword auctions requires weighting advertisers' bids by their expected click-through-rates, and requires the same minimum weighted bids. The revenue-maximizing weighting scheme may or may not favor advertisers with low click-generating potential. The revenue-maximizing minimum-bid policy differs from those prescribed in the standard auction design literature. Keyword auctions that employ the revenue-maximizing weighting scheme and differentiated minimum bid policy can generate higher revenue than standard fixed-payment auctions. We draw managerial implications for pay-per-click and other pay-for-performance auctions and discuss potential applications to other areas.
Current knowledge management (KM) technologies and strategies advocate two different approaches: knowledge codification and knowledge-sharing networks. However, the extant literature has paid limited attention to the interaction between them. This research draws on the literature on formal modeling of networks to examine the interaction between knowledge codification and knowledge-sharing networks. The analysis suggests that an increase in codification may damage existing network-sharing ties. Anticipating that, individuals may hoard their knowledge to protect their network ties, even when there are nontrivial rewards for codification. We find that despite the aforementioned tension between the codification and the network approach, a firm may still benefit from combining the two approaches. Specifically, when the future sharing potential between knowledge workers is high, a combination of the two approaches may outperform a codification-only or a network-only approach because the codification reward causes fewer network ties to break down, and the benefit from increased codification can offset the loss of some network ties. However, when the future sharing potential is low, an increase in codification reward can quickly break down the whole network. Thus, firms may be better off by pursuing a codification-only or a network-only strategy.