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We investigate whether the discounts offered by online daily deals help attract consumer purchases. By tracking the sales of 19,978 deals on Groupon.com and conducting a battery of identification and falsification tests, we find that deep discounts reduce sales. A 1% increase in a deal’s discount decreases sales by 0.035%–0.256%. If a merchant offers an additional 10% discount from the sample mean of 55.6%, sales could decrease by 0.63%–4.60%, or 0.80–5.24 units and $42–$275 in revenue. This negative effect of discount is more prominent among credence goods and deals with low sales, and when the deals are offered in cities with higher income and better education. Our findings suggest that consumers are concerned about product quality, and excessive discounts may reduce sales immediately. A follow-up lab experiment provides further support to this quality-concern explanation. Furthermore, it suggests the existence of a “threshold” effect: the negative effect on sales is present only when the discount is sufficiently high. Additional empirical analysis shows that deals displaying favorable third-party support, such as Facebook fans and online reviews, are more susceptible to this adverse discount effect. We draw related managerial implications. The online appendix is available at https://doi.org/10.1287/isre.2017.0772 .

Online shopping is becoming one of the most popular applications on the Internet. Websites are the important interfaces in HCI (Human–Computer Interaction). Website design significantly affects online shopping behavior. This research used eye-tracker to track the eye-movement process for 42 college students when they were surfing websites with different levels of complexity and completing simple and complex tasks respectively. The study examines how website complexity and task complexity jointly affect users' visual attention and behavior due to different cognitive loads. The study fills a research gap by examining this phenomenon from the cognitive load perspective and taking the moderate effect of task complexity into consideration. The results show that task complexity can moderate the effect of website complexity on users' visual attention and behavior. Specifically, when users conducted a simple task, fixation count and task completion time were at the highest level on the website with high complexity, while fixation duration was not significantly different on the websites with different complexity. However, when users conducted a complex task on a website with medium complexity, task completion time, fixation count, and fixation duration were all at their highest level. The load theory of attention was used to provide the explanation for the results. The findings provide guidelines for website managers and designers to maximize users' visual attention.