Consumers’ Trust in Price-Forecasting Recommendation Agents
With the prevalence of data online, consumers increasingly shop not only for the product that best fits their needs, but also for the best time to purchase the product in order to reduce its cost. In line with this behavior, ecommerce websites often not only offer products, but also provide analytics based statements and recommendations relating to the best time to purchase a perishable product (e.g., air travel). This study examines the effects of such purchase timing statements and recommendations on consumers’ trusting beliefs in the recommendation facility. Our theoretical background comes from Toulmin’s (1958) argumentation model and the literature related to the role of explanation facilities in enhancing consumers’ trust. Results from our pilot study show evidence for the different roles Toulmin elements have, serving as explanation facilities in the context of predictive analytics.
In this paper,an econometric model on prices of Shanghai commercial residence houses over the last ten years is adopted,based on new classical economic theory.The model illustrates that among all the driving forces of the price,the increase of economic growth and the actual interest rate are not as significant as supposed.Instead,it is the rise of people's accumulated disposable income and the upgrade of supply mix towards mid-and-high-end market that pull the price up.