作者：
Li, QingmingZhao, H. VickyZhejiang Lab
Res Inst Artificial Intelligence Hangzhou 311100 Peoples R China Tsinghua Univ
Beijing Natl Res Ctr Informat Sci & Technol Dept Automat Beijing 100084 Peoples R China
Inter-temporal choices involve making decisions that require weighing costs in the present against benefits in the future. One specific type of inter-temporal choice is the decision between purchasing an individual it...
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Inter-temporal choices involve making decisions that require weighing costs in the present against benefits in the future. One specific type of inter-temporal choice is the decision between purchasing an individual item at full price or opting for a bundle including that item at a discounted price. Previous works assume that users have accurate expectations of factors involved in these decisions. However, in reality, users' perceptions of these factors are often biased, leading to irrational and suboptimal decision-making. In this work, we focus on two commonly observed biases: the projection bias and the reference-point effect. To address these biases, we propose a novel bias-embedded preference model called Probe. Probe introduces prospect theory from behavioral economics to model these biases, which incorporates a weight function to capture the projection bias and a value function to account for the reference-point effect. We propose a new method to learn users' individual projection biases from historical records and present four methods to estimate the referencepoint within the value function. We theoretically analyze the impact of projection bias on bundle pricing strategies. Through experimental results, we show that the proposed Probe model outperforms existing methods and leads to a better understanding of users' behaviors in bundle purchases. This investigation can facilitate a deeper comprehension of users' decision-making processes, enable personalized services, and help sellers design better product bundling strategies.
Weather, especially temperature, plays an important role in determining the supply and demand for a vast variety of goods and services. Though the economic impact of extreme weather is often measured and reported, the...
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Weather, especially temperature, plays an important role in determining the supply and demand for a vast variety of goods and services. Though the economic impact of extreme weather is often measured and reported, the impact of systematic changes in weather, such as long-term temperature trends or short-term heat and cold waves are seldom quantified. In this research, we posit that such systematic changes in temperature impact the profitability of firms, and we develop a two-step econometric model to quantify the impact. The proposed two-step model estimates the impact that temperature has on the profitability of firms and partitions this impact into a long-term and a short-term component. We take up the case of six liquid refreshment beverages (LRBs) for illustrating the impact that systematic change in temperature has on demand. The results indicate that (a) the demand for LRBs is increasing by about 0.21% (63 million gallons) from year to year on account of the rising temperature trend, and (b) there is an asymmetry in the effect of a heat wave versus a cold wave on beverage demand (i.e., the weekly demand for beverages increases by about 2.1% per degree on account of a heat wave while the weekly demand decreases by only 0.4% per degree on account of a cold wave). We also illustrate how these estimates of the impact of the long-term temperature trends could be linked to strategic decisions, such as facility location, and the estimates of the impact of the short-term temperature aberrations could be linked to operational decisions such as the inventory order quantity in a week when there is a temperature aberration.
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