We use psychological theory to investigate how attitudes toward homebuying relate to first-time home purchases over the past decade. Homeownership rates in the US have dropped to 20-year lows, but whether views toward homebuying shifted due to the financial crisis is not known because studies have not compared attitudes for the same respondents pre-and post-crisis. We address this gap with 2004-2014 panel data from low-income renters. We find that a negative shift in homebuying attitudes is associated with a decline in first-time home purchases. Older renters aged more than 35 years at baseline report the greatest declines in homebuying intentions. Younger renters aged 18-34 also report diminished homebuying intentions, yet express highest overall levels of homebuying intentions pre-and post-crisis. Blacks report greater homebuying intentions although their odds of home purchase are 29 per cent lower than whites. Homebuying norms and favorability are associated with homebuying intentions but not with actual purchases, while perceived control over homebuying influences both outcomes.

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This study focuses on determining the appointment scheduling for healthcare facilities with series patients. “Series” patients are patients who are scheduled for a series of appointments instead of a single appointment. Examples of healthcare services with series patients include radiotherapy/chemotherapy for cancer, physical therapy, kidney dialysis, diabetes treatment, etc. The aim of this study is to design appointment scheduling policies taking into account revenues per service per patient, costs of staffing, overtime, overbooking and delay. The appointment scheduling problem is formulated using an MDP model. However, due to the huge state space, computing the optimal policy is impractical. Hence, we propose the Index Policy (IP) based on a one‐step policy improvement algorithm applied to the MDP model. We study a further simplification obtained by approximating the distribution of the number of patient visits by a Geometric distribution. A key analytical contribution is to prove the MDP to be a uni‐chain, which implies that there exists an optimal policy that maximizes the long‐run average profit. We also find that the IP provides a significant improvement over the other policies. Especially with the Geometric approximation, the IP requires minimal effort in implementing, and works almost as well. To test the effectiveness of our proposed IP in a real‐world setting, we use the data from a local physical therapy center to compare its performance with two other commonly used policies, namely, the Next Available Day Policy and the Shortest Queue Policy. We recommend the IP with Geometric approximation for series patients’ scheduling, which is computationally efficient and can significantly increases profits by incorporating the series feature of the patients’ appointments. Finally, we provide analysis that incorporates several practical considerations such as accounting for patient heterogeneity in number of visits and inter‐visit times, the option to reject new patients when the system is at full capacity, and incorporating patients with known number of visits at the time of the scheduling decision.

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Curse of a Favorable Opportunity: Strategic Choice of Investment Size and Timing with Bayesian Learning