Working Papers
"How service quality variability hurts revenue when customers learn: Implications for dynamic personalized pricing" (with Gregory DeCroix and Jordan Tong), minor revision in Operations Research. [Download] (updated February 24, 2020)
Abstract: We formalize an understudied mechanism through which quality variability hurts firm revenues, analyze when and why this mechanism is important, and generate new insight into how dynamic personalized pricing strategies can mitigate the negative effects of quality variability. To do so, we model a firm that sells a service repeatedly with variable but stationary quality. Customers update their quality beliefs based on their experiences (exponential smoothing), and their purchase probability in each period increases with their respective beliefs about mean quality (logit choice). For any fixed price, we show that quality variability reduces the firm's revenue and leads to a downward bias in customer beliefs about quality. These effects arise even when customers are risk neutral and update their beliefs symmetrically after good and bad experiences. We then investigate whether the firm can improve revenues through dynamic personalized pricing. We find that a "fixed perceived surplus" pricing policy---charging a lower price when a customer believes the quality is lower to induce a constant purchase probability---is not only optimal but can also match the optimal revenue when quality is not variable. The revenue gain from implementing this pricing policy (as compared with fixed pricing) is greatest when quality variability is large, customers react strongly to recent experiences, and/or mean service quality is high. Our numerical results further show that firms can achieve significant revenue gains through dynamic pricing even in information-poor or low-price-flexibility environments. Finally, we extend our model to consider social learning as well as competition between two firms.
"Sustainability in the fast fashion industry" (with Javad Nasiry), under revision. [Download]
(updated December 24, 2019)
Abstract: A fast fashion system allows firms to react quickly to changing consumer demand by replenishing inventory (via quick response) and introducing more fashion styles. In this paper, we study the environmental impact of the fast fashion business model by analyzing its implications for product quality, variety, and inventory decisions. Our results show that the fast fashion model is conducive to low quality products. In particular, we find that a key driver of low product quality in the fast fashion industry is the firm's incentive to offer variety to hedge against uncertain fashion trends. When variety is endogenous, quality decreases as consumers become more sensitive to fashion or as the cost of introducing new styles decreases. We also identify conditions under which expected leftover inventory increases as the firm's fast fashion capabilities increase. To counter the environmental impact of the fast fashion business model due to low quality and overproduction, we assess the effectiveness of three environmental initiatives (waste disposal regulations, consumer education, and post-consumer recycling programs). We show that waste disposal policies are effective in reducing the firm's leftover inventory---but may have the unintended consequence of lowering product quality. We also compare firm-owned versus third-party recycling programs and propose a revenue-sharing scheme which could induce higher levels of recycling rate and product quality while increasing the system's total profit.
Publications
- Honorable Mention in the CSAMSE Annual Conference/Columbia China Business Initiative Best Paper Award, 2016.
- Honorable Mention in the 2015 POMS-HK International Conference Student Paper Competition.
Conference Presentations
"How service quality variability hurts revenue when customers learn: Implications for dynamic personalized pricing" (with Gregory DeCroix and Jordan Tong), minor revision in Operations Research. [Download] (updated February 24, 2020)
Abstract: We formalize an understudied mechanism through which quality variability hurts firm revenues, analyze when and why this mechanism is important, and generate new insight into how dynamic personalized pricing strategies can mitigate the negative effects of quality variability. To do so, we model a firm that sells a service repeatedly with variable but stationary quality. Customers update their quality beliefs based on their experiences (exponential smoothing), and their purchase probability in each period increases with their respective beliefs about mean quality (logit choice). For any fixed price, we show that quality variability reduces the firm's revenue and leads to a downward bias in customer beliefs about quality. These effects arise even when customers are risk neutral and update their beliefs symmetrically after good and bad experiences. We then investigate whether the firm can improve revenues through dynamic personalized pricing. We find that a "fixed perceived surplus" pricing policy---charging a lower price when a customer believes the quality is lower to induce a constant purchase probability---is not only optimal but can also match the optimal revenue when quality is not variable. The revenue gain from implementing this pricing policy (as compared with fixed pricing) is greatest when quality variability is large, customers react strongly to recent experiences, and/or mean service quality is high. Our numerical results further show that firms can achieve significant revenue gains through dynamic pricing even in information-poor or low-price-flexibility environments. Finally, we extend our model to consider social learning as well as competition between two firms.
"Sustainability in the fast fashion industry" (with Javad Nasiry), under revision. [Download]
(updated December 24, 2019)
Abstract: A fast fashion system allows firms to react quickly to changing consumer demand by replenishing inventory (via quick response) and introducing more fashion styles. In this paper, we study the environmental impact of the fast fashion business model by analyzing its implications for product quality, variety, and inventory decisions. Our results show that the fast fashion model is conducive to low quality products. In particular, we find that a key driver of low product quality in the fast fashion industry is the firm's incentive to offer variety to hedge against uncertain fashion trends. When variety is endogenous, quality decreases as consumers become more sensitive to fashion or as the cost of introducing new styles decreases. We also identify conditions under which expected leftover inventory increases as the firm's fast fashion capabilities increase. To counter the environmental impact of the fast fashion business model due to low quality and overproduction, we assess the effectiveness of three environmental initiatives (waste disposal regulations, consumer education, and post-consumer recycling programs). We show that waste disposal policies are effective in reducing the firm's leftover inventory---but may have the unintended consequence of lowering product quality. We also compare firm-owned versus third-party recycling programs and propose a revenue-sharing scheme which could induce higher levels of recycling rate and product quality while increasing the system's total profit.
Publications
- "Wage transparency and social comparison in salesforce compensation" (with Javad Nasiry), Management Science, Forthcoming. [Download]
- "A behavioral study of abandonment decisions in multi-stage projects" (with Javad Nasiry and Yaozhong Wu), Management Science, Forthcoming. [Download] [Download Appendix]
- Honorable Mention in the CSAMSE Annual Conference/Columbia China Business Initiative Best Paper Award, 2016.
- "Quality in supply chain encroachment" (with Albert Ha and Javad Nasiry). Manufacturing & Service Operations Management, 2016, 18(2) pp. 280-298.
- Honorable Mention in the 2015 POMS-HK International Conference Student Paper Competition.
- "Prospect theory explains newsvendor behavior: The role of reference points" (with Javad Nasiry). Management Science, 2015, 61(12) pp. 3009-3012. [Download]
Conference Presentations
- Modeling Customer Response to Service Quality Variability with Implications for Pricing, INFORMS, Seattle, Oct 2019
- Sustainability in the Fast Fashion Industry, INFORMS, Seattle, Oct 2019
- Wage Transparency in Sales Agents' Compensation Schemes, Seattle, Oct 2019
- Sustainability in the Fast Fashion Industry, CSAMSE International Conference, Chengdu, China, Jul 2019
- Modeling Customer Response to Service Quality Variability with Implications for Pricing, M&SOM Conference, Singapore, Jul 2019
- Modeling Customer Response to Service Quality Variability with Implications for Pricing, INFORMS RM&P Conference, Palo Alto, Jun 2019
- Quality and Product Variety in Fast Fashion, 2019 Early-career Sustainable OM Workshop, San Diego, Mar 2019
- Wage Transparency in Sales Agents' Compensation Schemes, POMS, Houston, May 2018
- A Behavioral Study on Abandonment Decisions in Multi-Stage Projects, POMS, Houston, May 2018
- Wage Transparency in Sales Agents' Compensation Schemes, INFORMS, Houston, Oct 2017.
- A Behavioral Study on Abandonment Decisions in Multi-Stage Projects, INFORMS, Houston, Oct 2017.
- A Behavioral Study on Abandonment Decisions in Multi-Stage Projects, INFORMS, Nashville, Nov 2016.
- A Behavioral Study on Abandonment Decisions in Multi-Stage Projects, CSAMSE International Conference, Hefei, China, Jul 2016.
- A Behavioral Study on Abandonment Decisions in Multi-Stage Projects, M&SOM Conference, Auckland, New Zealand, Jun 2016.
- Informational Effect of Project Reviews, INFORMS, Philadelphia, Nov 2015.
- Quality in Supply Chain Encroachment, INFORMS, Philadelphia, Nov 2015.
- Quality in Supply Chain Encroachment, POMS-HK International Conference, Guangzhou, Jan 2015.
- Quality in Supply Chain Encroachment, INFORMS, San Francisco, Nov 2014.
- Quality in Downstream Encroachment, POMS International Conference, Singapore, Aug 2014.
