Designing Layouts for Sequential Experiences: Application to Cultural Institutions

Aouad, Ali; Deshmane, Abhishek; Martínez‐de‐Albéniz, Victor

doi:10.2139/ssrn.4158587

Cited by 2 publications

(1 citation statement)

References 66 publications

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“…Our model assumes that the browsing distribution does not depend on the placement solution. This may not be true in general, especially in settings such as cultural institutions (Aouad et al 2022), and finding an approximation algorithm without this assumption remains a challenging open problem.…”

Section: Discussionmentioning

confidence: 99%

Joint Assortment Optimization and Customization Under a Mixture of Multinomial Logit Models: On the Value of Personalized Assortments

Housni

Topaloğlu

2023

Operations Research

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Assortment Personalization in E-commerce In the age of big data, online businesses have access to a tremendous amount of browsing and purchasing data from their customers. Consequently, there has been great effort in exploiting this data to offer personalized product assortments to each customer based on what is known about her or his preferences. A personalized assortment can potentially allow enhancing the customer experience as well as improving the revenue of the retailer. In “Joint Assortment Optimization And Customization Under A Mixture Of Multinomial Logit Models: On The Value Of Personalized Assortments,” Omar El Housni and Huseyin Topaloglu consider an optimization model that jointly optimizes the assortment of products carried by an online retailer as well as the personalized assortments offered to each customer. They study the value of personalization and develop algorithms with provable theoretical guarantees to solve the optimization problem.

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Section: Discussionmentioning

confidence: 99%

Joint Assortment Optimization and Customization Under a Mixture of Multinomial Logit Models: On the Value of Personalized Assortments

Housni

Topaloğlu

2023

Operations Research

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Ups and Downs in Experience Design

Chen,

Hu,

Liu

et al. 2024

Production and Operations Management

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We show how prospect theory uncovers critical decision-making insights in the design of sequential experiences by formulating a general framework and applying it to three experience design settings. First, we study the problem of releasing a piece of good news versus bad news, where a firm may incrementally reveal the news over a preemptive period. We characterize the optimal release strategy for both types of news and show that when the ultimate news is good (resp., bad) and the audience is sufficiently gain-seeking, it is optimal first to release information of a negative (resp., positive) sentiment. Second, we consider the problem of organizing an event such as a concert with performances of known valuations, where an event organizer needs to arrange the sequence of all performances. We show that for both loss-averse and gain-seeking audiences, interior peaks can be optimal, where pleasant and aversive performances are arranged to alternate throughout the event. Lastly, we investigate the problem of simultaneous versus sequential release of a series, such as songs or TV episodes, where a content provider does not know a priori the audience’s exact valuation of each item. We show that if the audience’s sensitivity to losses is sufficiently small (resp., large), the optimal strategy is to release all items in the series sequentially (resp., simultaneously). Across all of the settings, we show that the audience’s sensitivity to losses relative to a reference point is a critical factor that governs how to design and manage the audience’s evolving experience dynamics.

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Designing Layouts for Sequential Experiences: Application to Cultural Institutions

Cited by 2 publications

References 66 publications

Joint Assortment Optimization and Customization Under a Mixture of Multinomial Logit Models: On the Value of Personalized Assortments

Joint Assortment Optimization and Customization Under a Mixture of Multinomial Logit Models: On the Value of Personalized Assortments

Ups and Downs in Experience Design

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