Interactive bundle pricing strategy for online pharmacies

Online retail pharmacies usually price their products differently from traditional drugstores. Based on real-time consumer behaviors, this paper proposes a dynamic bundle pricing strategy to maximize the pharmacy's profit. Given free shipping thresholds and consumer budgets, we propose a mixed-integer nonlinear programming model and a heuristic to sequentially price customized bundles. We further conduct a numerical study using the data from a leading e-pharmacy in China. Our computational results indicate that the proposed model not only improves the e-pharmacy's profit by attracting more customers but noticeably contributes to consumer surplus. Through sensitivity analysis, our model is proved to be robust under various scenarios.</p

Revenue sharing at music streaming platforms

We study the problem of sharing the revenues raised from subscriptions to music streaming platforms among content providers. We provide direct, axiomatic and game-theoretical foundations for two focal (and somewhat polar) methods widely used in practice: pro-rata and user-centric. The former rewards artists proportionally to their number of total streams. With the latter, each user's subscription fee is proportionally divided among the artists streamed by that user. We also provide foundations for a family of methods compromising among the previous two, which addresses the rising concern in the music industry to explore new streaming models that better align the interests of artists, fans and streaming services.Comment: 30 page

Integration of On-Premises and Cloud-Based Software: The Product Bundling Perspective

Firms in the cloud-computing era are facing the critical issue of integrating on-premises software and cloud-based software services. To date, the software industry has designed two different types of integration methods—an enterprise service bus (ESB) and an integration platform as a service (iPaaS). However, there are conflicting views on when and how to use these different integration methods to fulfill integration needs. This study aims to resolve this confusion through economic modeling. By focusing on the indirect network effect and following a two-product bundling framework, we establish a stylized model to investigate optimal pricing and bundling decisions and the best integration choice. Our findings contradict common perceptions that an iPaaS is the better choice for integration and show that firms can derive higher value by adopting ESB to integrate on-premises software and cloud-based software services. Conceptually, given that the overall network value received from a cloud-based software service is higher, the use of ESB can contribute toward significantly improving the total value of the two software applications. We also find that unbundling is the best marketing strategy for firms because software integration can improve the valuation of individual software. Our findings have important implications for software vendors. They suggest that vendors can leverage a higher network value from the software service by integrating it with on-premises software applications through ESB rather than iPaaS and eventually realize higher profits by extracting more value from consumers. Since integration increases the value of individual products, vendors should sell them separately instead of offering them as a bundle

Efikasnost društvenih mehanizama

U ovom radu bavili smo se dizajnom mehanizama i svojstvima funkcija društvenog izbora. Prvo poglavlje proučava teoriju probira. Prodavatelj nastoji prodati dobro jednom kupcu te traži optimalnu proceduru kako to učiniti. Pretpostavljamo kvazi linearne funkcije korisnosti, tj. one koje su aditivno separabilne i neutralne na rizik u novcu. Počinjemo davanjem cijene jednom nedjeljivom dobru. Definiramo kupčev tip kao kupčevu procjenu vrijednosti dobra koja nije poznata prodavatelju. Pitamo se je li odabiranje cijene $p$ za dobro optimalna prodajna strategija. Počinjemo definicijom direktnog mehanizma te iskazujemo princip objave koji nam omogućava da se usredotočimo upravo na takve mehanizme. Uvodimo ograničenja poticajne kompatibilnosti i individualne racionalnosti. Dolazimo do zaključka da je fiksiranje cijene stvarno bio najbolji postupak za prodavatelja. Dalje se okrećemo beskonačno djeljivom dobru. Ponovo definiramo direktni mehanizam u takvom okruženju te korištenjem analogona propozicija iz prethodnog odjeljka dobivamo prodajnu proceduru koja maksimizira očekivani profit. Na kraju ovog poglavlja dotičemo se i slaganja gdje prodavatelj ima dva različita nedjeljiva dobra, dobro $A$ i dobro $B$. Zaključujemo da prodavatelj nudi kupcu manju cijenu ako kupi dobra zajedno nego da ih je kupio odvojeno. To je iznenađujuće s obzirom da su, iz kupčevog stajališta, dobra potpuno nepovezana. U sljedećem poglavlju dajemo primjere mehanizama gdje postoji jedan prodavatelj i dva potencijalna kupca. Pobjednički kupac je onaj koji je ponudio najviše, a njegova isplata prodavatelju je ili najviša ponuda ili druga najviša ponuda. Ova dva slučaja implementiramo kroz direktne i indirektne mehanizme. Kod indirektnih mehanizama to su poznate aukcije prve, odnosno druge cijene, sa zapečaćenim ponudama. Posljednje poglavlje bavi se neprenosivom korisnošću. Napuštamo pretpostavke o aditivnoj separabilnosti i neutralnosti na rizik. Imamo konačan skup agenata $I = \{1; 2; \dots, N\}$ koji moraju izabrati jednu alternativu iz konačnog skupa $A$ međusobno isključujućih alternativa. Svaki agent ima relaciju preferencije $R_i$ nad $A$. Ponovo definiramo direktni mehanizam koji se u ovom slučaju naziva funkcija društvenog izbora. Također definiramo i poticajno kompatibilnu dominantnu strategiju te diktatorstvo. Iskazujemo teorem Gibbard Satterthwaite, ključni teorem ovog rada. On kaže da ako pretpostavimo da $A$ ima najmanje tri elementa i da je direktni mehanizam $f$ surjektivan, tada je $f$ poticajno kompatibilna dominantna strategija ako i samo ako je diktatorski. Koristeći se brojnim pomoćnim propozicijama pomno izlažemo dokaz ovog teorema. Za kraj navodimo moguće opuštanje strogih zahtjeva GS teorema ograničavanjem domene. Uvodimo jednovrsne relacije preferencije. U slučaju takvih preferencija i istih pretpostavki kao kod GS teorema, za razliku od prethodnog rezultata, postoje direktni mehanizmi koji su poticajno kompatibilne dominantne strategije, ali nisu diktatorski.In this paper we discussed mechanism design and properties of social choice functions. First chapter studies theory of screening. Seller seeks to sell the good to one buyer and tries to find an optimal selling procedure to do so. We assume quasi linear utility functions i.e. these who are additively separable and risk neutral in money. We start by pricing a single indivisible good. We define buyer’s type as buyer’s valuation of the good that is not known to the seller. We wonder if picking a price $p$ of the good is optimal selling strategy. We start by defining direct mechanism and state revelation principle which shows us that without loss of generality we can restrict our attention to these mechanisms. We introduce incentive compatibility and individual rationality constraints. We come to a conclusion that fixing a price really is best what seller can do. Further we turn to infinitely divisible good. Again we define direct mechanism in such environment and by using analogous propositions to the ones in previous section we get selling procedure that maximizes expected profit. In the end of this chapter we mention bundling where seller has two distinct indivisible goods, good $A$ and good $B$. We conclude that seller offers the buyer lower price if he buys goods as a bundle than if he had bought them separately. That is surprising considering that, from buyer’s point of view, goods are entirely unrelated. In the next chapter we give examples of mechanisms where there is one seller and two potential buyers. The highest bidder is declared the winner and he pays to the seller either the highest bid or the second highest. We implement these two cases by direct and indirect mechanisms. In implementation by indirect mechanisms we have famous first price and second price auctions with sealed bids. The last chapter studies non-transferable utility. We abandon assumptions about additive separability and risk neutrality. There is a finite set of agents $I = \{1; 2; \dots, N\}$ which have to choose one alternative from a finite set $A$ of mutually exclusive alternatives. Each agent has a preference relation $R_i$ over $A$. Again we define direct mechanism which, in this case, we call social choice function. Also, we define dominant strategy incentive compatibility and dictatorship. We state Gibbard Satterthwaite theorem, essential theorem of this paper. It states that if we assume that $A$ has at least three elements and that direct mechanism $f$ is surjective, then $f$ is a dominant strategy incentive compatible if and only if it is dictatorial. Using a numerous auxiliary propositions we expose proof of this theorem in detail. For the end we cite possible relaxation of stringent requirements of GS theorem by restricting the domain. We introduce single peaked preference relations. In case of these preferences and same assumptions as in GS theorem, unlike previous result, there are direct mechanisms which are dominant strategy incentive compatible but not dictatorial

Three Models for Pricing Decisions in Services or under Inventory Considerations

This dissertation studies pricing decisions under three different service settings. First, we consider a service system in which customers of two different types share the same service environment and their services are influenced by the presence of others. Specifically, when receiving services, customers interact with each other, and the effect of this interaction on the customers' utility may be positive or negative. Using a game-theoretic model, we show that in any Nash equilibrium, competing service providers will never benefit from price discrimination unless the externalities are negative and strong. With a numerical study, we find that when the two providers have small capacities, price discrimination will improve profits. However, when the two facilities have ample capacities, price discrimination might even hurt profits because of increased competition. The second setup is for a service system where competing service providers need to first perform an inspection to provide a quote to interested customers. We develop a game-theoretic model and fully characterize the equilibrium. With a numerical analysis, we find that, in equilibrium, firms might make profits mainly through the fees charged at the inspection stage. For the third setting, we consider the classical revenue management problem under inventory considerations with the additional feature that the firm has the option to bundle the product in clearance with a stable item. We prove that the optimal dynamic pricing strategy is of threshold-type, that is, it is optimal to offer a discount on the bundle when the value of an additional product is between two thresholds.Doctor of Philosoph

SPARSE SOLUTION IN OPERATIONS: ROUTING AND PRICING PROBLEMS

Ph.DDOCTOR OF PHILOSOPH

Dynamic, data-driven decision-making in revenue management

Thesis: Ph. D., Massachusetts Institute of Technology, Sloan School of Management, Operations Research Center, 2018.Cataloged from PDF version of thesis.Includes bibliographical references (pages 233-241).Motivated by applications in Revenue Management (RM), this thesis studies various problems in sequential decision-making and demand learning. In the first module, we consider a personalized RM setting, where items with limited inventories are recommended to heterogeneous customers sequentially visiting an e-commerce platform. We take the perspective of worst-case competitive ratio analysis, and aim to develop algorithms whose performance guarantees do not depend on the customer arrival process. We provide the first solution to this problem when there are both multiple items and multiple prices at which they could be sold, framing it as a general online resource allocation problem and developing a system of forecast-independent bid prices (Chapter 2). Second, we study a related assortment planning problem faced by Walmart Online Grocery, where before checkout, customers are recommended "add-on" items that are complementary to their current shopping cart (Chapter 3). Third, we derive inventory-dependent priceskimming policies for the single-leg RM problem, which extends existing competitive ratio results to non-independent demand (Chapter 4). In this module, we test our algorithms using a publicly-available data set from a major hotel chain. In the second module, we study bundling, which is the practice of selling different items together, and show how to learn and price using bundles. First, we introduce bundling as a new, alternate method for learning the price elasticities of items, which does not require any changing of prices; we validate our method on data from a large online retailer (Chapter 5). Second, we show how to sell bundles of goods profitably even when the goods have high production costs, and derive both distribution-dependent and distribution-free guarantees on the profitability (Chapter 6). In the final module, we study the Markovian multi-armed bandit problem under an undiscounted finite time horizon (Chapter 7). We improve existing approximation algorithms using LP rounding and random sampling techniques, which result in a (1/2 - eps)- approximation for the correlated stochastic knapsack problem that is tight relative to the LP. In this work, we introduce a framework for designing self-sampling algorithms, which is also used in our chronologically-later-to-appear work on add-on recommendation and single-leg RM.by Will (Wei) Ma.Ph. D