Optimal trade-in strategy for advance selling with strategic consumers proportion

Purpose This study aimed to optimize the trade-in pricing strategy. To leverage market share, many sellers adopt trade-in strategy for advance selling, Customers can return their old products at a discount price when they buy new products. This can help increase the market share and decrease natural resource consumption. Design/Methodology/Approach We consider a seller who sells new-generation products over two periods: advance selling and regular selling. Based on the rational expectation equilibrium, we adopt dynamic programming to construct a two-period pricing model with three different trade-in strategies–only in period 2, in both periods, and not at all–explaining the trade-in strategy as a promotion tool used by a monopolist to discriminate for advance selling between new and old customers. Findings The results suggest that the optimal price is determined by the proportion of old customers, discount factor and product innovation level. Whether and when to give a trade-in rebate to old customers depends on these parameters. The seller’s choice of optimal trade-in strategy depends on the threshold value of the new customer demand and trade-in demand. Originality/Value Most existing literature focuses on advance selling strategies and trade-in strategies. To the best of our knowledge, this is a pioneering study that adopts trade-in as part of the advance selling strategy

The Value of “Bespoke”: Demand Learning, Preference Learning, and Customer Behavior

“Bespoke,” or mass customization strategy, combines demand learning and preference learning. We develop an analytical framework to study the economic value of bespoke systems and investigate the interaction between demand learning and preference learning. We find that it is possible for demand learning and preference learning to be either complements or substitutes, depending on the customization cost and the demand uncertainty profile. They are generally complements when the personalization cost is low and the probability of having high demand is large. Contrary to usual belief, we show that higher demand uncertainty does not necessarily yield more complementarity benefits. Our numerical study shows that the complementarity benefit becomes weaker when customers are more strategic. Interestingly, the substitute loss can occur when the personalization cost is small and the probability of having high demand is large, when customers are strategic.postprin

Essays on Service Operations Management

This dissertation studies three different problems service firms can face. The first chapter looks at the optimal way to price reservations and services when customers make reservations in advance, while they are uncertain about the future value of service, to avoid waiting on the day of service. We show that charging customers the full price as non-refundable deposit when they make reservations and charging zero for service when they show up to claim their reservations is optimal for the firm. When the firm faces very large potential market, then it is better for the firm to not take reservations and accept only walk-ins. The second chapter looks at a problem of how to mitigate worker demotivations due to fairness concerns, when workers have intrinsic difference in quality, and higher quality server tends to be overcrowded by customers willing to receive higher quality service. We suggest distributing workload fairly between workers and compensating workers per workload as potential remedies and show which remedy works well under what operational conditions. We show that compensating workers per customer they serve results in high customer expected utility and expected quality. However, when customers also care about fairness and dislike receiving inferior service compared to other customers, then there does not exist a single remedy that results in both high customer expected utilization and high expected quality. In the third chapter, we study how a service firm should choose its advertising strategy when the service quality is not perfectly known to the customers. We model customers\u27 learning process using a Markov chain, and show that when customers do not perfectly learn the quality of service from advertisements, then the firm is better off by advertising actively when customers\u27 initial belief about service quality is low. Oppositely, when customers initially believe the service quality to be high, then it is better for the firm to stay silent and not use advertisement to signal its quality. In all three chapters, we use game theory to model the interactions among the participants of the problem and find the equilibrium outcomes

Advance Selling Programs: When to Introduce and What to Inform Consumers

We study a two-stage model in which the information processed by consumers at the first stage (advance selling stage) is endogenously determined. In the model, the firm decides whether to introduce an advance selling program, chooses what attribute information to disclose and determines an advance selling price and a retail price. Forward-looking consumers strategically choose, based on the disclosed information, to buy in advance or to make a purchase decision at the second stage (retail stage) when all information is revealed. We characterize the firm's optimal choice on the advance selling program and the strategy of information disclosure. In particular, we show that the firm always prefers to introduce the advance selling program except when underlying consumer preferences are extremely homogenous. In addition, we find that fully revealing horizontal product information at the advance selling stage is never optimal to the firm, but revealing either partial or no product information can be optimal depending on the underlying consumer preferences. Our finding that partial information disclosure is sometimes optimal to the firm is in contrast to the result in the literature of horizontal information provision that a firm maximizes profit by revealing either no or full information to consumers

Online marketing:When to offer a refund for advanced sales

Advance selling is a marketing strategy commonly used by online retailers to increase sales by exploiting consumer valuation uncertainty. Recently, some online retailers have started to allow refunds on products sold in advance. On the one hand this reduces the net advance sales, but on the other hand it allows a higher advance sales price. This research is the first to explore the overall effect of allowing a refund on profits from advance sales, identifying conditions where advance selling with or without refunds (or no advance selling at all) is best. We analytically compare the profits of three advance selling strategies: none, without refund, and with refund. We show that selling in advance and allowing a refund is optimal for products with a relatively small profit margin and small strategic market size, and that the added profit can be considerable. Our results guide managers in selecting the right advance selling strategy. To facilitate this, we graphically display, based on the two dimensions of regular profit margin and strategic market size, under what conditions the different strategies are optimal

Optimal pricing strategy:How to sell to strategic consumers?

Technological advances are preparing consumers to plan their purchases strategically. Selling to strategic consumers at a fixed price forgoes the profit from salvaging inventory, whereas high-low pricing, as a ubiquitous pricing strategy, is costly due to the offered markdown discount. This research explores the overall impact of consumer's strategic buying behaviour on a pricing strategy, and identifies conditions where fixed pricing, strategic high pricing, or high-low pricing is the best approach by analytically comparing the profits of the three pricing strategies. Our results show that high-low pricing is appropriate only if the offered markdown discount is relatively small. If strategic consumers have a small population and the needed markdown discount is relatively large, retailers can ignore strategic buying behaviour and sell products at a fixed price. Our results emphasize that the markdown discount for clearance sales and the market structure of heterogeneous consumers play vital roles in determining the optimal pricing strategy

Advance Selling and Advertising:A Newsvendor Framework

Many firms offer consumers the opportunity to place advance orders at a discount when introducing a new product to the market. Doing so has two main advantages. First, it can increase total expected sales by exploiting valuation uncertainty of the consumers at the advance ordering stage. Second, total sales can be estimated more accurately based on the observed advance orders, reducing the need for safety stock and thereby obsolescence cost. In this research, we derive new insights into trading off these benefits against the loss in revenue from selling at a discount at the advance stage. In particular, we are the first to explore whether firms should advertise the advance ordering opportunity. We obtain several structural insights into the optimal policy, which we show is driven by two dimensions: the fraction of consumers who potentially buy in advance (i.e., strategic consumers) and the size of the discount needed to make them buy in advance. If the discount is below some threshold, then firms should sell in advance and they should advertise that option if the fraction of strategic consumers is sufficiently large. If the discount is above the threshold, then firms should not advertise and only sell in advance if the fraction of strategic consumers is sufficiently small. Graphical displays based on the two dimensions provide further insights

The promise of reward crowdfunding

Research Question/IssueWe study reward crowdfunding (RC), the most innovative segment of the crowdfunding market, where, instead of a debt or equity contract, fund providers are promised some good or service in the future in exchange for their contribution to the funding of the investment project under a contract that does not penalize the creator's failure to deliver. The existing economic and legal literature is puzzled by the platform's use of this seemingly inefficient contract where a standard pre-sale contract would appear to work better. Research Findings/InsightsCounterintuitively, we prove that the no-penalty contract is the optimal contract between creators of unknown talent and early adopters of their products when creators can benefit from being discovered as talented and from the goodwill generated by delivering on their promise to early adopters. Theoretical/Academic ImplicationsOur analysis contributes to understanding RC by showing that the no-penalty RC contract, far from being an inefficiency, is a contractual innovation specifically designed for talent discovery. We also contribute to the literature on relationship contracts, showing that even in a one-shot game, it is possible to sustain a contract in the desire to build a reputation that will be useful in a future contract with a third party. Practitioner/Policy ImplicationsOur analysis has important policy implications on how backers should be protected. Standard measures of consumer or investor protection may be counterproductive.María Gutiérrez‐Urtiaga gratefully acknowledges the financial support from Comunidad de Madrid and the EU's European Social Fund through grant S2015/HUM‐3353 EARLYFIN‐CM and from the European Regional Development Fund through grant FEDER UNC315‐EE‐3636

The role of crowdfunding in promoting entrepreneurship

Crowdfunding is a collaborative initiative, usually via internet, where people network to collectively raise funds in order to invest in and support projects delivered by other people or organizations. Tools such as crowdfunding are born and thrive in a grassroots environment, with a strong potential to positively disrupt the entrepreneurial generation setting and grow to a position of significant relevance in society, namely at a time when alternatives to traditional forms of finance are welcome and the technology to deliver them is abundant. Entrepreneurship is the act of transforming ideas and projects into economic products or services. Entrepreneurship related to starting new businesses is better known as start‐up ventures. Entrepreneurs face a series of challenges, from idea conception and business plan design, to obtaining finance, promoting new products and services, generating revenues and profits and generally growing and sustaining a business for the long‐run. These challenges can be overwhelming, namely in the start‐up phase of a new venture, leaving several ideas on paper without them having a chance to “grow legs and walk”. This paper and its analysis offer important insights about the contribution of crowdfunding to facilitate the attainment of critical factors for successful entrepreneurship. With extensive use of real practical examples, leveraging previous analytical studies of other crowdfunding implications and reviewing expert literature, by interviewing entrepreneurs, crowdfunding platform owners and by benefitting from hands on experience of working in such an organization, we intend to clarify the impact of crowdfunding in what we considered to be 7 key entrepreneurial requirements detailed further in the introduction section and later in the body of the paper. The findings have implications for entrepreneurs, naturally, and for business generation theory, extending current entrepreneurial guidelines with innovative tools and methodologies capable of sustaining successful ventures in a newly highlighted cooperative world. We live in innovative times where the channels for the transfer of funds and resources suffer disruptive changes with the potential to significantly improve the ability to generate new initiatives for the well‐being of entrepreneurs and all related communities

Economic Perspectives on Automated Demand Responsive Transportation and Shared Taxi Services - Analytical models and simulations for policy analysis

The automated demand responsive transportation (DRT) and modern shared taxi services provide shared trips for passengers, adapting dynamically to trip requests by routing a fleet of vehicles operating without any fixed routes or schedules. Compared with traditional public transportation, these new services provide trips without transfers and free passengers from the necessity of using timetables and maps of route networks. Furthermore, automated DRT applies real-time traffic information in vehicle routing and in formulating trip offers with travel time promises, which enables differentiated pricing based on travel times and thereby tailored service provision for personal passenger needs.  This work considers the potential economic impacts of automated DRT and shared taxi services on urban transportation, and explores the effects of various transport policies on these new transport services as an integral part of urban transportation system. Analytical models are presented to define welfare optimal policies for these services, which have different trip production cost structures and external costs compared to conventional bus and taxi services. Moreover, simulation models are developed to analyse cost-effectiveness and regulation policies.  Furthermore, alternative pricing models for these services are analysed from the viewpoint of transport companies, passengers and transport policy.  The publications presented in this dissertation provide theoretical foundations, models and insights based on empirical data for further policy analyses and empirical research on automated DRT and shared taxi markets. These markets are evolving due to the advances in intellingent transportation technologies adopted by innovative and even revolutionary companies, and due to the increasing political pressures for sustainable transportation.Automatisoitu kysyntäohjautuva joukkoliikenne ja modernit jaetut taksipalvelut tarjoavat jaettuja kyytejä matkustajille makautuen dynaamisesti matkapyyntöihin reitittämällä operoivat ajoneuvot reaaliaikaisesti ilman ennalta määrättyjä reittejä ja aikatauluja. Verrattuna perinteiseen julkiseen liikenteeseen nämä uudet liikennepalvelut tarjoavat matkoja ilman vaihtoja ja vapauttavat matkustajat käyttämästä aikatauluja ja linjastokarttoja. Tämän lisäksi automatisoitu kysyntäohjautuva joukkoliikenne hyödyntää reaaliaikaista liikennetietoa ajoneuvojen reitityksessä ja muodostaessaan matka-aikalupauksia sisältäviä matkatarjouksia, mikä mahdollistaa matka-aikoihin perustuvan hintadifferoinnin ja siten yksilöllisemmän palvelutarjonnan matkustajien tarpeisiin.  Tämä työ tarkastelee automatisoidun kysyntäohjautuvan joukkoliikenteen ja jaettujen taksipalvelujen potentiaalisia vaikutuksia urbaanille liikenteelle sekä tutkii erilaisten liikennepolitiikkojen vaikutusta näihin palveluihin kiinteänä osana urbaania liikennesysteemiä. Työssä esitetään analyyttisiä malleja, joilla määritellään yhteiskunnan hyvinvoinnin optimoivia politiikkoja näille palveluille, joilla on perinteisiin bussi- ja taksipalveluihin verrattaessa erilaiset palvelutuotannon kustannusrakenteet sekä ulkoiskustannukset. Lisäksi työssä kehitetään simulointimalleja kustannustehokkuuden ja säännöstelypolitiikkojen analysointiin. Tämän lisäksi vaihtoehtoisia hinnoittelumalleja tarkastellaan liikenneyritysten, matkustajien ja liikennepolitiikan näkökulmasta.  Väitöskirjassa esitetyt julkaisut tarjoavat teoreettisen pohjan, malleja ja empiiriseen aineistoon pohjautuvia näkymyksiä automatisoidun kysyntäohjautuvan joukkoliikenteen ja jaettujen taksipalvelujen politiikkanalyysiin sekä empiirisen tutkimuksen tarpeisiin. Näiden uusien liikennepalveluiden markkinat ovat kehittymässä älyliikennneteknologioiden edistysaskelten ja niitä hyödyntävien innovatiivisten yritysten myötä sekä liikenteen kestävyyteen kohdistuvan kasvavan poliittisen paineen ja vaatimusten myötävaikutuksesta