Kay-Yut Chen

Dual Sales Channel Management with Service Competition

We study a manufacturer’s problem of managing his direct online sales channel together with an independently owned bricks-and-mortar retail channel, when the channels compete in service. We incorporate a detailed consumer channel choice model in which the demand faced in each channel depends on the service levels of both channels as well as the consumers’ valuation of the product and shopping experience. The direct channel’s service is measured by the delivery lead time for the product; the retail channel’s service is measured by product availability. We identify optimal dual channel strategies that depend on the channel environment described by factors such as the cost of managing a direct channel, retailer inconvenience, and some product characteristics. We also determine when the manufacturer should establish a direct channel or a retail channel if he is already selling through one of these channels. Finally, we conduct a sequence of controlled experiments with human subjects to investigate whether our model makes reasonable predictions of human behavior. We determine that the model accurately predicts the direction of changes in the subjects’ decisions, as well as their channel strategies in response to the changes in the channel environment. These observations suggest that the model can be used in designing channel strategies for an actual dual channel environment. 1

Predicting the Future

We present a novel methodology for predicting future outcomes that uses small numbers of individuals participating in an imperfect information market. By determining their risk attitudes and performing a nonlinear aggregation of their predictions, we are able to assess the probability of the future outcome of an uncertain event and compare it to both the objective probability of its occurrence and the performance of the market as a whole. Experiments show that this nonlinear aggregation mechanism vastly outperforms both the imperfect market and the best of the participants. We then extend the mechanism to prove robust in the presence of public information.

Trust in Forecast Information Sharing

This paper investigates the capacity investment decision of a supplier who solicits private forecast information from a manufacturer. To ensure abundant supply, the manufacturer has an incentive to inflate her forecast in a costless, nonbinding, and nonverifiable type of communication known as “cheap talk.” According to standard game theory, parties do not cooperate and the only equilibrium is uninformative---the manufacturers report is independent of her forecast and the supplier does not use the report to determine capacity. However, we observe in controlled laboratory experiments that parties cooperate even in the absence of reputation-building mechanisms and complex contracts. We argue that the underlying reason for cooperation is trust and trustworthiness. The extant literature on forecast sharing and supply chain coordination implicitly assumes that supply chain members either absolutely trust each other and cooperate when sharing forecast information, or do not trust each other at all. Contrary to this all-or-nothing view, we determine that a continuum exists between these two extremes. In addition, we determine (i) when trust is important in forecast information sharing, (ii) how trust is affected by changes in the supply chain environment, and (iii) how trust affects related operational decisions. To explain and better understand the observed behavioral regularities, we also develop an analytical model of trust to incorporate both pecuniary and nonpecuniary incentives in the game-theoretic analysis of cheap-talk forecast communication. The model identifies and quantifies how trust and trustworthiness induce effective cheap-talk forecast sharing under the wholesale price contract. We also determine the impact of repeated interactions and information feedback on trust and cooperation in forecast sharing. We conclude with a discussion on the implications of our results for developing effective forecast management policies. This paper was accepted by Ananth Iyer, operations and supply chain management.

Contract Complexity and Performance Under Asymmetric Demand Information: An Experimental Evaluation

Exploring the tension between theory and practice regarding complexity and performance in contract design is especially relevant. The goal of this paper is to understand why simpler contracts may commonly be preferred in practice despite being theoretically suboptimal. We study a two-tier supply chain with a single supplier and a single buyer to characterize the impact of contract complexity and asymmetric information on performance and to compare theoretical predictions to actual behavior in human subject experiments. In the experiments, the computerized buyer faces a newsvendor setting and has better information on end-consumer demand than the human supplier. The supplier offers either a quantity discount contract (with two or three price blocks) or a price-only contract, contracts that are commonplace in practice, yet different in complexity. Results show that, contrary to theoretical predictions, quantity discounts do not necessarily increase the suppliers profits. We also observe a more equitable distribution of profits between the supplier and the buyer than what theory predicts. These observations can be described with three decision biases (the probabilistic choice bias, the reinforcement bias, and the memory bias) and can be modeled using the experience-weighted attraction learning model. Our results demonstrate that simpler contracts, such as a price-only contract or a quantity discount contract with a low number of price blocks, are sufficient for a supplier designing contracts under asymmetric demand information. This paper was accepted by Christian Terwiesch, operations and supply chain management.

Evaluating Promotional Activities in an Online Two-Sided Market of User-Generated Content

We measure the value of promotional activities and referrals by content creators to an online platform of user-generated content. To do so, we develop a modeling approach that explains individual-level choices of visiting the platform, creating, and purchasing content as a function of consumer characteristics and marketing activities, allowing for the possibility of interdependence of decisions within and across users. Empirically, we apply our model to Hewlett-Packards (HP) print-on-demand service of user-created magazines, named MagCloud. We use two distinct data sets to show the applicability of our approach: an aggregate-level data set from Google Analytics, which is a widely available source of data to managers, and an individual-level data set from HP. Our results compare content creator activities, which include referrals and word-of-mouth efforts, with firm-based actions, such as price promotions and public relations. We show that price promotions have strong effects but are limited to the purchase decisions, whereas content creator referrals and public relations efforts have broader effects that impact all consumer decisions at the platform. We provide recommendations as to the level of a firms investments when “free” promotional activities by content creators exist. These free marketing campaigns are likely to have a substantial presence in most online services of user-generated content.

A Quantum Treatment of Public Goods Economics

AbstractQuantum generalizations of conventional games broaden the range of available strategies, which can help improve outcomes for the participants. With many players, such quantum games can involve entanglement among many states which is difficult to implement, especially if the states must be communicated over some distance. This paper describes a quantum approach to the economically significant n-player public goods game that requires only two-particle entanglement and is thus much easier to implement than more general quantum mechanisms. In spite of the large temptation to free ride on the efforts of others in the original game, two-particle entanglement is sufficient to give near optimal expected payoff when players use a simple mixed strategy for which no player can benefit by making different choices. This mechanism can also address some heterogeneous preferences among the players. PACS: 03.67-a; 02.50Le; 89.65.Gh

Forecasting uncertain events with small groups

We present a novel methodology for predicting future outcomes that uses small numbers of individuals participating in an imperfect information market. By determining their risk attitudes and performing a nonlinear aggregation of their predictions, we are able to assess the probability of the future outcome of an uncertain event and compare it to both the objective probability of its occurrence and the performance of the market as a whole. Experiments show that this nonlinear aggregation mechanism vastly outperforms both the imperfect market and the best of the participants.

Supply Chain Contract Design: Impact of Bounded Rationality and Individual Heterogeneity

In this article, we model various forms of non-optimizing behavior in a newsvendor setting, including biases such as recency, reinforcement, demand chasing, and anchoring, as well as unsystematic decision errors. We assume that a newsvendor may evaluate decisions by examining both past outcomes and future expected payoffs. Our model is motivated by laboratory observations under several types of supply chain contracts. Ordering decisions are found to follow multi-modal distributions that are dependent on contract structures and incentives. We differ from previous research by using statistics to determine which behavioral factors are applicable to each decision maker. A great deal of heterogeneity was discovered, indicating the importance of calibrating a contract to the individual. Our analysis also shows that the profit performance and the effectiveness of co-ordinating contracts can be affected by non-optimizing behaviors significantly. We conclude that, in addition to the aggregate order quantities, the decision distributions should be considered in designing contracts.

AutONA: a system for automated multiple 1-1 negotiation

The AutONA (Automated One-to-one Negotiation Agent) system was conceived as a means of reducing these operational procurement costs, enabling procurement departments to automate as much price negotiation as possible, thus creating the option of reducing direct costs and/or redeployment of operational effort into strategic procurement requiring high human involvement. The problem domain has been limited to the automation of multiple 1:1 negotiations over price for quantities of a substitutable good subject to the organisations procurement constraints of target quantity, price ceiling and deadline.

How Well Do People Play a Quantum Prisoner's Dilemma?

Game theory suggests quantum information processing technologies could provide useful new economic mechanisms. For example, using shared entangled quantum states can alter incentives so as to reduce the free-rider problem inherent in economic contexts such as public goods provisioning. However, game theory assumes players understand fully the consequences of manipulating quantum states and are rational. Its predictions do not always describe human behavior accurately. To evaluate the potential practicality of quantum economic mechanisms, we experimentally tested how people play the quantum version of the prisoner’s dilemma game in a laboratory setting using a simulated version of the underlying quantum physics. Even without formal training in quantum mechanics, people nearly achieve the payoffs theory predicts, but do not use mixed-strategy Nash equilibria predicted by game theory. Moreover, this correspondence with game theory for the quantum game is closer than that of the classical game.