Price-Setting Models for Innovative Products
Modern organizations have abundant choices in selecting the right product supply chain. Functional products are items that are purchased regularly, are widely available from multiple sources, and have long life cycles. Alternatively, innovative products are new to the marketplace, have unpredictable demand, and usually have short life cycles.
Read this article. Researchers suggest that products belong to either a functional or innovative category, where innovative products are much more challenging to price. What innovative products do you own, and how do you know you are getting the value you paid for?
Introduction
As a fundamental and important inventory management problem, the newsvendor models have been extensively reviewed. The newsvendor model applies to various decision-making contexts, such as inventory decisions, supply chain contracting and healthcare management. It examines a particular choice under uncertainty: A decision maker sets a quantity to match an uncertain variable, either too high or too low leads to a loss. Although the essential newsvendor model characterizes a one-variable problem that emphasizes operational efficiency, it also is foundational to the development of joint-decision models for defining and characterizing the operations/marketing interface, that is a decision maker sets not only a quantity, but a price to match a price depending uncertain variable. In this context, the newsvendor problem becomes a price-setting newsvendor problems.
Starting with the seminal work of Fisher, researchers in supply chain management have extensively studied innovative products. As Fisher's definition, products essentially belong to either innovative or functional categories. Compared with functional products, innovative products have shorter life cycles and unpredictable demands. For innovative products, before the selling season, the manufacturer has to make a decision on both the production quantity and the retail price, i.e., the pricing-setting newsvendor problem.
For one kind of innovative product, since the lifecycle is usually shorter than its procurement lead time, there is usually only one non-repeating selling season, only one demand quantity (scenario) will occur in only one selling season. Therefore, only one scenario would make sense for evaluating the newsvendor decisions related to the innovative product. Guo firstly raised the one-shot decision theory (OSDT), in which only some particular scenario is utilized to evaluate the objective function, for dealing with such problems. The one-shot decision process is separated into two steps. The first step is to seek an appropriate scenario from all possible states for each alternative. This scenario is called as the focus point of the alternative. The second step is to evaluate the alternatives by the satisfaction levels incurred by the focus points for obtaining the optimal alternative. Based on OSDT, plenty kinds of decision-making problems have been researched. Guo and Ma proposed the newsvendor model for innovative products where the manufacturer was in a perfect, competitive market so that the sale price was given. Zhu and Guo analyzed the approaches to bi-level programming problems. Recently, Guo proposed the focus theory of choice (FTC) that is a generalization of OSDT and provided axiomation to a decision-making procedure under risk and uncertainty. Several well-known anomalies, such as the Allais, Ellsberg and St. Petersburg paradoxes are well explained in the models. Based on the FTC, Guo and Zhu presented the focus programming, which provides a fundamental alternative for stochastic optimization problems.
There is a growing literature to show the decision biases in the real-world phenomena and experimental observations of the newsvendor type problems. The current models (e.g., risk-neutral, risk-seeking and risk-averse) do not describe actual decisions in the newsvendor setting very well and "another theory is needed". Therefore, it is interesting and valuable to continue examining the behaviors of the manufacturer in a monopolistic market with alternative decision rules or theories. We consider the manufacturer who produces and sells a kind of innovative product in a monopoly market. The manufacturer has only chance to decide both the production quantity and the sale price with the uncertain demand. The OSDT based price-setting newsvendor model is proposed for this situation. In this model, the decisions of the retail price and ordering quantity are both structured by the OSDT. It is a substantial extension of the research and enriches the literature of newsvendor.
The contributions are as follows:
First, the existing price-setting newsvendor models seek optimal inventories and prices to maximize the expected utilities (EUs). In these models, choosing a production quantity is equal to choosing a lottery (or a probability distribution). Because of the short life cycle of an innovative product, producing/selling such a product is a typical one-time decision. The risk attitudes of newsvendors for such a one-time decision are reflected by the differences of the utility functions (linear, concave and convex ones). Based on the OSDT, we build the price-setting newsvendor models and argue that the different behaviors of the manufacturers caused by their different personalities. According to the types of scenario (demand), they focus on the manufacturers can be divided into active, passive, apprehensive and daring types. The scenario-based price-setting newsvendor model is proposed, which is a fundamentally different model for analyzing the newsvendor problems in a monopoly market of an innovative product. Second, the theoretical analysis provides insights into the behaviors of manufacturers and several phenomena in the luxury goods market are well explained.
The remainder of the paper is structured as follows. In Section 2, the newsvendor models with the OSDT are introduced. In Section 3, the price-setting newsvendor model for innovative products is constructed. In Section 4, some theoretical analysis results are given, and several phenomena in the luxury goods market are examined. In Section 5, the numerical example is performed to demonstrate the proposed models. In Section 6, the conclusions and future research directions are given.