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ABSTRACTThe global economy is transitioning from product economy to service economy, and the optimization of product line with value-added services is one of the important issues faced by enterprises. Therefore, this paper studies the pricing optimization of product line with value-added services considering consumer choice behavior. First, we apply the multinomial logit (MNL) model to simulate consumer choice behavior, and establish a MNL-based product line pricing optimization model considering value-added services. Then, the optimal pricing strategies for products and services are solved for three different scenarios: single product with service, homogeneous products with services, and heterogeneous products with services. Finally, through numerical experiments, we analyze the changing trends of the optimal pricing, market share and profit of products line with value-added services with some impact factors, such as product quality, service level, consumer sensitivity, and number of products under three different scenarios. We also obtain some managerial implications when an enterprise develops product line with value-added service.

Price anchoring and online reviews are prominent features in the customer purchasing process on the platform. These factors adjust customer cognition and significantly impact their choice behavior, ultimately affecting product rollover strategies. Focusing on the product single rollover, this study develops a multistage dynamic pricing and attribute optimization model based on online reviews and price anchoring effect. We explore dynamic pricing, product exit strategies, attributes optimization, and product rollover strategies. The study shows that considering price anchoring effects usually results in firms achieving higher profits compared to when they ignore this factor. As a result, skimming and penetration pricing strategies emerge as preferred strategies for current product dynamic pricing. However, excessively low prices for current products may diminish profits from upgraded products after product rollover, prompting firms to carefully balance current product pricing with upgraded product sales. Additionally, two threshold conditions are obtained, which can determine the priority of attribute improvement and the total quantity of optimized attributes. Counterintuitively, as consumer willingness to pay rises, firms may reduce their innovation efforts. Furthermore, we expanded the product rollover framework and derived sufficient conditions and optimal strategies to adopt dual rollover. The research findings provide theoretical foundations and decision-making support for the product rollover and marketing strategies of innovative enterprises.

Bid evaluation plays an important role in reverse auctions, as it determines the winner. By the assumption of bounded rationality, the fairness of bid evaluation is influenced by the behavior and management strategy of the referees. In this article, a tripartite game model between the technical experts, the business experts, and the management department is constructed for grouped multiattribute reserve auctions. The static equilibrium strategies and the factors that affect the equilibrium behavior of each player are analyzed by evolutionary game theory. Finally, to study the behaviors of three subjects, a simulation system is established on MATLAB GUI that quantitatively indicates the effect of initial conditions and related parameter changes on the evolution results, and then the corresponding management strategies are provided. It is demonstrated that the behaviors of each party will evolve in a favorable direction by adjusting the model parameters. This article contributes to predict the behavioral evolution of bid evaluation participants and improve the fairness in bid evaluation.

Products exhibit network effects when the utility a customer obtains from buying a product depends not only on its attributes but also on the sales of the same or similar products. In this article, we study product line optimization problem considering network effects. We first characterize consumer choice model considering network effects. Then we investigate the product line optimization problem under such model. In the homogeneous case with the same products, we find that the optimal choice probabilities and optimal prices may be different for each product. In the heterogeneous case with different products, there is at most one product that takes the “high” market share while all the other products take “low” market share. In particular, when only the network effects are heterogeneous, the larger the network effect, the lower the optimal pricing and the higher the market share. Through numerical experiment, finally, we demonstrate the importance of considering network effects and test the robustness of solutions.

Reverse auctions with multiple attributes have been extensively applied for centralized purchasing of large enterprises and governments. This paper focuses on the bid evaluation behaviors of referee experts and employs an evolutionary game approach to improve the fairness and reliability of bid evaluation. First, the bid evaluation process and existing problems in the mechanism are described. Second, a static game model is constructed to analyze the conditions that are necessary for achieving a long-term cooperative equilibrium between business and technical groups. Third, some evolutionary paths and factors influencing bid evaluation behaviors are analyzed, and then a simulation system is developed based on the evolution process and run several times on a MATLAB GUI platform. The simulation results explicitly make a wider gamut of decision-making parameters as well as start-up variants on initial conditions that determine further evolution. The methods and results presented in this paper can provide decision support for administrative departments in the bid evaluations of centralized purchasing. Those bodies can then choose from the best existing management policies to guide the referee experts' behaviors into the desired channels and toward optimal outcomes. A more judicious bidding evaluations process may result.

This paper investigates the product-positioning problem for a monopolist developing of a new product. The majority of the literature on product positioning assumes that the consumer choice model and parameters are both precisely known. In reality, however, the marketer may be uncertain about the model structure or the parameters due to incomplete information, small sample data size, etc. In this paper, we investigate a robust product-positioning problem based on the multinomial logit model to account for parameter uncertainty. We first establish a nominal product-positioning model, in which valuation parameters are assumed to be known. Then, we investigate a static robust product-positioning problem with the multinomial logit model to obtain the maximin revenue. We also propose a two-period dynamic robust model. For each setting, we consider both homogeneous and heterogeneous customers' preferences. Finally, numerical experiments are presented to compare the nominal model with the static robust model, and to compare the static robust model with the dynamic robust model. The experiments show that when facing uncertain parameters, the robust model obtains more stable revenue than the nominal model; the dynamic robust model obtains higher revenue than the static robust model.

ABSTRACTThe probabilistic choice model is an important theory foundation for investigating consumer choice behavior in product optimization. In most studies, probabilistic choice behavior is simulated by the multinomial logit (MNL) model and a product always obtains some market share even though the utility a consumer obtains from buying the product is negative. However, the MNL model has a very restrictive substitution pattern – the independence of irrelevant alternatives (IIA). This paper investigates a product optimization problem based on the marginal moment model (MMM). Residual utility is involved in the MMM and negative utility is considered as well. The optimization model of product line design, based on the improved MMM, is established to maximize total profit through three types of problems. The established model fits reality better because the MMM does not have the IIA problem and has good statistical performance. Numerical experiments are carried out to evaluate the feasibility of the proposed model. Meanwhile, the relationships are explored between the optimal solutions and several factors, including the competitive products’ prices, utility variance, rate of cost reduction, and utility of competitive products.

Reverse auctions with multiattributes are widely used for centralized procurements of large enterprises and government departments. The bid evaluation mechanism is a key factor for a fair auction and resource allocation. The current bid evaluation process is usually done by two groups, a business expert group and a technical expert group, separately. Taking bounded rationality as a precondition, we analyze the existence of antagonistic feelings between the two groups. The antagonistic feelings may grow as time goes by. To verify the discovered points, a multiagent-based approach is used to simulate the bid evaluation behaviors. The prototype system of a current bid evaluation mechanism is described by a multiagent model. In the model, the behaviors of both auctioneer and bidders are described by the attributes of each agent and decision rules. Their interactions are described by the collaboration and information exchange between different agents. The procedure of multiagent simulation is specifically presented. Then, the multiagent simulation system is developed and repeatedly runs on the platform of MATLAB GUI while adjusting relevant parameters. The results demonstrate that the behaviors of raising and repressing bid scores are increasingly severe with the passage of time. The result is that differences between the two groups increase with a decrease in the objectiveness of experts. The accumulation of antagonistic feelings can be obviously observed. The current mechanism is unfair to the bidders, as it may make the best bid lose the auction. To solve this problem, two modified bid evaluation mechanisms are suggested. The simulation comparison results show that the new bid evaluation mechanisms can efficiently weaken the antagonistic feelings of the two groups. Finally, three constructive suggestions are put forward to the organizer of tendering and bidding.