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Online product pricing is an important research field in the platform economy, and a two‐stage mixed presale is a mainstream mode of online sales. In the process of online consumption, the payment method and presale mode have an important impact on consumer behaviour and product pricing. Based on the two‐stage mixed presale mode, this study considers the impact of anchoring and the payment pain reduction effect on consumer behaviour, establishes the corresponding product pricing model and obtains the optimal presale price, sales and profit. It sheds light on the influence mechanism of anchoring and the payment pain reduction effect on consumer behaviour and online product pricing. Theoretical and numerical analyses reveal that the payment pain reduction effect can help to raise the product price, stimulate market vitality and bring higher profits for online retailers, and the anchoring effect and consumers' loss aversion psychology can enhance the profits and sales of online retailers, but they will discourage setting high prices for products. The research results will further enrich the relevant research on customer behaviour and product pricing in the platform economy and will provide decision bases for platform enterprises and online retailers to participate in presale activities and formulate product pricing strategies. [ABSTRACT FROM AUTHOR]

Online product pricing is an important factor that affects the purchase of customers and the earnings of e‐commerce platform enterprises. It has an increasingly prominent influence on consumers' purchasing decisions. To study the influence of customers' anchoring psychology and product pricing on customers' purchasing behaviors, this paper proposes a pricing model that considers online consumers to be anchored by the product price and sales. The cognitive bias of online consumers is described by a utility function based on an anchoring‐adjustment heuristic, and consumer choice behavior and an online product pricing strategy are studied with a multinomial logit model. Then, it studies the influence of the anchoring point and anchoring degree on optimal pricing, sales and profit. In particular, when consumers are anchored only by sales of goods, the optimal solution is monotonic with respect to the anchoring degree. However, when consumers are anchored by both price and sales, both factors affect consumer behaviors and produce more complex results. This paper provides a flexible pricing mechanism for platform enterprises, and it can provide a theoretical basis and decision support for dynamic pricing of platform enterprises based on historical consumption data. [ABSTRACT FROM AUTHOR]

With the rapid development of O2O, offline experience and online purchase have become a method of purchase for more and more customers. Through offline experience, consumers can feel the quality of products directly. Such channel switching behavior of consumers will produce a "showroom" effect and affect the return rate of online channels. This study adopts the multinomial logit model to maximize profits by considering the difference in quality between online and offline products, quality defects, and offline service. Then, a pricing decision model is developed to analyze the influence of returning goods due to quality problems on the retailers' optimal pricing and profit. The result shows that retailers can obtain the optimal profit when the offline service is maintained at a certain level. As the return rate increases, the optimal pricing increases, but the maximum profit decreases. The optimal pricing decreases with the increase in online product quality, but the maximum profit increases accordingly. In the omni-channel environment, customers can freely switch between channels according to utility and preference when purchasing products. Based on customer returns, retailers can dynamically adjust their service, control product quality, and set optimal product pricing, thus achieving maximum profits. This study can provide a theoretical basis and decision support for omni-channel retailers in platform operation and revenue management. [ABSTRACT FROM AUTHOR]

Incorporating consumer choice behavior into a product line design optimization model enhances the understanding of consumer choices and improves the opportunities to increase profit. Most product line optimization problems assume that parameters are precisely known in consumer choice model. However, the decision maker does not precisely know the model parameters because of insufficient sample data, measurement problems, and other factors. We investigate the problem of establishing robust product line pricing under a multinomial logit model to account for the uncertainty of the valuation parameter. First, we present a nominal product line model to maximize profit. We then establish a robust product line model to maximize the worst-case expected profit, where the valuation parameter lies in an uncertainty set. We consider both single and multiple products development and derive the optimal prices' closed-form expressions. Through numerical experiments, we illustrate the benefit of robust product line pricing to address parameter uncertainty. We demonstrate that the difference between the expected nominal profit and the worst-case profit increases with the increase of the interval of the uncertainty set, and the robust profit relative to the worst-case nominal profit improves. The robust product line design can ensure steadier, even higher profit. [ABSTRACT FROM AUTHOR]

With recent developments in information technology and the extensive promotion of Internet Plus, the use of online centralized procurement by governments and enterprise groups has become progressively more common, and the winning bid evaluation decision making method is particularly important in this context. However, experts might not be completely rational during the process of bid evaluation, which may induce the enhancement or repression of bid scores. To address such behaviors during the process of bid evaluation, an automatic mechanism to identify and correct such tendencies is proposed in this study. Because experts have different preferences for different alternatives, which are directly reflected in the evaluation of attribute values. Based on selection preference, this paper proposes a selection preference method for solving the subjective weight of attributes. Firstly, the weights of relevant attributes are first determined via the entropy weight method and the selection preference method, and the weights corresponding to groups are determined according to the differences between the scores assigned by experts. Then, a grouped multi-attribute bid evaluation decision making method is proposed based on the selection preference. Finally, an example is used to verify the effectiveness of the method and its superiority over existing methods. Thus, a theoretical basis and a decision support mechanism are provided in this study for centralized procurement departments of governments and enterprises. Further, it also provides guidance for multi-attribute decision making problems with identical grouped features. [ABSTRACT FROM AUTHOR]

Isothermal thermal decomposition method was used to study the thermal behavior of the HMX-based PBX explosive JOL-1. The gas pressure versus time curves of the isothermal decomposition of JOL-1 were obtained within the temperature range of 90°C to 130°C. Kinetic parameters such as activation energy and frequency factor for the thermal decomposition of JOL-1 were obtained using the Arrhenius equation and model-fitting method. The model-fitting method further proved that the isothermal decomposition of JOL-1 at 90°C, 100°C, 110°C, 120°C, and 130°C is consistent with the No. 8 mechanism function, namely, the anti-Jander equation, controlled by 3D diffusion. The storage life of JOL-1 was estimated by the Semenov equation and the extent of reaction reached 0.1–0.4%. Results showed that the effective storage life of JOL-1 at 25°C, 40°C, and 60°C are 68 years, 10 years, 1 year, respectively, when the extent of reaction reached 0.1%. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The complex network effect of the product exhibits has a significant impact on the product line optimization design. The multinomial logit (MNL) model which is used to simulate consumer choice behavior is applied in most of product line optimization problems. However, its assumptions, independence of irrelevant alternatives (IIA) and the same Gumbel distribution of random error terms, are usually difficult to be met in practice. The marginal moment model (MMM) can be used when the mean and variance of consumer's utility error are known. The MMM not only has weak assumption conditions but also overcomes the IIA problem of MNL model. In this paper, we study the product pricing problem based on MMM with endogenous negative network effect. Firstly, we construct a variant of MMM considering network effect in product line optimization design. Secondly, we prove that the revenue function is concave in market share. We propose the solving methods of the model to obtain the optimal price, the corresponding market share, and the revenue under three different scenarios, i.e., developing single product, homogeneous products, and heterogeneous products. Finally, numerical experiments show that the proposed model can better simulate consumer choice behavior and potentially increase revenue. [ABSTRACT FROM AUTHOR]

During warhead penetration, which lasts several milliseconds, warheads undertake moderate pressures reaching hundreds of MPa. Previous methods have been unable to mimic such stimuli to evaluate the safety of ammunitions. Hence, new safety evaluation methods with moderate pressures and long durations to assess the stability of the explosive charges during actual penetrations are needed. Based on existing explosives safety estimation technologies and preliminary understanding of overload environments during penetration, a confined impact model was developed. The peak stimuli pressure is more than 0.3 GPa and the duration of the pressure is between 1 to 3 milliseconds. Various scales of a polymer-bonded explosive (PBX-9) were subjected to this confined impact test to study the response characteristics. The ignition mechanism of PBX-9 was obtained by synthesizing results from X-ray photoelectron spectroscopy (XPS), computed tomography (CT) scanning, differential scanning calorimetry (DSC) and thermalgravimetric analysis (TG). It was found that cracks formed on the surface during impact and the initial ignition of PBX-9 is mainly due to the decomposition of Ammonium perchlorate (AP) and hydroxyl-terminated polybutadiene (HTPB) on the interface at low temperature. Our study indicates that the designers of the PBX formulation should try to control the early decomposition of AP and HTPB in order to let the PBX survive the penetration. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]