微信社群互动行为对用户理财产品投资组合风险决策的影响

微信社群如何影响用户理财产品购买决策是当下金融产品营销的一个重要理论问题。本研究依据效价理论提出感知风险、感知收益与用户理财产品的投资组合风险决策的关系模型,并将用户的微信社群互动纳入模型。基于287个用户问卷数据,129个微信社群的互动行为数据,以及用户理财产品实际购买行为的数据分析,发现用户购买理财产品的投资组合风险决策受到其感知风险与感知收益的影响,而且微信社群的互动频率负向影响用户感知风险与用户投资组合风险决策之间的负向关系、微信社群的消极情绪会加强感知风险对用户投资组合风险决策的负向影响并削弱感知利益对于用户投资组合风险决策的正向影响。本研究扩展了有关用户理财产品决策影响因素的分析视角,并对理财产品的用户管理有借鉴价值。     

Consumer choice behaviour and new product development: an integrated market simulation approach

The extremely high costs associated with the commercial failure of a new product, stresses the importance of a model that will effectively forecast the market penetration of a product at the design stage. The purpose of our study is to discover heuristics that will better explain market share, an issue of considerable concern to industry, which also, if successfully pursued, will increase the value of the analytical tools developed for managers. A method easy to implement is presented, which improves the value of market simulations in conjoint analysis. The proposed approach deals with two issues common to traditional market simulations in the context of conjoint analysis applications—the lack of differential impact of attributes across alternatives and the absence of accounting for differential substitution across brands (ie, the Independence from Irrelevant Alternatives problem). We deal with the first issue by ‘tuning’ utilities with individual level exponents, as opposed to a common exponent under the ‘ALPHA’ rule (the current state of the art approach). These exponents derive from the range, skewness and kurtosis of the distribution of utilities that a respondent assigns to various products. While these exponents are individual specific, the effects of the coefficients are assumed to be homogeneous across consumers to preserve model parsimony, while accounting for observed heterogeneity in the data. The second issue is studied in the model via a similarity ‘correction’ for each pair of products. The performance of the approach is validated both on real data from a market survey concerning milk, and on simulated data through the design of a Monte Carlo experiment. The results of the simulation for different market scenarios indicate that the approach appropriately exhibits the theoretical properties that are necessary for the efficient representation of consumer choice behaviour. In addition, the proposed model outperforms the state of the art methodology, as well as some more traditional approaches, with regard to the forecasting accuracy on market shares estimation, both on the real and the simulated data sets. The results obtained have important implications for marketing managers concerning the design of new products. A new concept can be tested before it enters the production stage, using data obtained from a market survey. The high predictive accuracy of the model may assist a firm in minimizing the uncertainty and risks associated with a new product launch. The case study with data from a real market survey, illustrates the practical applicability of the approach.     

Factors which influence decision making in new product evaluation

New product development is indeed very important for companies. However, developing new products is a risky and uncertain process. In order to reduce the risks and uncertainties, companies need to evaluate their new product initiatives carefully and make accurate decisions. Although the outcome of a new product evaluation decision can be influenced by the environmental uncertainties that are beyond a company’s control, companies can successfully improve the accuracy of their new product evaluation decisions. This article presents an integrated framework for understanding how various factors affect decision making in new product evaluation and provides guidelines for reducing their negative impacts on new product decisions. The results indicate that the quality of new product evaluation decisions is affected by four major sets of factors, namely the nature of the task, the type of individuals who are involved in the decisions, the way the individuals’ opinions are elicited and the way the opinions are aggregated.     

Selling to customers with both Veblen and network effects

For the products that provide not only intrinsic value from their functions but also stylish consumption experience, there often exist both Veblen and network effects. Some customers are more likely to purchase the product if fewer customers can afford it, while others might appreciate the existence of more peers. Focusing on these products, we study the market equilibrium under rational expectations. The optimal pricing and quantity decisions reveal interesting insights about the effects of such mixed consumption externalities.     

SAA-regularized methods for multiproduct price optimization under the pure characteristics demand model

Utility-based choice models are often used to determine a consumer’s purchase decision among a list of available products; to provide an estimate of product demands; and, when data on purchase decisions or market shares are available, to infer consumers’ preferences over observed product characteristics. These models also serve as a building block in modeling firms’ pricing and assortment optimization problems. We consider a firm’s multiproduct pricing problem, in which product demands are determined by a pure characteristics model. A sample average approximation (SAA) method is used to approximate the expected market share of products and the firm profit. We propose an SAA-regularized method for the multiproduct price optimization problem. We present convergence analysis and numerical examples to show the efficiency and the effectiveness of the proposed method.     

周期与季节性因素影响下的短生命周期产品预测优化模型

短生命周期产品因为需求的随机性和产品价值的瞬间变化性,对预测准确性提出了更高的要求.然而许多企业在使用多种预测模型后发现其预测准确率并没有得到显著提升.以短生命周期产品需求特点为背景,在需求预测影响的BASS模型基础上,建立受生命周期和季节性因素影响的需求预测优化模型,最后通过一个产品的实例证实了验证了模型的合理性.     

Information acquisition in new product introduction

In the presence of huge losses from unsuccessful new product introductions, companies often seek forecast information from various sources. As the information can be costly, companies need to determine how much effort to put into acquiring the information. Such a decision is strategically important because an insufficient investment may cause lack of knowledge of product profitability, which in turn may lead to introducing a loss-making product or scrapping a potentially profitable one. In this paper, we use decision analytical models to study information acquisition for new product introduction. Specifically, we consider a decision maker (DM) who, prior to introducing a new product, can purchase forecasts and use the information to update his knowledge of the market demand. We analyze and compare two approaches: The first approach is to determine the total amount of forecasts to purchase all at once. The second one is to purchase forecasts sequentially and, based on the purchased forecasts, determine whether those forecasts are informative enough for making an introduction decision or an additional forecast is needed. We present dynamic programming formulations for both approaches and derive the optimal policies. Via a numerical study, we find the second approach, i.e., purchasing forecasts sequentially, can generate a significant profit advantage over the first one when (1) the cost of acquiring forecasts is neither too high nor too low, (2) the precision of the forecasts is of a moderate level, and (3) the profit margin of the new product is small.     

A duopolistic model of dynamic competitive advertising

This paper proposes a differential game model of competitive advertising decisions for non-durable products by extending the Lanchester model and the Deal model of competitive advertising in the literature. The proposed model is compared empirically with the Lanchester model for model fitting and forecast accuracy. It is shown that the model is suitable for an actual market and out-performs the Lanchester model in forecast accuracy. The model provides a sensible modeling alternative to the Lanchester model for the study of dynamic competitive advertising decisions. Necessary and sufficient conditions for open-loop and closed-loop Nash equilibrium solutions to the model are discussed. A numerical algorithm for open-loop and closed-loop Nash strategies to the model is developed.     

一种使用在线评论信息的商品购买决策分析方法

在线评论信息对消费者的商品购买决策影响非常显著,如何使用数据体量较大的在线评论信息来进行有针对性的商品购买决策分析是近年来尤为需要关注的一个新研究内容。本文提出一种使用在线评论信息的商品购买决策分析方法。首先,通过在线评论信息的挖掘来确定了消费者所重点关注的关于候选商品的商品特征及其权重;然后,通过消费者情感的分析来构建了关于各候选商品的商品购买决策矩阵;在此基础上,通过给出的一种基于随机TOPSIS的方案排序方法来进行了各候选商品的排序。最后,依据携程网提供的关于三家客栈的在线评论信息进行了数据实验,从而说明了本文提出方法的实用性与可行性。     

基于顾客资产驱动因素与同辈影响的青少年购买行为研究

研究的主要内容围绕着顾客资产驱动因素及同辈影响对青少年消费者购买意向和实际购买行为的影响展开.在文献综述的基础上,以运动品牌为例,分析价值资产、品牌资产、关系资产以及同辈影响对于青少年消费者购买意向的影响.实证研究表明,同辈影响对于青少年消费者购买意向有着非常显著的影响,同辈群体的炫耀、谈论与推荐行为越多,则青少年消费者的购买意向越强烈.与此同时,购买意向对于实际购买行为的影响虽是正向且显著地,但受到购买惯性的影响而减弱.结论一定程度上从统计上论证了青少年消费者的购买特点,同时也为运动品牌的青少年产品营销活动提供了参考依据.     

Impact of demographic and economic variables on financial policy purchase timing decisions

This paper investigates the extent to which consumers' demographic factors influence their financial policy purchasing behaviours and also explores how the external economic environment affects consumers' propensities to purchase financial products. The Cox proportional hazard model is used to explore these issues. The results suggest that consumer decisions on the timing of financial product purchases are largely explained by changes in the economic environment in terms of stock market, the housing market, average earnings, consumer confidence, and interest rates. The influence of customer demographic factors is also important but secondary.     

Analytical and managerial implications of integrating product substitutability in the joint pricing and procurement problem

This paper studies the analytical and managerial implications of product substitutability on the joint pricing and procurement decisions. We consider a single-period model with two products: an existing product and an improved new product that can substitute the demand for the existing product in case of a shortage. Demand for each product follows a general distribution with an expected value that is a linear function of the price of the new product. While the price of the existing product is determined by the market, it is necessary to determine the new product’s price and the procurement quantities of both products so as to maximize the profits. We analytically show that the expected profit function is unimodal and in the existence of substitution: the expected total profit is higher; the optimal price and the safety stock of the new product are higher; and the optimal safety stock of the existing product is less. Using these properties an efficient algorithm is developed. We also provide a numerical analysis to demonstrate that considering substitution in advance could increase the profitability by 58% and the new product price by 5% while decreasing the total procurement quantity by 15%.     

An integrated product returns model with logistics and marketing coordination

We develop an integrated approach for analyzing logistics and marketing decisions within the context of designing an optimal returns system for a retailer servicing two distinct market segments. At the operational level, we show that the optimal refund price is not unique. Moreover, it is such that if both market segments return a purchased product, then neither segment will receive a full money-back refund; and it is such that if one or both segments do not return a purchased product, then a refund premium over the purchase price is possible, but the refund premium will not be enough to offset a customer's total net cost of purchase and return. We also show that any improvement to the returns system that results in increased logistical efficiency or marketing effectiveness will be accompanied by an increase in the selling price of the product. At the strategic level, we show that if the retailer does not coordinate its logistics and marketing efforts to improve the overall returns system, then it will tend to over-invest in one of the functions and under-invest in the other. Finally, we illustrate how our model can be generalized to the case in which a customer's ex post valuation of the product falls along a continuum.     

Choice of a New Product,its Selling Pattern and Price

A decision theory model which takes account of competitive reaction to the introduction of new brands into an existing market was developed. It led to a linear programming solution. The experience and knowledge of the marketing and sales personnel were quantified to provide data for the model. Results from the model were implemented and the information obtained was used as the basis for subsequent decisions. A change in profit was predicted with good accuracy.     

An agent-based investigation into the new product development capability

The capability to bring products to market which comply with quality, cost and development time goals is vital to the survival of firms in a competitve environment. New product development comprises knowledge creation and search and can be organized in different ways. In this paper, we study the performance of several alternative organizational models for new product development using a model of distributed, self-adapting (learning) agents. The agents (a marketing and a production agent) are modelled via neural networks. The artificial new product development process analyzed starts with learning on the basis of an initial set of production and marketing data about possible products and their evaluation. Subsequently, in each step of the process, the agents search for a better product with their current models of the environment and, then, refine their representations based on additional prototypes generated (new learning data). Within this framework, we investigate the influence of different types of new product search methods and generating prototypes/learning according to the performance of individual agents and the organization as a whole. In particular, sequential, team-based Trial & Error and House of Quality guided search are combined with prototype sampling methods of different intensity and breadth; also, the complexity of the agents (number of hidden units) is varied. It turns out that both the knowledge base and the search procedure have a significant impact on the agents' generalization ability and success in new product development. Andreas Mild was born in Vienna, Austria, in 1973. He studied business administration in Vienna, in 2000 he received his Ph.D. from the Vienna University of Economics and Business Administration (WU). Since 2003 he is associated professor at the WU. He has been guest professor in Frankfurt, Germany, Sydney, Australia and Bangkok, Thailand. Previous research appeared in Journals such as MIS Quarterly, Management Science and Marketing Science. His research interests currently include agent-based models, new product development and recommender systems. Alfred Taudes was born in Vienna, Austria, in 1959. He studied business administration and management information systems (MIS) in Vienna (doctorate 1984), in 1991 he received his Ph.D. from the Vienna University of Economics and Business Administration (WU). He was assistant professor at the WU (1986–1991) and professor for MIS at the German Universities of Augsburg (1991), Münster (1991/92) and Essen (1992/93). Since 1993, he has been professor for MIS at the WU and Head of the Department for Production Management. Since 2000, Dr. Taudes has been speaker for the Special Research Area SFB # 010 (Adaptive Information Systems and Modelling in Economics and Management Science). His research interests currently include agent-based models of industry structures, management of innovation, technology management and business strategy.     

On the product line selection problem under attraction choice models of consumer behavior

Product line design (PLD) involves important decisions at the interface of operations and marketing that are very costly to implement and change, and, simultaneously, determinant for market success. To evaluate the financial performance of a product line, a number of mathematical programming approaches have been proposed. Problem formulations are typically mixed or pure integer non-linear optimization models that are intractable for exact solution - in particular when empirically supported consumer choice models are incorporated.     

基于在线评论的多个竞争制造商和零售商的产品定价策略

在线评论作为一种产品信息传播载体,越来越受到网上电商及消费者的重视,并在很大程度上影响消费者的购买决策。本文在多个竞争性制造商为在线零售商提供可替代性产品并通过零售商销售给网络消费者的电子商务环境下,研究在线评论信息如何影响网络消费者购买决策及在线零售商和制造商的定价策略。以neo-Hoteling模型为基础,构建了依赖零售渠道在线评论的消费者选择模型,并通过模型求解定量分析了二级供应链结构分散系统下在线评论对多个竞争性制造商及零售商最优决策的影响。得到当制造商基于评论制定最优定价策略时,在线评论对市场竞争强度没有影响,但决定潜在市场大小;各产品的均衡批发价及销售价按一定的比例随评论揭示的该产品与其他产品质量均值之差(正或负)增加或减少,评论信息通常会使制造商因好评而获利,由于评论增加了不同产品需求的不对称性,零售商因而具有更大的调价空间,往往通过提高(降低)占据有利(不利)评论的产品价格获得更高的利润。     

Investing in product development and production capabilities: The crucial linkage between time-to-market and ramp-up time

Shorter product life cycles, more rapid product obsolescence, and the increasing intensity of global competition have driven firms to strive for a more rapid introduction of new products to market. We introduce a normative model which yields insights concerning several key new product development (NPD) decisions. First, we examine investment strategies related to the timing and duration for investments in both design and process capacity over a given planning horizon. Second, the model offers guidance regarding the optimal time-to-market and ramp-up time necessary to meet peak demand for the new product. The model thus provides both theoretical and managerial insights into the crucial linkage between time-to-market and ramp-up time decisions. Finally, the implications of several specific NPD investment mechanisms on these NPD metrics are explored.     

Operationalizing technology improvements in product development decision-making

Achieving competitive advantage and price premiums in many technology-based markets requires the incorporation of current technology in new products. To do so, firms in hyper-competitive environments increasingly plan and design their products concurrent with the independent development and validation of underlying technologies. Simultaneous validation of a core technology has important implications for a company’s product positioning and launch sequence decisions making these traditional marketing decisions relevant to operations managers. Prior research has shown that to minimize cannibalization in the absence of such improvements in technology, a firm should not launch low-end products before high-end products. However, concurrent evolution of technology can make it desirable and even necessary to introduce low-end products before high-end products. This is because in technology-based industries, improvements in technology delay the introduction of a high-end product, and a firm must trade-off the benefit of launching the low-end product earlier (greater discounted profits) against the cost of cannibalization of high-end product sales. High-end product cannibalization can be further reduced by offering the customer an option to upgrade from the low-end to high-end product, with important implications for the firm’s product positioning and introduction sequence decisions. Based on our study in the high technology industry, we model the product positioning and introduction sequence decisions under the simultaneous evolution of technology. Our analysis indicates that it may be optimal in a variety of circumstances for a firm to launch products in an increasing order of performance, even in the absence of network externalities. Besides presenting analytical results for product positioning and profit from different introduction sequences, the paper also makes a contribution to managerial practice by providing insights in the form of a conceptual framework.     

Green product development under competition: A study of the fashion apparel industry

Motivated by the observed industrial issues, we analytically develop a fashion supply chain consisting of one manufacturer and two competing retailers and investigate how retail competition and consumer returns affect green product development in fashion apparel. In the basic model, that is, the pure “product greenness level” game, we find that the optimal greenness level of the fashion product decreases along with the level of market competition. This finding implies that a more competitive market leads to a lower optimal greenness level. We also identify that when the consumer return rate increases, the optimal product greenness level is substantially reduced. In the extended model with joint decisions on greenness and pricing, we find that the optimal product greenness level for the whole channel is always higher in the scenario when both retailers charge a higher retail price than in the case with a lower retail price. As such, the underdevelopment of green fashion products is a result of fashion industry features, such as an extremely competitive environment for green product development, relatively low retail prices for fashion products, and high consumer return rates. Therefore, fashion companies should join a co-opetition game for the green product market and simultaneously enhance their efficiency in managing consumer returns. To support our analytical findings, we conduct extensive industrial interviews with various representative companies. Based on this multi-methodological approach (MMA), this paper generates practice-relevant managerial insights that not only contribute to the literature, but also act as valuable references for industrialists.