Understanding the impacts of product knowledge and product type on the accuracy of intentions-based new product predictions

New product development involves several critical decisions. A key decision making area in new product development is the evaluation of the viability and the market potentials of a new product. In the absence of any relevant historical data, companies ask the potential buyers of their products about their intentions to buy those products when assessing their viability. Despite the popularity of the use of behavioral intentions in predicting the market acceptance of new product ideas, both survey and empirical studies suggest that the accuracy of such predictions is usually very low. Although earlier case-based studies suggest that a number of factors can affect the quality of new product decisions, it is still empirically unclear how product knowledge and the type of new products might impact the predictive accuracy of intentions-based new product forecasting. This study utilized a longitudinal research design and empirically tested the hypotheses across two new products. The study first collected purchase intentions data about the new products. Second, it collected subsequent actual purchase data about the new products. The results of series of hierarchical regression analyses comparing the initial purchase intentions and subsequent actual behaviors showed that while product knowledge is positively related to the predictive accuracy and consistency of intentions-based new product forecasting, product type is negatively related to them.     

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.     

Supply chain dynamic configuration as a result of new product development

This study considers supply chain network configuration in an innovative environment while the new product development (NPD) will affect the supply chain configuration (SCC). The time of new product introduction has a significant effect on the market performance while it has an effect on the supply chain configuration. Supplier integration into the new product introduction is the key parameter for successfully new product introduction, which may contribute to supply chain reconfiguration. Consequently By considering the new product development concept, we may face with dynamic supply chain configuration during a planning horizontal time. In this study, a new model is presented to consider the dynamic configuration of a supply chain by developing new products. In the proposed model, the dynamic configuration of a supply chain and the new product launching time is optimized simultaneously. The proposed model considers production, sales and transportation planning for the entire supply chain in order to achieve an integrative and efficient supply as well. Then some numerical analyses have been done to show the applicability of the proposed model. The results show that the new product development has a significant effect on the configuration of supply chain.     

基于犹豫模糊偏好关系FMEA方法的改进

为有效解决产品在研发过程中存在的一系列质量可靠性问题,本文提出了一种新的基于犹豫模糊偏好关系的改进FMEA方法。考虑到专家小组对不同失效模式评估时主要依据相关标准和自身经验,存在犹豫模糊不确定或自身偏好问题。本文首先对风险因子的评分标准进行犹豫模糊化,并用犹豫模糊偏好关系对失效模式的相对风险矩阵进行处理;其次,将得到的具有犹豫模糊偏好关系的综合偏好值与犹豫模糊评价信息相结合,得到改进的风险优先数,从而得出新的失效模式风险评估顺序对FMEA进行改进;最后,利用改进的FMEA模型对产品研发过程中的质量风险进行分析验证,使得风险结果更接近实际情况,进而提高研发成功率,显示该方法可行、有效。     

Shortening cycle times in multi-product,capacitated production environments through quality level improvements and setup reduction

This paper addresses the issue of investing in reduced setup times and defect rates for a manufacturer of several products operating in a JIT environment. Production cycle times can be shortened by investing in setup time and defect rate reductions, respectively. The objective is to determine optimal levels of setup time and defect rate reductions along with the corresponding optimal levels of investments respectively, and the optimal production cycle time for each product. The problem is constrained by demand requirements, process improvement budget limitations, and manufacturing and warehousing capacity constraints. We consider the cases of product-specific quality improvements and joint-product quality improvements. A general nonlinear optimization models of these problems are formulated. A convex geometric programming approximation of these models is developed respectively, in order to solve them. The approximation can be made to any desired degree of accuracy. Our empirical findings provide insights into a number of managerial issues surrounding investment decisions in product-specific quality improvements and setup reductions due to a product redesign as well as in joint-product improvements due to a process redesign.     

Weibull分布在新产品市场渗透研究中的应用拓展

在应用Weibull模型研究新产品市场渗透时,"永不采用人群"、消费者个体之间的差异、消费者群体之间的差异是研究新产品采用时需要考虑的三种因素。本文基于这三种因素分别建立了三个拓展的Weibull模型,并利用面板数据进行了实证研究,发现三种拓展之后的模型在数据拟合和数据预测方面均有显著的提高.然后,本文将三种因素整合至一个模型之中形成了一种新的综合Weibull模型,实证分析结果显示新的模型有很好的新产品市场渗透数据拟合和预测能力.     

选择与评价新产品开发的风险决策研究

本文针对企业投资决策者在新产品开发中的风险决策,基于贝叶斯决策理论及其相关研究建立了评估外部情报信息价值的数学模型,探讨投资决策者风险倾向、新产品开发风险投资未来市场需求以及情报费用对投资决策的影响机制,并用于评估新产品开发决策。研究结果有助于理解企业决策者进行新产品开发决策时应考虑的因素和情境,并能够辅助决策。最后,将这一数学模型应用到一家大型高科技企业的案例中。应用案例分析结果表明:本文的研究结论能够为企业开发新产品提供相关的决策依据。     

Autonomous and induced production learning under price and quality competition

Recent empirical studies indicate that improvements in product conformance quality exhibit learning-by-doing patterns. We address quality improvement in a competitive duopoly market for partially substitutable products characterized by levels of quality that are not necessarily identical. The products’ quality is described with a hazard rate that can be improved both by accumulating production experience (autonomous learning) and quality improvement efforts (induced learning). Given that defective items are fully reimbursable and the demands exhibit increasing returns to scale, we derive Nash equilibrium pricing and induced learning effort dynamic policies. We show that when the effectiveness of autonomous learning prevails over the effectiveness of efforts in induced learning, equilibrium prices gradually grow over time; the trend is quite the opposite when autonomous learning is less effective than induced learning.     

短视型创新企业最优定价研究

率先创新使企业拥有时间和产品竞争力上的优势,获得先动优势;而模仿创新减少企业的研发成本,更能满足顾客的需求,从而可以获得更高的成功率,使模仿创新企业获得后进优势.针对短视型创新企业行为,研究以原始创新产品进入市场、模仿创新产品进入市场、原始创新产品的升级换代产品进入市场为分隔点的产品生命周期不同阶段下率先创新企业对产品的最优定价,以及模仿创新企业采用不同价格策略下的产品均衡定价.结论表明:无论企业采用什么价格策略,升级换代产品进入市场的最优时间都应满足升级换代产品进入市场前创新企业的阶段末瞬时利润率与进入市场后的初始瞬时利润率相等.     

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.     

金融发展对我国出口产品质量的非线性异质影响研究

中国出口产品往往面临量高而质低的困境,这直接导致了我国产品在国际市场上往往只能定位在较低的价格。本文使用2000-2006年中国工业企业数据库和海关数据库匹配所得的微观数据,从产品层面出发测算企业出口产品质量,结合行业层面间接融资渠道测度的金融发展指标,运用非参数分位数面板研究发现：(1)金融发展对出口产品质量存在非线性异质影响且影响模式显著不同,在高分位处呈现“倒N型”特征;(2)在不同分位点处存在差异化的最优金融发展水平,并随分位点下降而降低;(3)非东部地区、高技术产品的质量对金融发展的敏感程度更高,而对低分位产品质量促进作用更大。本文结论表明,区域金融发展宏观调控应考虑到企业自身产品质量水平影响。     

The direct marketing of insurance

An insurance company, like many in the financial services industry, will advertise a product in the press and some readers will avail themselves of it. Often the cost of an advertisement will exceed the income derived from the accepted respondents in the following years. It only becomes profitable if acquiring names into a database results in purchases in future years of the advertised and other, cross-sold products. Therefore evaluating advertising effectiveness requires the development of future lifetime values (LTVs), which vary over time between individuals for the different products. Real examples include evaluating the media vehicle, size, content and frequency of advertisements.     

考虑消费者具有质量和价格偏好的双渠道供应链最优决策

产品价格和质量是消费者永恒的关注点。虽然多渠道给消费者带来了便捷的购物途径, 但是不同渠道的产品存在质量和价格分差异, 消费者在购买时须面对一个渠道、价格和质量的协调选择问题。本文提出了消费者对产品质量和价格偏好的双渠道定价决策模型, 并讨论了以制造商为领导者的分散决策和集中决策情形下的最优策略。比较了消费者偏好及产品质量水平对不同决策情形下的供应链决策的影响, 并通过设计收益共享契约机制实现了渠道的协调并证明了其有效性。研究表明:当产品质量在一定范围内时, 制造商和零售商可以获得最大利润;当消费者对质量的偏好逐渐增加时, 制造商的利润和零售商的利润随着消费者对质量的偏好提高而下降;制造商和零售商可以通过协调销售价格消除供应链的双重边际效应,从而实现供应链的协调。最后利用算例分析了消费者的质量、价格偏好对总利润的影响并给出了相应的管理启示。     

环境规制对出口产品质量的影响研究——基于行业面板数据的实证分析

本文以环境规制作为解释变量,基于2003~2010年中国19个行业出口产品质量和环境规制数据,采用固定效用模型实证检验了环境规制对出口产品质量的影响。研究结果表明,环境规制对出口产品质量的影响呈“U”型,即环境规制增强前期成本效应大于创新效应,经营成本提高导致产品质量下降;环境规制增强后期创新效应大于成本效应,研发创新促使产品质量提高。不同行业对环境规制的敏感度不一样,将样本数据中涉及的19个部门,分为重污染行业和轻污染行业进行分类回归,回归结果显示环境规制对轻度污染行业出口产品质量的影响呈倒“U”型,即具有先促进后抑制的作用;环境规制对重度污染行业出口产品质量的影响呈“U”型,即具有先抑制后促进的作用。据此,提出有效利用环境规制以提高出口产品质量和发展绿色贸易的政策启示。     

基于Entropy-Topsis模型的产品创新过程分析与实证检验

基于生态位的理念,本研究将产品创新过程划分为概念设计生态位、研发生态位、调试生态位、工业生产生态位以及市场交易生态位,以此形成产品创新过程中的演进序列;通过分析产品创新过程中不同创新生态位的影响因素,继而测度不同创新生态位的演进状态。此后,本研究以103个处于不同创新生态位的制造业企业产品创新项目作为实证分析对象,应用Entropy-Topsis模型测评不同产品创新生态位的演进态势,对收集的样本调查数据进行分析并验证理论模型。     

The optimal pace of product updates

Some firms (e.g. Intel and Medtronics) use a time-pacing strategy for product development (PD), introducing new generations at regular intervals. If the firm adopts a fast pace (introducing frequently), it prematurely cannibalizes its old generation, incurring high development costs, while if it has a slow pace, it fails to capitalize on customer willingness-to-pay for improved technology. We develop a model to gain insight into which factors drive the pace. We consider PD cost, the diffusion rate (coefficients of innovation and imitation), the rate of margin decline, and the degree to which a new generation stimulates market growth. We find that a faster pace is generally associated with faster diffusion, a higher market growth rate and faster margin decay. Not so intuitively, we find that relatively minor differences in the development cost function can significantly impact the pace.     

On well-dominated direct,Cartesian and strong product graphs

If each minimal dominating set in a graph is a minimum dominating set, then the graph is called well-dominated. Since the seminal paper on well-dominated graphs appeared in 1988, the structure of well-dominated graphs from several restricted classes has been studied. In this paper we give a complete characterization of nontrivial direct products that are well-dominated. We prove that if a strong product is well-dominated, then both of its factors are well-dominated. When one of the factors of a strong product is a complete graph, the other factor being well-dominated is also a sufficient condition for the product to be well-dominated. Our main result gives a complete characterization of well-dominated Cartesian products in which at least one of the factors is a complete graph. In addition, we conjecture that this result is actually a complete characterization of the class of nontrivial, well-dominated Cartesian products.     

A possibilistic decision model for new product supply chain design

This paper models supply chain (SC) uncertainties by fuzzy sets and develops a possibilistic SC configuration model for new products with unreliable or unavailable SC statistical data. The supply chain is modeled as a network of stages. Each stage may have one or more options characterized by the cost and lead-time required to fulfill required functions and may hold safety stock to prevent an inventory shortage. The objective is to determine the option and inventory policy for each stage to minimize the total SC cost and maximize the possibility of fulfilling the target service level. A fuzzy SC model is developed to evaluate the performance of the entire SC and a genetic algorithm approach is applied to determine near-optimal solutions. The results obtained show that the proposed approach allows decision makers to perform trade-off analysis among customer service levels, product cost, and inventory investment depending on their risk attitude. It also provides an alternative tool to evaluate and improve SC configuration decisions in an uncertain SC environment.     

Application of a primarily deductive framework describing time consumption for hauling of logs to road-side

Forest management planning decisions are often based on the forest owner’s goals, which typically focus on economic criteria. Logging operation work productivity functions are used when costing forest operations. These functions affect the conclusions drawn during forest management analyses because different logging environments give rise to different harvesting costs. When evaluating new combinations of machines and environments, there is generally a shortage of field data on productivity that can be examined in advance. We applied a previously published deductive framework describing time consumption in forwarding to known environments, in which field studies on forwarding have been conducted and for which extensive data are available. We then adapted the deductive framework to better reproduce the results obtained in the time studies. The deductive framework accurately reproduced the observed forwarding productivities; on average, the adaptation process improved the accuracy of this reproduction. However, it may also have reduced the accuracy of individual predictions. We conclude that the deductive framework can be used as a basis for constructing work productivity functions for forest management analyses, and can serve as a foundation when constructing new productivity functions based on time study results to use when pricing forwarding.     

Optimum advertising policy over time for subscriber service innovations in the presence of service cost learning and customers’ disadoption

On the theoretical side, this paper characterizes qualitatively optimal advertising policy for new subscriber services. A monopolistic market is analyzed first for which customers’ disadoption, discounting of future profits streams and a service cost learning curve are allowed. After characterizing the optimal policy for a general diffusion model, the results pertaining to a specific diffusion model for which advertising affects the coefficient of innovation that incorporates the disadoption rate are reported. The results of the theoretical research show that the advertising policy of the service firm in the presence of customers’ disadoption could be very different from the same when disadoption is ignored.On the empirical side, four alternative diffusion models are estimated and their predictive powers using a one-step-ahead forecasting procedure compared. The diffusion data analyzed are related to the Canadian cable TV industry. Empirical research findings suggest that the specific diffusion model considered above is not only of theoretical appeal but also of major empirical relevance.The analytical findings of the study are documented in six theoretical propositions for which proofs are provided in a separate Appendix. The results of a related numerical experiment together with the analytical findings pertaining to the competitive role of advertising are included. Managerial implications of the study together with directions for future research are also discussed.