scholarly journals A CBR-Based and MAHP-Based Customer Value Prediction Model for New Product Development

2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Yu-Jie Zhao ◽  
Xin-xing Luo ◽  
Li Deng
Keyword(s):  
Product Development ◽  
Prediction Model ◽  
New Product Development ◽  
Customer Value ◽  
Transition Probability ◽  
New Product ◽  
Case Based Reasoning ◽  
Analytic Hierarchy ◽  
Value Prediction ◽  
Customer Needs

In the fierce market environment, the enterprise which wants to meet customer needs and boost its market profit and share must focus on the new product development. To overcome the limitations of previous research, Chan et al. proposed a dynamic decision support system to predict the customer lifetime value (CLV) for new product development. However, to better meet the customer needs, there are still some deficiencies in their model, so this study proposes a CBR-based and MAHP-based customer value prediction model for a new product (C&M-CVPM). CBR (case based reasoning) can reduce experts’ workload and evaluation time, while MAHP (multiplicative analytic hierarchy process) can use actual but average influencing factor’s effectiveness in stimulation, and at same time C&M-CVPM uses dynamic customers’ transition probability which is more close to reality. This study not only introduces the realization of CBR and MAHP, but also elaborates C&M-CVPM’s three main modules. The application of the proposed model is illustrated and confirmed to be sensible and convincing through a stimulation experiment.

Alcatel-Lucent falls, Huawei ascends: new product development makes the difference

2017 ◽  
Vol 38 (1) ◽  
pp. 22-30 ◽  
Author(s):  
Jie Yan ◽  
Le Wang ◽  
Jie Xiong
Keyword(s):  
Product Development ◽  
New Product Development ◽  
Customer Value ◽  
New Product ◽  
Technology Leadership ◽  
Comparative Case Study ◽  
Content Type ◽  
Technology Leader ◽  
The Difference ◽  
Value Strategy

Purpose This study aims to use the new product development (NPD) perspective to understand why traditional leading telecom equipment companies, such as Alcatel-Lucent (ALu), have stagnated but the newcomer Huawei has achieved steady growth. Design/methodology/approach This paper takes the form of a comparative case study. Findings Three significant differences in NPD process between the companies were discovered: first, although both companies claim that they are market-oriented, Huawei’s NPD projects are customer-driven, and ALu projects are joint considerations of customer demand and technology leadership; second, Huawei uses a design-to-value strategy, and ALu applies a design-for-quality-premium strategy; third, resources are allocated and shared at the corporate level in Huawei and at the business division level in ALu. Practical implications This study offers several implications for NPD managers. First, holding a market leader position is more important than being a technology leader. Companies must fundamentally change their mind-sets, restructure NPD models and prioritize and empower marketing and sales departments in the decision-making and management of NPD projects. Second, to maximize customer value, managers must balance cost and quality and avoid overengineering. A quality premium no longer necessarily leads to product competitiveness. Third, to improve the efficiency of NPD performance, companies must build up a mechanism to enable across-boundary resources. Originality/value This study highlights a number of key NPD strategy issues. It was conducted in the telecom equipment industry, but NPD managers of other industries will also gain useful insights from the discussion.

scholarly journals Analytic Hierarchy Process for New Product Development

10.5772/56816 ◽  
2013 ◽  
Vol 5 ◽  
pp. 42 ◽  
Author(s):  
Elisa Battistoni ◽  
Andrea Fronzetti Colladon ◽  
Laura Scarabotti ◽  
Massimiliano M. Schiraldi
Keyword(s):  
Product Development ◽  
Analytic Hierarchy Process ◽  
New Product Development ◽  
Methodological Approach ◽  
New Product ◽  
Analytic Hierarchy ◽  
Potential Consumer ◽  
Market Needs ◽  
The One ◽  
Hierarchy Process

The success of a New Product Development (NPD) process strongly depends on the deep comprehension of market needs and Analytic Hierarchy Process (AHP) has been commonly used to find weights for customers' preferences. AHP best practices suggest that low-consistency respondents should be considered untrustworthy; however, in some NPD cases – such as the one presented here – this stake can be extremely big. This paper deals with the usage of AHP methodology to define the weights of customer needs connected to the NPD process of a typical impulse buying good, a snack. The aim of the paper is to analyse in a critical way the opportunity to exclude or include non-consistent respondents in market analysis, addressing the following question: should a non-consistent potential customer be excluded from the analysis due to his inconsistency or should he be included because, after all, he is still a potential consumer? The chosen methodological approach focuses on evaluating the compatibility of weight vectors among different subsets of respondents, filtered according to their consistency level. Results surprisingly show that weights do not significantly change when non-consistent respondents are excluded.

scholarly journals New product development projects prioritization with Analytic Hierarchy Process in an automotive company

2011 ◽  
Vol 9 (2) ◽  
pp. 157-162
Author(s):  
Valério Antonio Pamplona Salomon ◽  
Sandra Miranda Neves ◽  
Jefferson Olegário de Paula ◽  
Marcos Rolando Piccilli ◽  
Carlos Eduardo Sanches da Silva
Keyword(s):  
Product Development ◽  
Analytic Hierarchy Process ◽  
New Product Development ◽  
New Product ◽  
Development Projects ◽  
Analytic Hierarchy ◽  
Automotive Company ◽  
Hierarchy Process

scholarly journals Integrating Kano Model, AHP, and QFD Methods for New Product Development Based on Text Mining, Intuitionistic Fuzzy Sets, and Customers Satisfaction

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Ming Li ◽  
Jie Zhang
Keyword(s):  
Decision Making ◽  
Product Development ◽  
New Product Development ◽  
Quality Function Deployment ◽  
New Product ◽  
Kano Model ◽  
Analytic Hierarchy ◽  
Customer Preference ◽  
Intuitionistic Fuzzy ◽  
Hierarchy Process

Online reviews are crucial to any online business that wants to increase sales on the Internet. Customer reviews have information about product attributes, customer requirements (CRs), and shopping experience; mining reviews provide the direction of decision-making for new product development and design (NPDD). Besides, the information of customer preference has vagueness and uncertainty, and the accuracy of decision-making information directly affects the success of NPDD. This paper proposed a methodology that integrates the Kano model (KM), analytic hierarchy process (AHP), and quality function deployment (QFD) methods with intuitionistic fuzzy set (IFS) to solve decision-making problems in NPDD. By the new method, the web crawler technology was first applied to e-commerce web sites to collect raw data, and the representative CRs were extracted through combining LDA model with Apriori algorithm. Second, the intuitionistic fuzzy Kano model (IFKM) is proposed to evaluate adjustment coefficient of CRs and Kano categories via customer preference membership functions. Thirdly, overall weights which contained emotional needs (ENs) and functional needs (FNs) are obtained via intuitionistic fuzzy analytic hierarchy process (IFAHP); thus, the adjusted weights are calculated from IFKM and IFAHP. Next, the intuitionistic fuzzy quality function deployment (IFQFD) is proposed to acquire engineering characteristics (ECs) of weights through combining competition benchmarks and based on technical benchmarks to make goals for a company’s NPDD. Finally, the method was applied to study vertical-configured air conditioner (VAC) as an example. The results showed that the application of text mining and IFS to improve CS is both reliable and scientific.

The application of case based reasoning to decision support in new product development

2003 ◽  
Vol 14 (1) ◽  
pp. 36-45 ◽  
Author(s):  
R. Belecheanu ◽  
K.S. Pawar ◽  
R.J. Barson ◽  
B. Bredehorst ◽  
F. Weber
Keyword(s):  
Decision Support ◽  
Product Development ◽  
New Product Development ◽  
New Product ◽  
Case Based Reasoning ◽  
Case Based
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