Analytic hierarchy prioritisation of new product development activities for electronics manufacturing

2012 ◽  
Vol 50 (17) ◽  
pp. 4860-4866 ◽  
Author(s):  
Eduardo G. Salgado ◽  
Valerio A.P. Salomon ◽  
Carlos H.P. Mello
2014 ◽  
Vol 2014 ◽  
pp. 1-18 ◽  
Author(s):  
Yu-Jie Zhao ◽  
Xin-xing Luo ◽  
Li Deng

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.


10.5772/56816 ◽  
2013 ◽  
Vol 5 ◽  
pp. 42 ◽  
Author(s):  
Elisa Battistoni ◽  
Andrea Fronzetti Colladon ◽  
Laura Scarabotti ◽  
Massimiliano M. Schiraldi

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.


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

2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Ming Li ◽  
Jie Zhang

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.


2021 ◽  
Vol 8 (4) ◽  
pp. 57-77
Author(s):  
Rhys Williams ◽  
Pouya S. Moghadam ◽  
John Mulyata

This paper develops a conceptual model for finding key factors for new product development (NPD) evaluation. It builds on the work of the most cited and published authors on innovation management, but transfers attention from advertising aspects and efficiency, to factors identified within the NPD process such as new product project definition, a firm’s resources, organisation-product fit, and commercial entity, that would lead to success with “Information acquired” being identified as the underlying key factor. This paper presents a summary of the results of correlation coefficients calculated between the factors identified and outcome measures, derived from the leading authors’ work. Further, analytic hierarchy process (AHP) was used to evaluate the results of the correlation coefficients of sub-factors, which were modified by considering the ranking of each author.


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