Empirical Study on the Key Intelligent Factors of Intelligent Consumer Products

Abstract

Abstract: On the basis of literature review and case analysis, twenty-five intelligent elements' measurement items of intelligence consumer products are extracted. Then through the questionnaire collected data, the dimensions of key intelligent factors and their effect for user experience are empirically researched by the methods of factor analysis and regression analysis. The research results indicate that the key intelligent factors of intelligent consumer products consists of five main dimensions, which are real-time monitoring, intelligent control, automation, optimization ability and mobile Internet. Among these factors, the most significant one is autonomy, followed in turn by real-time monitoring, intelligent interaction, optimization capabilities and mobile internet. Based on the research conclusions, countermeasures and suggestions for the development of intelligent consumer products in manufacturing enterprises are given in the end of the paper.

Key words: intelligence consumer product, key intelligent factors, empirical study

Li Taofen, Guo Peng, Yang Shuili. Empirical Study on the Key Intelligent Factors of Intelligent Consumer Products[J]. , 2017, 29(2): 106-113.

References

[1] 苗圩. 推进信息化和工业化融合?打造中国制造业升级版[J]. 市场观察, 2014,10(5):32-36
[2] Mcfarlane D., Sanjay S., Jin L. C. The Intelligent Products in Manufacturing Control and Management[C]. 15th Triennial World Congress, Barcclona(Spain), 2002
[3] Kärkkäinen M., Holmström J., Främling K. Intelligent Products-a Step Towards a More Effective Project Delivery Chain[J]. Computers in Industry, 2003,50(2):141-151
[4] Främling K., Holmström, Loukkola J. Sustainable PLM through Intelligent Products[J]. Engineering Applications of Artificial Intelligence, 2013,26(5):789-799
[5] Valckenaers P., Germain B. S., Verstraete P. Intelligent Product:Agere versus Essere[J]. Computers in Industry, 2013,60(3):217-228
[6] Porter M., Ignatus A., Chandrasekaran N. How Smart, Connected Products are Transforming Competition[J]. Harvard Business Review, 2015,40(4):38-69
[7] Gerben G. M., Framling K., Holmstrom J. Intelligent Product:A Survey[J]. Computers in Industry, 2009,60(3):137-148
[8] Kiritsis D. Closed-loop PLM for Intelligent Products in the Era of Internet of Things[J]. Computer-Aided Design, 2011,43(6):479-501
[9] Yang X. Y., Moore P., Chong S. K. Intelligent Products:From Lifecycle Data Acquisition to Enabling Product-related Services[J]. Computers in Industry, 2009,60(3):184-194
[10] Mohelska H., Sokolova M. Smart, Connected Products Change a Company's Business Strategy Orientation[J]. Applied Economics, 2016,9(4):1-8
[11] Thirtha S. Innovation Model for Smart Products and Services:A 3-Dimensional Innovation Model for Business Impact[J]. International Journal of Applied Research & and Studies, 2015,4(2):48-58
[12] Leitão P., Rodrigues N., Barbosa J. Intelligent Products:The Grace Experience[J]. Control Engineering Practice, 2015,42(3):95-105
[13] Valencia A., Mugge R., Schoormans J. P. The Design of Smart Product-Service Systems(PSSs):An Exploration of Design Characteristic[J]. International Journal of Design, 2015,9(1):13-26
[14] Pasricha S., Donohoo B. K., Ohlsen C. A Middleware Framework for Application-aware and User-specific Energy Optimization in Smart Mobile Devices[J]. Pervasive and Mobile Computing, 2015,20(5):47-63
[15] Zhang Y. B., Pei L., Patrick R. Playing with Multiple Wearable Devices:Exploring the Influence of Display, Motion and Gender[J]. Computers in Human Behavior, 2015,50(12):148-158
[16] Wang C. H. A Market-oriented Approach to Accomplish Product Positioning and Product Recommendation for Smart Phones and Wearable Devices[J]. International Journal of Production Research, 2015,53(8):2542-2553
[17] 黄浩. 移动内容服务采纳过程中的信任变化分析[J]. 管理评论, 2014,26(4):122-129
[18] 顾忠伟,徐福缘,卫军. 可穿戴商务消费者初始信任影响因素的实证研究[J]. 管理评论, 2015,27(7):168-176
[19] 王娜. 探索性因子分析中统计方法的比对研究[J]. 价值工程, 2001,2(17):274-278
[20] 刘晓莉. 试验设计中多元回归分析方法的研究[J]. 数理统计与管理, 2001,20(4):14-18