Skip to main content

Advertisement

Log in

A novel method for determining the key customer requirements and innovation goals in customer collaborative product innovation

  • Published:
Journal of Intelligent Manufacturing Aims and scope Submit manuscript

Abstract

Customer collaborative production innovation (CCPI) has become a worldwide new product design trend. The essential step to implement CCPI is to clear customer requirements and innovation goals for products. Based on the integration of traditional competitive priority ratings of customer requirements method for quality function deployment and grey relational analysis, this paper proposes a novel hybrid competitive priority ratings of customer requirements method for CCPI to identify the key customer requirements and innovation goals for a product. The method takes the heterogeneity of customers into consideration and allows different types of customers to assess customer requirements in their preferred or familiar formats which reflect their uncertainty degree. The proposed hybrid competitive priority ratings of customer requirements method represents a general approach for CCPI, does not require any transformation of multiform customers’ assessments that would cause information loss or information distortion. Its potential applications in determining the key customer requirements and innovation goals for CCPI are illustrated with a case study of smart phone development.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6

Similar content being viewed by others

References

  • Alavi, S. (2013). Collaborative customer relationship management-co-creation and collaboration through online communities. International Journal of Virtual Communities & Social Networking, 5(1), 1–18.

    Article  Google Scholar 

  • Ayağ, Z., Samanlioglu, F., & Büyüközkan, G. (2013). A fuzzy QFD approach to determine supply chain management strategies in the dairy industry. Journal of Intelligent Manufacturing, 24(6), 1111–1122.

    Article  Google Scholar 

  • Berthon, P. R., Pitt, L. F., McCarthy, I., & Kates, S. M. (2007). When customers get clever: Managerial approaches to dealing with creative consumers. Business Horizons, 50(1), 39–47.

    Article  Google Scholar 

  • Büyüközkan, G., Feyzioğlu, O., & Ruan, D. (2007). Fuzzy group decision-making to multiple preference formats in quality function deployment. Computers in Industry, 58(5), 392–402.

    Article  Google Scholar 

  • Chan, L. K., & Wu, M. L. (2005). A systematic approach to quality function deployment with a full illustrative example. Omega, 33(2), 119–139.

    Article  Google Scholar 

  • Chan, L. K., Kao, H. P., & Wu, M. L. (1999). Rating the importance of customer needs in quality function deployment by fuzzy and entropy methods. International Journal of Production Research, 37(11), 2499–2518.

    Article  Google Scholar 

  • Chen, C. C., & Chuang, M. C. (2008). Integrating the Kano model into a robust design approach to enhance customer satisfaction with product design. International Journal of Production Economics, 114(2), 667–681.

    Article  Google Scholar 

  • Dain, M. A. L., Calvi, R., & Cheriti, S. (2011). Proposition of a tool to evaluate customer’s performance in collaborative product development with suppliers. International Journal for Interactive Design & Manufacturing, 5(2), 73–83.

    Article  Google Scholar 

  • Deng, J. L. (1982). Control problems of grey systems. Systems & Control Letters, 1(5), 288–294.

    Article  Google Scholar 

  • Fan, Z. P., Zhang, X., Chen, F. D., & Liu, Y. (2013). Extended TODIM method for hybrid multiple attribute decision making problems. Knowledge-Based Systems, 42, 40–48.

    Article  Google Scholar 

  • Greer, C. R., & Lei, D. (2012). Collaborative innovation with customers: A review of the literature and suggestions for future research. International Journal of Management Reviews, 14(1), 63–84.

    Article  Google Scholar 

  • Hsieh, M. H., Huang, C. Y., Luh, D. B., Liu, S. F., & Ma, C. H. (2013). An application of implementing a cognitive structure model to obtain consensus from consumers. International Journal of Design, 7(2), 53–65.

    Google Scholar 

  • Hsu, Y. T., Yeh, J., & Chang, H. (2000). Grey relational analysis for image compression. The Journal of Grey System, 12(2), 131–138.

    Google Scholar 

  • Kuo, T. C. (2013). Mass customization and personalization software development: A case study eco-design product service system. Journal of Intelligent Manufacturing, 24(5), 1019–1031.

    Article  Google Scholar 

  • Kuo, Y., Yang, T., & Huang, G. W. (2008). The use of grey relational analysis in solving multiple attribute decision-making problems. Computers & Industrial Engineering, 55(1), 80–93.

    Article  Google Scholar 

  • Kutschenreiter-Praszkiewicz, I. (2013). Application of neural network in QFD matrix. Journal of Intelligent Manufacturing, 24(2), 397–404.

    Article  Google Scholar 

  • Lai, X., Xie, M., Tan, K. C., & Yang, B. (2008). Ranking of customer requirements in a competitive environment. Computers & Industrial Engineering, 54(2), 202–214.

    Article  Google Scholar 

  • Li, F., & Yang, Y. (2012). Efficiency evaluation of customer collaborative product innovation based on PSO-WNN. Metalurgia International, 17(7), 118–124.

    Google Scholar 

  • Li, F., Yang, Y., Xie, J. Z., & Zhang, F. (2014a). Importance evaluation method for innovative customer in collaborative products innovation. Computer Integrated Manufacturing Systems, 20(3), 537–543

  • Li, F., Yang, Y., Xie, J. Z., Liu, A. J., & Chen, Q. (2014b). Selection method of customer partners in customer collaborative product innovation. Journal of Intelligent Systems, 23(4), 423–435.

  • Li, F., Yang, Y., Xie, J. Z., Zhang, F., & Bao, B. F. (2013). Characteristic analysis of complex network for customer collaborative innovation network. Journal of Chongqing University, 36(7), 27–31.

    Google Scholar 

  • Li, Q. X., Liu, S. F., & Lin, Y. (2012). Grey enterprise input–output analysis. Journal of Computational and Applied Mathematics, 236(7), 1862–1875.

    Article  Google Scholar 

  • Li, S., Nahar, K., & Fung, B. C. M. (2015). Product customization of tablet computers based on the information of online reviews by customers. Journal of Intelligent Manufacturing, 26(1), 97–110.

    Article  Google Scholar 

  • Li, Y. B., & Zhang, J. P. (2014). Topsis method for hybrid multiple attribute decision making with 2-tuple linguistic information and its application to computer network security evaluation. Journal of Intelligent and Fuzzy Systems, 26(3), 1563–1569.

    Google Scholar 

  • Li, Y. L., Tang, J. F., & Luo, X. G. (2010). An ECI-based methodology for determining the final importance ratings of customer requirements in MP product improvement. Expert Systems with Applications, 37(9), 6240–6250.

    Article  Google Scholar 

  • Li, Y. L., Tang, J. F., Luo, X. G., & Xu, J. (2009). An integrated method of rough set, Kano’s model and AHP for rating customer requirements’ final importance. Expert Systems with Applications, 36(3), 7045–7053.

    Article  Google Scholar 

  • Liang, X., Bao, B., & Deng, F. (2012). Study on knowledge sharing performance evaluation and application of customer collaborative product innovation process. Journal of Convergence Information Technology, 7(3), 27–38.

    Article  Google Scholar 

  • Liu, C., Ramirez-Serrano, A., & Yin, G. (2011). Customer-driven product design and evaluation method for collaborative design environments. Journal of Intelligent Manufacturing, 22(5), 751–764.

    Article  Google Scholar 

  • Liu, P. D. (2009). A novel method for hybrid multiple attribute decision making. Knowledge-Based Systems, 22(5), 388–391.

    Article  Google Scholar 

  • Liu, S. F., & Forrest, J. (2007). The current developing status on grey system theory. The Journal of Grey System, 2, 111–123.

    Google Scholar 

  • Lu, M. H., Madu, C. N., Kuei, C. H., & Winokur, D. (1994). Integrating QFD, AHP and benchmarking in strategic marketing. Journal of Business & Industrial Marketing, 9(1), 41–50.

    Article  Google Scholar 

  • Lüthje, C., & Herstatt, C. (2004). The Lead User method: An outline of empirical findings and issues for future research. R&D Management, 34(5), 553–568.

    Article  Google Scholar 

  • Ma, J. Q., Yang, Y., Li, F., & Xie, J. Z. (2013). An approach to determine importance degree of targets in customer collaborative products innovation. China Mechanical Engineering, 24(16), 2223–2230.

    Google Scholar 

  • Nahm, Y. E. (2013). A novel approach to prioritize customer requirements in QFD based on customer satisfaction function for customer-oriented product design. Journal of Mechanical Science and Technology, 27(12), 3765–3777.

    Article  Google Scholar 

  • Nahm, Y. E. (2013). New competitive priority rating method of customer requirements for customer-oriented product design. International Journal of Precision Engineering and Manufacturing, 14(8), 1377–1385.

    Article  Google Scholar 

  • Nahm, Y. E., Ishikawa, H., & Inoue, M. (2013). New rating methods to prioritize customer requirements in QFD with incomplete customer preferences. The International Journal of Advanced Manufacturing Technology, 65(9–12), 1587–1604.

    Article  Google Scholar 

  • Qattawi, A., Mayyas, A., Thiruvengadam, H., Kumar, V., Dongri, S., & Omar, M. (2014). Design considerations of flat patterns analysis techniques when applied for folding 3-D sheet metal geometries. Journal of Intelligent Manufacturing, 25(1), 109–128.

    Article  Google Scholar 

  • Rao, C., Peng, J., & Chen, W. (2007). Novel method for fuzzy hybrid multiple attribute decision making. In Cao B.Y. (Ed.), Fuzzy information and engineering (pp. 583–591). Springer, Berlin Heidelberg.

  • Reichwald, R., Seifert, S., & Walcher, D. (2004). Customers as part of value webs: Towards a framework for webbed customer innovation tools. Proceedings of the 37th Annual Hawaii International Conference on (pp. 1–10). IEEE.

  • Risdiyono, & Koomsap, P. (2013). Design by customer: Concept and applications. Journal of Intelligent Manufacturing, 24(2), 295–311.

    Article  Google Scholar 

  • Romero, D., & Molina, A. (2011). Collaborative networked organisations and customer communities: Value co-creation and coinnovation in the networking era. Production Planning & Control the Management of Operations, 22(5), 447–472.

    Article  Google Scholar 

  • Thomke, S. H., & Hippel, E. V. (2002). Customers as innovators: A new way to create value. Harvard Business Review, 80(4), 74–81.

    Google Scholar 

  • Urban, G. L., & Von Hippel, E. (1988). Lead user analyses for the development of new industrial products. Management Science, 34(5), 569–582.

    Article  Google Scholar 

  • Wang, W., & Cui, M. (2007). Hybrid multiple attribute decision making model based on entropy. Journal of Systems Engineering and Electronics, 18(1), 72–75.

    Article  Google Scholar 

  • Wang, X. L., Yang, Y., Zeng, Q., & Liang, X. D. (2009). Research on the complexity of customer collaborative product innovation and innovation agent stimulus-response model. Studies in Science of Science, 27(11), 1729–1735.

    Google Scholar 

  • Wang, Y. M. (2012). Assessing the relative importance weights of customer requirements using multiple preference formats and nonlinear programming. International Journal of Production Research, 50(16), 4414–4425.

    Article  Google Scholar 

  • Wei, G. W. (2008). Grey relational analysis method for hybrid multiple attribute decision making. Mathematics in Practice and Theory, 38(7), 30–34.

    Google Scholar 

  • Wei, G. W. (2011). Grey relational analysis model for dynamic hybrid multiple attribute decision making. Knowledge-Based Systems, 24(5), 672–679.

    Article  Google Scholar 

  • Wei, G. W. (2010). GRA method for multiple attribute decision making with incomplete weight information in intuitionistic fuzzy setting. Knowledge-Based Systems, 23(3), 243–247.

    Article  Google Scholar 

  • Wei, G. W. (2011). Gray relational analysis method for intuitionistic fuzzy multiple attribute decision making. Expert Systems with Applications, 38(9), 11671–11677.

    Article  Google Scholar 

  • Wu, H. H. (2002). A comparative study of using grey relational analysis in multiple attribute decision making problems. Quality Engineering, 15(2), 209–217.

    Article  Google Scholar 

  • Xing, Q. S., Yang, Y., Liu, A. J., & Yao, H. (2012). Research on knowledge sharing for customer collaborative product innovation based on knowledge grid. China Mechanical Engineering, 23(23), 2817–2824.

    Google Scholar 

  • Yang, J., Yang, Y., Wang, W. L., Zhao, X. H., & Song, L. J. (2008). Evaluation of collaborative innovative customer based on PWNN model and its application. Computer Integrated Manufacturing Systems, 14(5), 882–890.

    Google Scholar 

  • Yang, Y., Liang, X. D., Li, X. L., Bao, B. F., & Yang, J. (2010). Risk management and assessment for customer collaborative products innovation realization. Computer Integrated Manufacturing Systems, 16(5), 1020–1025.

    Google Scholar 

  • Yang, Y. S., Shih, C. Y., & Fung, R. F. (2014). Multi-objective optimization of the light guide rod by using the combined Taguchi method and grey relational approach. Journal of Intelligent Manufacturing, 25(1), 99–107.

    Article  Google Scholar 

  • Yang, Y., Guo, B., Yin, S., Wang, W. L., & Zhang, X. D. (2008). Connotation, theory framework and application of customer collaborative innovation. Computer Integrated Manufacturing Systems, 14(5), 944–950.

    Google Scholar 

  • Ye, B., Wang, F. Z., Li, L., Helian, N., & Dimitrakos, T. (2014). Mirroring mobile phone in the clouds. In IEEE International Conference on Mobile Services (MS), 2014 (pp. 140–146). IEEE.

  • Yin, M. S. (2013). Fifteen years of grey system theory research: A historical review and bibliometric analysis. Expert Systems with Applications, 40(7), 2767–2775.

    Article  Google Scholar 

  • Yu, G., Yu, Y., Xing, Q., & Li, F. (2014). Research on the time optimization model algorithm of Customer Collaborative Product Innovation. Journal of Industrial Engineering and Management, 10(1), 137–152.

    Article  Google Scholar 

  • Zhang, Z., & Chu, X. (2009). Fuzzy group decision-making for multi-format and multi-granularity linguistic judgments in quality function deployment. Expert Systems with Applications, 36(5), 9150–9158.

    Article  Google Scholar 

  • Zhang, Q., Ma, J., Fan, Z. P., & Chiang, W. C. (2003). A statistical approach to multiple-attribute decision-making with interval numbers. International Journal of Systems Science, 34(12–13), 683–692.

    Article  Google Scholar 

  • Zhang, X., Jin, F., & Liu, P. (2013). A grey relational projection method for multi-attribute decision making based on intuitionistic trapezoidal fuzzy number. Applied Mathematical Modelling, 37(5), 3467–3477.

    Article  Google Scholar 

  • Zhang, S. F., Liu, S. Y., & Zhai, R. H. (2011). An extended gra method for mcdm with interval-valued triangular fuzzy assessments and unknown weights. Computers & Industrial Engineering, 61(4), 1336–1341.

    Article  Google Scholar 

  • Zhang, Z. (2013). Hesitant fuzzy power aggregation operators and their application to multiple attribute group decision making. Information Sciences, 234, 150–181.

  • Zhang, L., Wang, X. L., Li, Z. S., Yang, Y., & Jin, H. (2010). Merged request pattern and its application on customer collaborative product innovation platform. Computer Integrated Manufacturing Systems, 16(3), 513–520.

    Google Scholar 

Download references

Acknowledgments

This work was partly supported by MOE (Ministry of Education in China) Project of Humanities and Social Sciences (Project No. 13XJC630011); Xi’an Science and Technology Plan Projects (Project No. SF1404).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hua Li.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, F., Li, H. & Liu, A. A novel method for determining the key customer requirements and innovation goals in customer collaborative product innovation. J Intell Manuf 29, 211–225 (2018). https://doi.org/10.1007/s10845-015-1102-0

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10845-015-1102-0

Keywords

Navigation