I Tetsuya Okamoto / Miok Im / 1990 CS Customer Satisfaction No.1 Heskett et al. 1994 ISO International Organization for Standardization ISO9001 1 2 12016 2 17 33,848 ISO9001 http://www.jab.or.jp 2 2010 p.34 004 2016 summer / No.408
3 Importance-Performance Analysis IPA 4 IPA II 1 IPA Martilla & James 1977 Martilla & James 1977 IPA Importance Performance 高 低 Ⅱ 過剰遂行 Possible Overkill Ⅲ 低優先度 Low Priority 低 2 1 5 重要度 1 2 4 Ⅰ 重点維持 Keep Up The Good Work Ⅳ 重点改善 Concentrate Here Keep Up The Good Work Possible Overkill 高 1 Martilla & James 1977 p.78 3 2016 2 22125 97 78% https://www.jmra-net.or.jp 4 CS Customer Satisfaction 2007 pp.357 364 CS 5 Martilla & James 1977 Importance-Performance Grid Importance-Performance Matrix 005
Low Priority Concentrate Here Martilla & James 1977 14 IPA 2 2 2 6 Michael et al., 2000 pp.104-105 Michael et al., 2000 p.107 6 Hill et al. 1999 Hema & Samuel 2011 IPA 006 2016 summer / No.408
7 3 Martilla & James 1977 IPA Dolinski 1991 8 Deng et al. 2008 Feng et al. 2014 Martilla & James 1977 4 Martilla & James 1977 5 4 2006 20085 3 0.5 Oh 200124 15 3 1 5 7 Matzler et al. 2004 performance asymmetric IPA 007
Heskett et al. 1994 48 5 1993 4 5 1991 5 4 6 3 3 2 III 1 1 4 0 8 8 1984 Reverse Quality Element 008 2016 summer / No.408
Deng et al. 2008 Feng et al. 2014 1 0 2 t0 t 5% t t t 0 3 009
IV 1 2010 2 4 5 515 10 CO NOX10 10 9 5 10 1 N 515 421 81.7 94 18.3 20 50 9.7 30 180 35.0 40 168 32.6 50 80 15.5 60 37 7.2 169 32.8 80 15.5 85 16.5 29 5.6 42 8.2 31 6.0 25 4.9 19 3.7 35 6.8 206 40.0 13 2.5 52 10.1 95 18.4 20 3.9 23 4.5 27 5.2 14 2.7 20 3.9 37 7.2 8 1.6 2 1 3 2 SD Standard Deviation IPA 2 3 Michael et al. 2000 2 11 9 10 10 1 2 3 4 5 1 2 3 4 5 010 2016 summer / No.408
2 N=515 N=169 N=85 t SD T SD H SD T H H T t 4.06 0.887 4.21 0.851 4.16 0.814 0.05 0.05 0.38 4.00 0.909 4.04 0.875 4.13 0.799 0.09 0.09 0.78 3.66 1.037 3.83 1.024 3.53 1.087 0.30 0.30 2.15* 3.68 1.021 3.64 1.055 3.88 0.878 0.24 0.24 1.83 3.71 1.008 3.73 0.998 3.84 0.871 0.11 0.11 0.84 3.70 0.985 3.74 1.013 3.75 0.975 0.01 0.01 0.10 3.08 1.175 2.99 1.249 3.33 1.169 0.34 0.34 2.10* 3.61 0.909 3.60 0.928 3.54 0.907 0.06 0.06 0.46 3.66 0.839 3.78 0.820 3.65 0.767 0.13 0.13 1.26 3.27 0.904 3.33 0.992 3.42 0.807 0.09 0.09 0.74 3.83 0.830 3.85 0.838 3.84 0.754 0.01 0.01 0.10 p<.10; *p<.05; **p<.01; ***p<.001 3 N=515 N=206 N=95 SD SD SD 3.92 0.899 3.99 0.864 3.83 0.919 4.10 0.836 4.06 0.827 3.98 0.850 4.03 0.834 4.00 0.847 3.95 0.790 4.07 0.814 4.08 0.776 4.00 0.786 4.07 0.793 4.07 0.765 3.98 0.743 4.17 0.769 4.26 0.684 4.09 0.745 4.29 0.793 4.38 0.734 4.46 0.665 4.35 0.713 4.43 0.671 4.35 0.681 4.20 0.760 4.29 0.726 4.21 0.667 3.73 0.960 3.89 0.866 3.77 0.818 4 N=515 N=169 N=85 t t t 0.140 3.90*** 0.209 3.39** -0.043-0.53 0.189 5.06*** 0.035 0.49 0.271 3.11** 0.095 2.65** 0.149 2.12* 0.121 1.52 0.047 1.03-0.028-0.33-0.006-0.06 0.171 3.59*** 0.139 1.49 0.276 2.98** 0.208 5.16*** 0.204 2.71** 0.235 2.72** 0.040 1.23 0.053 0.83 0.027 0.34 0.100 3.29** 0.172 3.03** 0.076 0.76 0.049 1.38 0.100 1.44 0.020 0.25 0.102 3.02** 0.105 1.58 0.247 3.19** R 2 0.662 0.661 0.720 R 2 0.656 0.639 0.682 F 98.921*** 30.780*** 19.017*** *p<.05; **p<.01; ***p<.001 11 515 2 4 10 5% 9 011
4 10 A 4 A B C 3 2 3 3 3 B 2 A B A 3 A B5 C B C 0.1140 4 2 3 012 2016 summer / No.408
A B C 3 7 3 A B A B6 B C 0.1220 4 6 23 5 3 2 013
5 A B C A B C 6 310 IMP1 IMP2 r=0.056 = 0.111 = 0.127 5% r= 0.317 = 0.135 = 0.231 PER1 PER2 10% 5% 6 N 10 IMP1 IMP2 PER1 PER2 IMP1 IMP2 PER1 PER2 IMP1 Pearson IMP2 0.056 0.317 r PER1 0.375 0.334 0.472 0.016 PER2 0.139 0.601 0.566 0.239 0.020 0.036 IMP1 Kendall IMP2 0.111 0.135 PER1 0.333 0.244 0.315 0.111 PER2 0.090 0.360 0.449 0.114 0.180 0.045 IMP1 Spearman IMP2 0.127 0.231 PER1 0.418 0.297 0.286 0.127 PER2 0.073 0.559 0.535 0.149 0.146 0.024 p<.10; *p<.05; **p<.01; ***p<.001 014 2016 summer / No.408
r=0.566 =0.449 =0.535 r= 0.036 =0.045=0.024 2 3A B B C 2 3 B C 0.114 0 0.122 0 4 2 5 2 C3 C 5% C C 4 V 1 3 015
1 5 6 76 21 2 1 t 2 1 3C Customer Company Competitor Martilla & James 1977 Company Customer Competitor 2 3C Performance 1994 Swan & Combs 1976 1994 pp.65-701999 pp.179-180 2010 p.147 016 2016 summer / No.408
3 2 1 1 4 1 2 3 A 12 Deng, W., Kuo, Y. and Chen, W.(2008), Revise importance-performance analysis: three-factor and benchmarking, The Service Industries Journal, 28(1), pp.37-51. Dolinsky, L.(1991), Considering the Competition in Strategy Development: An Extension of Importance- Performance Analysis, Journal of Health Care Marketing, 11(1), pp.31-36. Feng, M., Mangan, J., Wong, C., Xu, M. and Lalwani, C.(2014), Investing the different approaches to importance-performance analysis, The Service Industries Journal, 34(12), pp.1021-1041. Hema, N. M. and Samuel, S.(2011), Importance- Performance Analysis to determine Service Quality of a Restaurant Service An Empirical Study, Advances In Management, 4(2), pp.52-57. Heskett, J. L., Jones, T. O., Loveman, G. W., Sasser, W. E., Jr. and Schlesinger, L. A. (1994), Putting the Service-Profit Chain to Work, Harvard Business Review, March-April, pp.164-174. 12 9 r= 0.687(0.041) =0.611(0.022) =0.817(0.017) r= 0.792(0.011) =0.592(0.028) =0.619 (0.75) 017
Hill, N., MacDougall, R. and Brierley, J. (1995), How to Measure Customer Satisfaction, Gower Pub Co. 2005 1999 Johnson, M. D. and Gustafsson, A.(2000), Improving Customer Satisfaction, Loyalty, and Profit, John Wiley & Sons, Inc. 2001 1984 14(2) pp.39-48 Martilla, J. A. and James, J. C. 1977 Importance- Performance Analysis, Journal of Marketing, 41, pp.77-79. 2006 36(1) pp.99-109 2008 Matzler, K., Sauerwein, E. and Heischmidt, K. A.(2003), Importance-Performance Analysis Revisited: The Role of the Factor Structure of Customer Satisfaction, The Service Industries Journal, 23(2), pp.112-129. Matzler, K., Bailom, F., Hinterhuber, H. H.(2004), The asymmetric relationship between attribute-level performance and overall satisfaction: a reconsideration of the importance-performance analysis, Industrial Marketing Management, 33, pp.271-277. 1994 24 pp.36-46 2007 pp.357-364 Oh, H.(2001), Revisiting importance-performance analysis, Tourism Management, 22, pp.617-627. 2010 CS 1994 Swan, J. E. and Combs, L. J.(1976), Product Performance and Customer Satisfaction, Journal of Marketing, 40, pp.25-33. 018 2016 summer / No.408
Boundary Standardization and Significance Application in the Importance-Performance Matrix Tetsuya Okamoto Miok Im This study looks at three problems through an examination of previous research on the importance-performance matrix: the matrix involves both self-stated importance and statistical inferred importance; the matrix lacks a competitive perspective; and the matrix fails to define standards for boundaries between quadrants. To solve these problems, the study suggests applying β obtained by multiple linear regression analysis on the horizontal axis of the matrix and relative performance to a competing company on the vertical axis, setting quadrant boundaries to the origin, and employing statistical significance tests. The following three results were obtained through an analysis of data gathered from car owners in Japan. First, on the importance-performance matrix, product attributes plotted between each quadrant fluctuated considerably, either by applying self-stated importance or β on the horizontal axis or by applying performance or relative performance on the vertical axis. Second, fluctuations in the first analysis result were caused by two factors, namely, low correlations between self-stated importance and β, and between performance and relative performance and an absence of proper standards for establishing quadrant boundaries. Lastly, to avoid instability of the first result, using t-test s statistical significance to identify particular product attributes was confirmed as contributing to objective interpretations of the analysis results. Boundary Standardization and Significance Application in the Importance-Performance Matrix Tetsuya Okamoto Miok Im 019