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摘要: 基于高速公路服务和客户满意度的概念, 构建了包括客户期望、条件感知质量、环境感知质量、活动感知质量、客户满意度、客户抱怨和客户忠诚7个潜变量的客户满意度模型, 遵循完整性、重要性、独立性和可操作性原则, 用Delphi法从服务条件、服务环境、服务活动和客户抱怨四方面构建了高速公路客户满意度评价指标体系。将层次分析法和模糊数学原理相结合, 建立了高速公路客户满意度的模糊层次综合评价模型, 并应用模型对昌九高速公路客户满意度进行综合评价。评价结果表明: 该高速公路的客户满意度总体处于满意, 同时发现在服务活动和客户抱怨两方面均处于一般满意, 这与该高速公路的客户满意度调查统计数据相符合, 因此, 该模型合理有效。Abstract: The conceptions of expressway service and customer satisfaction were analyzed, a customer satisfaction model was designed, which included seven latent variables, such as customer expectation, condition perceived quality, environment perceived quality, activity perceived quality, customer satisfaction, customer complaint and customer faithfulness.Following the principles of integrality, importance, independency and maneuverability, the customer satisfaction evaluation index system of expressway service was constructed by using Delphi method from four aspects of service condition, service environment, service activity and customer complaint.Through combining fuzzy mathematics theory with analytic hierarchy process(AHP), a fuzzy hierarchy comprehensive evaluation model of customer satisfaction for expressway service was constructed, and the customer satisfaction of Nanchang-Jiujiang expressway was evaluated.Evaluation result shows that the customer satisfaction of the expressway is general satisfaction, but its service activity and customer complaint are lower satisfaction, which is consistent with the statistical data of customer satisfaction, so the model is rational and effective.
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表 1 X的判断矩阵和权重
Table 1. Judgement matrix and weights of X
X X1 X2 X3 X4 权重Wk X1 1 4 5 9 0.613 6 X2 1/4 1 2 5 0.208 3 X3 1/5 1/2 1 4 0.132 1 X4 1/9 1/5 1/4 1 0.046 0 注: λmax=4.108 5, CI=0.036 2, RI=0.90, CR=0.040 6 < 0.1, 一致性检验通过。 表 2 X1的判断矩阵和权重
Table 2. Judgement matrix and weights of X1
X1 X11 X12 X13 X14 权重Wk1 X11 1 4 7 9 0.631 3 X12 1/4 1 3 5 0.218 4 X13 1/7 1/3 1 4 0.106 3 X14 1/9 1/5 1/4 1 0.044 0 注: λmax=4.190 0, CI=0.063 3, RI=0.90, CR=0.071 1 < 0.1, 一致性检验通过。 表 3 X2的判断矩阵和权重
Table 3. Judgement matrix and weights of X2
X2 X21 X22 X23 X24 X25 权重Wk2 X21 1 3 1/3 1/2 2 0.168 1 X22 1/3 1 1/4 1/3 2 0.094 9 X23 3 4 1 2 4 0.407 4 X24 2 3 1/2 1 3 0.253 2 X25 1/2 1/2 1/4 1/3 1 0.076 3 注: λmax=5.162 5, CI=0.040 6, RI=1.12, CR=0.036 3 < 0.1, 一致性检验通过。 表 4 X3的判断矩阵和权重
Table 4. Judgement matrix and weights of X3
X3 X31 X32 X33 X34 X35 权重Wk3 X31 1 2 2 1 5 0.300 7 X32 1/2 1 2 1/3 3 0.163 8 X33 1/2 1/2 1 1/4 1 0.095 9 X34 1 3 4 1 5 0.370 3 X35 1/5 1/3 1 1/5 1 0.069 3 注: λmax=5.135 5, CI=0.027 6, RI=1.12, CR=0.024 6 < 0.1, 一致性检验通过。 表 5 X4的判断矩阵和权重
Table 5. Judgement matrix and weights of X4
X4 X41 X42 权重Wk4 X41 1 3 0.750 X42 1/3 1 0.250 注: λmax=2.000 0, CI=0.000 0, RI=0.00, CR=0.000 0 < 0.1, 一致性检验通过。 表 6 调查内容及模糊偏好值
Table 6. Survey content and values of fuzzy preference
目标 分类评价指标 单项评价指标 模糊偏好关系值 很满意 满意 一般满意 不满意 很不满意 X X1 X11 0.30 0.45 0.20 0.05 0.00 X12 0.25 0.35 0.20 0.12 0.08 X13 0.20 0.38 0.22 0.16 0.04 X14 0.20 0.45 0.24 0.11 0.00 X2 X21 0.25 0.33 0.26 0.12 0.04 X22 0.12 0.36 0.28 0.16 0.10 X23 0.24 0.38 0.24 0.10 0.04 X24 0.20 0.32 0.28 0.15 0.05 X25 0.20 0.28 0.32 0.12 0.08 X3 X31 0.22 0.40 0.26 0.07 0.05 X32 0.25 0.38 0.25 0.10 0.02 X33 0.10 0.20 0.36 0.25 0.09 X34 0.08 0.12 0.36 0.34 0.10 X35 0.12 0.43 0.25 0.16 0.04 X4 X41 0.00 0.20 0.36 0.34 0.10 X42 0.12 0.36 0.32 0.20 0.00 -
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