1 高端装备制造业协同创新伙伴选择评价指标构建
1.1 伙伴选择评价指标体系建立过程
表1 国内外创新伙伴选择评价指标 |
指标来源 | 评价指标 |
---|---|
Shevtshenko 等[10] | 合作成本、合作风险和创新效率 |
Santos 等[11] | 经济(财务状况及信誉、运营状况)、社会(声誉、知识相关性、可用资源)及环境(政府支持度) |
Arsanti 等[12] | 互补性(技术与资源)、兼容性(目标及文化一致)和信任性 |
Chowdhury 等[13] | 价值提供、技术复杂性及组织间兼容性 |
Li等[14] | 主体间的利益分配模式、技术创新水平、组织结构、合作意愿与兼容性 |
刘澜等[15] | 管理水平、经济情况、人力资源、技术水平、信誉度及兼容性 |
李柏洲等[16] | 创新能力、兼容性、信任度与合作意愿 |
李柏洲等[17] | 合作水平、聚合资源能力及合作聚合度 |
李翠等[18] | 互补性、兼容性、企业规模、技术水平、财务状况和企业发展情况 |
孟贤等[19] | 合作成本、服务水平、风险共担能力及信息共享能力 |
刘嘉等[20] | 生产能力、质量评估、业务能力、合作互补性及环境影响 |
李红艳等[21] | 人力资源条件、财力资源条件、设备资源条件、协同意愿、协同沟通能力及协同创新产出能力 |
黄哲等[22] | 基本条件、运营状态、企业文化、资源互补性、契约精神、信任度和技术实力 |
1.2 评价指标体系的确定
2 高端装备制造业协同创新伙伴选择评价模型构建
2.1 评价矩阵
2.1.1 问题描述
2.1.2 评价矩阵聚合
2.2 权重计算
2.2.1 基于社会网络信任关系的决策专家权重计算
2.2.2 评价指标权重计算
表2 1~9标度所对应的一致性指数 |
1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | |
---|---|---|---|---|---|---|---|---|---|
一致性指数 | 0.00 | 0.44 | 1.00 | 1.63 | 2.30 | 3.00 | 3.73 | 4.47 | 5.23 |
2.3 基于可能度矩阵的概率犹豫模糊EDAS决策方法
2.3.1 可能度矩阵
2.3.2 EDAS决策排序
3 算例分析
3.1 算例应用
表3 候选伙伴2020-2022年基本研发数据 |
研究对象 | 年份 | 已获得专利/件 | 发明专利 | 研发人员数量/人 | 人员占比/% | 研发投入/元 | 投入占比/% |
---|---|---|---|---|---|---|---|
X 1 | 2020 | - | - | 531 | 11.55 | 29 380 357.08 | 2.19 |
2021 | 62 | - | 218 | 6.9 | 45 373 606.29 | 2.67 | |
2022 | 55 | 4 | 202 | 7.13 | 64 684 359.08 | 3.87 | |
X 2 | 2020 | 15 | 3 | 1 014 | 10.18 | 224 272 543.4 | 5.48 |
2021 | 20 | - | 1 026 | 10.36 | 280 944 269.4 | 5.56 | |
2022 | 25 | 17 | 1 068 | 11.08 | 340 216 354.3 | 8.3 | |
X 3 | 2020 | - | - | - | - | 24 298 000 | 5.92 |
2021 | - | - | - | - | 27 746 500 | 5.42 | |
2022 | 21 | 1 | 74 | 23.27 | 24 452 345.72 | 4.92 | |
X 4 | 2020 | - | - | 64 | 5.24 | 20 048 400 | 4.52 |
2021 | 12 | 2 | 60 | 4.74 | 27 116 695.08 | 5.29 | |
2022 | 15 | 5 | 66 | 5 | 28 546 108.86 | 4.95 |
3.2 基于可能度矩阵的概率犹豫模糊EDAS评价步骤
表4 专家 给出的评价矩阵 Q 1 |
E 1 | b1 | b2 | b3 | b4 | b5 | b6 | b7 |
---|---|---|---|---|---|---|---|
X 1 | {0.6(0.5), 0.8(0.5)} | {0.8(0.6), 0.9(0.4)} | {0.6(0.7), 0.7(0.3)} | {0.7(0.8), 0.8(0.2)} | {0.6(0.4), 0.8(0.6)} | {0.8(0.3), 0.9(0.7)} | {0.6(0.3), 0.8(0.7)} |
X 2 | {0.7(0.4), 0.8(0.6)} | {0.4(0.3), 0.6(0.7)} | {0.7(0.7), 0.9(0.3)} | {0.3(0.4), 0.5(0.6)} | {0.7(0.6), 0.9(0.4)} | {0.6(0.6), 0.7(0.4)} | {0.7(0.8), 0.8(0.2)} |
X 3 | {0.5(0.4), 0.6(0.6)} | {0.7(0.3), 0.8(0.7)} | {0.6(0.4), 0.8(0.6)} | {0.4(0.4), 0.5(0.6)} | {0.2(0.3), 0.4(0.7)} | {0.5(0.6), 0.7(0.4)} | {0.4(0.6), 0.6(0.4)} |
X 4 | {0.6(0.8), 0.7(0.2)} | {0.6(0.4), 0.8(0.6)} | {0.7(0.8), 0.8(0.2)} | {0.4(0.4), 0.5(0.6)} | {0.4(0.5), 0.5(0.5)} | {0.6(0.8), 0.8(0.2)} | {0.5(0.5), 0.6(0.5)} |
表5 专家 给出的评价矩阵 Q 2 |
E 2 | b1 | b2 | b3 | b4 | b5 | b6 | b7 |
---|---|---|---|---|---|---|---|
X 1 | {0.7(0.5), 0.8(0.5)} | {0.5(0.2), 0.7(0.8)} | {0.8(0.5), 0.9(0.5)} | {0.7(0.7), 0.8(0.3)} | {0.5(0.3), 0.7(0.7)} | {0.5(0.2), 0.7(0.8)} | {0.7(0.6), 0.9(0.4)} |
X 2 | {0.4(0.7), 0.5(0.3)} | {0.7(0.7), 0.8(0.3)} | {0.5(0.2), 0.7(0.8)} | {0.6(0.7), 0.7(0.3)} | {0.5(0.5), 0.7(0.5)} | {0.5(0.2), 0.6(0.8)} | {0.6(0.3), 0.8(0.7)} |
X 3 | {0.5(0.5), 0.6(0.5)} | {0.6(0.2), 0.7(0.8)} | {0.3(0.7), 0.5(0.3)} | {0.4(0.6), 0.5(0.4)} | {0.4(0.8), 0.6(0.2)} | {0.6(0.6), 0.7(0.4)} | {0.3(0.7), 0.5(0.3)} |
X 4 | {0.6(0.8), 0.8(0.2)} | {0.3(0.8), 0.8(0.2)} | {0.2(0.5), 0.4(0.5)} | {0.5(0.7), 0.6(0.3)} | {0.3(0.5), 0.5(0.5)} | {0.4(0.8), 0.6(0.2)} | {0.5(0.5), 0.7(0.5)} |
表6 专家 给出的评价矩阵 Q 3 |
E 3 | b1 | b2 | b3 | b4 | b5 | b6 | b7 |
---|---|---|---|---|---|---|---|
X 1 | {0.4(0.2), 0.6(0.8)} | {0.6(0.3), 0.8(0.7)} | {0.6(0.3), 0.8(0.7)} | {0.8(0.4), 0.9(0.6)} | {0.6(0.2), 0.7(0.8)} | {0.7(0.5), 0.9(0.5)} | {0.7(0.4), 0.8(0.6)} |
X 2 | {0.6(0.4), 0.8(0.6)} | {0.5(0.2), 0.7(0.8)} | {0.7(0.5), 0.8(0.5)} | {0.4(0.2), 0.6(0.8)} | {0.6(0.5), 0.8(0.5)} | {0.5(0.6), 0.7(0.4)} | {0.6(0.5), 0.8(0.5)} |
X 3 | {0.6(0.8), 0.7(0.2)} | {0.6(0.8), 0.7(0.2)} | {0.5(0.6), 0.6(0.4)} | {0.5(0.7), 0.6(0.3)} | {0.6(0.4), 0.8(0.6)} | {0.6(0.5), 0.7(0.5)} | {0.5(0.4), 0.6(0.6)} |
X 4 | {0.7(0.7), 0.8(0.3)} | {0.4(0.7), 0.6(0.3)} | {0.4(0.8), 0.6(0.2)} | {0.4(0.7), 0.6(0.3)} | {0.4(0.6), 0.5(0.4)} | {0.6(0.6), 0.8(0.4)} | {0.6(0.6), 0.7(0.4)} |
表7 综合评价矩阵 Q |
b1 | b2 | b3 | b4 | b5 | b6 | b7 | |
---|---|---|---|---|---|---|---|
X 1 | {0.616 6(0.4),0.762 2 (0.6)} | {0.623 9(0.366 7),0.794 0(0.633 3)} | {0.717 2(0.5),0.843 5(0.5)} | {0.728 9(0.633 3),0.831 8(0.366 7)} | {0.552 8(0.3),0.728 9(0.7)} | {0.650 0(0.333 3),0.826 8(0.666 7)} | {0.677 6(0.433 3),0.858 6(0.566 7)} |
X 2 | {0.544 1(0.5),0.683 8 (0.5)} | {0.594 6(0.4),0.736 8(0.6)} | {0.612 7(0.466 7),0.794 0(0.533 3)} | {0.490 9(0.433 3),0.633 7(0.566 7)} | {0.583 8(0.533 3),0.794 0(0.466 7)} | {0.527 1(0.466 7),0.653 6(0.533 3)} | {0.627 8(0.533 3),0.8(0.466 7)} |
X 3 | {0.527 1(0.566 7),0.627 8(0.433 3)} | {0.627 8(0.433 3),0.728 9(0.566 7)} | {0.440 5(0.566 7),0.623 9(0.433 3)} | {0.426 7(0.566 7),0.527 1(0.433 3)} | {0.417 4(0.5),0.627 8(0.5)} | {0.577 1(0.566 7),0.7(0.433 3)} | {0.380 8(0.566 7),0.552 8(0.433 3)} |
X 4 | {0.627 8(0.766 7),0.778 7(0.233 3)} | {0.414 4(0.633 3),0.762 2(0.366 7)} | {0.417 4(0.7),0.588 0(0.3)} | {0.452 3(0.6),0.577 1(0.4)} | {0.351 9(0.533 3),0.5(0.466 7)} | {0.510 1(0.733 3),0.717 2(0.266 7)} | {0.527 1(0.533 3),0.677 6(0.466 7)} |
表8 得分函数 |
b1 | b2 | b3 | b4 | b5 | b6 | b7 | |
---|---|---|---|---|---|---|---|
X 1 | 0.703 9 | 0.731 7 | 0.780 3 | 0.766 6 | 0.676 1 | 0.767 9 | 0.780 2 |
X 2 | 0.613 9 | 0.679 9 | 0.709 4 | 0.571 8 | 0.681 9 | 0.594 6 | 0.708 2 |
X 3 | 0.570 7 | 0.685 1 | 0.520 0 | 0.470 2 | 0.522 6 | 0.630 3 | 0.455 3 |
X 4 | 0.663 0 | 0.541 9 | 0.468 6 | 0.502 2 | 0.421 0 | 0.565 3 | 0.597 3 |
表9 指标结果 |
b1 | b2 | b3 | b4 | b5 | b6 | b7 |
---|---|---|---|---|---|---|
9 | 6 | 1 | 3 | 4 | 5 | 2 |
1 | 2 | 9 | 7 | 6 | 7 | 8 |
表10 正向距离矩阵 |
PDA | b1 | b2 | b3 | b4 | b5 | b6 | b7 |
---|---|---|---|---|---|---|---|
X 1 | 0.599 6 | 0.646 3 | 0.585 3 | 0.957 8 | 0.905 0 | 0.811 0 | 0.773 5 |
X 2 | 0.395 0 | 0.529 9 | 0.599 0 | 0.460 3 | 0.731 9 | 0.402 2 | 0.609 8 |
X 3 | 0.296 9 | 0.541 5 | 0.225 4 | 0.200 9 | 0.269 4 | 0.486 6 | 0.035 1 |
X 4 | 0.506 4 | 0.219 3 | 0 | 0.282 5 | 0.143 9 | 0.333 2 | 0.357 9 |
表11 反向距离矩阵 |
NDA | b1 | b2 | b3 | b4 | b5 | b6 | b7 |
---|---|---|---|---|---|---|---|
X 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
X 2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
X 3 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
X 4 | 0 | 0 | 0.012 7 | 0 | 0 | 0 | 0 |
3.3 对比分析
表12 对比结果 |
方法 | 排序结果 |
---|---|
TOPSIS | |
VIKOR | |
PHFWA算子 | |
PHFWG算子 | |
本文 |