How to Evaluate College Students’ Green Innovation Ability—A Method Combining BWM and Modified Fuzzy TOPSIS
Abstract
:1. Introduction
- A set of criteria (including four main criteria and thirteen sub criteria) to evaluate college students’ green innovation ability is proposed.
- A novel three-phase framework to evaluate college students’ green innovation ability is formulated from the perspective of open innovation. The weights of the criteria are calculated using the best worst method (BWM), which requires less comparison data and leads to more consistent comparisons, compared with other multiple-criteria decision-making (MCDM) methods. Modified fuzzy technique for order of preference by similarity to ideal solution technique (TOPSIS) is adopted to rank the alternatives considering the relative importance of the two separations.
- Implications are summarized from three aspects, including the academic, industry, and policymakers.
2. Literature Review
2.1. Green Innovation and Open Innovation
2.2. Related MCDM Methods
- (1)
- MCDM methods based on multi-attribute utility and value theories. First, this type of approach requires building a decision matrix of alternatives. Then, a score for each alternative over each criterion is given by experts. Finally, combined with weights of criteria, the rating of each alternative can be obtained using some aggregation functions. Several methods belongs to this approach, such as TOPSIS [48], VIKOR (VIse Kriterijumska Optimizacija kompromisno Resenje in Serbian, multiple criteria optimization compromise solution) [49,50], MULTIMOORA (multiplicative multi-objective optimization by ratio analysis) [51], MACBETH (measuring attractiveness by a categorical based evaluation technique) [52], and UTA (utilities additives) [53].
- (2)
- MCDM methods based on outranking methods. This method is pairwise-based, which compares two alternatives regarding each criterion to obtain dominance degrees. Then, the out ranking is calculated using an aggregate function of dominance degrees. There are several common outranking methods, for instance, BWM [67], AHP (analytic hierarchy process) [68,69], PROMETHEE (preference ranking organization method for enrichment evaluations) [70], ELECTRE (ELimination Et Choix Traduisant la REalité in French, elimination and choice expressing the reality) [71], and GLDS (gained and lost dominance score) [72].
2.3. Green Innovation Ability Evaluation Methods
3. Methodology
3.1. Identification of Criteria
3.2. Calculation of Criteria Weights Using BWM
3.3. Ranking the Students’ Green Innovation Ability Using Modified Fuzzy TOPSIS
4. Case Study
4.1. Case Background
4.2. Identification of Criteria
4.3. Determination of Criteria Weights
4.4. Ranking the Students’ Green Innovation Ability
5. Results and Discussion
5.1. Results
5.2. Discussions
- (1)
- Academic implication
- (2)
- Industry implication
- (3)
- Policymakers implication
6. Conclusions and Future Research
Author Contributions
Funding
Institutional Review Board Statement
Informed Consent Statement
Data Availability Statement
Acknowledgments
Conflicts of Interest
References
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Linguistic Variables | Corresponding Fuzzy Numbers |
---|---|
Very Low (VL) | (0, 0.1, 0.3) |
Low (L) | (0.1, 0.3, 0.5) |
Medium (M) | (0.3, 0.5, 0.7) |
High (H) | (0.5, 0.7, 0.9) |
Very High (VH) | (0.7, 0.9, 1.0) |
Main Criteria | Sub Criteria | Description | References |
---|---|---|---|
Green innovation knowledge accumulation (C1) | Basic knowledge accumulation related to green development (C11) | Knowledge about environmental issues and the concept and evolution of green development | [84,85] |
Professional frontier knowledge accumulation related to green innovation (C12) | Such as green logistics and green supply chain, etc. | [12] | |
Interdisciplinary knowledge accumulation related to green innovation (C13) | Such as green product design, green materials, green equipment, green recycling, green packaging, digital technology, etc. | [12] | |
Green technology innovation ability (C2) | Green thinking (C21) | Integrate environment concerns and frontier technologies in port development | [86] |
Green product innovation ability (C22) | Skills in improving ecological maintenance, environmental protection, and green initiatives | [4,5] | |
Green process innovation ability (C23) | Skills in improving energy saving and emission reduction, cleaner production, and process upgrading | [4,5,6,7,8] | |
Green management innovation ability (C3) | Systems thinking (C31) | Develop an effective strategy and a broad collection of analytical skills | [87,88] |
Green management mechanism innovation ability (C32) | Mechanism design for improving environment management, energy management, quality management, etc. | [4,5,6,7,8] | |
Green management practice innovation ability (C33) | Practices in improving environment management, energy management, quality management, etc. | [4,5,6,7,8] | |
Green Innovation Achievements (C4) | Papers related to green innovation (C41) | The number and quality of published papers related to green innovation | [12] |
Patents related to green innovation (C42) | The number of patents related to green innovation | [12] | |
Scientific and technological works related to green innovation (C43) | The number of award-winning works related to green innovation | [12] | |
Promotion and application of green innovation-related achievements (C44) | Promotion and application of the above achievements | [12] |
BO | C1 | C2 | C3 | C4 |
---|---|---|---|---|
Best criteria: C3 | 9 | 2 | 1 | 2 |
OW | Worst criteria: C1 | |||
C1 | 1 | |||
C2 | 5 | |||
C3 | 9 | |||
C4 | 4 |
BO | C11 | C12 | C13 |
---|---|---|---|
Best criteria: C13 | 9 | 2 | 1 |
OW | Worst criteria: C11 | ||
C11 | 1 | ||
C12 | 4 | ||
C13 | 9 |
BO | C21 | C22 | C23 |
---|---|---|---|
Best criteria: C23 | 9 | 3 | 1 |
OW | Worst criteria: C21 | ||
C21 | 1 | ||
C22 | 4 | ||
C23 | 9 |
BO | C31 | C32 | C33 |
---|---|---|---|
Best criteria: C33 | 9 | 2 | 1 |
OW | Worst criteria: C31 | ||
C31 | 1 | ||
C32 | 3 | ||
C33 | 9 |
BO | C41 | C42 | C43 | C44 |
---|---|---|---|---|
Best criteria: C44 | 9 | 4 | 3 | 1 |
OW | Worst criteria: C41 | |||
C41 | 1 | |||
C42 | 2 | |||
C43 | 4 | |||
C44 | 9 |
Main Criteria | Sub Criteria | ||||
---|---|---|---|---|---|
Criteria | Weights | Criteria | Local Weights | Global Weights | Ranking |
C1 | 0.053 | C11 | 0.071 | 0.004 | 13 |
C12 | 0.304 | 0.016 | 11 | ||
C13 | 0.625 | 0.033 | 9 | ||
C2 | 0.245 | C21 | 0.071 | 0.017 | 10 |
C22 | 0.243 | 0.060 | 5 | ||
C23 | 0.686 | 0.168 | 2 | ||
C3 | 0.474 | C31 | 0.077 | 0.036 | 7 |
C32 | 0.288 | 0.137 | 3 | ||
C33 | 0.635 | 0.301 | 1 | ||
C4 | 0.228 | C41 | 0.060 | 0.014 | 12 |
C42 | 0.154 | 0.035 | 8 | ||
C43 | 0.206 | 0.047 | 6 | ||
C44 | 0.580 | 0.132 | 4 |
Students | C11 | C12 | C13 | C21 | C22 | C23 | C31 | C32 | C33 | C41 | C42 | C43 | C44 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
S1 | (0.3, 0.6, 0.9) | (0.5, 0.7, 0.9) | (0.1, 0.4, 0.7) | (0.3, 0.6, 0.9) | (0.3, 0.5, 0.7) | (0.5, 0.7, 0.9) | (0.1, 0.3, 0.5) | (0.3, 0.5, 0.7) | (0.1, 0.3, 0.5) | (0.3, 0.5, 0.7) | (0.1, 0.3, 0.5) | (0.3, 0.5, 0.7) | (0.5, 0.7, 0.9) |
S2 | (0.3, 0.5, 0.7) | (0.1, 0.45, 0.7) | (0.5, 0.7, 0.9) | (0.1, 0.35, 0.7) | (0.3, 0.65, 0.9) | (0.3, 0.6, 0.9) | (0.3, 0.6, 0.9) | (0.1, 0.3, 0.5) | (0.5, 0.7, 0.9) | (0.5, 0.7, 0.9) | (0.1, 0.4, 0.7) | (0.5, 0.7, 0.9) | (0.3, 0.65, 0.9) |
S3 | (0.3, 0.5, 0.7) | (0.3, 0.5, 0.7) | (0.3, 0.6, 0.9) | (0.5, 0.7, 0.9) | (0.3, 0.5, 0.7) | (0.3, 0.6, 0.9) | (0.1, 0.5, 0.9) | (0.3, 0.5, 0.7) | (0.3, 0.5, 0.7) | (0.3, 0.6, 0.9) | (0.5, 0.7, 0.9) | (0.3, 0.5, 0.7) | (0.1, 0.35, 0.7) |
S4 | (0.3, 0.65, 0.9) | (0.1, 0.3, 0.5) | (0.3, 0.6, 0.9) | (0.5, 0.7, 0.9) | (0.3, 0.6, 0.9) | (0.3, 0.55, 0.9) | (0.5, 0.7, 0.9) | (0.5, 0.7, 0.9) | (0.3, 0.65, 0.9) | (0.1, 0.5, 0.9) | (0.3, 0.5, 0.7) | (0.3, 0.6, 0.9) | (0.1, 0.3, 0.5) |
S5 | (0.5, 0.7, 0.9) | (0.1, 0.3, 0.5) | (0.3, 0.6, 0.9) | (0.1, 0.3, 0.5) | (0.5, 0.7, 0.9) | (0.3, 0.5, 0.7) | (0.3, 0.55, 0.9) | (0.3, 0.5, 0.7) | (0.1, 0.3, 0.5) | (0.3, 0.5, 0.7) | (0.3, 0.5, 0.7) | (0.1, 0.3, 0.5) | (0.3, 0.6, 0.9) |
Students | C11 | C12 | C13 | C21 | C22 | C23 | C31 | C32 | C33 | C41 | C42 | C43 | C44 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
S1 | (0.33, 0.67, 1.0) | (0.56, 0.78, 1.0) | (0.11, 0.44, 0.78) | (0.33, 0.67, 1.0) | (0.33, 0.56, 0.78) | (0.56, 0.78, 1.0) | (0.11, 0.33, 0.56) | (0.33, 0.56, 0.78) | (0.11, 0.33, 0.56) | (0.33, 0.56, 0.78) | (0.11, 0.33, 0.56) | (0.33, 0.56, 0.78) | (0.56, 0.78, 1.0) |
S2 | (0.33, 0.56, 0.78) | (0.11, 0.5, 0.78) | (0.56, 0.78, 1.0) | (0.11, 0.39, 0.78) | (0.33, 0.72, 1.0) | (0.33, 0.67, 1.0) | (0.33, 0.67, 1.0) | (0.11, 0.33, 0.56) | (0.56, 0.78, 1.0) | (0.56, 0.78, 1.0) | (0.11, 0.44, 0.78) | (0.56, 0.78, 1.0) | (0.33, 0.72, 1.0) |
S3 | (0.33, 0.56, 0.78) | (0.33, 0.56, 0.78) | (0.33, 0.67, 1.0) | (0.56, 0.78, 1.0) | (0.33, 0.56, 0.78) | (0.33, 0.67, 1.0) | (0.11, 0.56, 1.0) | (0.33, 0.56, 0.78) | (0.33, 0.56, 0.78) | (0.33, 0.67, 1.0) | (0.56, 0.78, 1.0) | (0.33, 0.56, 0.78) | (0.11, 0.39, 0.78) |
S4 | (0.33, 0.72, 1.0) | (0.11, 0.33, 0.56) | (0.33, 0.67, 1.0) | (0.56, 0.78, 1.0) | (0.33, 0.67, 1.0) | (0.33, 0.61, 1.0) | (0.56, 0.78, 1.0) | (0.56, 0.78, 1.0) | (0.33, 0.72, 1.0) | (0.11, 0.56, 1.0) | (0.33, 0.56, 0.78) | (0.33, 0.67, 1.0) | (0.11, 0.33, 0.56) |
S5 | (0.56, 0.78, 1.0) | (0.11, 0.33, 0.56) | (0.33, 0.67, 1.0) | (0.11, 0.33, 0.56) | (0.56, 0.78, 1.0) | (0.33, 0.56, 0.78) | (0.33, 0.61, 1.0) | (0.33, 0.56, 0.78) | (0.11, 0.33, 0.56) | (0.33, 0.56, 0.78) | (0.33, 0.56, 0.78) | (0.11, 0.33, 0.56) | (0.33, 0.67, 1.0) |
Students | C11 | C12 | C13 | C21 | C22 | C23 | C31 | C32 | C33 | C41 | C42 | C43 | C44 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|
S1 | (0.001, 0.003, 0.004) | (0.009, 0.012, 0.016) | (0.004, 0.015, 0.026) | (0.006, 0.011, 0.017) | (0.02, 0.033, 0.047) | (0.093, 0.131, 0.168) | (0.004, 0.012, 0.02) | (0.046, 0.076, 0.107) | (0.033, 0.1, 0.167) | (0.005, 0.008, 0.011) | (0.004, 0.012, 0.019) | (0.016, 0.026, 0.037) | (0.073, 0.103, 0.132) |
S2 | (0.001, 0.002, 0.003) | (0.002, 0.008, 0.012) | (0.018, 0.026, 0.033) | (0.002, 0.007, 0.013) | (0.02, 0.043, 0.06) | (0.056, 0.112, 0.168) | (0.012, 0.024, 0.036) | (0.015, 0.046, 0.076) | (0.167, 0.234, 0.301) | (0.008, 0.011, 0.014) | (0.004, 0.016, 0.027) | (0.026, 0.037, 0.047) | (0.044, 0.095, 0.132) |
S3 | (0.001, 0.002, 0.003) | (0.005, 0.009, 0.012) | (0.011, 0.022, 0.033) | (0.009, 0.013, 0.017) | (0.02, 0.033, 0.047) | (0.056, 0.112, 0.168) | (0.004, 0.02, 0.036) | (0.046, 0.076, 0.107) | (0.1, 0.167, 0.234) | (0.005, 0.009, 0.014) | (0.019, 0.027, 0.035) | (0.016, 0.026, 0.037) | (0.015, 0.051, 0.103) |
S4 | (0.001, 0.003, 0.004) | (0.002, 0.005, 0.009) | (0.011, 0.022, 0.033) | (0.009, 0.013, 0.017) | (0.02, 0.04, 0.06) | (0.056, 0.103, 0.168) | (0.02, 0.028, 0.036) | (0.076, 0.107, 0.137) | (0.1, 0.217, 0.301) | (0.002, 0.008, 0.014) | (0.012, 0.019, 0.027) | (0.016, 0.031, 0.047) | (0.015, 0.044, 0.073) |
S5 | (0.002, 0.003, 0.004) | (0.002, 0.005, 0.009) | (0.011, 0.022, 0.033) | (0.002, 0.006, 0.009) | (0.033, 0.047, 0.06) | (0.056, 0.093, 0.131) | (0.012, 0.022, 0.036) | (0.046, 0.076, 0.107) | (0.033, 0.1, 0.167) | (0.005, 0.008, 0.011) | (0.012, 0.019, 0.027) | (0.005, 0.016, 0.026) | (0.044, 0.088, 0.132) |
Students | CCi | Ranking | ||
---|---|---|---|---|
S1 | 12.461 | 0.577 | 0.031 | 4 |
S2 | 12.352 | 0.694 | 0.054 | 1 |
S3 | 12.43 | 0.617 | 0.039 | 3 |
S4 | 12.371 | 0.682 | 0.052 | 2 |
S5 | 12.497 | 0.547 | 0.025 | 5 |
Students | w+ = 0.2, w− = 0.8 | w+ =0.4, w− = 0.6 | w+ = 0.5, w− = 0.5 | w+ = 0.6, w− = 0.4 | w+ = 0.8, w− = 0.2 |
---|---|---|---|---|---|
1 | −0.123 | −0.046 | −0.008 | 0.031 | 0.108 |
2 | −0.115 | −0.03 | 0.012 | 0.054 | 0.138 |
3 | −0.12 | −0.041 | −0.001 | 0.039 | 0.118 |
4 | −0.116 | −0.032 | 0.01 | 0.052 | 0.135 |
5 | −0.126 | −0.051 | −0.013 | 0.025 | 0.1 |
Main Criteria | w3 = 0.474 | w3 = 0.2 | w3 = 0.4 | w3 = 0.6 | w3 = 0.8 |
---|---|---|---|---|---|
C1 | 0.053 | 0.0806 | 0.060 | 0.040 | 0.020 |
C2 | 0.245 | 0.3726 | 0.279 | 0.186 | 0.093 |
C3 | 0.474 | 0.2000 | 0.4 | 0.6 | 0.8 |
C4 | 0.228 | 0.3468 | 0.260 | 0.173 | 0.087 |
Students | w3 = 0.474 | w3 = 0.2 | w3 = 0.4 | w3 = 0.6 | w3 = 0.8 |
---|---|---|---|---|---|
1 | 4 | 2 | 2 | 4 | 5 |
2 | 1 | 1 | 1 | 2 | 2 |
3 | 3 | 4 | 4 | 3 | 3 |
4 | 2 | 3 | 3 | 1 | 1 |
5 | 5 | 5 | 5 | 5 | 4 |
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Li, T.; Zhao, D.; Liu, G.; Wang, Y. How to Evaluate College Students’ Green Innovation Ability—A Method Combining BWM and Modified Fuzzy TOPSIS. Sustainability 2022, 14, 10084. https://doi.org/10.3390/su141610084
Li T, Zhao D, Liu G, Wang Y. How to Evaluate College Students’ Green Innovation Ability—A Method Combining BWM and Modified Fuzzy TOPSIS. Sustainability. 2022; 14(16):10084. https://doi.org/10.3390/su141610084
Chicago/Turabian StyleLi, Tingting, Dan Zhao, Guiyun Liu, and Yuhong Wang. 2022. "How to Evaluate College Students’ Green Innovation Ability—A Method Combining BWM and Modified Fuzzy TOPSIS" Sustainability 14, no. 16: 10084. https://doi.org/10.3390/su141610084