Supplier selection for housing development by an integrated method with interval rough boundaries
Abstract
Residential whole-decoration is an important initiative for housing industrialization in China. Selecting the most suitable component supplier for housing development is of great significance for both property developers and buyers in the implementation of such a strategy. To address such a problem, this study uses hesitant fuzzy linguistic term sets to express the inaccurate judgments of individuals and then introduces a novel probability aggregation approach based on interval rough boundaries to enable a realistic presentation of the collective evaluations of a group. Then, we propose a hybrid multi-expert multiple criteria decision-making model by integrating the Best Worst Method (BWM) and Combined Compromise Solution (CoCoSo) method based on the interval rough boundaries. A case study about the supplier selection for housing development is carried out, which demonstrates the feasibility and applicability of our proposed hybrid model. A comparison study is also performed to further validate the robustness of the model.
Keyword : multi-criteria decision making, supplier selection for housing development, interval rough boundaries, Combined Compromise Solution method, Best-Worst method, hesitant fuzzy linguistic term set, probabilistic linguistic term set
How to Cite
Zhang, Z., Liao, H., Al-Barakati, A., Zavadskas, E. K., & Antuchevičienė, J. (2020). Supplier selection for housing development by an integrated method with interval rough boundaries. International Journal of Strategic Property Management, 24(4), 269-284. https://doi.org/10.3846/ijspm.2020.12434
This work is licensed under a Creative Commons Attribution 4.0 International License.
References
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Gou, X. J., Liao, H. C., Xu, Z. S., & Herrera, F. (2017). Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: a case of study to evaluate the implementation status of haze controlling measures. Information Fusion, 38, 22–34. https://doi.org/10.1016/j.inffus.2017.02.008
Greco, S., Matarazzo, B., & Slowinski, R. (2001). Rough sets theory for multicriteria decision analysis. European Journal of Operational Research, 129(1), 1–47. https://doi.org/10.1016/S0377-2217(00)00167-3
Herrera, F., Herrera-Viedma, E., & Verdegay, J. L. (1995). A sequential selection process in group decision making with a linguistic assessment approach. Information Sciences, 85(4), 223–239. https://doi.org/10.1016/0020-0255(95)00025-K
Lam, K. C., Tao, R., & Lam, M. C. K. (2010). A material supplier selection model for property developers using fuzzy principal component analysis. Automation in Construction, 19(5), 608–618. https://doi.org/10.1016/j.autcon.2010.02.007
Li, H., Li, D., Zhai, Y., Wang, S., & Zhang, J. (2016). A novel attribute reduction approach for multi-label data based on rough set theory. Information Sciences, 367, 827–847. https://doi.org/10.1016/j.ins.2016.07.008
Liao, H. C., & Wu, X. L. (2020). DNMA: a double normalizationbased multiple aggregation method for multi-expert multicriteria decision making. Omega, 94, 102058.
https://doi.org/10.1016/j.omega.2019.04.001
Liao, H. C., Jiang, L. S., Lev, B., & Fujita, H. (2019a). Novel operations of PLTSs based on the disparity degrees of linguistic terms and their use in designing the probabilistic linguistic ELECTRE III method. Applied Soft Computing, 80, 450–464. https://doi.org/10.1016/j.asoc.2019.04.018
Liao, H. C., Mi, X. M., & Xu, Z. S. (2020). A survey of decisionmaking methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions. Fuzzy Optimization and Decision Making, 19(1), 81–134. https://doi.org/10.1007/s10700-019-09309-5
Liao, H. C., Mi, X. M., Yu, Q., & Luo, L. (2019b). Hospital performance evaluation by a hesitant fuzzy linguistic best worst method with inconsistency repairing. Journal of Cleaner Production, 232, 657–671. https://doi.org/10.1016/j.jclepro.2019.05.308
Liao, H. C., Wen, Z., & Liu, L. L. (2019c). Integrating BWM and ARAS under hesitant linguistic environment for digital supply chain finance supplier selection. Technological and Economic Development of Economy, 25(6), 1188–1212. https://doi.org/10.3846/tede.2019.10716
Liao, H. C., Xu, Z. S., & Zeng, X. J. (2014). Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Transactions on Fuzzy Systems, 23(5), 1343–1355. https://doi.org/10.1109/TFUZZ.2014.2360556
Liao, H. C., Xu, Z. S., Herrera-Viedma, E., & Herrera, F. (2018). Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the art survey. International Journal of Fuzzy Systems, 20(7), 2084–2110. https://doi.org/10.1007/s40815-017-0432-9
Liao, H. C., Xu, Z. S., Zeng, X. J., & Merigó, J. M. (2015). Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets. Knowledge-Based Systems, 76, 127–138. https://doi.org/10.1016/j.knosys.2014.12.009
Luo, Z., He, J., Pan, H., & Yang, Y. (2016). Research on the selection strategy of green building parts supplier based on the catastrophe theory and Kent index method. Advances in Materials Science and Engineering, 2016, 1–12. https://doi.org/10.1155/2016/4673526
Matić, B., Jovanović, S., Das, D. K., Zavadskas, E. K., Stević, Ž., Sremac, S., & Marinković, M. (2019). A new hybrid MCDM model: Sustainable supplier selection in a construction company. Symmetry, 11(3), 353. https://doi.org/10.3390/sym11030353
Mi, X. M., Liao, H. C., Wu, X. L., & Xu, Z. S. (2020). Probabilistic linguistic information fusion: a survey on aggregation operators in terms of principles, definitions, classifications, applications and challenges. International Journal of Intelligent Systems, 35(3), 529–556. https://doi.org/10.1002/int.22216
Mi, X. M., Tang, M., Liao, H. C., Shen, W. J., & Lev, B. (2019). The state-of-the-art survey on integrations and applications of the best worst method in decision making: why, what, what for and what’s next? Omega, 87, 205–225. https://doi.org/10.1016/j.omega.2019.01.009
Ministry of Housing and Urban-Rural Development of the People’s Republic of China. (1999). Several opinions on promoting the modernization of housing industry and improving the quality of housing. http://www.mohurd.gov.cn/wjfb/200611/t20061101_155382.html
Ministry of Housing and Urban-Rural Development of the People’s Republic of China. (2008). Notice on further strengthening the management of residential fit-out and decoration. Ministry of Housing and Urban-Rural Development of the People’s Republic of China. http://www.gov.cn/zwgk/200808/01/content_1061518.htm
Ministry of Housing and Urban-Rural Development of the People’s Republic of China. (2013). Green building action plan. http://www.gov.cn/zwgk/2013-01/06/content_2305793.htm
Onar, S. Ç., Büyüközkan, G., Öztayşi, B., & Kahraman, C. (2016). A new hesitant fuzzy QFD approach: an application to computer workstation selection. Applied Soft Computing, 46, 1–16. https://doi.org/10.1016/j.asoc.2016.04.023
Pamučar, D., Mihajlović, M., Obradović, R., & Atanasković, P. (2017). Novel approach to group multi-criteria decision making based on interval rough numbers: hybrid DEMATELANP-MAIRCA model. Expert Systems with Applications, 88, 58–80. https://doi.org/10.1016/j.eswa.2017.06.037
Pamučar, D., Petrović, I., & Ćirović, G. (2018). Modification of the Best–Worst and MABAC methods: a novel approach based on interval-valued fuzzy-rough numbers. Expert Systems with Applications, 91, 89–106. https://doi.org/10.1016/j.eswa.2017.08.042
Pang, Q., Wang, H., & Xu, Z. (2016). Probabilistic linguistic term sets in multi-attribute group decision making. Information Sciences, 369, 128–143. https://doi.org/10.1016/j.ins.2016.06.021
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57. https://doi.org/10.1016/j.omega.2014.11.009
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: some properties and a linear model. Omega, 64, 126–130. https://doi.org/10.1016/j.omega.2015.12.001
Rodriguez, R. M., Martinez, L., & Herrera, F. (2011). Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20(1), 109–119. https://doi.org/10.1109/TFUZZ.2011.2170076
Safa, M., Shahi, A., Haas, C. T., & Hipel, K. W. (2014). Supplier selection process in an integrated construction materials management model. Automation in Construction, 48, 64–73. https://doi.org/10.1016/j.autcon.2014.08.008
Seth, D., Nemani, V. K., Pokharel, S., & Al Sayed, A. Y. (2018). Impact of competitive conditions on supplier evaluation: a construction supply chain case study. Production Planning & Control, 29(3), 217–235. https://doi.org/10.1080/09537287.2017.1407971
Shi, Q., Zuo, J., & Zillante, G. (2012). Exploring the management of sustainable construction at the programme level: a Chinese case study. Construction Management and Economics, 30(6), 425–440. https://doi.org/10.1080/01446193.2012.683200
Song, W. Y., Ming, X. G., & Wu, Z. Y. (2013). An integrated rough number-based approach to design concept evaluation under subjective environments. Journal of Engineering Design, 24(5), 320–341. https://doi.org/10.1080/09544828.2012.732994
Stević, Ž., Pamučar, D., Vasiljević, M., Stojić, G., & Korica, S. (2017). Novel integrated multi-criteria model for supplier selection: case study construction company. Symmetry, 9(11), 279. https://doi.org/10.3390/sym9110279
Torra, V. (1996). Negation functions based semantics for ordered linguistic labels. International Journal of Intelligent Systems, 11(11), 975–988. https://doi.org/10.1002/(SICI)1098111X(199611)11:11<975::AID-INT5>3.0.CO;2-W
Wang, T. K., Zhang, Q., Chong, H. Y., & Wang, X. (2017). Integrated supplier selection framework in a resilient construction supply chain: an approach via analytic hierarchy process (AHP) and grey relational analysis (GRA). Sustainability, 9(2), 289. https://doi.org/10.3390/su9020289
Wen, Z., Liao, H. C., Zavadskas, E. K., & Al-BaIrakati A. (2019). Selection third-party logistics service providers in supply chain finance by a hesitant fuzzy linguistic combined compromise solution method. Economic Research-Ekonomska Istrazivanja, 32(1), 4033–4058. https://doi.org/10.1080/1331677X.2019.1678502
Wu, X. L., & Liao, H. C. (2018). An approach to quality function deployment based on probabilistic linguistic term sets and ORESTE method for multi-expert multi-criteria decision making. Information Fusion, 43, 13–26. https://doi.org/10.1016/j.inffus.2017.11.008
Wu, X. L., & Liao, H. C. (2019). A consensus-based probabilistic linguistic gained and lost dominance score method. European Journal of Operational Research, 272(3), 1017–1027. https://doi.org/10.1016/j.ejor.2018.07.044
Xu, Z. S. (2005). Deviation measures of linguistic preference relations in group decision making. Omega, 33(3), 249–254. https://doi.org/10.1016/j.omega.2004.04.008
Yazdani, M., Wen, Z., Liao, H. C., Banaitis, A., & Turskis, Z. (2019a). A grey combined compromise solution (CoCoSo-G) method for supplier selection in construction management. Journal of Civil Engineering and Management, 25(8), 858–874. https://doi.org/10.3846/jcem.2019.11309
Yazdani, M., Zarate, P., Zavadskas, E. K., & Turskis, Z. (2019b). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501–2519. https://doi.org/10.1108/MD-05-2017-0458
Yin, S., Li, B. Z., Dong, H. M., & Xing, Z. Y. (2017). A new dynamic multicriteria decision-making approach for green supplier selection in construction projects under time sequence. Mathematical Problems in Engineering, 2017, 1–13. https://doi.org/10.1155/2017/7954784
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning–I. Information Sciences, 8(3), 199–249. https://doi.org/10.1016/0020-0255(75)90036-5
Zhai, L. Y., Khoo, L. P., & Zhong, Z. W. (2008). A rough set enhanced fuzzy approach to quality function deployment. The International Journal of Advanced Manufacturing Technology, 37(5–6), 613–624. https://doi.org/10.1007/s00170-007-0989-9
Zhang, X., Shen, L., & Wu, Y. (2011). Green strategy for gaining competitive advantage in housing development: a China study. Journal of Cleaner Production, 19(2–3), 157–167. https://doi.org/10.1016/j.jclepro.2010.08.005
Zhang, Y. X., Xu, Z. S., & Liao, H. C. (2017). A consensus process for group decision making with probabilistic linguistic preference relations. Information Sciences, 414, 260–275. https://doi.org/10.1016/j.ins.2017.06.006
Zhu, G. N., Hu, J., Qi, J., Gu, C. C., & Peng, Y. H. (2015). An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics, 29(3), 408–418. https://doi.org/10.1016/j.aei.2015.01.010
Eshtehardian, E., Ghodousi, P., & Bejanpour, A. (2013). Using ANP and AHP for the supplier selection in the construction and civil engineering companies: case study of Iranian company. KSCE Journal of Civil Engineering, 17(2), 262–270. https://doi.org/10.1007/s12205-013-1141-z
Gou, X. J., Liao, H. C., Xu, Z. S., & Herrera, F. (2017). Double hierarchy hesitant fuzzy linguistic term set and MULTIMOORA method: a case of study to evaluate the implementation status of haze controlling measures. Information Fusion, 38, 22–34. https://doi.org/10.1016/j.inffus.2017.02.008
Greco, S., Matarazzo, B., & Slowinski, R. (2001). Rough sets theory for multicriteria decision analysis. European Journal of Operational Research, 129(1), 1–47. https://doi.org/10.1016/S0377-2217(00)00167-3
Herrera, F., Herrera-Viedma, E., & Verdegay, J. L. (1995). A sequential selection process in group decision making with a linguistic assessment approach. Information Sciences, 85(4), 223–239. https://doi.org/10.1016/0020-0255(95)00025-K
Lam, K. C., Tao, R., & Lam, M. C. K. (2010). A material supplier selection model for property developers using fuzzy principal component analysis. Automation in Construction, 19(5), 608–618. https://doi.org/10.1016/j.autcon.2010.02.007
Li, H., Li, D., Zhai, Y., Wang, S., & Zhang, J. (2016). A novel attribute reduction approach for multi-label data based on rough set theory. Information Sciences, 367, 827–847. https://doi.org/10.1016/j.ins.2016.07.008
Liao, H. C., & Wu, X. L. (2020). DNMA: a double normalizationbased multiple aggregation method for multi-expert multicriteria decision making. Omega, 94, 102058.
https://doi.org/10.1016/j.omega.2019.04.001
Liao, H. C., Jiang, L. S., Lev, B., & Fujita, H. (2019a). Novel operations of PLTSs based on the disparity degrees of linguistic terms and their use in designing the probabilistic linguistic ELECTRE III method. Applied Soft Computing, 80, 450–464. https://doi.org/10.1016/j.asoc.2019.04.018
Liao, H. C., Mi, X. M., & Xu, Z. S. (2020). A survey of decisionmaking methods with probabilistic linguistic information: bibliometrics, preliminaries, methodologies, applications and future directions. Fuzzy Optimization and Decision Making, 19(1), 81–134. https://doi.org/10.1007/s10700-019-09309-5
Liao, H. C., Mi, X. M., Yu, Q., & Luo, L. (2019b). Hospital performance evaluation by a hesitant fuzzy linguistic best worst method with inconsistency repairing. Journal of Cleaner Production, 232, 657–671. https://doi.org/10.1016/j.jclepro.2019.05.308
Liao, H. C., Wen, Z., & Liu, L. L. (2019c). Integrating BWM and ARAS under hesitant linguistic environment for digital supply chain finance supplier selection. Technological and Economic Development of Economy, 25(6), 1188–1212. https://doi.org/10.3846/tede.2019.10716
Liao, H. C., Xu, Z. S., & Zeng, X. J. (2014). Hesitant fuzzy linguistic VIKOR method and its application in qualitative multiple criteria decision making. IEEE Transactions on Fuzzy Systems, 23(5), 1343–1355. https://doi.org/10.1109/TFUZZ.2014.2360556
Liao, H. C., Xu, Z. S., Herrera-Viedma, E., & Herrera, F. (2018). Hesitant fuzzy linguistic term set and its application in decision making: a state-of-the art survey. International Journal of Fuzzy Systems, 20(7), 2084–2110. https://doi.org/10.1007/s40815-017-0432-9
Liao, H. C., Xu, Z. S., Zeng, X. J., & Merigó, J. M. (2015). Qualitative decision making with correlation coefficients of hesitant fuzzy linguistic term sets. Knowledge-Based Systems, 76, 127–138. https://doi.org/10.1016/j.knosys.2014.12.009
Luo, Z., He, J., Pan, H., & Yang, Y. (2016). Research on the selection strategy of green building parts supplier based on the catastrophe theory and Kent index method. Advances in Materials Science and Engineering, 2016, 1–12. https://doi.org/10.1155/2016/4673526
Matić, B., Jovanović, S., Das, D. K., Zavadskas, E. K., Stević, Ž., Sremac, S., & Marinković, M. (2019). A new hybrid MCDM model: Sustainable supplier selection in a construction company. Symmetry, 11(3), 353. https://doi.org/10.3390/sym11030353
Mi, X. M., Liao, H. C., Wu, X. L., & Xu, Z. S. (2020). Probabilistic linguistic information fusion: a survey on aggregation operators in terms of principles, definitions, classifications, applications and challenges. International Journal of Intelligent Systems, 35(3), 529–556. https://doi.org/10.1002/int.22216
Mi, X. M., Tang, M., Liao, H. C., Shen, W. J., & Lev, B. (2019). The state-of-the-art survey on integrations and applications of the best worst method in decision making: why, what, what for and what’s next? Omega, 87, 205–225. https://doi.org/10.1016/j.omega.2019.01.009
Ministry of Housing and Urban-Rural Development of the People’s Republic of China. (1999). Several opinions on promoting the modernization of housing industry and improving the quality of housing. http://www.mohurd.gov.cn/wjfb/200611/t20061101_155382.html
Ministry of Housing and Urban-Rural Development of the People’s Republic of China. (2008). Notice on further strengthening the management of residential fit-out and decoration. Ministry of Housing and Urban-Rural Development of the People’s Republic of China. http://www.gov.cn/zwgk/200808/01/content_1061518.htm
Ministry of Housing and Urban-Rural Development of the People’s Republic of China. (2013). Green building action plan. http://www.gov.cn/zwgk/2013-01/06/content_2305793.htm
Onar, S. Ç., Büyüközkan, G., Öztayşi, B., & Kahraman, C. (2016). A new hesitant fuzzy QFD approach: an application to computer workstation selection. Applied Soft Computing, 46, 1–16. https://doi.org/10.1016/j.asoc.2016.04.023
Pamučar, D., Mihajlović, M., Obradović, R., & Atanasković, P. (2017). Novel approach to group multi-criteria decision making based on interval rough numbers: hybrid DEMATELANP-MAIRCA model. Expert Systems with Applications, 88, 58–80. https://doi.org/10.1016/j.eswa.2017.06.037
Pamučar, D., Petrović, I., & Ćirović, G. (2018). Modification of the Best–Worst and MABAC methods: a novel approach based on interval-valued fuzzy-rough numbers. Expert Systems with Applications, 91, 89–106. https://doi.org/10.1016/j.eswa.2017.08.042
Pang, Q., Wang, H., & Xu, Z. (2016). Probabilistic linguistic term sets in multi-attribute group decision making. Information Sciences, 369, 128–143. https://doi.org/10.1016/j.ins.2016.06.021
Rezaei, J. (2015). Best-worst multi-criteria decision-making method. Omega, 53, 49–57. https://doi.org/10.1016/j.omega.2014.11.009
Rezaei, J. (2016). Best-worst multi-criteria decision-making method: some properties and a linear model. Omega, 64, 126–130. https://doi.org/10.1016/j.omega.2015.12.001
Rodriguez, R. M., Martinez, L., & Herrera, F. (2011). Hesitant fuzzy linguistic term sets for decision making. IEEE Transactions on Fuzzy Systems, 20(1), 109–119. https://doi.org/10.1109/TFUZZ.2011.2170076
Safa, M., Shahi, A., Haas, C. T., & Hipel, K. W. (2014). Supplier selection process in an integrated construction materials management model. Automation in Construction, 48, 64–73. https://doi.org/10.1016/j.autcon.2014.08.008
Seth, D., Nemani, V. K., Pokharel, S., & Al Sayed, A. Y. (2018). Impact of competitive conditions on supplier evaluation: a construction supply chain case study. Production Planning & Control, 29(3), 217–235. https://doi.org/10.1080/09537287.2017.1407971
Shi, Q., Zuo, J., & Zillante, G. (2012). Exploring the management of sustainable construction at the programme level: a Chinese case study. Construction Management and Economics, 30(6), 425–440. https://doi.org/10.1080/01446193.2012.683200
Song, W. Y., Ming, X. G., & Wu, Z. Y. (2013). An integrated rough number-based approach to design concept evaluation under subjective environments. Journal of Engineering Design, 24(5), 320–341. https://doi.org/10.1080/09544828.2012.732994
Stević, Ž., Pamučar, D., Vasiljević, M., Stojić, G., & Korica, S. (2017). Novel integrated multi-criteria model for supplier selection: case study construction company. Symmetry, 9(11), 279. https://doi.org/10.3390/sym9110279
Torra, V. (1996). Negation functions based semantics for ordered linguistic labels. International Journal of Intelligent Systems, 11(11), 975–988. https://doi.org/10.1002/(SICI)1098111X(199611)11:11<975::AID-INT5>3.0.CO;2-W
Wang, T. K., Zhang, Q., Chong, H. Y., & Wang, X. (2017). Integrated supplier selection framework in a resilient construction supply chain: an approach via analytic hierarchy process (AHP) and grey relational analysis (GRA). Sustainability, 9(2), 289. https://doi.org/10.3390/su9020289
Wen, Z., Liao, H. C., Zavadskas, E. K., & Al-BaIrakati A. (2019). Selection third-party logistics service providers in supply chain finance by a hesitant fuzzy linguistic combined compromise solution method. Economic Research-Ekonomska Istrazivanja, 32(1), 4033–4058. https://doi.org/10.1080/1331677X.2019.1678502
Wu, X. L., & Liao, H. C. (2018). An approach to quality function deployment based on probabilistic linguistic term sets and ORESTE method for multi-expert multi-criteria decision making. Information Fusion, 43, 13–26. https://doi.org/10.1016/j.inffus.2017.11.008
Wu, X. L., & Liao, H. C. (2019). A consensus-based probabilistic linguistic gained and lost dominance score method. European Journal of Operational Research, 272(3), 1017–1027. https://doi.org/10.1016/j.ejor.2018.07.044
Xu, Z. S. (2005). Deviation measures of linguistic preference relations in group decision making. Omega, 33(3), 249–254. https://doi.org/10.1016/j.omega.2004.04.008
Yazdani, M., Wen, Z., Liao, H. C., Banaitis, A., & Turskis, Z. (2019a). A grey combined compromise solution (CoCoSo-G) method for supplier selection in construction management. Journal of Civil Engineering and Management, 25(8), 858–874. https://doi.org/10.3846/jcem.2019.11309
Yazdani, M., Zarate, P., Zavadskas, E. K., & Turskis, Z. (2019b). A combined compromise solution (CoCoSo) method for multi-criteria decision-making problems. Management Decision, 57(9), 2501–2519. https://doi.org/10.1108/MD-05-2017-0458
Yin, S., Li, B. Z., Dong, H. M., & Xing, Z. Y. (2017). A new dynamic multicriteria decision-making approach for green supplier selection in construction projects under time sequence. Mathematical Problems in Engineering, 2017, 1–13. https://doi.org/10.1155/2017/7954784
Zadeh, L. A. (1975). The concept of a linguistic variable and its application to approximate reasoning–I. Information Sciences, 8(3), 199–249. https://doi.org/10.1016/0020-0255(75)90036-5
Zhai, L. Y., Khoo, L. P., & Zhong, Z. W. (2008). A rough set enhanced fuzzy approach to quality function deployment. The International Journal of Advanced Manufacturing Technology, 37(5–6), 613–624. https://doi.org/10.1007/s00170-007-0989-9
Zhang, X., Shen, L., & Wu, Y. (2011). Green strategy for gaining competitive advantage in housing development: a China study. Journal of Cleaner Production, 19(2–3), 157–167. https://doi.org/10.1016/j.jclepro.2010.08.005
Zhang, Y. X., Xu, Z. S., & Liao, H. C. (2017). A consensus process for group decision making with probabilistic linguistic preference relations. Information Sciences, 414, 260–275. https://doi.org/10.1016/j.ins.2017.06.006
Zhu, G. N., Hu, J., Qi, J., Gu, C. C., & Peng, Y. H. (2015). An integrated AHP and VIKOR for design concept evaluation based on rough number. Advanced Engineering Informatics, 29(3), 408–418. https://doi.org/10.1016/j.aei.2015.01.010