caa a22 4500 606158898 CHVBK 20210128100622.0 cr unu---uuuuu 210128e20150101xx s 000 0 eng 10.1007/s00521-014-1719-5 doi (NATIONALLICENCE)springer-10.1007/s00521-014-1719-5 Location selection using fuzzy-connective-based aggregation networks: a case study of the food and beverage chain industry in Taiwan [Elektronische Daten] [Fang-Fang Wang, Li-Fei Chen, Chao-Ton Su] Location selection is a significant part of strategic management activities. The plurality and interactions of the evaluation criteria involved in the problem complicates the decision-making process. This study successfully proposes a set of systematic procedure for location selection using fuzzy-connective-based aggregation networks. The fuzzy-connective-based aggregation network can aggregate the relative status or achievement among locations in various location-related variables through a hierarchical decision-making structure. Finally, an overall evaluation of location is produced from various aspects. The trained model approximates the relationship between turnover and individual location-related factors, which can be used to predict the potential performance of candidate sites and to answer "what if” questions. The transparency and interpretation ability also makes the proposed method desirable. The weights and parameters in the evaluation model help identify the major factors influencing the turnover and the compensatory relationship among location-related factors. The effectiveness and applicability are confirmed through a case study of the food and beverage chain industry in Taiwan. The Natural Computing Applications Forum, 2014 Locations selection nationallicence Fuzzy-connective-based aggregation network nationallicence Multi-criteria decision making nationallicence Wang Fang-Fang Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan aut Chen Li-Fei Department of Business Administration, Fu Jen Catholic University, New Taipei, Taiwan aut Su Chao-Ton Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan aut Neural Computing and Applications Springer London 26/1(2015-01-01), 161-170 0941-0643 26:1<161 2015 26 521 https://doi.org/10.1007/s00521-014-1719-5 text/html Onlinezugriff via DOI BK010053 XK010053 XK010000 Metadata rights reserved Springer special CC-BY-NC licence nationallicence 1 research-article jats NATIONALLICENCE NATIONALLICENCE NL-springer NATIONALLICENCE 856 40 https://doi.org/10.1007/s00521-014-1719-5 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Wang Fang-Fang Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan aut NATIONALLICENCE 700 1- Chen Li-Fei Department of Business Administration, Fu Jen Catholic University, New Taipei, Taiwan aut NATIONALLICENCE 700 1- Su Chao-Ton Department of Industrial Engineering and Engineering Management, National Tsing Hua University, Hsinchu, Taiwan aut NATIONALLICENCE 773 0- Neural Computing and Applications Springer London 26/1(2015-01-01), 161-170 0941-0643 26:1<161 2015 26 521