{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,3]],"date-time":"2026-04-03T00:44:45Z","timestamp":1775177085258,"version":"3.50.1"},"reference-count":24,"publisher":"World Scientific Pub Co Pte Ltd","issue":"17","funder":[{"name":"Research on the test and measurement of asset price bubbles from the perspective of data generation process","award":["21BJY213"],"award-info":[{"award-number":["21BJY213"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["J CIRCUIT SYST COMP"],"published-print":{"date-parts":[[2022,11,30]]},"abstract":"<jats:p> Based on the analysis of the reasons, principles and classification of fuzzy set data calibration, we analyze that the fuzzy set data calibration membership is influenced by different data distribution, the crossover anchored points setting and transformation selection. Starting from the common problems existing in the current fuzzy-set qualitative comparative analysis (fsQCA) application research, this paper analyzes the possible reasons for ignoring the data calibration research, divides the relationship between the three dimensions of original data distribution, the crossover anchored points setting and calibration transformation and data calibration, and makes a visual analysis on their influence relationship through simulated data. Data distribution, crossover points anchored setting and transformation selection all have a significant impact on fsQCA calibration membership. The distribution of the original data will be a skew attribute consistent with the calibration membership. The cross combination of the high, medium and low setting of the crossover points and the selection of the calibration transformation will produce a significantly different calibration membership, and the crossover points anchored setting has a more obvious impact on the calibration membership than the selection of the calibration transformation. <\/jats:p>","DOI":"10.1142\/s0218126622502930","type":"journal-article","created":{"date-parts":[[2022,6,9]],"date-time":"2022-06-09T08:19:53Z","timestamp":1654762793000},"source":"Crossref","is-referenced-by-count":2,"title":["Simulation Analysis of Influencing Factors of fsQCA Calibration Membership"],"prefix":"10.1142","volume":"31","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8669-9710","authenticated-orcid":false,"given":"Haiwen","family":"Yang","sequence":"first","affiliation":[{"name":"Business School, Anyang Institute of Technology, Anyang, Henan 455000, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Haifeng","family":"Jiang","sequence":"additional","affiliation":[{"name":"Business School, Anhui University of Technology, Ma\u2019anshan, Anhui 243032, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Yingya","family":"Yang","sequence":"additional","affiliation":[{"name":"Business School, Anyang Institute of Technology, Anyang, Henan 455000, P.\u00a0R.\u00a0China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2022,7,29]]},"reference":[{"key":"S0218126622502930BIB001","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.101.2001126"},{"key":"S0218126622502930BIB002","doi-asserted-by":"publisher","DOI":"10.7208\/chicago\/9780226702797.001.0001"},{"key":"S0218126622502930BIB003","author":"Tan L.","year":"2021","journal-title":"IEEE Trans. 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