{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,5,14]],"date-time":"2025-05-14T02:29:46Z","timestamp":1747189786920,"version":"3.40.5"},"reference-count":70,"publisher":"World Scientific Pub Co Pte Ltd","issue":"05","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Int. J. Info. Tech. Dec. Mak."],"published-print":{"date-parts":[[2023,9]]},"abstract":"<jats:p> The ubiquity of data, and in particular in MCDM situations, makes it challenging for the Decision Makers (DM) to figure out a way of making proper use of data. This paper presents a three-stage decision framework for DMs to consider the performance range of alternatives holistically. The framework consists of (i) data preparation, (ii) two distance-based Gray Multi-Criteria Decision-Making (MCDM-G) methods using gray interval data to rank the alternatives and (iii) a decision analysis template. For comparison, gray Evaluation based on Distance from Average Solution (EDAS) and gray Multi-Attributive Border Approximation area Comparison (MABAC) methods that rely on arithmetic and geometric mean respectively are used to generate the ranks. The mean-based ranking methods produce stable and efficient ranks in comparison to extremum-based comparison methods, due to their innate nature. The correlation of ranks is analyzed to conclude that the stability of ranks is better when gray interval data is considered. As an example, this paper considers performance range of the 10 criteria used in computing Ease of Doing Business (EDB) index as the gray interval. The sample performance of the G20 countries during the period 2004 to 2020 was used to illustrate the calculations. Further, a general analytic template based on the rank deviation on account of differences in upper and lower bounds of performance helped in classifying the economies as stable leaders, predictable middle and volatile followers. The paper contributes a suitable MCDM and analysis approach when the DM is presented with a gray interval as the alternatives\u2019 performance. <\/jats:p>","DOI":"10.1142\/s021962202250078x","type":"journal-article","created":{"date-parts":[[2022,11,14]],"date-time":"2022-11-14T08:23:05Z","timestamp":1668414185000},"page":"1651-1691","source":"Crossref","is-referenced-by-count":2,"title":["Ease of Doing Business: Performance Comparison of G20 Countries Using Gray MCDM"],"prefix":"10.1142","volume":"22","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7074-5265","authenticated-orcid":false,"given":"Kalyana C.","family":"Chejarla","sequence":"first","affiliation":[{"name":"Operations Management, Institute of Management Technology, Hyderabad, India"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Omkarprasad S.","family":"Vaidya","sequence":"additional","affiliation":[{"name":"Operations Management, Indian Institute of Management, Lucknow, India"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"219","published-online":{"date-parts":[[2022,11,11]]},"reference":[{"issue":"3","key":"S021962202250078XBIB001","first-page":"274","volume":"29","author":"Chejarla K. 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