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Empirical studies using real-world data show that the new measure can lead to a more discriminating and flexible spatio-temporal data analysis framework. In contrast with its predecessor, this measure also allows the discovery of leading (and potentially causal) event types whose occurrences precede those of other event types. Findings from analyses employing this measure may bear important managerial implications.<\/p>","DOI":"10.4018\/jdm.2013040102","type":"journal-article","created":{"date-parts":[[2013,9,20]],"date-time":"2013-09-20T13:20:36Z","timestamp":1379683236000},"page":"13-34","source":"Crossref","is-referenced-by-count":9,"title":["Cross-Correlation Measure for Mining Spatio-Temporal Patterns"],"prefix":"10.4018","volume":"24","author":[{"given":"James","family":"Ma","sequence":"first","affiliation":[{"name":"Hasan School of Business, Colorado State University, Pueblo, CO, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel","family":"Zeng","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Management and Control for Complex Systems, Institute of Automation, Chinese Academy of Sciences, Beijing, China & Department of MIS, Eller College of Management, University of Arizona, Tucson, AZ, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Huimin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Sheldon B. 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