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To address this question, the present study has applied four prominent binary classifiers - logit regression, linear discriminant analysis, artificial neutral network and decision tree analysis to develop predictive models. Findings of the study shall help the marketers in accurately forecasting shoppers' buying behaviour. Various indices have been used to check the predictive accuracy of four techniques. The outcome of the study shows that the models developed using decision tree analysis and artificial neutral network provide better results in predicting consumers' continuous intention to buy through app. Based on the findings, the paper has also provided implications for the retailers.<\/jats:p>","DOI":"10.4018\/ijsds.2018070103","type":"journal-article","created":{"date-parts":[[2018,6,25]],"date-time":"2018-06-25T14:43:36Z","timestamp":1529937816000},"page":"69-83","source":"Crossref","is-referenced-by-count":1,"title":["Predicting Shoppers' Continuous Buying Intention Using Mobile Apps"],"prefix":"10.4018","volume":"9","author":[{"given":"Sanjeev","family":"Prashar","sequence":"first","affiliation":[{"name":"Indian Institute of Management (IIM) Raipur, Raipur, India"}]},{"given":"Priyanka","family":"Gupta","sequence":"additional","affiliation":[{"name":"Indian Institute of Management (IIM) Raipur, Raipur, India"}]},{"given":"Chandan","family":"Parsad","sequence":"additional","affiliation":[{"name":"Rajagiri Business School, Kochi, India"}]},{"given":"T. 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