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These models first train themselves with price data and property characteristics, then they are tested by measuring their ability to predict prices. Most of them compare the effectiveness of traditional econometric models against the use of machine learning algorithms. Although the latter seem to offer better performance, there is not yet a complete survey of the literature to confirm the hypothesis.</jats:p></jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Design/methodology/approach</jats:title><jats:p>All tests comparing regression analysis and AVMs machine learning on the same data set have been identified. The scores obtained in terms of accuracy were then compared with each other.</jats:p></jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Findings</jats:title><jats:p>Machine learning models are more accurate than traditional regression analysis in their ability to predict value. Nevertheless, many authors point out as their limit their black box nature and their poor inferential abilities.</jats:p></jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Practical implications</jats:title><jats:p>AVMs machine learning offers a huge advantage for all real estate operators who know and can use them. Their use in public policy or litigation can be critical.</jats:p></jats:sec><jats:sec><jats:title content-type=\"abstract-subheading\">Originality/value</jats:title><jats:p>According to the author, this is the first systematic review that collects all the articles produced on the subject done comparing the results obtained.</jats:p></jats:sec>",56  "DOI": "10.1108/jpif-12-2019-0157",57  "type": "journal-article",58  "created": {59   "date-parts": [60    [61     2020,62     3,63     2764    ]65   ],66   "date-time": "2020-03-27T06:48:08Z",67   "timestamp": 158529168800068  },69  "page": "213-225",70  "source": "Crossref",71  "is-referenced-by-count": 72,72  "title": [73   "Who performs better? 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