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DSS are designed to support users in making more informed decisions in specialized tasks through more accurate predictions and recommendations. This mixed-methods user study contributes to the research on trust calibration by analyzing the potential effects of integrated reliability indication in DSS user interfaces for process management in first-time usage situations characterized by uncertainty. Ten experts specialized in digital tools for construction were asked to test and assess two versions of a DSS in a renovation project scenario. We found that while users stated that they need full access to all information to make their own decisions, reliability indication in DSS tends to make users more willing to make preliminary decisions, with users adapting their confidence and reliance to the indicated reliability. Reliability indication in DSS also increases subjective usefulness and system reliability. Based on these findings, it is recommended that for the design of reliability indication practitioners consider displaying a combination of reliability information at several granularity levels in DSS user interfaces, including visualizations, such as a traffic light system, and to also provide explanations for the reliability information. Further research directions towards achieving trustworthy decision support in complex environments are proposed.<\/jats:p>","DOI":"10.1007\/s41233-022-00053-0","type":"journal-article","created":{"date-parts":[[2022,9,5]],"date-time":"2022-09-05T12:10:45Z","timestamp":1662379845000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":7,"title":["Effects of reliability indicators on usage, acceptance and preference of predictive process management decision support systems"],"prefix":"10.1007","volume":"7","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-2502-5947","authenticated-orcid":false,"given":"Peter","family":"Fr\u00f6hlich","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Alexander G.","family":"Mirnig","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Damiano","family":"Falcioni","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Johann","family":"Schrammel","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Lisa","family":"Diamond","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Isabel","family":"Fischer","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manfred","family":"Tscheligi","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2022,9,5]]},"reference":[{"issue":"103","key":"53_CR1","first-page":"299","volume":"44","author":"SO Abioye","year":"2021","unstructured":"Abioye SO, Oyedele LO, Akanbi L et al (2021) Artificial intelligence in the construction industry: A review of present status, opportunities and future challenges. 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