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An important example of this design problem occurs in fire protection IoT, where individual edge computers attached to sensors might be empowered to make decisions (have decision rights) about how to manage the fire. Alternatively, decision rights could be held exclusively by a central server isolated from the fire, because the designer is concerned damage to edge computers could cause them to act unreliably. This research models this allocation of decision rights to identify the relative influence of various decision factors. We first model the allocation of decision rights under the following assumptions: (1) The central server cannot make an error the edge computer cannot make; (2) the central server cannot update the edge computer with its information in a timely manner; and (3) the central server cannot reverse an action initiated by the edge computer to explore the factors impacting decision rights conferral. We then relax each of these three assumptions. We show how relaxing each assumption radically changes the factors impacting decision rights conferral. We also show that allowing the central server to update information on the edge computer or reverse the edge computer's decision making can result in overall lower system performance. We then perform a series of numerical experiments to understand how changing various parameters affect the problem. We show for the general real-world scenario, the key factor influencing the decision is the ability of the edge computer to detect false alarms. We also show magnitude of loss and ratio of real to false incidents have a linear and logarithmic relationship to the reliability of the edge computer.<\/jats:p>","DOI":"10.1145\/3582081","type":"journal-article","created":{"date-parts":[[2023,2,17]],"date-time":"2023-02-17T11:56:59Z","timestamp":1676635019000},"page":"1-24","update-policy":"https:\/\/doi.org\/10.1145\/crossmark-policy","source":"Crossref","is-referenced-by-count":0,"title":["Situational Factor Determinants of the Allocation of Decision Rights to Edge Computers"],"prefix":"10.1145","volume":"14","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9384-1535","authenticated-orcid":false,"given":"Cecil Eng Huang","family":"Chua","sequence":"first","affiliation":[{"name":"Missouri S&amp;T - Business and Information Technology"}]},{"ORCID":"https:\/\/orcid.org\/0000-0003-3246-4769","authenticated-orcid":false,"given":"Fred","family":"Niederman","sequence":"additional","affiliation":[{"name":"Saint Louis University - Decision Sciences and ITM"}]}],"member":"320","published-online":{"date-parts":[[2023,6,23]]},"reference":[{"key":"e_1_3_1_1_2","doi-asserted-by":"publisher","DOI":"10.1109\/ICWS53863.2021.00104"},{"key":"e_1_3_1_2_2","article-title":"IoT technology is changing the future of fire safety","author":"Agrawal S.","year":"2021","unstructured":"S. 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