{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,12,24]],"date-time":"2025-12-24T12:43:12Z","timestamp":1766580192352},"reference-count":0,"publisher":"Walter de Gruyter GmbH","issue":"9","content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2016,9,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n               <jats:p>There is a broad consensus that the transformative power of the Internet of Things (IoT) will affect all kinds of\nindustries; or, to put it in a more optimistic light, that almost no domain is excluded from the opportunities to leverage\nthe IoT. But, what does this mean for the future of industrial processes? This article introduces the concept of\nhigh-resolution management (HRM). IoT enables the collection of high-resolution data for the physical world where, as in\nthe digital world, every aspect of business operations can be measured in real-time. This capability facilitates\nhigh-resolution management, such as short optimization cycles in industrial production, logistics and equipment\nefficiency, comparable to methods like A\/B-Testing or Search Engine Optimization, which are state of the art in digital\nbusiness. We take the following two perspectives on leveraging high-resolution management. First, through greater insights\ninto their industrial processes, companies that apply HRM in their operations are able to achieve higher efficiency,\nquality and flexibility. The example of vehicle fleet management illustrates this effect. Second, we build upon the\nSt. Gallen Business Model Navigator in order to look in greater detail on how the IoT affects industrial\nprocesses. Gassmann et\u202fal.<jats:fn symbol=\"1\" id=\"j_auto-2016-0054_fn_0001_w2aab2b8c10b1b7b1aab1c15b1b1Ab1\">\n                     <jats:p>Gassmann, O., Frankenberger, K., and Csik, M. (2014). The business model navigator:\n55 models that will revolutionise your business. Financial Times.<\/jats:p>\n                  <\/jats:fn>\nintroduce 55 generic business model\npatterns, of which our extended research identified 20 that could profit significantly from the\nIoT<jats:fn symbol=\"2\" id=\"j_auto-2016-0054_fn_0002_w2aab2b8c10b1b7b1aab1c15b1b3Ab1\">\n                     <jats:p>Fleisch, E., Weinberger, M., and Wortmann, F. (2014). Gesch\u00e4ftsmodelle im Internet der\nDinge. HMD Praxis der Wirtschaftsinformatik, 51(6), 812\u2013826; Gassmann, O., Frankenberger, K., and Csik, M. (2014). The\nbusiness model navigator: 55 models that will revolutionise your business. Financial Times.<\/jats:p>\n                  <\/jats:fn>. Analyzing these\n20 patterns allowed for the identification of six key components: <jats:italic>Remote Usage<\/jats:italic>\n                  <jats:italic>and Condition\nMonitoring<\/jats:italic>, <jats:italic>Object Self Service<\/jats:italic>, <jats:italic>Digital Add-on<\/jats:italic>, <jats:italic>Digital Lock-in<\/jats:italic>, <jats:italic>Product as a Point\nof Sales<\/jats:italic> and <jats:italic>Physical Freemium<\/jats:italic>. These building blocks help companies to supply HRM-supported offerings. Finally,\nthe example of remote monitoring of process parameters shows that these business model components can also be deployed to\ncreate offerings that\nenable others to apply HRM.<\/jats:p>","DOI":"10.1515\/auto-2016-0054","type":"journal-article","created":{"date-parts":[[2016,9,14]],"date-time":"2016-09-14T16:36:20Z","timestamp":1473870980000},"page":"699-706","source":"Crossref","is-referenced-by-count":33,"title":["IoT business models in an industrial context"],"prefix":"10.1515","volume":"64","author":[{"given":"Markus","family":"Weinberger","sequence":"first","affiliation":[{"name":"Bosch Software Innovation GmbH, Bosch IoT Lab, Dufourstrasse 40a, 9000 St. Gallen, Switzerland Switzerland"}]},{"given":"Dominik","family":"Bilgeri","sequence":"additional","affiliation":[{"name":"ETH Zurich, 8092 Zurich, Switzerland Switzerland"}]},{"given":"Elgar","family":"Fleisch","sequence":"additional","affiliation":[{"name":"University of St. Gallen, Dufourstrasse 40a, 9000 St. Gallen, Switzerland Switzerland"}]}],"member":"374","published-online":{"date-parts":[[2016,9,13]]},"container-title":["at - Automatisierungstechnik"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/www.degruyter.com\/view\/j\/auto.2016.64.issue-9\/auto-2016-0054\/auto-2016-0054.xml","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2016-0054\/xml","content-type":"application\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2016-0054\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2021,6,21]],"date-time":"2021-06-21T18:30:10Z","timestamp":1624300210000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.degruyter.com\/document\/doi\/10.1515\/auto-2016-0054\/html"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2016,9,13]]},"references-count":0,"journal-issue":{"issue":"9","published-online":{"date-parts":[[2016,9,13]]},"published-print":{"date-parts":[[2016,9,28]]}},"alternative-id":["10.1515\/auto-2016-0054"],"URL":"https:\/\/doi.org\/10.1515\/auto-2016-0054","relation":{},"ISSN":["0178-2312","2196-677X"],"issn-type":[{"value":"0178-2312","type":"print"},{"value":"2196-677X","type":"electronic"}],"subject":[],"published":{"date-parts":[[2016,9,13]]}}}