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Descripción
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| Big data value engineering for business model innovation requires a drastically different approach as compared with method s for engineering value under existing business model s . Tak ing a Design Science approach, we conducted an exploratory study to formulate the requirements for a method to aid in engineering value via innovation . We then developed a method, called Eco - ARCH (Eco - ARCHitecture) for value discovery . This method is tigh tly integrated with the BDD (Big Data Design) method for value realization , to form a big data value engineering methodology for addressing these requirements. The Eco - ARCH approach is most suitable for the big data context where system boundaries are flu id, requirements are ill - defined, many stakeholders are unknown , desig n goals are not provided, no central architecture pre - exists, system behavior is non - deterministic and continuously evolving, and co - creation with consumers and prosumers is essential to achieving innovation goals. The method was empirically validated in collaboration with an IT service company in the Electric Power industry. | |
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Internacional
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Si |
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Nombre congreso
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50th Hawaii International Conference on System Sciences, {HICSS} 2017 |
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Tipo de participación
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960 |
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Lugar del congreso
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Hilton Waikoloa Village, Hawaii, USA |
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Revisores
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Si |
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ISBN o ISSN
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978-0-9981331-0-2 |
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DOI
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URI: http://hdl.handle.net/10125/41877 |
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Fecha inicio congreso
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04/01/2018 |
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Fecha fin congreso
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07/01/2018 |
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Desde la página
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5921 |
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Hasta la página
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5930 |
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Título de las actas
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50th Hawaii International Conference on System Sciences, {HICSS} 2017, Hilton Waikoloa Village, Hawaii, USA, January 4-7, 2017 |