Chen, Hong-MeiKazman, RickGarbajosa, JuanGonzalez, Eloy2016-12-292016-12-292017-01-04978-0-9981331-0-2http://hdl.handle.net/10125/41877Big data value engineering for business model innovation requires a drastically different approach as compared with methods for engineering value under existing business models. Taking 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 tightly 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 fluid, requirements are ill-defined, many stakeholders are unknown, design 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.10 pagesengAttribution-NonCommercial-NoDerivatives 4.0 Internationalarchitecture landscapeBig Dataeco-architecturevalue engineering methodologybig data value discoveryConference Paper10.24251/HICSS.2017.713