Big Data Value Engineering for Business Model Innovation

نویسندگان

  • Hong-Mei Chen
  • Rick Kazman
  • Juan Garbajosa
  • Eloy González
چکیده

Big 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 (EcoARCHitecture) 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.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Computational Models for Business and Engineering Domains

Information is the value that is now of critical importance in building competitive advantage. However, the amount and variety of data becomes a challenge for business and IT. Both possess a large amount of information, its accelerating growth and expectations of more effective management of these data still give birth to new technical problems and system. When BI proved to be insufficient to p...

متن کامل

From Smart Meters to Smart Products: Reviewing Big Data driven Product Innovation in the European Electricity Retail Market

This paper tries to provide a perspective on energy informatics that goes beyond solely technical research. Combining the viewpoints of energy informatics and information systems in a review of top-ranked literature, we aim to start the discussion how to bridge the gap between a technology-driven focus on big data possibilities (such as smart grid, smart metering, etc.) and a business model-dri...

متن کامل

Big data integration with business processes: a literature review

Purpose – The purpose of this paper is to improve the understanding of the integration of business process management (BPM), business process re-engineering (BPR) and business process innovation (BPI) with big data. It focusses on synthesizing research published in the period 2006-2016 to establish both what the authors know and do not know about this topic, identifying areas for future researc...

متن کامل

Open innovation, networking, and business model dynamics: the two sides

A business model describes the design of the value creation and capture mechanisms needed to yield profit. We contend that for a business model to be viable in turbulent and hypercompetitive environments, its dynamics are important and must leverage, out of all key business model modules proposed in different studies, on a combined value and network perspective. These different elements present...

متن کامل

Investigating the Effect of Integrative Capability and Flexible Culture on Firm Performance: Mediating Role of Business Model Innovation and Moderating Role of Firm’s Strategy

It is essential to evaluate the firms’ performance as a strategic process to comprehend the sustainability of each company. Therefore, firms are persistently looking to enhance their performance, in order to succeed in a dynamic and competitive environment. On the other side, through this condition achieving superior performance requires improvement and innovation in the business model to creat...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2017