Analytics Ecosystem Transformation: A Force for Business Model Innovation

Chen, Ying; Kreulen, Jeffrey; Campbell, Murray; Abrams, Carl

doi:10.1109/srii.2011.12

Cited by 33 publications

(23 citation statements)

References 4 publications

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“…The consultant role was seen as an additional source of revenue for the open data companies through consulting the raw data providers about the options and possibilities. Moreover, Chen et al [12] identify two new roles related to data analytics; Data-as-a-Service (DaaS) providers collect, generate, and aggregate the content (i.e., data), and Analytics-as-a-Service (AaaS) providers deliver analytics services to analytics consumers. In addition, data value chains can include other non-profit roles, which support the finding, publishing and marketing of open VOLUME 2, 2014 data sources, promoting the use of open data and networkingrelated data.…”

Section: B Value Chains Of Datamentioning

confidence: 99%

“…In addition to being used in business, data has been found to be valuable in information-and knowledge-based management and decision making inside companies, helping in the understanding of the line of business and the market situation at hand [2]. The emerging analytics business models include the proprietary model, the shared data model, the shared analytics model, the shared value model, the co-development model and the new business development model [12]. The last model describes how DaaS and AaaS provide opportunities for application developers to create new business.…”

Section: Business Models Of Datamentioning

confidence: 99%

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Requirements of an Open Data Based Business Ecosystem

2014

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Emerging opportunities for open data based business have been recognized around the world. Open data can provide new business opportunities for actors that provide data, for actors that consume data, and for actors that develop innovative services and applications around the data. Open data based business requires business models and a collaborative environment-called an ecosystem-to support businesses based on open data, services, and applications. This paper outlines the open data ecosystem (ODE) from the business viewpoint and then defines the requirements of such an ecosystem. The outline and requirements are based on the state-of-the-art knowledge explored from the literature and the state of the practice on databased business in the industry collected through interviews. The interviews revealed several motives and advantages of the ODE. However, there are also obstacles that should be carefully considered and solved. This paper defines the actors of the ODE and their roles in the ecosystem as well as the business model elements and services that are needed in open data based business. According to the interviews, the interest in open data and open data ecosystems is high at this moment. However, further research work is required to establish and validate the ODE in the near future. INDEX TERMSBusiness ecosystem, open data.

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Section: B Value Chains Of Datamentioning

confidence: 99%

Section: Business Models Of Datamentioning

confidence: 99%

Requirements of an Open Data Based Business Ecosystem

2014

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“…Business ecosystems (Iansiti & Levien, 2004;Moore, 1993) and datarelated business models are emerging, providing services like data (data-asa-service), analytics (analysis-as-a-service) or Internet of Things-related offerings (Chen et al, 2011;Leminen et al, 2012). Many new startup firms follow the trailblazers like Google or Amazon and formulate their entire business models on top of or around the data.…”

Section: Introductionmentioning

confidence: 99%

Innovation capabilities as a mediator between big data and business model

Ylijoki

Sirkiä

Porras

et al. 2018

Journal of Enterprise Transformation

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The digital transformation is forcing organizations to change towards more data-driven business models. In this paper, we propose a conceptual framework that explains the role of innovation capabilities as a mediator between big data and business model. Using the design science research method approach, we built the framework based on the existing literature. We then applied the framework to the real-world context with three firms and refined it based on the feedback. This study contributes to big data research by pointing out the role of human and data-driven innovation capabilities in the big data value creation process. The developed framework is practitioner oriented, offering a systematic approach towards the development of big data capabilities.

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“…In this paper, we have identified some of the issues in content security and authentication in Mobile eLearning for providing persistent document security and authentication. The research work in [17] provides four key trends in analytics that include big data, big analytics, big infrastructure and big insights. The authors elaborated on aggregated data services (public and private) in terms of DaaS (Data as a Services) and analytics services called (AaaS) Analytics as a Service.…”

Section: Related Workmentioning

confidence: 99%

A framework for mobile elearning (mLearning) with analytical decision model

Dewan

Chowdhury

2014

15th IEEE/ACIS International Conference on Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed C

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Mobile eLearning (mLearning) can create a revolution in eLearning with the popularity of smart mobile devices and Application. However, contents are the king to make this revolution happen. Moreover, for an effective mLearning system, analytical aspects such as, quality of contents, quality of results, performance of learners, needs to be addressed. This paper presents a framework for personal mLearning. In this paper, we have used graph-based model called bipartite graph for content authentication and identification of the quality of results. Furthermore, we have used statistical estimation process for trustworthiness of weights in the bipartite graph using confidence interval and hypothesis test as analytical decision model tool.

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Analytics Ecosystem Transformation: A Force for Business Model Innovation

Cited by 33 publications

References 4 publications

Requirements of an Open Data Based Business Ecosystem

Requirements of an Open Data Based Business Ecosystem

Innovation capabilities as a mediator between big data and business model

A framework for mobile elearning (mLearning) with analytical decision model

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