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Decision support framework for opening business data. / Buda, Anamaria; Ubacht, Jolien; Janssen, Marijn; Sips, Robert Jan.

Proceedings of the 16th European Conference on e-Government, ECEG 2016. Vol. 2016-January Academic Conferences, 2016. p. 29-37.

Research output: Chapter in Book/Report/Conference proceedingChapterScientific

Harvard

Buda, A, Ubacht, J, Janssen, M & Sips, RJ 2016, Decision support framework for opening business data. in Proceedings of the 16th European Conference on e-Government, ECEG 2016. vol. 2016-January, Academic Conferences, pp. 29-37, 16th European Conference on eGovernment, llubliana, Slovenia, 16/06/16.

APA

Buda, A., Ubacht, J., Janssen, M., & Sips, R. J. (2016). Decision support framework for opening business data. In Proceedings of the 16th European Conference on e-Government, ECEG 2016 (Vol. 2016-January, pp. 29-37). Academic Conferences.

Vancouver

Buda A, Ubacht J, Janssen M, Sips RJ. Decision support framework for opening business data. In Proceedings of the 16th European Conference on e-Government, ECEG 2016. Vol. 2016-January. Academic Conferences. 2016. p. 29-37

Author

Buda, Anamaria ; Ubacht, Jolien ; Janssen, Marijn ; Sips, Robert Jan. / Decision support framework for opening business data. Proceedings of the 16th European Conference on e-Government, ECEG 2016. Vol. 2016-January Academic Conferences, 2016. pp. 29-37

BibTeX

@inbook{afe1fe03c26a40bfb65af92a06fb01ac,
title = "Decision support framework for opening business data",
abstract = "The open data trend is considered to be a robust driver for innovation. The expectation is that open datasets will stimulate benefits across a variety of sectors (public, private, academia etc.), such as greater transparency, innovation and the rise of new business models (European Commission, 2011; Davies, 2010). Although they are one of the primary users of governmental open datasets, private sector companies themselves are not very active yet in opening the massive amount of data they produce (Bonina, 2013; Herzberg 2014). A variety of barriers hold back this potential, such as privacy issues, data security, proprietary interests and data protectionism (Verhulst 2014, Ponte 2015). Therefore our objective was to develop a decision support framework that offers an overview of the various steps required for such an action, taking the barriers and the benefits into account. We followed a design science approach in which we conducted a literature review on the concept of business open data, performed an in-depth analysis of seven empirical case studies of well-known examples such as Nike, Syngenta and IBM, and we conducted expert interviews. We thus developed a prototype of the decision support framework, based on the concept of open data ecosystems (Heimst{\"a}dt et al, 2014; Ponte, 2015). The framework was evaluated by high-level experts in the field. We not only identified the main business drivers for private sector companies to open up datasets, such as community building, promotion, business innovation, and new revenue streams. We also addressed the key challenges encountered by the private organizations, which are: characteristics of the data itself, the process for opening-up the data and obstacles in using business open data (ie. the risks of misinterpretation). Our framework addresses the drivers as well as the barriers for private organizations to decide which datasets are eligible to be opened up, and supports them to consider all aspects that need to be taken into account during the decision making process. We claim that opening up data provides an opportunity to create a new business open data ecosystem, in which the private company supplying open data acts as a keystone by providing data as resource to the other members of the ecosystem. First movers can reap all the benefits that come with being a dominator in their business open data ecosystem.",
keywords = "Barriers, Business open data, Decision support framework, Design science, Drivers, Open data ecosystem",
author = "Anamaria Buda and Jolien Ubacht and Marijn Janssen and Sips, {Robert Jan}",
year = "2016",
language = "English",
volume = "2016-January",
pages = "29--37",
booktitle = "Proceedings of the 16th European Conference on e-Government, ECEG 2016",
publisher = "Academic Conferences",

}

RIS

TY - CHAP

T1 - Decision support framework for opening business data

AU - Buda, Anamaria

AU - Ubacht, Jolien

AU - Janssen, Marijn

AU - Sips, Robert Jan

PY - 2016

Y1 - 2016

N2 - The open data trend is considered to be a robust driver for innovation. The expectation is that open datasets will stimulate benefits across a variety of sectors (public, private, academia etc.), such as greater transparency, innovation and the rise of new business models (European Commission, 2011; Davies, 2010). Although they are one of the primary users of governmental open datasets, private sector companies themselves are not very active yet in opening the massive amount of data they produce (Bonina, 2013; Herzberg 2014). A variety of barriers hold back this potential, such as privacy issues, data security, proprietary interests and data protectionism (Verhulst 2014, Ponte 2015). Therefore our objective was to develop a decision support framework that offers an overview of the various steps required for such an action, taking the barriers and the benefits into account. We followed a design science approach in which we conducted a literature review on the concept of business open data, performed an in-depth analysis of seven empirical case studies of well-known examples such as Nike, Syngenta and IBM, and we conducted expert interviews. We thus developed a prototype of the decision support framework, based on the concept of open data ecosystems (Heimstädt et al, 2014; Ponte, 2015). The framework was evaluated by high-level experts in the field. We not only identified the main business drivers for private sector companies to open up datasets, such as community building, promotion, business innovation, and new revenue streams. We also addressed the key challenges encountered by the private organizations, which are: characteristics of the data itself, the process for opening-up the data and obstacles in using business open data (ie. the risks of misinterpretation). Our framework addresses the drivers as well as the barriers for private organizations to decide which datasets are eligible to be opened up, and supports them to consider all aspects that need to be taken into account during the decision making process. We claim that opening up data provides an opportunity to create a new business open data ecosystem, in which the private company supplying open data acts as a keystone by providing data as resource to the other members of the ecosystem. First movers can reap all the benefits that come with being a dominator in their business open data ecosystem.

AB - The open data trend is considered to be a robust driver for innovation. The expectation is that open datasets will stimulate benefits across a variety of sectors (public, private, academia etc.), such as greater transparency, innovation and the rise of new business models (European Commission, 2011; Davies, 2010). Although they are one of the primary users of governmental open datasets, private sector companies themselves are not very active yet in opening the massive amount of data they produce (Bonina, 2013; Herzberg 2014). A variety of barriers hold back this potential, such as privacy issues, data security, proprietary interests and data protectionism (Verhulst 2014, Ponte 2015). Therefore our objective was to develop a decision support framework that offers an overview of the various steps required for such an action, taking the barriers and the benefits into account. We followed a design science approach in which we conducted a literature review on the concept of business open data, performed an in-depth analysis of seven empirical case studies of well-known examples such as Nike, Syngenta and IBM, and we conducted expert interviews. We thus developed a prototype of the decision support framework, based on the concept of open data ecosystems (Heimstädt et al, 2014; Ponte, 2015). The framework was evaluated by high-level experts in the field. We not only identified the main business drivers for private sector companies to open up datasets, such as community building, promotion, business innovation, and new revenue streams. We also addressed the key challenges encountered by the private organizations, which are: characteristics of the data itself, the process for opening-up the data and obstacles in using business open data (ie. the risks of misinterpretation). Our framework addresses the drivers as well as the barriers for private organizations to decide which datasets are eligible to be opened up, and supports them to consider all aspects that need to be taken into account during the decision making process. We claim that opening up data provides an opportunity to create a new business open data ecosystem, in which the private company supplying open data acts as a keystone by providing data as resource to the other members of the ecosystem. First movers can reap all the benefits that come with being a dominator in their business open data ecosystem.

KW - Barriers

KW - Business open data

KW - Decision support framework

KW - Design science

KW - Drivers

KW - Open data ecosystem

UR - http://www.scopus.com/inward/record.url?scp=84979642770&partnerID=8YFLogxK

M3 - Chapter

VL - 2016-January

SP - 29

EP - 37

BT - Proceedings of the 16th European Conference on e-Government, ECEG 2016

PB - Academic Conferences

ER -

ID: 6476852