1.
Juell-Skielse, Gustaf, et al.
(författare)
Improving E-Government through Benefit Analysis and Value Modeling
2009
Ingår i: 2009 IEEE 33RD INTERNATIONAL COMPUTER SOFTWARE AND APPLICATIONS CONFERENCE, VOL. 1. - New York : IEEE. - 9781424445257 - 9780769537269 ; , s. 332-339
Konferensbidrag (refereegranskat) abstract
Sweden is a precursor in e-government and development of municipal e-services. For example, the Swedish government has announced a national action plan for fast development of e-government using e-services and workflow systems for effective public administration. However, introducing e-government is a complex process including many different actors with different goals: public organizations with a complex combination of economic and non-economic goals, citizens and private organizations with different relations to the public organization, and IT vendors, offering different tools and techniques to develop and maintain e-services. In order to implement a right mix of e-services in the public sector, the benefits and costs of different e-services, and combinations of e-services, for all involved actors need to be investigated. In this paper, two established approaches for value analysis, Peng and Value modeling, are combined. Peng is a participative, bottom-up approach for identifying and estimating benefits and costs for IT-investments, while Value modeling is a top-down approach for analyzing economic viability of an entire net-work of actors. The aim of this paper is to demonstrate the application of the combined approach using a case study from the municipality of Jarfalla, a suburb of Stockholm. The results show that value analysis can be improved by combining these two models. The results also initiated an important discussion in the municipality of Järfalla on how to realize the potential values of a new e-service.
2.
Ayele, Workneh Yilma, 1978-
(författare)
A toolbox for idea generation and evaluation : Machine learning, data-driven, and contest-driven approaches to support idea generation
2022
Doktorsavhandling (övrigt vetenskapligt/konstnärligt) abstract
Ideas are sources of creativity and innovation, and there is an increasing demand for innovation. For example, the start-up ecosystem has grown in both number and global spread. As a result, established companies need to monitor more start-ups than before and therefore need to find new ways to identify, screen, and collaborate with start-ups.The significance and abundance of data are also increasing due to the growing digital data generated from social media, sensors, scholarly literature, patents, different forms of documents published online, databases, product manuals, etc. Various data sources can be used to generate ideas, yet, in addition to bias, the size of the available digital data is a major challenge when it comes to manual analysis.Hence, human-machine interaction is essential for generating valuable ideas where machine learning and data-driven techniques generate patterns from data and serve human sense-making. However, the use of machine learning and data-driven approaches to generate ideas is a relatively new area. Moreover, it is also possible to stimulate innovation using contest-driven idea generation and evaluation. However, the measurement of contest-driven idea generation processes needs to be supported to manage the process better. In addition, post-contest challenges hinder the development of viable ideas. A mixed-method research methodology is applied to address these challenges.The results and contributions of this thesis can be viewed as a toolbox of idea-generation techniques, including a list of data-driven and machine learning techniques with corresponding data sources and models to support idea generation. In addition, the results include two models, one method and one framework, to better support data-driven and contest-driven idea generation. The beneficiaries of these artefacts are practitioners in data and knowledge engineering, data mining project managers, and innovation agents. Innovation agents include incubators, contest organizers, consultants, innovation accelerators, and industries.Future projects could develop a technical platform to explore and exploit unstructured data using machine learning, visual analytics, network analysis, and bibliometric for supporting idea generation and evaluation activities. It is possible to adapt and integrate methods included in the proposed toolbox in developer platforms to serve as part of an embedded idea management system. Future research could also adapt the framework to barriers that constrain the development required to elicit post-contest digital service. In addition, since the proposed artefacts consist of process models augmented with AI techniques, human-centred AI is a promising area of research that can contribute to the artefacts' further development and promote creativity.
3.
Ayele, Workneh Y., et al.
(författare)
Unveiling Topics from Scientific Literature on the Subject of Self-driving Cars using Latent Dirichlet Allocation
2018
Ingår i: 2018 IEEE 9th Annual Information Technology, Electronics and Mobile Communication Conference (IEMCON). - : IEEE. - 9781538672679 - 9781538672662 ; , s. 1113-1119
Konferensbidrag (refereegranskat) abstract
Self-driving cars are becoming popular topics in academia. Consumers of self-driving cars and vehicles have different concerns, for example, safety and security, to name a few. Also, the public sector has interests in self-driving cars such as amending policies to enable the management of self-driving vehicles in cities, urban planning, traffic management and, etc. In this paper, more than 2700 corpus are extracted from literature from several subject areas to identify latent (hidden) topics of self-driving cars. Latent Dirichlet Allocation (LDA) is used for topic identification. The result of this study shows that topics identified are valid research areas such as urban planning, driver car (computer) interaction, self-driving control and system design, ethics in self-driving cars, safety and risk assessment, training dataset quality and machine learning in self-driving cars are among the topics identified. Furthermore, the network visualization of association graph of terms shows that the most frequently discussed concepts reveal that control of self-driving cars is based on algorithms, data, design, method, and model. The methods used in this study and the results can be used as decision tools, if carefully applied, in diverse disciplines that are disrupted by the introduction of self-driving cars. For future study, we plan to extend this study with a larger dataset and other data mining techniques.
4.
Hjalmarsson, Anders, et al.
(författare)
From contest to market entry : A longitudinal survey of innovation barriers constraining open data service development
2015
Ingår i: ECIS 2015 Completed Research Papers. - : Association for Information Systems. - 9783000502842
Konferensbidrag (refereegranskat) abstract
Open data services have emerged as a research field. One important area of investigation within this field is exploration into how sustainable open data markets are created. Contests have become a popular method to propel and catalyse open data service development providing services to such markets. Recent research has identified numerous innovation barriers hampering development adjacent to the contest in developers' effort to transform contest contributions to viable digital services based on open data. Little is however known about what innovation barriers over time constrain the post-contest process to transform initial innovations to finalized open data services ready for market entry. This paper presents a longitudinal survey of innovation barriers constraining teams performing open data service development after an innovation contest. The survey provides insights into 1) 24 innovation barriers constraining development, 2) a comparison of barrier importance based on team progress, and 3) a conceptualisation of phases structuring the process from contests to market entry, stipulating different innovation barriers impact open data service development. The results contribute to the understanding of how sustainable open data markets emerge and serve as a starting point for investigating how different stakeholders can manage innovation barriers constraining open data service development.
5.
Juell-Skielse, Gustaf, et al.
(författare)
Modes of collaboration and expected benefits of inter-organizational E-government initiatives : A multi-case study
2017
Ingår i: Government Information Quarterly. - : Elsevier. - 0740-624X .- 1872-9517. ; 34:4, s. 578-590
Tidskriftsartikel (refereegranskat) abstract
Collaboration among governmental organizations has been regarded as essential for realizing benefits of e-government investments. Inter-organizational collaboration on e-government can appear in several forms and can aim at varying types of benefits. However, few if any studies have delved deeper into analysis of how chosen forms of collaboration might relate to targeted e-government benefits. This article studies five cases of how contemporary acquisitions and implementations of digital archiving systems have been launched through five modes of collaboration (autonomous, standardization, framework agreement, consortium, and central service organization) among organizations in the Swedish public sector. Our analysis reveals that whereas the target system, digital archive in our case, stays similar, expected benefits vary. The article contributes by elaborating the concept of mode of collaboration that identifies typical benefits justifying a choice of a particular collaboration form on e-government development and describing the five modes in more detail based on a multi-case study. The article also outlines fourteen related propositions of the correlation between the collaboration modes and expected benefits to be verified by further research.
6.
Susha, Iryna, 1986-, et al.
(författare)
Open Data Research in the Nordic Region : Towards a Scandinavian Approach?
2016
Ingår i: Electronic Government. - Cham : Springer. - 9783319444208 - 9783319444215 ; , s. 61-73
Konferensbidrag (refereegranskat) abstract
Since 2009 open data has been growing into a specialized research area, including in the Nordic countries. Historically Information Systems research from this region has managed to develop a distinct identity on the international research arena. Hence, the expectation is that also in the context of open data there exists room for unique contributions of Nordic researchers. However, no systematic overview exists yet of the open data research conducted in these countries or of the emerging research community. This paper, therefore, aims to fill this gap by conducting a comprehensive literature review. Our study focuses on the following aspects: (1) which perspectives and topics are exam- ined and (2) which empirical settings and methods are applied in Nordic open data research. Finding answers to these questions will enable us to propose a future research agenda and thereby stimulate debate in the Nordic open data research community.
7.
Juell-Skielse, Gustaf, et al.
(författare)
What happens next? : A survey of the afterlife of innovation contests
2014
Ingår i: Proceedings of 2014 Pre-ECIS Workshop Rethinking Information Systems in the Public Sector. - : Association for Information Systems.
Konferensbidrag (refereegranskat) abstract
Innovation contests are becoming popular instruments for stimulating development of digital services using open data. However, experience indicates that only a limited number of the results developed during these events become viable digital services attracting a significant user base. Hence, an unresolved question is how organizers choose to support the service development process after the contest is concluded. To further deepen our knowledge about the design of digital innovation contests and the support for the processes after the contests are concluded, we conducted a survey of the websites of 33 digital innovation contests.
8.
Ayele, Workneh Y., et al.
(författare)
A Method for Designing Digital Innovation Contest Measurement Models
2016
Konferensbidrag (refereegranskat) abstract
As contests become more popular means for organizing digital innovation, the need for measuring contest performance increases. The Digital Innovation Contest Measurement-model (DICM-model), which is the basis for this study was designed based on a single case study, and its evaluation indicated that there is a need for a customizable methodological approach that can accommodate differences in organizational requirements for designing and refining DICM-models. Therefore, in this paper, we present a summary of the evaluation of the DICM-model and propose a nine-step method to design and refine DICM-models using a quality oriented approach. The proposed method is based on the Goal-Question-Metric and the Balanced Scorecard to elicit measures and to enable agility in measuring the fulfilment of measurement goals of innovation contests. Also, the method facilitates knowledge management to refine, record and communicate best practices. An exante evaluation of the method indicates that the method provides practical support in designing and improving a DICM model. For future study, it is suggested to widen the scope of the method to aid in the design of measurement models for digital innovations using open data, in general.
9.
Ayele, Workneh Yilma, et al.
(författare)
Evaluating open data innovation : A measurement model for digital innovation contests
2015
Ingår i: PACIS 2015 Proceedings. - : AIS electronic library.
Konferensbidrag (refereegranskat) abstract
Digital innovation contests emerge as important intermediaries in open data markets. However the understanding of how contests affect innovation value chains is low and there is a lack of innovation measurement frameworks to support the management of digital innovation contests. Therefore, in this paper we apply design science to design a measurement model for digital innovation contests from the organizer's perspective that adds to the available knowledge of innovation measurement. We use a recent case of digital innovation contests to motivate the model and discuss its implications on the innovation value chain. The measurement model contributes with new knowledge in the area of open data innovation and provides support for practice in managing innovation through digital innovation contests. For future research we intend to enhance the model to also measure the effects on innovation ecosystems, to operationalize the measures and to evaluate the model in several digital innovation contests as well as to include the perspective of the participants.
10.
Ayele, Workneh Y., et al.
(författare)
Unveiling DRD : A Method for Designing Digital Innovation Contest Measurement Models
2018
Ingår i: Systems, Signs & Actions. - 1652-8719. ; 11:1, s. 25-53
Tidskriftsartikel (refereegranskat) abstract
The growing open data market opens possibilities for the development of viable digital artifacts that facilitate the creation of social and business values. Contests are becoming popular means to facilitate the development of digital artifacts utilizing open data. The increasing popularity of contests gives rise to a need for measuring contest performance. However, the available measurement model for digital innovation contests, the DICM-model, was designed based on a single case study and there is a need for a methodological approach that can accommodate for contests’ variations in scope. Therefore, we use design science to construct a nine-step method, the DRD method, to design and refine DICM-models. The DRD-method is designed using goal- and quality oriented approaches. It extends innovation measurement to the application domain of digital innovation contests and provides an improvement of innovation measurement as it offers a new solution for a known problem. The DRD-method provides comprehensive support to practice for designing and refining DICM-models and supports reflection and organizational learning across several contests. For future study, we suggest an ex-post evaluation of the method inconjunction with real contests and systematic efforts to generalize the method within as well as beyond the context of the contest. Finally, we propose to further investigate the potential of topdown and goal oriented approaches to measure open and iterative forms of innovation.
