Qualitative Structural Model for Capabilities in Open Data Organizations

Open data is increasingly becoming an essential asset for many organizations. However, large numbers of organizations fall short when it comes to utilizing open data effectively to fully leverage the potential of it. There are ample evidences that this shortcoming is attributable to the poor understanding of what types of capabilities are required to successfully conduct data related activities. At the same time, research on open data capabilities and how they relate to one another remains sparse. Based on the theoretical foundation constructed from the integration of Capability-based Theory and Dynamic Capability Theory and, extant literature and interviews of leadership of open data organizations, we attempt to address this knowledge gap by investigating open data capabilities and relationships between them. Findings help validate the two theories in the open data organizations and reveal unknown knowledge about open data capability areas and how they affect one another

Open Data Capability Architecture - An Interpretive Structural Modeling Approach

Despite of increasing availability of open data as a vital organizational resource, large numbers of start-ups and organizations fail when it comes to utilizing open data effectively. This shortcoming is attributable to the poor understanding of what types of capabilities are required to successfully conduct data related activities. At the same time, research on open data capabilities and how they relate to one another remains sparse. Guided by extant literature, interviews of these organizations, and drawn from Interpretive Structural Modeling (ISM) approach which are pair comparison methods to evolve hierarchical relationships among a set of elements to convert unclear and unstructured mental models of systems into well-articulated models that act as base for conceptualization and theory building, this study explores open data capabilities and the relationships and the structure of the dependencies among these areas. Findings from this study reveal hitherto unknown knowledge regarding how the capability areas relate one another in these organizations. From the practical standpoint, the resulting architecture has the potential to transform capability management practices in open data organizations towards greater competitiveness through more flexibility and increased value generation. From the research point of you, this paper motivates theory development in this discipline

Towards Open Data Impact Evaluation Framework – An Empirical Analysis of the Demand-side Response

Open data is widely presumed to have a social, environmental, political, and economic impact; however, the evidence to that impact has remained scarce. The impacts must be explored and quantified to give a reasonable insight into the supply-side activities and demand-side responses. Based on the data collected from open data users in Ireland, we address the questions what the impacts of open data are and what indicators can be used to quantify the impacts of future open data initiatives. Findings from this study revealed impact categories, areas, and specific indicators to each impact areas. Output of this research directly contributes to the development and implementation of the National Open Data Strategy. This research recommends that open data leaders revisit indicators in respond to the change of social context and call for new forms of joint action between public and private stakeholders to deliver data-driven public goods

An Ontology for Open Government Data Business Model

Despite the existence of number of well-known conceptualization in e-Business and e-Commerce, there have been no efforts so far to develop a detailed, comprehensive conceptualization for business model. Current business literature is replete with fragmented conceptualizations, which only partially describe aspects of a business model. In addition, the existing conceptualizations do not explicitly support the emerging phenomenon of open government data – an increasingly valuable economic and strategic resource. Consequently, no comprehensive, formal, executable open government data business model ontology exists, that could be directly leveraged to facilitate the design, development of an operational open data business model. This paper bridges this gap by providing a parsimonious yet sufficiently detailed, conceptualization and formal ontology of open government data business model for open data-driven organizations. Following the design science approach, we developed the ontology as a ‘design artefact’ and validate the ontology by using it to describe an open data business model of an open data-driven organization

Entrepreneurism and e-government in Finland: Barriers to Entry

Entrepreneurship is generally considered as central to economic development. Therefore, decisions by government to directly support entrepreneurs with Electronic Government (e-Gov) services can have significant impact on economic development. Given the current downward trend in new entrepreneur numbers in many countries, e-Gov services may arguably be best targeted at promotion and lowering of barriers in establishing new businesses. However, delivering effective e-Gov services to entrepreneurs in starting new businesses will require concrete knowledge of entrepreneurial needs on one hand and the barriers to entry and challenges on the other hand. Unfortunately, research dedicated to the real needs of entrepreneurs with respect to e-Gov services is limited. This work fills this knowledge gap through a study of the e-Gov related factors that could contribute to lowering the barriers to entry for new entrepreneurs. Based on the analysis of the information gathered from a series of structured and semi-structured interviews involving 36 fresh entrepreneurs in Finland, we identified four factors related to e-Gov services which could lower the barrier to entrepreneurship

A Tale of Open Data Innovations in Five Smart Cities

Open Data initiatives are increasingly considered as defining elements of emerging smart cities. However, few studies have attempted to provide a better understanding of the nature of this convergence and the impact on both domains. This paper presents findings from a detailed study of 18 open data initiatives across five smart cities -- Barcelona, Chicago, Manchester, Amsterdam, and Helsinki. Specifically, the study sought to understand how open data initiatives are shaped by the different smart cities contexts and concomitantly what kinds of innovations are enabled by open data in these cities. The findings highlight the specific impacts of open data innovation on the different smart cities domains, governance of the cities, and the nature of datasets available in the open data ecosystem

Multi-functional view of technology governance in tax administration: A case study

Despite digital technology gaining importance in recent years, a holistic view on its governance in public and tax administration is yet to be clearly articulated, a shortcoming made more acute by the centrality of the government sector. Guided by a case study approach considering three key perspectives in a European tax administration – 1.) Customer Service Leader; 2.) Information and Technology Leader; and 3.) Operations Leader. This study surfaces the elements central to the effective governance of disruptive digital technologies

A term extraction approach to survey analysis in health care

The voice of the customer has for a long time been a key focus of businesses in all domains. It has received a lot of attention from the research community in Natural Language Processing (NLP) resulting in many approaches to analysing customers feedback ((aspect-based) sentiment analysis, topic modeling, etc.). In the health domain, public and private bodies are increasingly prioritising patient engagement for assessing the quality of the service given at each stage of the care. Patient and customer satisfaction analysis relate in many ways. In the domain of health particularly, a more precise and insightful analysis is needed to help practitioners locate potential issues and plan actions accordingly. We introduce here an approach to patient experience with the analysis of free text questions from the 2017 Irish National Inpatient Survey campaign using term extraction as a means to highlight important and insightful subject matters raised by patients. We evaluate the results by mapping them to a manually constructed framework following the Activity, Resource, Context (ARC) methodology (Ordenes et al., 2014) and specific to the health care environment, and compare our results against manual annotations done on the full 2017 dataset based on those categories

Capability architecture for open data

Open data is increasingly becoming an essential asset for many organizations. Large numbers of new start-ups are emerging to benefit from the potential of this asset for a wide range of new products and services. However, despite of significant advances in open data technical and infrastructure capabilities, large numbers of organizations fall short when it comes to utilizing open data effectively. Consequently, they fail to fully leverage the potential of open data. There are ample evidences that this shortcoming is attributable to the poor understanding of what types of capabilities are required to successfully conduct data related activities. At the same time, research on open data capabilities and how they relate to one another remains sparse. The thesis addresses this knowledge gap by investigating capability areas and specific capabilities that are important for generating value from open data, enabling and improving agility and competitive advantage of organizations using open data as one of their key resources to meet their mission goals. In addition, the thesis explores the relationships among the capability areas and the structure of the dependencies among these areas. We adopt a Design Science Research Approach with a theoretical foundation constructed from the integration of Capability-based Theory and Dynamic Capability Theory. Guided by extant literature, data from a global survey of open data organizations and in-depth interviews of leadership of these organizations were analyzed based on the developed theoretical model to identify specific capabilities associated with each capability areas and how these capability areas impact one another. Structural modelling technique was employed to refine these relationships into a layered architecture specifying the dependencies among the capability areas. The structural analysis performed also enables the determination of the nature of these capability areas. Findings from the thesis do not only help validate and refine Capability-based Theory and Dynamic Capability Theory in the open data organization; they reveal hitherto unknown knowledge regarding how the capability areas affect one another in these organizations. From the practical standpoint, the resulting architecture has the potential to transform capability management practices in open data organizations towards greater competitiveness through more flexibility and increased value generation.2019-07-3