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

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

User Perception of the U.S. Open Government Data Success Factors

This quantitative correlational study used the information systems success model to examine the relationship between the U.S. federal departments\u27 open data users\u27 perception of the system quality, perception of information quality, perception of service quality, and the intent to use open data from U.S. federal departments. A pre-existing information system success model survey instrument was used to collect data from 122 open data users. The result of the standard multiple linear regression was statistically significant to predict the intent to use the U.S. open government data F(3,99) = 6479.916, p \u3c0.01 and accounted for 99% of the variance in the intent to use the U.S. open government data (R²= .995), adjusted R²= .995. The interdependent nature of information quality, system quality, and service quality may have contributed to the value of the R². Cronbach\u27s alpha for this study is α=.99, and the value could be attributed to the fact that users of open data are not necessarily technical oriented, and were not able to distinguish the differences between the meanings of the variables. The result of this study confirmed that there is a relationship between the user\u27s perception of the system quality, perception of information quality, perception of service quality, and the intent to use open data from U.S. federal departments. The findings from this study might contribute to positive social change by enabling the solving of problems in the healthcare, education, energy sector, research community, digitization, and preservation of e-government activities. Using study, the results of this study, IT software engineers in the US federal departments, may be able to improve the gathering of user specifications and requirements in information system design

Creating a Culture of Data-Driven Decision-Making

Researchers have consistently shown that a supportive culture is one of the most crucial success factors in the implementation of any big data solution. Creating a culture that supports data-driven decision-making is a difficult but ultimately required step in transforming an organization into one that can readily and successfully adopt business intelligence technologies. The purpose of this qualitative case study was to understand the ways in which organizations can foster a culture of smarter decision-making and accountability so that businesses can improve operational metrics and ultimately profitability. Participants identified three major themes that drive the adoption of a data-driven culture. These themes included building trust between decision-makers and their data, developing a team-driven culture, and instituting data governance and standard work processes to maintain quality of systems

Strategies for Ethiopian Small Retailers Businesses To Succeed Beyond 3 Years

In Ethiopia, some small retail business owners (SRBOs) embark on initiatives without adequate preparation, which results in a risk of failure within the first three years. Grounded in the conceptual frameworks of resource-based views, dynamic-capabilities views, and relational views, the purpose of this qualitative multiple case study was to explore strategies used by SRBOs leaders to survive and grow beyond three years. The participants were four SRBOs from Ethiopia who succeeded in business for more than three years. Data were collected from semistructured interviews, company documents, observations, notes from data sources and analyzed using Yin’s 5-step data analysis process. Six themes emerged: business-centric knowledge, entrepreneurial skills, relationships and networking, innovation and creativity, customer-centric approach, and support system. A key recommendation for SRBOs is to develop strategies through business-centric knowledge to succeed. The implications for a positive social change include the potential for SRBOs to stimulate economic growth by creating jobs and generating income for the Ethiopian citizens and providing an expanded government infrastructure with increased tax revenues

Open government data: an institutional logics perspective

Many countries in the world recently initiated the Open Government Data (OGD) to achieve transparency, accountability, value from the data and to transform public sector into smart and open government. However, the (OGD) initiatives faces challenges that hinders the initiatives to achieve the desired objectives, particularly in developing countries. The information systems adoption literature indicates a lack of studies investigating OGD adoption at an early stage from the national ecosystem perspective. This research investigates the early stage of adoption of the national OGD. The study adopts the institutional perspective to investigate the role of institutional logics and institutional pillars. The research aims to answer the research question: How do the institutional logics affect the emergence and adoption of the Open Government Data initiative in the public sector? This study adopts the interpretive research methodology with data collected from a singleembedded case study that encompasses nine government organisations in Oman. It captures the institutional logics qualitatively, by applying pattern inducting technique, that affects the adoption of OGD in the public sector in a complex institutional environment. The phenomena investigated reveals that the institutional pillars affect the institutional logics in the institutional environment. It shows how the institutional logics and institutional pillars interplay at the macro- and micro-level. It also shows that normative and cultural-cognitive pillar have a prominent effect, whereas the regulative pillar has less-prominent effect. This study captured one dominant and three competing logics that enable/hinder the OGD initiative from achieving the desired objectives: Institutional Acceptance Logic (ACL), Institutional Roles Logic (IRL), Ownership and Control Logic (OCL) and Institutional Capabilities Logic (ICL). The findings show that dominant logic is complemented by three co-existing subordinate institutional logics. This research contributes to the IS literature and to the institutional theory and further explains how the institutional logics and institutional pillars affect the adoption of the OGD initiative. It outlines how institutional logics are shaped and reconciled in the complex environment at the national level. It offers a holistic view from an ecosystems perspective and explains how institutional logics interact in a heterogeneous institutional environment. Given the tensions between the dominant and competing institutional logics, the adoption progresses at a slower pace. These tensions exist between micro and macro levels, and contribute negatively to the adoption of the OGD initiative. The study suggests that in order to reconcile the competing logics, a combined collaborative initiative to be formed between regulatory authorities at the national level. In addition, it offers a conceptual framework for OGD adoption at an early stage, and assists the policymakers and practitioners by presenting a holistic view from the institutional perspectives to attain the desired objectives