Public Values in the Age of Big Data: A Public Information Perspective

Ingrams, Alex

doi:10.1002/poi3.193

Cited by 28 publications

(22 citation statements)

References 51 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…BDA tools must therefore be incorporated into the study of public agencies. One of the challenges identified by Giest (2017) and Ingrams (2019) is limited institutional support for BD management and capacity within the government. As highlighted by MAMPU (2017), when the government has low level of analytical capacity, they would have to source for additional stakeholders with the right skill sets.…”

Section: Assessing the Public Sector To Adopt Big Data Analyticsmentioning

confidence: 99%

Determinants factors of intention to adopt big data analytics in Malaysian public agencies

Sahid

Sani

Noordin

et al. 2021

JIEM

View full text Add to dashboard Cite

Purpose: This research objective was to analyze factors affecting IT practitioners’ behavioral intentions in adopting (BDA) using a combination of Initial Trust Model (ITM), Unified Theory Of Acceptance And Use Of Technology (UTAUT) AND Task-Technology Fit (TTF) Model acceptance models.Design/methodology/approach: Using a cross sectional survey, empirical data were collected. A total of 200 questionnaires were obtained and screened. 14 insufficient answers were subsequently discarded leaving 186 valid structured data review questionnaires. Data was analizad using the Partial Least Square Modeling of Structural Equations due to one of the best software for verifying structured data on structural equations modeling (SEM).Findings: Our findings show that two key factors determine behavioral intention to adopt BDA in government agencies. Firstly, the assumption that the technology is going to produce great results raises the expectation of performance. TTF was the second determinant factor. Surprisingly, Initial trust, on the other hand, had not been considered to be a key determinant of behavioural intention and was found to be adversely related to the BDA intentionResearch limitations/implications: These findings identify the crucial model, that would be useful to IT officers in public agencies in making investment choices and designing non-adopter-friendly outreach strategies because they have more barriers to acceptance than adopters and lead adopters in the reward ladder.Practical implications: The findings suggest significant recommendations and consequences for BDA systems practitioners and application developers, which could coincide with the successful implementation of BDA systems. This research gives practitioners an initial way to incorporate and endorse BDA activities in their organization to make the most of the advantages of revolutionary technology, particularly within public agencies.Originality/value: This study's model is helpful and promotes a theory for further BDA research. By utilizing the model, existing public agencies can know their own BDA capability, centered around activities with specifically tailored outcomes, organization dynamics, resources, skills and potential services.

show abstract

Section: Assessing the Public Sector To Adopt Big Data Analyticsmentioning

confidence: 99%

Determinants factors of intention to adopt big data analytics in Malaysian public agencies

Sahid

Sani

Noordin

et al. 2021

JIEM

View full text Add to dashboard Cite

show abstract

“…BDA tools must therefore be incorporated into the study of public agencies. One of the challenges identified by Giest (2017) and Ingrams (2019) is limited institutional support for BD management and capacity within the government. As highlighted by MAMPU (2016), when the government has low level of analytical capacity, they would have to source for additional stakeholders with the right skill sets.…”

Section: Assessing the Public Sector To Adopt Big Data Analyticsmentioning

confidence: 99%

Factors Influencing Intent to Adopt Big Data Analytics in Malaysian Government Agencies

Sani

Zaini

Sahid

et al. 2021

IJBS

View full text Add to dashboard Cite

In Big Data Analytics (BDA), many government agencies directly raised their ICT expenditure in their effort to understand the attitude of the users towards new technologies. This research is intended to analyze factors affecting IT practitioners’ behavioral intentions in adopting (BDA) using a combination of multiple technology acceptance models. The synergistic three IS theory strengths: (1) Task Technology Fit (TTF), (2) Unified Technology Acceptance and Utilization Theory (UTAUT), and the (3) Initial Trust Model (ITM). The concept was validated in Malaysian government agencies, one of the highly dependent BDA promoters and initiators. 186 respondents in the Information Management departments of public agencies were recruited as part of the rigorous methodology to gather rich data. Partial least squares were analyzed by the structural models (PLS). The two key factors determine behavioral intention to adopt BDA in government agencies. Firstly, the assumption that the technology is going to produce great results raises the expectation of performance. Technological fit was the second determinant factor. Initial trust, on the other hand, was found to be adversely related to the BDA intention. Implicitly, the proposed model would be useful to IT officers in public agencies in making investment choices and designing non-adopter-friendly outreach strategies because they have more barriers to acceptance than adopters and lead adopters in the reward ladder. All public agencies will benefit from the findings of this study in gaining awareness of BDA application and fostering psychological empowerment of employees to adopt this revolutionary approach. The article outlines how dynamic TTF, UTAUT and ITM are for researchers to integrate in their emerging decision support framework for the study of new technology adoption.

show abstract

“…In recent years, both data variety and volume have increased exponentially. Along with digital records of citizens, the use of service apps, social media, digital sensors, and other digital footprints, big data also give policymakers insights into citizen choice and is, therefore, potentially supportive of public value such as participation and openness (Ingrams, 2018). Veenstra & Kotterink (2017) state that data can be used for the real time monitoring of policy.…”

Section: Theoretical Backgroundmentioning

confidence: 99%

Development of a Market Trend Evaluation System for Policy Making

Gružauskas¹,

Kriščiūnas²,

Čalnerytė³

et al. 2020

JOC

View full text Add to dashboard Cite

The previous economic crisis has increased the attention of government to focus their activities more on economic stability. The development of government subsidies requires an analytically based analysis, one which would identify problematic areas of regional development more precisely. However, to monitor market changes in a highly dynamic market is time consuming and inefficient. Without proper market monitoring, the level of competitiveness within regions might decrease in the long run. Thus, the goal of the article is to establish the framework of a market trend monitoring system. To achieve this goal, the research methodology consists of a scientific literature analysis, an analysis of available data infrastructure for market trend analysis, and a statistical analysis together with a machine learning approach. The authors of the publication propose a market monitoring framework which would provide an infrastructure for evidencebased policy recommendations for government institutes and might provide guidelines of how to increase their competitiveness. A case study of real estate data and macroeconomic indicators of Lithuania was conducted, during which a clustering algorithm was applied to identify groups in Lithuania. The 60 municipalities of Lithuania were grouped into 4 clusters in terms of noteworthy relationships between industrial development and population size. In 3 of the clusters, the relationship of industrial growth and population was direct. In cluster 4, however, the relationship was opposite, a result which requires a further analysis of infrastructure and industrial sectors to provide more precise policy recommendations. The theoretical contribution and findings from the case study provides grounding to develop the market monitoring system.

show abstract

Public Values in the Age of Big Data: A Public Information Perspective

Cited by 28 publications

References 51 publications

Determinants factors of intention to adopt big data analytics in Malaysian public agencies

Determinants factors of intention to adopt big data analytics in Malaysian public agencies

Factors Influencing Intent to Adopt Big Data Analytics in Malaysian Government Agencies

Development of a Market Trend Evaluation System for Policy Making

Contact Info

Product

Resources

About