A Dempster–Shafer Big Data Readiness Assessment Model

Areerakulkan, Natapat; Pongpech, Worapol Alex

doi:10.5220/0010506205810585

Cited by 6 publications

(1 citation statement)

References 0 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…V tem kontekstu se digitalna preobrazba pomika proti novi paradigmi, imenovani podatkovno vodena digitalna preobrazba. Podatkovno-vodena preobrazba je proces, pri katerem organizacija preoblikuje svojo infrastrukturo, strategije, način poslovanja, tehnologije ali organizacijsko kulturo, da olajša in spodbudi vedenje pri odločanju, ki temelji na podatkih (Areerakulkan & Pongpech, 2021;Hagen & Hess, 2020).…”

Section: Sustainability Reportingunclassified

Towards Collaborative Business Intelligent Framework: Crowdsourcing Approach

Cherednichenko¹,

Vovk²,

Sutiahin³

2023

42nd International Conference on Organizational Science Development

View full text Add to dashboard Cite

Collaborative Business Intelligence goes beyond the organization frame and collecting people in one virtual space in order to give their opinion concerning certain issue results in an opportunity to boost the decision-making process and make it more reasonable. Strangers solve one problem without direct interaction and use the developed results. Tourists often search for information from different sources and compare found facts. It takes a lot of time and effort. So, having an application, where users could find relevant information and use it for decisionmaking is essential. The aim of the paper is to develop an application for tourists using which they could make a decision about where and why to go. We propose an approach to collect and clear data related to tourism, preprocess and structure tourism data convenient interface and tools for collaborative analysis.

show abstract

Section: Sustainability Reportingunclassified

Towards Collaborative Business Intelligent Framework: Crowdsourcing Approach

Cherednichenko¹,

Vovk²,

Sutiahin³

2023

42nd International Conference on Organizational Science Development

View full text Add to dashboard Cite

show abstract

Big data readiness in the public sector: an assessment model and insights from Indonesian local governments

Ariansyah,

Setiawan,

Hikmaturokhman

et al. 2024

JSTPM

View full text Add to dashboard Cite

Purpose This study aims to establish an assessment model to measure big data readiness in the public sector, specifically targeting local governments at the provincial and city/regency levels. Additionally, the study aims to gain valuable insights into the readiness of selected local governments in Indonesia by using the established assessment model. Design/methodology/approach This study uses a mixed-method approach, using focus group discussions (FGDs), surveys and exploratory factor analysis (EFA) to establish the assessment model. The FGDs involve gathering perspectives on readiness variables from experts in academia, government and practice, whereas the survey collects data from a sample of selected local governments using a questionnaire developed based on the variables obtained in FGDs. The EFA is used on survey data to condense the variables into a smaller set of dimensions or factors. Ultimately, the assessment model is applied to evaluate the level of big data readiness among the selected Indonesian local governments. Findings FGDs identify 32 essential variables for evaluating the readiness of local governments to adopt big data. Subsequently, EFA reduces this number by five and organizes the remaining variables into four factors: big data strategy, policy and collaboration, infrastructure and human resources and data collection and utilization. The application of the assessment model reveals that the overall readiness for big data in the selected local governments is primarily moderate, with those in the Java cluster displaying higher readiness. In addition, the data collection and utilization factor achieves the highest score among the four factors. Originality/value This study offers an assessment model for evaluating big data readiness within local governments by combining perspectives from big data experts in academia, government and practice.

show abstract

42nd International Conference on Organizational Science Development

2023

View full text Add to dashboard Cite

After ISO 5500x series standards were issued back in 2014, a body of literature on asset management and asset management system has been growing. However, implementation of asset management system and its certification have not attracted much research attention. In practice, asset management system is not so widely embraced by top management, even though it supports organizations to realize value from the assets while balancing risk and opportunity, cost and performance. Hence, an interesting research question is arising, i.e., what are the key factors influencing top management's decision to either implement an asset management system or not. After introducing a theoretical background, the paper suggests research methodology and a conceptual research model. The results of the future research should allow for a better understanding of the top management's decision-making process related to asset management system implementation, and indicate potential areas to be addressed in the future to provide guidance to decision makers.

show abstract

A Dempster–Shafer Big Data Readiness Assessment Model

Cited by 6 publications

References 0 publications

Towards Collaborative Business Intelligent Framework: Crowdsourcing Approach

Towards Collaborative Business Intelligent Framework: Crowdsourcing Approach

Big data readiness in the public sector: an assessment model and insights from Indonesian local governments

42nd International Conference on Organizational Science Development

Contact Info

Product

Resources

About