Business Intelligence and Big Data Analytics for Organizational Performance Management in Public Sector: The Conceptual Framework

被引:1
|
作者
Yahaya, Jamaiah H. [1 ]
Deraman, Aziz [2 ]
Abai, Nor Hani Zulkifli [1 ]
Mansor, Zulkefli [1 ]
Jusoh, Yusmadi Yah [3 ]
机构
[1] Univ Kebangsaan Malaysia, Fac Informat Sci & Technol, Bangi 43000, Selangor, Malaysia
[2] Univ Malaysia Terengganu, Sch Informat & Appl Math, Kuala Terengganu 21030, Malaysia
[3] Univ Putra Malaysia, Fac Comp Sci & Informat Technol, Serdang 43400, Selangor, Malaysia
关键词
Business Intelligence; Big Data Analytics; Organizational Performance Management; Public Sector;
D O I
10.1166/asl.2016.7741
中图分类号
O [数理科学和化学]; P [天文学、地球科学]; Q [生物科学]; N [自然科学总论];
学科分类号
07 ; 0710 ; 09 ;
摘要
The implementation of business intelligence (BI) and big data analytic (BDA) in managing organizational performance especially in public sector is important and critical. Weakness in managing the implementation strategy and the performance can result a massive impact to people and nation. Therefore, integration of BI and BDA are necessity to assist decision makers to increase efficiency in public services. However, preliminary study had identified limited implementation of BI and business analytics with organisation performance management (OPM) that led to inefficient performance in management practice. At the same time, large amount of data from various resources have headed to the emergent of big data analytics. Therefore, this research is proposed with the aim to develop an integrated framework of business intelligence and big data analytics (BI-BDA) for OPM. To achieve this goal, elements and sub elements of integrated BI-BDA and OPM implementation will be identified which focuses on big data analytics. Main outcome from this research is the new integrated framework of BI and BDA (BI-BDA) for OPM in public sector. The proposed framework is valuable for the practitioners as well as the stakeholders to ensure the OPM system to be more effective and dynamic.
引用
收藏
页码:1919 / 1923
页数:5
相关论文
共 50 条
  • [31] A Big Data Conceptual Model to Improve Quality of Business Analytics
    Park, Grace
    Chung, Lawrence
    Johng, Haan
    Sugumaran, Vijayan
    Park, Sooyong
    Zhao, Liping
    Supakkul, Sam
    RESEARCH CHALLENGES IN INFORMATION SCIENCE (RCIS 2020), 2020, 385 : 20 - 37
  • [32] Business Intelligence (BI) in Firm Performance: Role of Big Data Analytics and Blockchain Technology
    Pancic, Mladen
    Cucic, Drazen
    Serdarusic, Hrvoje
    ECONOMIES, 2023, 11 (03)
  • [33] An Integrated Model of Business Intelligence & Analytics Capabilities and Organizational Performance
    Ramakrishnan, Thiagarajan
    Khuntia, Jiban
    Kathuria, Abhishek
    Saldanha, Terence J., V
    COMMUNICATIONS OF THE ASSOCIATION FOR INFORMATION SYSTEMS, 2020, 46 : 722 - 750
  • [34] Designing a Conceptual Framework for Organizational Entrepreneurship in the Public Sector in Iran
    Yeazdanshenas, Mehdi
    IRANIAN JOURNAL OF MANAGEMENT STUDIES, 2014, 7 (02) : 365 - 390
  • [35] A big data analytics framework for scientific data management
    Fiore, Sandro
    Palazzo, Cosimo
    D'Anca, Alessandro
    Foster, Ian
    Williams, Dean N.
    Aloisio, Giovanni
    2013 IEEE INTERNATIONAL CONFERENCE ON BIG DATA, 2013,
  • [36] Conceptual Framework for Implementing Temporal Big Data Analytics in Companies
    Mach-Krol, Maria
    APPLIED SCIENCES-BASEL, 2022, 12 (23):
  • [37] Big data analytics and business analytics
    Duan, Lian
    Xiong, Ye
    JOURNAL OF MANAGEMENT ANALYTICS, 2015, 2 (01) : 1 - 21
  • [38] Business-driven data analytics: A conceptual modeling framework
    Nalchigar, Soroosh
    Yu, Eric
    DATA & KNOWLEDGE ENGINEERING, 2018, 117 : 359 - 372
  • [39] New development: Leveraging "big data' analytics in the public sector
    Gamage, Pandula
    PUBLIC MONEY & MANAGEMENT, 2016, 36 (05) : 385 - 390
  • [40] SURVEY ON BIG DATA ANALYTICS IN PUBLIC SECTOR OF RUSSIAN FEDERATION
    Anna, Kuraeva
    Nikolay, Kazantsev
    3RD INTERNATIONAL CONFERENCE ON INFORMATION TECHNOLOGY AND QUANTITATIVE MANAGEMENT, ITQM 2015, 2015, 55 : 905 - 911