Conceptual Model Development of Big Data Analytics Implementation Assessment Effect on Decision-Making

Adrian, Cecilia; Abdullah, Rusli; Atan, Rodziah; Jusoh, Yusmadi Yah

doi:10.9781/ijimai.2018.03.001

Cited by 33 publications

(40 citation statements)

References 17 publications

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“…For this reason, the challenges of Big Data, with a focus on social media data, were reviewed in the SLR as these challenges might also influence the quality of social media Big Data, which can influence the adoption and success of SMA. These challenges have not yet been adequately addressed [25][26][27][28]. The number of studies [29,30] that have reported challenges of Big Data, do not consider associated challenges related to techniques for data analysis and those related to SMA and BDA.…”

Section: Review Findings: Data Lifecycle and Sma Challengesmentioning

confidence: 99%

A Conceptual Model of the Challenges of Social Media Big Data for Citizen e-Participation: A Systematic Review

Yakobi¹,

Scholtz²,

Berg³

2020

Lecture Notes in Computer Science

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The emergence of Citizen Relationship Management (CzRM) for government plays a central role in developing citizen relationships and e-participation. As such, the South African government has shown its commitment towards citizenry and the provision of effective service delivery. Social Media Analytics (SMA) has emerged as a potential new solution to support decision-making for service delivery in CzRM. It is believed that the demand for SMA adoption will increasingly rise. However, the reality of social media Big Data comes with the challenges of analysing it in a way that brings Big Value. The purpose of this paper is to identify the challenges of social media Big Data Analytics (BDA) and to incorporate these in a conceptual model that can be used by governments to support the e-participation of citizens. The model was developed through a systematic literature review (SLR). The findings revealed that data challenges relate to designing an optimal architecture for analysing data that caters for both historic data and real-time data at the same time.

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Section: Review Findings: Data Lifecycle and Sma Challengesmentioning

confidence: 99%

A Conceptual Model of the Challenges of Social Media Big Data for Citizen e-Participation: A Systematic Review

Yakobi¹,

Scholtz²,

Berg³

2020

Lecture Notes in Computer Science

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“…Solow's (1987) productivity paradox -IT is everywhere except in productivity statistics -encapsulates several decades of research demonstrating that people's attitudes and ways of working can be barriers and result in dilemmatic outcomes in IT-related innovation. Researchers such as Adrian et al (2017Adrian et al ( , 2018 and Halaweh and Massry (2015) suggest that the same enablers and barriers that apply to IT-related innovations are also relevant to BD-related innovations. From the perspective of the technology used and people's interactions with the innovations, this is true; however, from the perspective of knowledge, the two are quite diff erent, for the reasons given above.…”

Section: Bd-related Readiness In the Public-sector Contextmentioning

confidence: 99%

“…Unlike IT, however, established BD systems also give rise to new knowledge, creating continuous decision cycles that also create uncertainties tending to result in dilemmas (Pink et al 2018;Hampden-Turner 2009). Adrian et al's (2017Adrian et al's ( , 2018 capabilities is readiness, which, unfortunately, is left undefi ned. Klievink et al (2017, 268), following a similar capabilities approach, suggested that readiness amounts to organisational alignment, organisational maturity and organisational capabilities.…”

Section: Bd-related Readiness In the Public-sector Contextmentioning

confidence: 99%

“…Conceptually, this study draws on the incorporation interaction of combining the tenets of readiness (Adrian et al 2017(Adrian et al , 2018 and the dilemma approach (Hampden-Turner 1990). Th e hindrances in BD-driven transformations in the two case organisations of this study are associated with the individual actors' (manag-ers) either / or choices and their readiness for BD-related transformations that might generate dilemmas in public organisations.…”

Section: Figurementioning

confidence: 99%

“…Th is paper explores the challenges public-sector managers face in BD-related organisational transformations, by clarifying Adrian et al's (2018) idea of readiness and synthesising it with Hampden-Turner's (1990) dilemma approach. We (a) identify the core dilemma pairs hindering public-sector managers in their BD-related transformation work and (b) revisit Hampden-Turner's ( 1990Hampden-Turner and Trompenaars 2015) dilemma approach in the novel context of BD-related transformations in public-sector organisations.…”

Section: Introductionmentioning

confidence: 99%

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Examining the Core Dilemmas Hindering Big Data-related Transformations in Public-Sector Organisations

Kuoppakangas

Kinder

Stenvall

et al. 2019

NISPAcee Journal of Public Administration and Policy

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This study examines public organisations planning big data-driven transformations in their service provision. Without radical structural change or managerial system changes, leaders face dilemmas: simply bolting on big data makes little difference. This study is based on a qualitative empirical case study using data collected from the cities of Helsinki and Tampere in Finland. The three core dilemma pairs detected and connected to the big data-related organisational changes are: (1) repetitive continuity vs. visionary change, (2) risk-taking vs. security-seeking and (3) technology-based development vs. human-based development. This study suggests that organisational readiness involves not only capabilities; instead, readiness involves absorbing knowledge, making decisions, handling ambiguities, managing dilemmas. Thus, big data-related transformations in public organisations require embracing the world of dilemmas, since selected and cancelled experiments may each have valuable outcomes. The capability to act on intentions is a prerequisite for readiness; however, a preparedness to detect and address dilemmas is central to big data-related transformations. Thus, the ability to make dilemma decisions is a more complicated characteristic of readiness. In conclusion, our data analysis suggests that traditional public organisational and chance management approaches produce unsolved dilemmas in big data-related organisational changes.

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The barriers to big data adoption in developing economies

Alalawneh

Alkhatib

2020

E J Info Sys Dev Countries

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Big data adoption (BDA) and its barriers, opportunities, and expected benefits are increasingly attracting researchers' and practitioners' attention. For developing economies, BDA has special importance; however, they have struggled to identify the barriers hindering it. This study aims to identify the barriers to BDA in developing economies and their relative importance across sectors to identify sectors' readiness for BDA. Based on a review of the BDA literature, semi‐structured interviews with big data (BD) experts, and a questionnaire‐based survey, five barrier sets, and 19 sub‐barriers were identified. Thereafter, barrier sets for each sector were identified, analyzed, discussed, and compared. Analytic hierarchy process (AHP) was used to identify the relative importance of these barriers across sectors, while the technique for order of preference by similarity to ideal solution (TOPSIS) was used to rank sectors according to their readiness for BDA. This study positions itself as a reference for scholars and practitioners interested in BDA in developing economies.

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Conceptual Model Development of Big Data Analytics Implementation Assessment Effect on Decision-Making

Cited by 33 publications

References 17 publications

A Conceptual Model of the Challenges of Social Media Big Data for Citizen e-Participation: A Systematic Review

A Conceptual Model of the Challenges of Social Media Big Data for Citizen e-Participation: A Systematic Review

Examining the Core Dilemmas Hindering Big Data-related Transformations in Public-Sector Organisations

The barriers to big data adoption in developing economies

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