Modelling and analysis of big data platform group adoption behaviour based on social network analysis

Lei, Zhimei; Chen, Yandan; Lim, Ming K.

doi:10.1016/j.techsoc.2021.101570

Cited by 10 publications

(5 citation statements)

References 31 publications

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“…To answer the study question, the study carried out the SLR to determine the top factors that affect BDA adoption among SMEs, upon which the factors that influence the adoption of BDA are identified. This is followed by (Gong & Janssen, 2021), (Lei et al, 2021), (Shahbaz et al, 2021), (Raut et al, 2021), (Dubey et al, 2021), (Wook et al, 2021), (Alalawneh & Alkhatib, 2021), (Rahman et al, 2023), (Bakici et al, 2023), (Benzidia et al, 2021), (Keshavarz et al, 2021), (Ghaleb et al, 2021), (Park & Kim, 2021) 2020 11 (Saleem et al, 2020), (Shabbir & Gardezi, 2020), (Ghasemaghaei, 2020), (Yadegaridehkordi et al, 2020), (Cabrera-Sa ´nchez & Villarejo-Ramos, 2020), (Mikalef & Krogstie, 2020), (Dubey et al, 2020), (Shahbaz et al, 202010 (Raut et al, 2019, (Moktadir et al, 2019), (Ghasemaghaei, 2019), (Nam et al, 2019), (Okcu et al, 2019), (Shahbaz et al, 2019), (Shamim et al, 2019), (Singh & El-Kassar, 2019), (Dubey et al, 2019), (Shorfuzzaman et al, 2019) 2018 8 (Yadegaridehkordi et al, 2018), (Verma et al, 2018), (Caesarius & Hohenthal, 2018), (Raguseo, 2018), (Lai et al, 2018), (Joshi & Biswas, 2018), (Dubey et al, 2018), (Mahesh et al, 2018) 2017 4 (Brock & ...…”

Section: Factors Extracted By Slrmentioning

confidence: 93%

Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review

Aldossari,

Mokhtar,

Abdul Ghani

2023

Sage Open

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In the current market landscape, enterprises face tremendous pressure to remain competitive and innovative to extend their businesses globally. Thus, a need exists for a new data analysis technique and a tool known as Big Data Analytics (BDA), which refers to massive data sets in light of their volume, velocity, variety, and veracity. Small and Medium Enterprises (SMEs) face challenges in obtaining and utilizing the knowledge derived from big data to make informed decisions regarding market selection and adopting appropriate internationalization strategies. These enterprises encounter resource limitations that hinder their ability to effectively acquire and implement big data insights for strategic decision-making in these areas. This systematic literature review aims to investigate the state of research on adopting big data analytics in SMEs. The study focuses on identifying key factors that influence the adoption of BDA. The study extracted 13 significant factors that are the highest influencers for BDA in SMEs. Those factors are top management support, training, relative advantage, it infrastructure, security, compatibility, complexity, adaptability, government it policies, competency, collaboration, digital transformation tools, and decision quality. The findings of this review are useful for practitioners, researchers, and decision-makers in understanding the factors that influence the adoption of big data analytics and the potential benefits and challenges associated with its implementation. Findings will shed light on the interplay between data governance and other factors influencing adoption, providing valuable insights for organizations seeking to establish robust data governance frameworks that support successful BDA initiatives.

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Section: Factors Extracted By Slrmentioning

confidence: 93%

Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review

Aldossari,

Mokhtar,

Abdul Ghani

2023

Sage Open

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“…As participants in the literary discourse of BD, Lei et al (2021) opine that the TAM provides a veritable framework that can underpin studies on the adoption of BD. Therefore, given that the current research pivots around technology and BD in particular, the TAM is considered as relevant and this study will be anchored on it.…”

Section: Empirical Review and Hypothesis Developmentmentioning

confidence: 99%

Antecedents of big data adoption in financial institutions

Eresia-Eke,

Mojalefa,

Nyanga

2023

IJRBS

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Big data (BD) adoption is still relatively slow despite the numerous business opportunities that it embodies. Within the context of financial institutions in South Africa, the specific drivers of big data adoption remain largely indeterminate. Consequently, this study explores the possible relationships between perceived usefulness and perceived ease of use and actual big data adoption, while being duly cognisant of the role that behavioural intention to adopt big data could play. The study employed a survey research approach and relied on data collected from a purposive sample of 195 management level employees of financial institutions. Regression analysis to test the hypothesised relationships in the study revealed that perceived usefulness and perceived ease of use were statistically significant predictors of big data adoption. Instructively, this relationship was subject to the extent of behavioural intention of respondents. For respondents with a low behavioural intention to adopt big data, perceived usefulness and perceived ease of use displayed a statistically insignificant relationship with big data adoption. Conversely, the regression model for the group of respondents with a high behavioural intention to adopt big data is statistically significant. These findings enrich literature related to big data from a developing country context while concurrently identifying veritable antecedents of big data adoption in financial institutions.

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“…Thus, the SNA plays a critical role in determining problem-solving solutions, organisational processes, and the extent of individuals' success in goal accomplishment (Mastan & Christianto, 2021). Prior researchers in other disciplines also applied SNA to assess individuals, groups, organisations, and communities (Gandasari et al, 2022;Lei et al, 2021;Parnell, 2018;Selden & Goodie, 2018;Storey et al, 2021;Tahmasebi & Askaribezayeh, 2020).…”

Section: Social Network and Social Network Analysismentioning

confidence: 99%

Social Network Analysis of Basic Necessity Scarcity on Twitter: Evidence from Indonesia

Gandasari¹,

Dwidienawati

Tjahjana

et al. 2023

JICC

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The scarcity of basic necessities, a popular discussion topic in Indonesia, poses significant challenges to the citizens. Indonesians frequently comment on the issue on social media, including Twitter, which is perceived as a democratic public space to express opinions, interests, and information discursively in establishing communications as part of intercultural dialogues. The current study aims to analyse relevant communication networks and content regarding the topic of fundamental necessity scarcity in Indonesia on Twitter. Specifically, a cross-sectional design was employed with social network analysis (SNA) and content analysis (CA) conducted on public Twitter accounts. The study discovered a low communication intensity between nodes due to the existing dominance of several central actors. Simultaneously, the most frequently employed words were food, oil, cooking, the task force, and the hashtag phrase “punishthehoardersofcookingoil”. Auto-coded sentiment results demonstrated 8,963 references at neutral levels, 566 with moderately negative degrees, 500 with high negative levels, 90 with moderately positive, and 21 with highly positive degrees. The findings propounded that Twitter is an online public space, allowing autonomous and unrestricted debates on pertinent topics.

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Modelling and analysis of big data platform group adoption behaviour based on social network analysis

Cited by 10 publications

References 31 publications

Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review

Factor Influencing the Adoption of Big Data Analytics: A Systematic Literature and Experts Review

Antecedents of big data adoption in financial institutions

Social Network Analysis of Basic Necessity Scarcity on Twitter: Evidence from Indonesia

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