Intention to Adopt Big Data in Supply Chain Management: A Brazilian Perspective

Queiroz, Maciel M.; Pereira, Susana Carla Farias

doi:10.1590/s0034-759020190605

Cited by 14 publications

(13 citation statements)

References 68 publications

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“…consider the predicted performance in the UTAUT as the expected performance in the technology adoption model and consideration it as a critical part of the proposal to the technology acceptor . The statistically direct relationship in the context of performance expectancy and behaviour BDA intention is confirmed by several studies (Cabrera-Sánchez & Villarejo-Ramos, 2019;Chao, 2019;Queiroz, & Farias, 2019).…”

Section: Hypothesissupporting

confidence: 63%

“…The findings of the study show two key determinant factors of behavioral intention to use BDA in Malaysian government agencies. The assumption that the technology is going to yield decent results raises the performance expectancy, as seen in past studies (Cabrera-Sánchez & Villarejo-Ramos, 2019;Brünink, 2016;Chao, 2019;Queiroz, & Farias, 2019) who found that expected results have positive and significant repercussions on BDA adoption. This indicates perception of, as has been shown in previous studies, the implementation of BDA (better decision making, competitiveness, improve services, strategic planning, new innovation in services etc.)…”

Section: Discussionmentioning

confidence: 92%

“…However, trust does not affect the behavioral intention of implementing BD in government agencies, therefore it contradicts and is not consistent with previous studies (eg. Shahbaz et al 2019;Queiroz & Pereira, 2019;Alalwan, Dwivedi & Rana, 2017). It could be clarified that this discrepancy is due to the difficulty of the government agencies in Malaysia and its departments to protect the data privacy of the public.…”

Section: Discussionmentioning

confidence: 99%

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

Sahid

Sani

Noordin

et al. 2021

JIEM

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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.

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Section: Hypothesissupporting

confidence: 63%

Section: Discussionmentioning

confidence: 92%

Section: Discussionmentioning

confidence: 99%

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

Sahid

Sani

Noordin

et al. 2021

JIEM

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“…Oliveira et al (2014) considered the predicted performance in the UTAUT as the expected performance in the technology adoption model and consideration it as a critical part of the proposal to the technology acceptor (Oliveira et al, 2014). The statistically direct relationship in the context of performance expectancy and behaviour BDA intention is confirmed by several studies (Cabrera-Sánchez & Villarejo-Ramos, 2019;Chao, 2019;Queiroz & Farias, 2019).…”

Section: H6: the Task-technology Fit Has A Positive Effect On Users' Behavioral Intent In Adopting Bda In Government Agenciesmentioning

confidence: 79%

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

Sani

Zaini

Sahid

et al. 2021

IJBS

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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.

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“…Chondrichthyes represents one of the most threatened marine taxa worldwide [1], and its species are highly susceptible to anthropogenic pressure, both in coastal and offshore environments [2,3]. In particular, the main factor affecting these vulnerable organisms is bycatch (incidental catch), which needs to be reduced to correctly manage and conserve cartilaginous fishes [4].…”

Section: Introductionmentioning

confidence: 99%

Filling the Gap and Improving Conservation: How IUCN Red Lists and Historical Scientific Data Can Shed More Light on Threatened Sharks in the Italian Seas

et al. 2020

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Chondrichthyans are one of the most threatened marine taxa worldwide. This is also the case in the Mediterranean Sea, which is considered an extinction hotspot for rays and sharks. The central position of the Italian peninsula makes it an ideal location for studying the status and changes of this sea. There is a lack of biological, ecological and historical data when assessing shark populations, which is also highlighted in the Red List of Threatened Species compiled by the International Union for the Conservation of Nature (IUCN). Historical data can provide important information to better understand how chondrichthyan populations have changed over time. This study aims to provide a clearer understanding of the changes in distribution and abundance of eight shark species in the Italian seas that are currently classified as at risk of extinction by the IUCN. In this respect, a bibliographic review was conducted on items from the 19th century to the first half of the 20th century, focusing on the selected species. The results show that all sharks were considered common until the beginning of the 20th century but have declined since, with a clear negative trend, mainly in the past 70 years. The strong local decline has been attributed to overexploitation, bycatch, habitat loss, depletion of prey items and environmental pollution. Furthermore, historical data also allow us to avoid the issue of a ‘shifting baseline’, in which contemporary abundances are assumed to be “normal”. Using historical data to further our knowledge of the marine environment is becoming increasingly common, and is fundamental in understanding human impact and evaluating mitigation measures to manage and conserve marine species and environments.

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Intention to Adopt Big Data in Supply Chain Management: A Brazilian Perspective

Cited by 14 publications

References 68 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

Filling the Gap and Improving Conservation: How IUCN Red Lists and Historical Scientific Data Can Shed More Light on Threatened Sharks in the Italian Seas

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