A Spectrum of Big Data Applications for Data Analytics

Chauhan, Ritu; Kaur, Harleen

doi:10.1007/978-3-319-16598-1_7

Cited by 14 publications

(2 citation statements)

References 24 publications

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“…Since the factor-loading value of the exploratory factor analysis on the variable items was higher than ±0.50, the extracted factors were deemed to secure the construct's validity [58]. In addition, Cronbach's α for each extracted factor was 0.60 or higher, showing that the data are reliable and internally consistent [59,60]. This study conducted factor analysis based on principal component analysis and used the Varimax rotation option.…”

Section: Reliability and Validity Analysismentioning

confidence: 99%

Empirical Finding on the Determinants of Collective Consumption: Focused on Consumption Values, Trust, and Perceived Risk

Park

Yoon

2022

Journal of Open Innovation: Technology, Market, and Complexity

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The rapid advances in information and communications technologies, combined with increased social awareness of today’s consumers, ushered in transformation in consumers’ purchase behavior. This big shift away from the traditional ownership-based economy into a sharing economy is causing an urgent necessity to understand the shifted decision mechanism. Although there have been quite a few previous studies on antecedents of consumers’ decision to engage in collective consumption, it is somewhat difficult to find previous research that focused on consumption values as antecedent predictors. To abridge this gap, this study aims to determine whether two predictors (social value and ethical value) affect consumers’ intention to utilize collective consumption. In addition, the current study verifies the role of perceived risk as a moderator between perceived trust and the intention to use collective consumption. For the purpose of hypothesis verification, the study uses multiple regression and hierarchical moderated regression analysis. Responses from a total of 246 respondents are used for statistical analysis. The respondents were selected from the students attending a university located in Seoul, South Korea. The results indicate that social value and ethical value exerted significant impacts on the perceived trust of collective consumption. However, the magnitude of the social value’s impact was slightly greater than that of ethical value. The result also confirms the mediating role of the perceived trust. Furthermore, perceived risk moderated the relationship between trust and the intention to utilize collective consumption.

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Section: Reliability and Validity Analysismentioning

confidence: 99%

Empirical Finding on the Determinants of Collective Consumption: Focused on Consumption Values, Trust, and Perceived Risk

Park

Yoon

2022

Journal of Open Innovation: Technology, Market, and Complexity

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“…The largely unstructured or fluid nature of Big Data puts it primarily in the domain of exploratory data analysis (Chauhan & Kaur, 2015) including predictive analytics and data mining. Big Data does not typically refer to large conventional (relational) databases, with structured data existing as well-defined variables, collected to examine specific a priori research questions, objectives, or hypotheses.…”

Section: Conceptualizing Big Datamentioning

confidence: 99%

A Foundation for Inductive Reasoning in Harnessing the Potential of Big Data

Hassad

2020

SERJ

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Training programs for statisticians and data scientists in healthcare should give greater importance to fostering inductive reasoning toward developing a mindset for optimizing Big Data. This can complement the current predominant focus on the hypothetico-deductive reasoning model, and is theoretically supported by the constructivist philosophy and Gestalt theory. Big-Data analytics is primarily exploratory in nature, aimed at discovery and innovation, and this requires fluid or inductive reasoning, which can be facilitated by epidemiological concepts (taxonomic and causal) as intuitive theories. Pedagogical strategies such as problem-based learning (PBL) and cooperative learning can be effective in this regard. Empirical research is required to ascertain instructors’ and practitioners’ perceptions about the role of inductive reasoning in Big-Data analytics, what constitutes effective pedagogy, and how core epidemiological concepts interact with the evidence from Big Data to produce outcomes. Together these can support the development of guidelines for an effective integrated curriculum for the training of statisticians and data scientists First published February 2020 at Statistics Education Research Journal Archives

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A Study on Sampling-Based Parameter Estimation Techniques in Big Data Analytics Environment

Alim

Shukla

2020

Intelligent Computing Applications for Sustainable Real-World Systems

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A Spectrum of Big Data Applications for Data Analytics

Cited by 14 publications

References 24 publications

Empirical Finding on the Determinants of Collective Consumption: Focused on Consumption Values, Trust, and Perceived Risk

Empirical Finding on the Determinants of Collective Consumption: Focused on Consumption Values, Trust, and Perceived Risk

A Foundation for Inductive Reasoning in Harnessing the Potential of Big Data

A Study on Sampling-Based Parameter Estimation Techniques in Big Data Analytics Environment

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