Factors influencing effective use of big data: A research framework

Surbakti, Feliks Prasepta Sejahtera; Wang, Wei; Indulska, Marta; Sadiq, Shazia

doi:10.1016/j.im.2019.02.001

Cited by 115 publications

(127 citation statements)

References 61 publications

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“…One of the latest studies of 2020 indicated that still a significant lacking of studies which highlights the most appropriate use of big data technology (Surbakti et al, 2020). The terminology is actually associated with large data sets i.e.…”

Section: Literature Reviewmentioning

confidence: 99%

“…of terabyte and exabyte (Rajeb, Rajeb & Keogh, 2020). However, there is also a significant probability for the increase of organizational data (Zanini & Dhawan, 2015) thus several studies which tries to explore challenges pertaining to big-data and most of these indicated further investigation of benefits which organizations may urge through using big-data (Surbakti et al, 2020). There was lack of evidence for the relationship of big-data and marketing functions but big-data provide companies way to create edge and value (Zeng & Glaister, 2018) However recent work of Rajeb et al (2020) highlighted that big-data is playing major role in improvement of functions like Marketing, supply chain as well as in process of decision making.…”

Section: Literature Reviewmentioning

confidence: 99%

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Sentiment Analysis through Big Data in online Retail Industry: A Conceptual Quantitative Study on linkage of Big-Data and Assortment Proactive of Online Retailers

Sultan

Jabeen

Mannan

2020

KJCIS

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Big-Data is the recent trend in data sciences prevailing all over the globe. The tool aids significantly in optimization of knowledge and has predominant use in optimization of knowledge and productivity. However, there is lack of understanding of concept and its application in Pakistan as indicated by Gallup Pakistan (2018) and stream of data is going to be doubled in two years’ time Tankard (2012). Therefore, there is a definite need of research which optimizes understanding associated with technology and its application from the context of Pakistan. Hence considering the application of big-data in retail sector this study aims to explore the impact of sentiment analysis through relating impact of big-data with effective assortment s of online stores. Although data has been collected from IT experts associated with online retail sector via quota sampling and SMART-PLS has been incorporated for the purpose of analysis. Results of the study highlights that big-data is perceived as the major tool for the betterment of assortment in online retail stores although data scientist and their applicability might diminish the impact of the use of big-data.

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

Sentiment Analysis through Big Data in online Retail Industry: A Conceptual Quantitative Study on linkage of Big-Data and Assortment Proactive of Online Retailers

Sultan

Jabeen

Mannan

2020

KJCIS

View full text Add to dashboard Cite

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“…Due to the unique big data challenges arising in the context of WFMS, not only these quantitative metrics themselves, but also an effective use becomes even more important [19,27]. In this context, the speed and ability to interpret data is closely related to a dimension of the 7V model, namely the visualization of metrics and data.…”

Section: Introductionmentioning

confidence: 99%

“…. Research AimFollowing authors such asSurbakti et al (2019) orOlszak & Zurada (2019), the effectiveness and speed of using insights into big data is a key factor in creating value for companies. As these abilities are closely linked to how information can be processed, this work aims at investigating how different visuali-Page 200…”

mentioning

confidence: 99%

Effects of Visualization Techniques on Understanding Inconsistencies in Automated Decision-Making

Corea¹,

Nagel²,

Delfmann³

2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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The automation of business processes and decision-making has received major interest from practice and academia. As automation allows us to execute more processes (cases), monitoring automated decision-making is currently evolving into a big data analytics problem for companies. Thus, not only monitoring insights themselves, but also an effective use of such insights become important. In this context, the speed and ability to interpret data is closely related to the visualization of metrics and data. While various approaches for quantitative insights on automated decision-making have been proposed, there is currently no evidence as to how the specific visualization of such metrics helps companies to create more value from their data. In this report, we therefore present the results of an empirical experiment analyzing the cognitive effects of different visualization techniques for quantitative insights on understanding inconsistencies in automated decisionmaking data.

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“…Their study also indicates that profitability is likely to affect adoption rates". Surbakti et al (2020), identified 41 factors affecting Big Data technology adoption. They however categorized these factors into seven themes including the following categories: data quality, data privacy and security and governance, perceived organizational benefit, process management, people aspects, systems, tools, and technologies, and organizational aspects.…”

Section: Factors Affecting Technology Adoption In Agriculturementioning

confidence: 99%

Big Data On Midwest Farms: Assessment Of Use, Concerns, And Challenges

Adomako¹

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Factors influencing effective use of big data: A research framework

Cited by 115 publications

References 61 publications

Sentiment Analysis through Big Data in online Retail Industry: A Conceptual Quantitative Study on linkage of Big-Data and Assortment Proactive of Online Retailers

Sentiment Analysis through Big Data in online Retail Industry: A Conceptual Quantitative Study on linkage of Big-Data and Assortment Proactive of Online Retailers

Effects of Visualization Techniques on Understanding Inconsistencies in Automated Decision-Making

Big Data On Midwest Farms: Assessment Of Use, Concerns, And Challenges

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