Applications of big data in emerging management disciplines: A literature review using text mining

Kushwaha, Amit Kumar; Kar, Arpan Kumar; Dwivedi, Yogesh K.

doi:10.1016/j.jjimei.2021.100017

Cited by 202 publications

(68 citation statements)

References 107 publications

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“…The importance of big data (BD) in creating a CA has been recognized by numerous scholars (Mikalef et al, 2020a, b;Ramadan et al, 2020;Gupta et al, 2018;Kushwaha et al, 2021) because BD has huge potential to revolutionize various fields of knowledge in general and the field of business and decision sciences (Fosso Wamba et al, 2019;Wamba et al, 2018).…”

Section: Theoretical Framework and Hypothesis Development 21 Big Data...mentioning

confidence: 99%

Can big data analytics capabilities promote a competitive advantage? Green radical innovation, green incremental innovation and data-driven culture in a moderated mediation model

Al-Khatib¹

2022

BPMJ

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PurposeThis study explores the connection between big data analytics capabilities and the competitive advantage of the manufacturing sector in Jordan through the mediating role of green radical innovation and green incremental innovation as well as the moderating role of a data-driven culture.Design/methodology/approachFor the purpose of this study, 356 questionnaires were analysed. Convergent validity and discriminant validity tests were performed through structural equation modelling in the Smart-PLS programme, and the data reliability was confirmed. A bootstrapping technique was used to analyse the data. The mediating effect for green radical and green incremental innovation and the moderating effect for data-driven culture were performed.FindingsThe empirical results showed that the proposed moderated-mediation model was accepted because the relationships between the constructs were statistically significant. The results of the data analysis supported a positive relationship between big data analytics capabilities and the competitive advantage as well as a mediating effect of green radical innovation and green incremental innovation. It was confirmed that there is a moderating relationship for data-driven culture between green radical innovation, green incremental innovation and competitive advantage.Research limitations/implicationsThis cross-sectional study provides a snapshot at a given moment in time, a methodological limitation that affects the generalization of its results, and the results are limited to one country.Originality/valueThis research developed a theoretical model to incorporate big data analytics capabilities, green radical innovation, green incremental innovation, data-driven culture, and competitive advantage. This study provides new findings that bridge the existing research gap in the literature by testing the moderated mediation model with a focus on the organizational benefits of big data analytics capabilities to improve levels of green innovation and competitive advantage in the Jordanian manufacturing sector.

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Section: Theoretical Framework and Hypothesis Development 21 Big Data...mentioning

confidence: 99%

Can big data analytics capabilities promote a competitive advantage? Green radical innovation, green incremental innovation and data-driven culture in a moderated mediation model

Al-Khatib¹

2022

BPMJ

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“…In this day and age, the development of high-throughput technologies has resulted in exponential increase in harvested information [1]. is exponential growth termed as "big data" (BD) is in terms of both dimensionality and sample size.…”

Section: Introductionmentioning

confidence: 99%

Big Data Value Calculation Method Based on Particle Swarm Optimization Algorithm

Hou

2022

Computational Intelligence and Neuroscience

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SI is a relatively recent technology that was inspired by observations of natural social insects and artificial systems. This system comprises multiple individual agents who rely on collective behavior in decentralized and self-organized networks. One of the biggest difficulties for existing computer techniques is learning from such large datasets, which is addressed utilizing big data. Big data-based categorization refers to the challenge of determining which set of classifications a new discovery belongs to. This classification is based on a training set of data that comprises observations that have been assigned to a certain category. In this paper, CIN-big data value calculation based on particle swarm optimization (BD-PSO) algorithm is proposed by operating in local optima and to improve the operating efficiency. The convergence speed of the particle swarm optimization (PSO), which operates in the local optima, is improved by big data-based particle swarm optimization (BD-PSO). It improves computing efficiency by improving the method, resulting in a reduction in calculation time. The performance of the BD-PSO is tested on four benchmark dataset, which is taken from the UCI. The datasets used for evaluation are wine, iris, blood transfusion, and zoo. SVM and CG-CNB are the two existing methods used for the comparison of BD-PSO. It achieves 92% of accuracy, 92% of precision, 92% of recall, and 1.34 of F1 measure, and time taken for execution is 149 ms, which in turn outperforms the existing approaches. It achieves robust solutions and identifies appropriate intelligent technique related to the optimization problem.

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“…Moreover, STDs can be central in helping the government to gain first-hand information about epidemics (Jia et al 2012 ) or in sharing real-time information in different response stages and support local governments’ decision-making (Aldunce et al 2015 ). Furthermore, Big Data and Analytics have helped tourists stuck in travelling countries to come back to their home countries with the travel restriction in the Covid-19 pandemics (Kushwaha et al 2021 ).…”

Section: Literature Reviewmentioning

confidence: 99%

How to exploit Big Social Data in the Covid-19 pandemic: the case of the Italian tourism industry

et al. 2022

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From March 2020, restrictive measures have been taken to limit the Covid-19 pandemic, thus impacting and hugely affecting the tourism industry. In this new scenario, tourism destination managers and stakeholders need to look ahead to the future, trying to wisely react to overcome this crisis. This paper aims at demonstrating how a Smart Tourism Destination can tackle the consequences of the Covid-19 pandemic using smart and digital technologies such as Big Data and Analytics. In particular, the monitoring of Italian public debates on social media allowed discovering knowledge from unstructured data that provide valuable insights for destination stakeholders and decision-makers.

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Applications of big data in emerging management disciplines: A literature review using text mining

Cited by 202 publications

References 107 publications

Can big data analytics capabilities promote a competitive advantage? Green radical innovation, green incremental innovation and data-driven culture in a moderated mediation model

Can big data analytics capabilities promote a competitive advantage? Green radical innovation, green incremental innovation and data-driven culture in a moderated mediation model

Big Data Value Calculation Method Based on Particle Swarm Optimization Algorithm

How to exploit Big Social Data in the Covid-19 pandemic: the case of the Italian tourism industry

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