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Article
Publication date: 13 January 2023

Santoshi Sengupta and Sanjay Dhir

The purpose of this study is to understand the rational cogent correlation among the factors that are responsible for the implementation of entrepreneurship to reinstate the…

Abstract

Purpose

The purpose of this study is to understand the rational cogent correlation among the factors that are responsible for the implementation of entrepreneurship to reinstate the severely affected ecosystem during the coronavirus disease 2019 (COVID-19) pandemic.

Design/methodology/approach

This paper attempts to identify the various units of entrepreneurship and public policies of entrepreneurship from the coherent literature review and examine the units' objectives. Examination of these units will help understand how the economy can recover from the COVID-19 impact. Total interpretive structural modeling (TISM) and matrix impacts cross multiplication applique and classement (MICMAC) have been used to recognize the factors, which are responsible for detangling the slowdown of the economy.

Findings

On the basis of the literature review, a total of 13 factors have been identified. The TISM methodology represents the hierarchical structure of the recognized factors and examines the pros and cons.

Research limitations/implications

The TISM lags to explain the strength and bond among the factors. The MICMAC addresses this problem and advises what factor plays an essential role and which factor impact is the least. An advocate administration of the factors could help to achieve a successful entrepreneurial plan.

Originality/value

An analytic study of the literature review demonstrates the relationship among the units to frame an entrepreneurial plan during the COVID-19 pandemic by using the TISM methodology. Hence, TISM provides reasonable facts to examine why and what factors need more attention for the generation of new business starters in the economic crisis.

Details

Benchmarking: An International Journal, vol. 30 no. 10
Type: Research Article
ISSN: 1463-5771

Keywords

Article
Publication date: 14 September 2022

Mythili Boopathi, Meena Chavan, Jeneetha Jebanazer J. and Sanjay Nakharu Prasad Kumar

The Denial of Service (DoS) attack is a category of intrusion that devours various services and resources of the organization by the dispersal of unusable traffic, so that…

Abstract

Purpose

The Denial of Service (DoS) attack is a category of intrusion that devours various services and resources of the organization by the dispersal of unusable traffic, so that reliable users are not capable of getting benefit from the services. In general, the DoS attackers preserve their independence by collaborating several victim machines and following authentic network traffic, which makes it more complex to detect the attack. Thus, these issues and demerits faced by existing DoS attack recognition schemes in cloud are specified as a major challenge to inventing a new attack recognition method.

Design/methodology/approach

This paper aims to detect DoS attack detection scheme, termed as sine cosine anti coronavirus optimization (SCACVO)-driven deep maxout network (DMN). The recorded log file is considered in this method for the attack detection process. Significant features are chosen based on Pearson correlation in the feature selection phase. The over sampling scheme is applied in the data augmentation phase, and then the attack detection is done using DMN. The DMN is trained by the SCACVO algorithm, which is formed by combining sine cosine optimization and anti-corona virus optimization techniques.

Findings

The SCACVO-based DMN offers maximum testing accuracy, true positive rate and true negative rate of 0.9412, 0.9541 and 0.9178, respectively.

Originality/value

The DoS attack detection using the proposed model is accurate and improves the effectiveness of the detection.

Details

International Journal of Pervasive Computing and Communications, vol. 19 no. 5
Type: Research Article
ISSN: 1742-7371

Keywords

Article
Publication date: 6 February 2024

Sanjay Dhingra and Abhishek

This study aims to explore and conceptualize metaverse adoption using a systematic literature review (SLR). It also aims to propose a conceptual model that identifies significant…

Abstract

Purpose

This study aims to explore and conceptualize metaverse adoption using a systematic literature review (SLR). It also aims to propose a conceptual model that identifies significant factors affecting metaverse adoption in the entertainment, education, tourism and health sectors.

Design/methodology/approach

A SLR was conducted using the “preferred reporting items for systematic reviews and meta-analyses” report protocol and the “theory, context, characteristics, methods” framework to include all relevant articles published up to March 2023, which were sourced from the Scopus and Web of Science databases.

Findings

The reviewed literature revealed that the countries with the highest publications in the field of metaverse were China and the USA. It was also found that the technology acceptance model was the most used theoretical framework. Survey-based research using purposive and convenience sampling techniques emerged as the predominant method for data collection, and partial least square-structural equation modeling was the most used analytical technique. The review also identified the top six journals and the variables that help to develop a proposed model.

Originality/value

This review presents a novel contribution to the literature on metaverse adoption by forming a conceptual model that incorporates the most used variables in the entertainment, education, tourism and health sectors. The possible directions for future research with identified research gaps were also discussed.

Details

Global Knowledge, Memory and Communication, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9342

Keywords

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