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Article
Publication date: 11 July 2024

Ashish Kumar and V.P. Joshith

This research lies in the domain of Vedic mathematics, and it explores the application of the related Vedic sutras in different branches of mathematics, science, education, and…

Abstract

Purpose

This research lies in the domain of Vedic mathematics, and it explores the application of the related Vedic sutras in different branches of mathematics, science, education, and engineering across Asia and Europe.

Design/methodology/approach

The study embraced a qualitative research design followed by a systematic literature review (SLR) approach which describes the significance of Vedic mathematics. The study made use of purposive sampling through which the data were collected from 102 articles by using inclusion and exclusion criteria. It includes publication years, the types of research methods, and uses of Vedic mathematics sutras in different branches of knowledge stated by the researchers. Its goal is to offer a more thorough explanation and an evaluation of how the inquiry affected the conclusions. The articles examined in this review included all the journal articles and doctoral theses from the databases of Google Scholar, Science Direct, Scopus, and Sodhganga which were published during the period 2010–2022.

Findings

The research found that the application of the sutras of Vedic mathematics has been increasing immensely in India. The researchers in this area are fond of qualitative research methods. This research has shown that sutras of Vedic mathematics especially “Urdhvatiryakbhyam” and “Nikhilam Navatascaramana Dasastah” have been frequently used in mathematics and engineering in technical higher education. The impact of other sutras has been quite useful, which augments that in many disciplines where the applications of Vedic mathematics are prevalent, it can be functional. The study concludes by reprising the result, its limitations, and the use of Vedic mathematics as a sustainable source of knowledge.

Research limitations/implications

Vedic mathematics is an area where a lot of potential applications are created in science, mathematics, engineering, and education. Even with the latest technological advancements like learning analytics, artificial intelligence has its connection with this branch of learning, which is the greatest treasure of the Indian knowledge system. The research in this area is not reported in any databases or any standard format so researchers find it difficult to locate and study this broad conceptual domain.

Practical implications

It will help the reader and other academic stakeholders to widen their view on the new and innovative techniques of Vedic mathematics. It is advised that additional studies would look at and evaluate papers published after this time so that readers may get a wider view of the concept of Vedic mathematics.

Social implications

It will help society to know the essence of Vedic mathematics that how useful it is. Vedic mathematics helps learners to learn in a very factual and accurate manner especially while dealing with mathematical calculations. It will enhance the problem-solving skills among learners. It will be beneficial for all types of learners which will help them to become better individuals for a nation.

Originality/value

The paper enriches understanding of the potential applications of different sutras from Vedic literature in different fields of knowledge. The outcome of the research encourages educationists and policymakers to include Vedic mathematics in the curriculum to foster quantitative reasoning and problem-solving at varied levels of learning.

Details

International Journal of Comparative Education and Development, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2396-7404

Keywords

Article
Publication date: 7 May 2024

Michael Obal, Wesley Friske and Todd Morgan

The COVID-19 pandemic has presented small-to-medium size enterprises (SMEs) with a massive and unexpected challenge that has caused many to adjust their operational standards…

Abstract

Purpose

The COVID-19 pandemic has presented small-to-medium size enterprises (SMEs) with a massive and unexpected challenge that has caused many to adjust their operational standards. Perhaps the biggest change has been the shift to remote work and away from traditional office spaces. Thus, this study aims to explore the implications of this shift within the context of customer participation in the new product development (NPD) process.

Design/methodology/approach

Our study surveys 218 small-to-medium size business-to-business firms in the USA on a variety of questions revolving around their NPD processes, customer collaboration and the shift to remote work. The authors use structural equation modeling in the AMOS program to analyze the data.

Findings

The findings indicate that both customer participation breadth and customer participation depth positively impact new product performance. Furthermore, these relationships are found to be contingent upon whether firms rely on remote work during the collaboration process. The results show that accessing a broader variety of explicit customer insights (i.e., breadth) has become easier in the increasingly remote collaboration environment. However, as face-to-face customer participation in NPD has decreased, the prospect of gaining deep, tacit customer knowledge relevant to product development (i.e., depth) has become more challenging.

Originality/value

This study contributes to the knowledge-based view of the firm and the customer participation literature, and it also has implications for managers adjusting to the shift to remote work following the COVID-19 pandemic. The findings provide additional evidence that customer participation is an effective strategy for SMEs (Morgan et al., 2018), but remote work has both positive and negative implications regarding the type of external knowledge that is acquired during customer participation in NPD.

Details

Journal of Business & Industrial Marketing, vol. 39 no. 7
Type: Research Article
ISSN: 0885-8624

Keywords

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