Search results

The research methodology used for this case study follows a comprehensive approach, combining both primary and secondary sources to ensure a well-rounded understanding of the subject. Primary sources include in-depth interviews with the founders of the company, providing valuable firsthand insights into their experiences and decision-making processes. Multiple company visits were also conducted, enabling a closer examination of the operational aspects and allowing for a more holistic perspective on the case. Complementing these primary sources, secondary sources were used, consisting of a diverse array of articles from leading journals, newspapers, magazines and other reputable sources. These secondary sources offer a broader context and perspective, enriching the case study’s content and ensuring a robust foundation for classroom discussion and analysis.

True Elements was a clean health food brand that emerged from the vision of Mr Sreejith Moolayil and co-founder, Mr Puru Gupta, who recognized the potential of promoting healthy foods in India inspired by the health-conscious lifestyle that they observed during their work tenure in China. The co-founders began their entrepreneurial journey in 2011 with “Healthy World” kiosks inside IT company campuses in Delhi, Mumbai and Pune. However, early challenges surfaced as the target market narrowed. Undeterred, the founders sought innovative solutions to expand their reach and created “True Elements” – a brand that resonated with health-conscious consumers given its positioning as a clean and minimally processed food brand devoid of chemicals, preservatives and added sugars. True Elements excelled in the online market and catered to a few offline markets. To sustain and augment their success, the entrepreneurs sought a strategic partnership and succeeded with Marico Ltd. However, challenges remained on the horizon. One was the need to appeal to a new target group: the 25–45 age group with a lower monthly income of INR 30,000. Another pressing question was exploring the entry into the modern trade sector.

This case can be taught in undergraduate and post-graduate business management programs for marketing, strategy and innovation and entrepreneurship related courses. Apart from that, this case can also be discussed in incubator programs as cases highlighting entrepreneurship can facilitate discussions among early-stage founders, providing practical insights and lessons for their ventures. This case also can be discussed very effectively in management classes for working executives.

This study aims to develop a database of existing academic information in house purchase decision (HPD) using systematic literature review (SLR), to facilitate worldwide advancement of research under HPD domain.

This research examined papers from two reputable databases – Scopus and Google Scholar – from 1992 to 2022 using a scoping review technique (Arksey and O’Malley, 2005) and a theme analysis method. Out of 374, 181 articles fit the inclusion parameters and were evaluated using the theme analysis approach.

Data from 181 articles was evaluated thematically to create a thematic map of HPD research. Five main themes and their sub-themes were identified: consumer behaviour, housing attributes, factors influencing purchasing decisions, investment analysis and demographics, which proved essential in understanding HPD and customer preferences for house purchase.

Data from 181 articles were evaluated thematically to create a thematic map of HPD research. This SLR intends to provide useful new insights on consumer concerns about home purchases in the rapidly developing residential real estate market and the issues that marketers, housing sector stakeholders, real estate industry and existing and future researchers should prioritize.

This research is unique such that it is the only 30-year-long SLR on the subject matter of HPD. This paper makes a significant contribution to residential real estate domain signifying the present state of research in HPD.

Unlike many existing methods that are primarily focused on two-dimensional localization, this research paper extended the scope to three-dimensional localization. This enhancement is particularly significant for unmanned aerial vehicle (UAV) applications that demand precise altitude information, such as infrastructure inspection and aerial surveillance, thereby broadening the applicability of UAV-assisted wireless networks.

The paper introduced a novel method that employs recurrent neural networks (RNNs) for node localization in three-dimensional space within UAV-assisted wireless networks. It presented an optimization perspective to the node localization problem, aiming to balance localization accuracy with computational efficiency. By formulating the localization task as an optimization challenge, the study proposed strategies to minimize errors while ensuring manageable computational overhead, which are crucial for real-time deployment in dynamic UAV environments.

Simulation results demonstrated significant improvements, including a channel capacity of 99.95%, energy savings of 89.42%, reduced latency by 99.88% and notable data rates for UAV-based communication with an average localization error of 0.8462. Hence, the proposed model can be used to enhance the capacity of UAVs to work effectively in diverse environmental conditions, offering a reliable solution for maintaining connectivity during critical scenarios such as terrestrial environmental crises when traditional infrastructure is unavailable.

Conventional localization methods in wireless sensor networks (WSNs), such as received signal strength (RSS), often entail manual configuration and are beset by limitations in terms of capacity, scalability and efficiency. It is not considered for 3-D localization. In this paper, machine learning such as multi-layer perceptrons (MLP) and RNN are employed to facilitate the capture of intricate spatial relationships and patterns (3-D), resulting in enhanced localization precision and also improved in channel capacity, energy savings and reduced latency of UAVs for wireless communication.

The purpose of this study is to identify and validate the key consumer-related factors influencing consumer attitude toward electric vehicles (EVs) and intention to purchase EVs. The role of consumer attitude in mediating consumer-related factors and intention to buy is also explored in this study. Consumer-related factors considered in this study include environmental orientation (EO), new technology orientation (NTO), social orientation (SO) and perceived monetary benefits (PMB).

Data for the study were collected from individuals who do not own an EV in Chennai, Tamil Nadu, India. Data were collected from 388 respondents using Google Forms. Convenience sampling technique was used to identify the respondents. Both descriptive and inferential statistics techniques were used to analyze data collected.

The study identified EO, SO and PMB as antecedents of attitude (ATT) toward EV and NTO, SO and PMB as potential drivers of EV purchase intention (PI). In addition, the authors also observe that EO is fully mediated by ATT toward consumer PI, whereas ATT partially mediates the relationship between the independent variables SO and PMB and the dependent variable PI.

EVs are at the forefront of automotive innovation. Automobile industries producing EVs showcase a commitment to embracing cutting-edge technology, positioning their companies as forward-thinking and technologically advanced. Creating awareness about EV technology, dispelling myths about range anxiety and charging times should be done methodologically. The lower operating costs of EVs and the government policies that reduce the total cost of ownership can lead to faster market penetration. The widespread adoption of EVs can contribute to a nation’s economic growth by adding new businesses in the industry, infrastructure development and job creation.

The reduced environmental impact of EVs, such as improved air quality and reduced greenhouse gas emissions, can lead to significant societal benefits in terms of better human health and mitigating the effects of climate change. Governments can leverage these benefits to achieve climate targets and improve public health.

Studies about EV diffusion and adoption in India are yet to gain momentum considering the slow penetration of EVs in the Indian automobile market. The Indian Government is enforcing policies and incentives to accelerate the adoption of EVs. However, without understanding the drivers of consumer EV adoption, it is difficult for policymakers to accelerate the growth of the EV market. The present study is one step toward understanding the same in its original sense.

Quality 4.0 is essential to the Industry 4.0 framework, notably in the electronics sector. It evaluates product quality in real-time using automatic process controls, quality tools and procedures. The implementation of Quality 4.0 criteria in the electronics industry is the subject of this study’s investigation and analysis. In this study, nine Customer Requirements (CRs) and 18 Design Requirements (DRs) have been defined to adopt Quality 4.0, aiming to increase yield while reducing defects. This study has developed a Quality 4.0 framework for effective implementation, incorporating the People, Process and Technology categories.

Many CRs and DRs of Quality 4.0 exhibit interdependencies. The Analytic Network Process (ANP) considers interdependencies among the criteria at various levels. Quality Function Deployment (QFD) can capture the customer’s voice, which is particularly important in Quality 4.0. Therefore, in this research, we use an integrated ANP-QFD methodology for prioritizing DRs based on the customers' needs and preferences, ultimately leading to better product and service development.

According to the research findings, the most critical consumer criteria for Quality 4.0 in the electronics sector are automatic systems, connectivity, compliance and leadership. The Intelligent Internet of Things (IIOTs) has emerged as the most significant design requirement that enables effective control in production. It is observed that robotics process automation and a workforce aligned with Quality 4.0 also play crucial roles.

Existing literature does not include studies on identifying CRs and DRs for implementing Quality 4.0 in the electronics industry. To address this gap, we propose a framework to integrate real-time quality measures into the Industry 4.0 context, thereby facilitating the implementation of Quality 4.0 in the electronics industry. This study can provide valuable insights for industry practitioners to implement Quality 4.0 effectively in their organizations.

This study attempts to recognize obstacles and barriers to financial inclusion in the agriculture sector, propose a framework based on the inter-contextual link between the barriers and understand the financial exclusion in the agriculture sector at the grassroots level. Previously published research articles were used to identify the barriers to financial inclusion, followed by informal interviews and collaborative discussions with the local farmers of the Sonipat district of Haryana and expert interviews using a structured questionnaire. TISM and MICMAC analysis are used to decern the nature of the relationship among the barriers discovered. The authors find that inadequate financial literacy, a shortage of financial awareness and the reluctance of various financial institutions are significant linkage barriers to strong driving and dependence power. High transaction costs and poor infrastructural support are the independent barriers. The paper identifies these new barriers to financial inclusion in the Indian agriculture sector and the framework depicting financial exclusion in India. This paper only gives a framework of barriers and does not quantify the effect of any relationship identified, but strongly emphasizes granting the Indian agriculture sector broad and simple financial access to advance and strengthen the nation's sustainable, inclusive economic growth.

COVID entered the world in 2019 as a pandemic and the intensity of this health crisis is only increasing in several regions. Therefore, it is critical to study and detect the public's frame of mind, government and economists' perception regarding the COVID crisis, as well as the primary worries that the public has expressed, and how this evolves over time. Responsive measures towards COVID-19 from the Indian economy have been explored as a key objective. Moreover, efforts have been made to explore recovery in India through economists and policymakers. Data have been explored through online interviews of key economists which were published in leading newspapers and covered through media channels such as NDTV, CNBC, etc. Moreover, various newspapers and reports were explored to understand government initiatives to address COVID-19 in India. The study's findings show how essential economic recovery from the second wave is in India, and how it may be achieved by strong fiscal and monetary policies, as well as specific attention to impoverished households, small and micro-businesses and increased employment. The short-term focus of the developing economic strategy must be on giving crisis relief to the most unprotected segments of society since long-term system stimulation is impossible.

Blockchain technology (BCT) can play a vital role in manufacturing industries by providing visibility and real-time transparency. With BCT adoption, manufacturers can achieve higher productivity, better quality, flexibility and cost-effectiveness. The current study aims to prioritize the performance metrics and ranking of enablers that may influence the adoption of BCT in manufacturing industries through a hybrid framework.

Through an extensive literature review, 4 major criteria with 26 enablers were identified. Pythagorean fuzzy analytical hierarchy process (AHP) method was used to compute the weights of the enablers and the Pythagorean fuzzy combined compromise solution (Co-Co-So) method was used to prioritize the 17-performance metrics. Sensitivity analysis was then carried out to check the robustness of the developed framework.

According to the results, data security enablers were the most significant among the major criteria, followed by technology-oriented enablers, sustainability and human resources and quality-related enablers. Further, the ranking of performance metrics shows that data hacking complaints per year, data storage capacity and number of advanced technologies available for BCT are the top three important performance metrics. Framework robustness was confirmed by sensitivity analysis.

The developed framework will contribute to understanding and simplifying the BCT implementation process in manufacturing industries to a significant level. Practitioners and managers may use the developed framework to facilitate BCT adoption and evaluate the performance of the manufacturing system.

This study can be considered as the first attempt to the best of the author’s knowledge as no such hybrid framework combining enablers and performance indicators was developed earlier.

Integrating additive manufacturing (AM) tools in traditional mold-making provides complex yet affordable sand molds and cores. AM processes such as selective laser sintering (SLS) and Binder jetting three-dimensional printing (BJ3DP) are widely used for patternless sand mold and core production. This study aims to perform an in-depth literature review to understand the current status, determine research gaps and propose future research directions. In addition, obtain valuable insights into authors, organizations, countries, keywords, documents, sources and cited references, sources and authors.

This study followed the systematic literature review (SLR) to gather relevant rapid sand casting (RSC) documents via Scopus, Web of Science and EBSCO databases. Furthermore, bibliometrics was performed via the Visualization of Similarities (VOSviewer) software.

An evaluation of 116 documents focused primarily on commercial AM setups and process optimization of the SLS. Process optimization studies the effects of AM processes, their input parameters, scanning approaches, sand types and the integration of computer-aided design in AM on the properties of sample. The authors performed detailed bibliometrics of 80 out of 120 documents via VOSviewer software.

This review focuses primarily on the SLS AM process.

A SLR and bibliometrics using VOSviewer software for patternless sand mold and core production via the AM process.

This research aims to conduct a literature review of Lean Six Sigma (LSS) in the Indian context and related research publications and apply bibliometric analysis and the author's visualization to map research trends in this area.

This article conducts a bibliometric analysis of LSS-related research in the Indian context using data gathered from Scopus and Web of Science databases from 2011 to 2022. The review provides information on LSS-related research in the Indian context and evaluates performance based on primary sources, authors, keywords, countries, affiliations, and documents. The analysis employs the Biblioshiny app and Bibliometrix R-tool for data analysis and scientific mapping.

The results of the bibliometric analysis indicate that the LSS culture has widely spread in India. The International Journal of Lean Six Sigma and Production Planning and Control were found to be the most productive sources for publishing LSS-related research articles. Antony J. was identified as the most active author in this field, contributing the most over the years. Among all organizations, NITs have conducted the most comprehensive research on LSS, indicating their significant investment of resources and efforts in studying this methodology and its applications in India. Additionally, the study examined the intellectual, social, and conceptual structures to identify implicit gaps and future research opportunities.

The findings of this study can inform academicians, researchers, practitioners, and policymakers about the state-of-the-art and the specifics of the most prolific studies. This study will facilitate their exploration of emerging research areas in LSS.

To the best of the authors knowledge, this is the first bibliometric analysis of LSS in the Indian context, providing an overview of relevant publications published between 2011 and 2022. This study analyzed 194 articles on LSS in India, which can help researchers and academics identify emerging research areas, suitable collaborators, and relevant journals for future publications.