Search results

The aim of this paper is to explore the brain–computer interface (BCI) as a methodology for generating awareness and increasing reliable use cases of the same so that an individual's quality of life can be enhanced via neuroscience and neural networks, and risk evaluation of certain experiments of BCI can be conducted in a proactive manner.

This paper puts forward an efficient approach for an existing BCI device, which can enhance the performance of an electroencephalography (EEG) signal classifier in a composite multiclass problem and investigates the effects of sampling rate on feature extraction and multiple channels on the accuracy of a complex multiclass EEG signal. A one-dimensional convolutional neural network architecture is used to further classify and improve the quality of the EEG signals, and other algorithms are applied to test their variability. The paper further also dwells upon the combination of internet of things multimedia technology to be integrated with a customized design BCI network based on a conventionally used system known as the message query telemetry transport.

At the end of our implementation stage, 98% accuracy was achieved in a binary classification problem of classifying digit and non-digit stimuli, and 36% accuracy was observed in the classification of signals resulting from stimuli of digits 0 to 9.

BCI, also known as the neural-control interface, is a device that helps a user reliably interact with a computer using only his/her brain activity, which is measured usually via EEG. An EEG machine is a quality device used for observing the neural activity and electric signals generated in certain parts of the human brain, which in turn can help us in studying the different core components of the human brain and how it functions to improve the quality of human life in general.

The purpose of this study is to comprehensively analyse and compare equity crowdfunding (ECF) regulations across 26 countries, shedding light on the diverse regulatory frameworks, investor and issuer limits and the evolution of ECF globally. By addressing this research gap and providing consolidated insights, the study aims to inform policymakers, researchers and entrepreneurs about the regulatory landscape of ECF, fostering a deeper understanding of its potential and challenges in various economies. Ultimately, the study contributes to the advancement of ECF as an alternative financing method for small and medium enterprises (SMEs) and startups, empowering them to access much-needed capital for growth.

The study used the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) model for a systematic literature review on global ECF regulations. Starting with 74 initial articles from Web of Sciences and Scopus databases, duplicates were removed and language criteria applied, leaving 42 articles. After a thorough full-text screening, 20 articles were excluded, resulting in the review of 22 papers from 2016 to 2022. PRISMA’s structured framework enhances the quality of systematic reviews, ensuring transparency and accessibility of findings for various stakeholders, including researchers, practitioners and policymakers, in the field of ECF regulations.

This study examines ECF regulations across various countries. Notably, the UK has advanced regulations, while the USA adopted them later through the Jumpstart Our Business Startups Act. Canada regulates at the provincial level. Malaysia and China were early adopters in Asia, but Hong Kong, Japan, Israel and India have bans. Turkey introduced regulations in 2019. New Zealand and Australia enacted laws, with Australia referring to it as “crowd-sourced equity funding”. Italy, Austria, France, Germany and Belgium have established regulations in Europe. These regulations vary in investor and issuer limits, disclosure requirements and anti-corruption measures, impacting the growth of ECF markets.

This study’s findings underscore the diverse regulatory landscape governing ECF worldwide. It reveals that regulatory approaches vary from liberal to protectionist, reflecting each country’s unique economic and political context. The implications of this research highlight the need for cross-country analysis to inform practical implementation and the effectiveness of emerging ECF ecosystems. This knowledge can inspire regulatory adjustments, support startups and foster entrepreneurial growth in emerging economies, ultimately reshaping early-stage funding for new-age startups and SMEs on a global scale.

This study’s originality lies in its comprehensive analysis of ECF regulations across 26 diverse countries, shedding light on the intricate interplay between regulatory frameworks and a nation’s political-economic landscape. By delving into the nuanced variations in investor limits, investment types and regulatory strategies, it unveils the multifaceted nature of ECF regulation globally. Furthermore, this research adds value by comparing divergent perspectives on investment constraints and offering an understanding of their impact on ECF efficacy. Ultimately, the study’s unique contribution lies in its potential to inform practical implementation, shape legislative frameworks and catalyse entrepreneurial ecosystems in emerging economies, propelling the evolution of early-stage funding practices.

In a volatile agricultural postharvest market, producers require more personalized information about market dynamics for informed decisions on the marketed surplus. However, this adaptive strategy fails to benefit them if the selection of a computational price predictive model to disseminate information on the market outlook is not efficient, and the associated risk of perishability, and storage cost factor are not assumed against the seemingly favourable market behaviour. Consequently, the decision of whether to store or sell at the time of crop harvest is a perennial dilemma to solve. With the intent of addressing this challenge for agricultural producers, the study is focused on designing an agricultural decision support system (ADSS) to suggest a favourable marketing strategy to crop producers.

The present study is guided by an eclectic theoretical perspective from supply chain literature that included agency theory, transaction cost theory, organizational information processing theory and opportunity cost theory in revenue risk management. The paper models a structured iterative algorithmic framework that leverages the forecasting capacity of different time series and machine learning models, considering the effect of influencing factors on agricultural price movement for better forecasting predictability against market variability or dynamics. It also attempts to formulate an integrated risk management framework for effective sales planning decisions that factors in the associated costs of storage, rental and physical loss until the surplus is held for expected returns.

Empirical demonstration of the model was simulated on the dynamic markets of tomatoes, onions and potatoes in a north Indian region. The study results endorse that farmer-centric post-harvest information intelligence assists crop producers in the strategic sales planning of their produce, and also vigorously promotes that the effectiveness of decision making is contingent upon the selection of the best predictive model for every future market event.

As a policy implication, the proposed ADSS addresses the pressing need for a robust marketing support system for the socio-economic welfare of farming communities grappling with distress sales, and low remunerative returns.

Based on the extant literature studied, there is no such study that pays personalized attention to agricultural producers, enabling them to make a profitable sales decision against the volatile post-harvest market scenario. The present research is an attempt to fill that gap with the scope of addressing crop producer's ubiquitous dilemma of whether to sell or store at the time of harvesting. Besides, an eclectic and iterative style of predictive modelling has also a limited implication in the agricultural supply chain based on the literature; however, it is found to be a more efficient practice to function in a dynamic market outlook.

This exploratory study aims to discover the different forms of challenges encountered by school stakeholders, including students, teachers, parents and management due to the coronavirus disease 2019 (COVID-19) pandemic.

Qualitative methodology was deployed for the study. A purposive sampling technique was used to select the respondents for a semi-structured interview. Data were examined using interpretative phenomenological analysis (IPA).

It was found that each stakeholder faced four different challenges: mental distress, physical immobility, financial crunches and technological concerns. Findings suggest that teachers are experiencing higher financial, technological and physical challenges as compared to other stakeholders followed by parents.

This paper discusses the major challenges faced by each stakeholder along with the opportunities. These findings will be useful for educationists, regulatory authorities, policymakers and management of educational institutions in developing countries to revisit their policy frameworks to develop new strategies and processes for the smooth implementation of remote learning during a period of uncertainty.

In this era of technological advancement, the capabilities of devices and telecommunications have changed the pattern of media consumption among consumers. This study examined the research landscape and advancements in OTT services.

This study adopted a hybrid review consisting of bibliometric and thematic analyses to present advancements in the OTT platforms. A hybrid review integrates both systematic and narrative approaches by emphasizing a literature search strategy and the study selection process.

This study focuses on previous literature to understand recent developments in the domain. The authors derive six major OTT themes: OTT infrastructure and technology advancement, OTT consumption behaviour, shifting trends towards OTT platforms, viewers’ engagement in digital media, OTT in the global market, OTT policies and regulatory mechanisms.

The findings of this study will be useful for marketers/stakeholders associated with the entertainment and media industries, such as sales promotion teams, media planners/advertisers, content management companies and policy regulators, to penetrate OTT viewers.

The literature related to OTT is progressively rising, but it remains highly fragmented because of inconsistencies in the methodologies and theories used in the domain of OTT. This study offers directions in terms of theory, methodology and future research on OTT services.

The mobile phone industry in India is highly competitive, fast paced and technology-driven. In such a hyper competitive era, effective advertising is considered a key success driver for a mobile phone brand. The purpose of this paper is to identify advertisement effectiveness dimensions for Indian mobile phone industry and to develop hierarchical interrelationships among these dimensions in the Indian print context.

Structured Delphi approach is used to derive the set of dimensions for advertisement effectiveness. Further, techniques such as interpretive structural modeling and MICMAC analysis are used to establish hierarchical linkages among identified dimensions.

On the basis of experts’ opinion, refinement through structured Delphi resulted in the identification of 14 advertisement effectiveness dimensions specific to Indian mobile phone industry. Interpretive structural modeling assisted in the development of linkages among these identified dimensions based on their interrelations. Further, attention, relevance, excitability, liking and consumer preference, etc., turned out to be the dimensions of utmost importance for measuring advertisement effectiveness for the Indian mobile phone industry.

The present research work is limited to the recognition and development of hierarchical interrelationships among advertisement effectiveness dimensions specific to mobile phone business in the Indian print context only. Further studies may be carried out for other product or service category in some different media context.

The present research has several significant implications for academics and advertising practitioners involved in designing and developing promotional campaigns for mobile phone brands in India. The identified 14 dimensions and developed hierarchical model provide valuable insights for improving advertisement effectiveness.

This paper demonstrated successful implementation of Delphi and interpretive structural modeling technique to explore the research area of advertisement effectiveness.

There is a lacuna in research work in terms of understanding how Indian IT organizations can become global brands. Benchmarking has not received much attention in marketing literature due to lack of benchmarking framework, and IT organizations are yet to make progress in benchmarking. The purpose of this paper is to examine the impact of brand strength on global branding by developing a conceptual benchmarking framework for Indian IT organizations.

Semi-structured in-depth interviews are conducted with thirty middle-level managers from two Indian IT organizations, two US-based global IT organizations and one UK-based leading bank, which is a customer of these IT organizations.

Results show a positive relationship between brand strength and global branding, between customer loyalty and global branding, between brand loyalty and competitive advantage and between global branding and competitive advantage. Indian IT organizations can benchmark global IT organizations to improve delivering brand promise, positioning, awareness building and authenticity toward making Indian IT organizations future ready to address the entire breadth of opportunities in the evolving world of cloud and digital.

This research helps managers with a brand strength-based benchmarking framework toward global branding of Indian IT organizations.

IT is instrumental for rapid growth of Indian’s economy. India should optimally utilize its greatest wealth, its human potential, with the latent global demand in IT through building global IT brands.

The originality of the study lies in conducting a qualitative study on global branding of Indian IT organizations and also proposing a conceptual benchmarking framework. The study further validates the model using qualitative analysis.