Search results

Diagnosing the crop diseases by farmers accurately with the naked eye can be challenging. Timely identification and treating these diseases is crucial to prevent complete destruction of the crops. To overcome these challenges, in this work a light-weight automatic crop disease detection system has been developed, which uses novel combination of residual network (ResNet)-based feature extractor and machine learning algorithm based classifier over a real-time crop dataset.

The proposed system is divided into four phases: image acquisition and preprocessing, data augmentation, feature extraction and classification. In the first phase, data have been collected using a drone in real time, and preprocessing has been performed to improve the images. In the second phase, four data augmentation techniques have been applied to increase the size of the real-time dataset. In the third phase, feature extraction has been done using two deep convolutional neural network (DCNN)-based models, individually, ResNet49 and ResNet41. In the last phase, four machine learning classifiers random forest (RF), support vector machine (SVM), logistic regression (LR) and eXtreme gradient boosting (XGBoost) have been employed, one by one.

These proposed systems have been trained and tested using our own real-time dataset that consists of healthy and unhealthy leaves for six crops such as corn, grapes, okara, mango, plum and lemon. The proposed combination of Resnet49-SVM and ResNet41-SVM has achieved accuracy of 99 and 97%, respectively, for the images that have been collected from the city of Kurukshetra, India.

The proposed system makes novel contribution by using a newly proposed real time dataset that has been collected with the help of a drone. The collected image data has been augmented using scaling, rotation, flipping and brightness techniques. The work uses a novel combination of machine learning methods based classification with ResNet49 and ResNet41 based feature extraction.

This paper aims to assess the factors favoring the adoption of the challenges faced and support mechanism, which will lead to the proliferation of glass fiber-reinforced gypsum (GFRG) technology in India.

Semi-structured interviews with 35 experts, including construction developers, architects, contractors, government officials and design consultants, were conducted. This qualitative data was analyzed using thematic analysis and matrix analysis.

GFRG-based buildings produce much less carbon footprints as compared to traditional ones and can be safely recommended as a promising, environmentally sensitive technology of the future. The major drivers in its adoption are its efficient construction capability, energy and soil conservation and significant waste reduction. Some of the challenges in implementation are long planning time, lack of skilled labor, lack of awareness about green building technologies and myopic perception of high cost incurred in green building adoption in people’s minds.

This study establishes that the construction industry has the potential to contribute toward creating a sustainable and green planet. It does so by evaluating and then positively positioning GFRG as an environmentally friendly building system.

The harmful effects of continuous environmental manipulation by humans leading to its degradation is a critical discussion agenda for most nations of the world. The issue has been taken up seriously by developing countries, and now, developing countries are also becoming sensitised to it. Several policies toward the attainment of this goal have been formulated and are being implemented by government and private bodies. Although some authors have studied the issues and challenges related to the adoption of green buildings, their attempts mostly focused on developed countries. Moreover, research that investigated the evaluation of the GFRG building system as a successful green technology of the future is inadequate.

In recent years, significant research has focused on the question of whether severe market periods are accompanied by herding behavior. As herding behavior is a considerable cause of the speculative bubble and leads to stock market deviations from their basic values it is necessary to examine the motivators which led to herding behavior among investors. The paper aims to discuss this issue.

In this study, the authors performed a two-phase analysis to address the research questions of the study. In the first phase, for text analysis NVivo software was used to identify the factors driving herding behavior among Indian stock investors. The analysis of a text was performed using word frequency analysis. While in the second phase, the Fuzzy-AHP analysis techniques were employed to examine the relative importance of all the factors determined and assign priorities to the factors extracted.

Results of the study depicted Investor Cognitive Psychology (ICP), Market Information (MI), Stock Characteristics (SC) as the top-ranked factors driving herding behavior, while Socio-Economic Factors (SEF) emerged as the least important factor driving herding behavior.

The current study was undertaken among stock investors from North India only. Moreover, numerous factors are not part of the study but might significantly influence the investors' herding behaviors.

Comprehending the influences of the different factors discussed in the study would enable stock investors to be more aware of their investment choices and not resort to herd behavior. This research enables decision-makers to understand the reasons for herd activity and helps them act accordingly to improve the stock market's performance.

The current study will provide an inclusive overview of herding behavior motivators among Indian stock investors. This study's results can be extremely useful for both academics and policymakers to gain some insight into the functioning of the Indian stock market.

The behavioural decision-making process of individuals highlights the importance of investors’ sentiment and their correlation with the real economy. This paper aims to contribute to the literature of behavioural finance by examining the influence of contextual factors on investment decision-making.

Using a questionnaire, a total of 445 valid responses were collected from March to May 2021 through online sources. The current study uses a technique of Fuzzy-analytical hierarchical process (AHP) to assign relative weights to various contextual factors influencing investment decision-making. Harman’s single factor test was used to check common method bias.

Results of the study reveal that accounting information, self-image/firm-image coincidence, and neutral information as the top-ranked factors in influencing investment decisions, whereas advocate recommendation and personal financial needs emerged as less important factors in influencing investment decisions.

The current study collects data from Indian stock market investors, which may limit the generalization of the study to India only. Moreover, this study is cross-sectional in nature, and there are numerous factors that are not part of the study but might significantly influence the investors’ decision-making process.

The research has implications for both academicians working in the area of behavioural finance and practitioners’ who are active in stock markets, more specifically dealing with retail investors and in the domain of personal finance. Also, the current study will accommodate different groups, i.e. policy makers, financial advisors, investors, investment professionals, etc. in carrying out their professional work.

The current study will provide a comprehensive overview of individual investor behaviour. To the best of the authors’ knowledge, the present study is one of its kind to use the Fuzzy-AHP technique for evaluating the relative ranks of contextual factors influencing investment decision-making.

Advanced bibliometric methods have emerged as key tools in mapping the history and trends of a discipline. This paper aims to demonstrate on applying various bibliometric methods to track a journal’s impact and review its knowledge contribution. In doing so, the authors take the case of IIMB Management Review (IMR) journal focused on management discipline, in consideration of its 10 years of publication presence.

Using bibliometric and Scopus metric methods, the authors map and analyze the productivity of IMR Journal and map its knowledge contributions.

The authors identify the IMR journal’s impact, its growth, the most prolific authors/affiliations, key research hotspots, cross-country collaboration and emerging trends over the past decade.

A 10-year longitudinal review helps the target group identify the main themes. It also provides key empirical insights to the journal editorial board and library managers for future planning and growth of the journal.

The study aims to explore and establish the relationship that exists between board independence and corporate social responsibility (CSR) practices of Indian firms.

A sample of 76 non-financial companies listed on the National Stock Exchange has been considered for a period of seven years (from 2013 to 2019). The study has used several statistical tools such as the static panel data model and the Arellano–Bond dynamic panel data model based on generalized method of moments approach.

The results of the analysis have indicated board independence to have a significant positive relationship with the firms’ CSR performance. However, board size and number of board meetings have been found to have a negative relationship with CSR. Further, outcomes have also revealed that variables such as companies’ size and liquidity have a positive effect on the extent of CSR activities performed.

The firms which have the intention to engage in impactful CSR activities should support the independent directors’ participation in companies’ boards. The study’s findings suggest the companies to appoint independent directors strategically, keeping in mind the requirements of their board. Also, the independent directors selected should be independent in true sense, i.e. they should not be acquaintances of the company’s chief executive officer. This would ensure unbiased decision-making and would enhance the company’s CSR performance.

In India, CSR has gained great importance. So much so that it was made mandatory by the Companies Act, 2013. However, research studies that may assist in understanding the influence of board independence on Indian firms’ CSR performance are still scarce. The present study would foster value to the existing set of limited literature. Besides, the study has considered the dynamic nature of the relationship and has also controlled the endogeneity bias which has been examined by few studies in the past.

Globally, the landscape of corporate carbon disclosures (CCD) is continually evolving as societal, environmental and regulatory expectations change over time. The goal of this study is to examine the challenges faced by Indian firms’ corporate carbon reporting (CCR). The literature recognized the hurdles to reaching net zero emissions and decarbonization, which are equally applicable to carbon disclosure (CD).

The scope 3 emission disclosure barriers (S3EDBs) identified from the literature were ranked, and their relationships were discovered using the “Grey-based decision-making trial and evaluation laboratory” (Grey- DEMATEL) technique.

The key findings are the S3EDBs, the most prominent barriers, their interrelationships and important insights for managers of organizations in prioritizing the action area for scope 3 CD. Eight S3EDBs were categorized in terms of cause and effect, threshold value is calculated as 0.78. “Quality, and reliability of data,” “Government policies and statutory requirement on emission disclosure” and “Traceability and managing supply chain partners” are the most prominent S3EDBs.

The results will help industry people in countries with emerging economies that have significant scope 3 carbon footprints. The managers can plan to deal with top S3EDBs as a step towards decarbonization and ultimately fighting climate change (CC).

This study is one of the first to rank these barriers to CD so that industry practitioners can prioritize their actions. The core contribution of this research is to detect the most significant S3EDBs and their interdependencies.

The researchers aim to investigate the role of psychological capital (PsyCap) in facilitating intrinsic motivation and goal-commitment among employees at the workplace, affecting outcome variables, namely, in-role and extra-role job performance.

Data were collected from 640 employees working in the information technology sector of India. Covariance-based structural equation modeling (CB-SEM) was used to test the hypothesized relationships.

Analysis revealed a significant positive impact of PsyCap on the two behavioral facets of job performance. Intrinsic motivation and goal-commitment were found mediating the influence of PsyCap on the two facets of job performance.

The information technology sector is characterised by continuous change. It requires voluntary prosocial behavior from employees, where the employees are expected to display multifaceted job performance behaviors, where they go beyond their job duties to cater for the dynamics of the IT sector. The present study provides means by which intrinsic motivated and goal-committed behavior are facilitated for both the in-role and extra-role job performance.

The present study is among the few preliminary studies that have provided evidence that intrinsic motivation and goal-commitment are the two variables which aid PsyCap in predicting both the prescribed and voluntary job performance behaviors.

The present study identifies the factors that impact behavioral intentions to adopt solar water heaters (SWHs) and examines their relationship with behavioral intentions using an extended “Unified Theory of Acceptance and Use of Technology” (UTAUT) model.

The study used a primary survey to collect data from 423 respondents across seven Indian states selected through purposive sampling. The collected data was analyzed using IBM SPSS software and “Structural Equation Modeling” (SEM) was performed using SmartPLS 3.5.5.

The results suggest that social influence is the most significant factor affecting SWH adoption, followed by effort, performance expectancy and facilitating conditions. The perceived cost negatively affects behavioral intentions and social influence on behavioral intentions is partially mediated by facilitating conditions. People prefer SWHs if they are easy to install and compatible with other home appliances. Positive perception of friends and family, easy access and government incentives contribute to SWH adoption.

SWH adoption can be promoted by designing sector-specific programs and improving ease of installation, operation, maintenance and after-sale services.

This study explores the behavioral intentions of individuals in India to adopt SWHs. India is a developing tropical country with a high potential for SWH adoption but has not received much attention. Further, the research integrates the perceived cost construct in the UTAUT model and examines the partial mediation impact of facilitating conditions to improve the model’s comprehensibility.

The literature provides evidence of consumers’ willingness to purchase (WTP) refurbished products. However, the studies focusing on young consumers’ (18–24 years) purchasing behaviour of refurbished products from online platforms/stores are limited. Therefore, the purpose of this study is to conduct a qualitative study to identify the key attributes/factors that influence young consumers’ WTP refurbished products.

Two qualitative techniques, focus group discussion (FGD) and depth interviews (DI), are used for data collection. Criterion sampling is used for sample selection. Consequently, 37 participants (20 for FGD and 17 for DI) from India were recruited.

The study’s findings indicate six broad attributes/factors (purchase attributes, product attributes, credibility, reviews/support, refurbishment process and ecological factors) that influence young consumers’ WTP refurbished products. In each attribute, some characteristics are unique (for example, greater trust in online platforms/stores, preference for video reviews and historical information of the product) to young consumers.

The current study integrates three literature streams: consumer behaviour in the online/offline context, young consumers’ inclination towards an online purchase and WTP refurbished products. To the best of the authors’ knowledge, this is the first study to do it.