Search results

This study describes a series of experiments investigating the upper hot layer temperature profile in a confined space under different ventilation conditions for porosity-controlled wood crib fires for pre-flashover conditions.

Full-scale compartment (4 m × 4 m × 4 m) experiments were carried out for four-door openings, i.e. 100%, 75%, 50% and 25% of the total vent area (2 m × 1 m) with the wood crib as a fuel load. The temperature of the upper hot smoke layers of the compartment was recorded with the help of four layers of thermocouples for varying vent areas.

The effect of ventilation on the properties, i.e. mass loss rate, enclosure temperature, heat release rate and carbon monoxide (CO) gas concentration, has been measured and analyzed. The effect of ventilation on heat flux and flame temperature has also been studied. Compartment gas temperature has been examined by five wood crib burning stages: Ignition, growth, steady burning, recess and collapse.

Findings demonstrate that the influence of vent openings varies for the burning parameters and upper layer temperature of the compartment. The current results are beneficial in analyzing thermal risks concerning compartment fire and fire safety engineering projects.

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.

Transformation and involvement from every organizational function are essential in creating a diverse and inclusive workplace. The paper explores the role of training and development (T&D) interventions in building a diverse and inclusive workplace.

Through the review of existing research studies, the authors report and discuss how T&D function supports fostering a diversity and inclusion (D&I) mindset in the workplace and propose an organizational schema that facilitates the systematic design and implementation of T&D interventions for D&I.

Based on the literature an organizational schema was developed which indicated that to foster a D&I mindset in the workplace, it is important that diversity training is designed after considering established diversity theories. Further diversity training can be conducted in two phases, where phase 1 would focus on awareness training and phase 2 on skill training. This would lead to an increase in employee competency development including knowledge, skills, behavior, and a positive attitude toward a D&I mindset.

HR and training managers can benefit from the paper indicating that for achieving effective results from diversity training, it must draw insights from established diversity theories. Through the organizational schema discussed in the paper, organizations can minimize the negative attitude and behavior that emerge from social categorization with the help of systematic T&D where employees are made self-aware of their prejudice and discrimination and further equipped with relevant skills to manage diversity.

A positive mindset incorporated by employees at a workplace with reference to Diversity & Inclusion through structured D& I training can percolate beneficially to the society as a whole.

The study is a rare one that explores the impact of T&D on D&I. The novelty of the research lies in the organizational schema presented in the study exploring how HR practitioners must systematically design T&D for D&I combining both theory and practice to achieve long-term organizational diversity management objectives.

This study aims to emphasize green energy-driven solutions to address environmental sustainability issues, particularly to promote the uptake of electric vehicles (EVs). This study intends to investigate user adoption of EVs as the existing predicament of converting car owners to EV buyers, demanding a push to create a facilitating environment for EV uptake.

A survey-based quantitative study involving 330 car owners and potential buyers was conducted involving four predictors, i.e. financial benefits, social influence, charging infrastructure and range consciousness. Environmental concerns and socio-demographic factors such as age, family income and gender were considered as moderators between these predictors and EV adoption intention. Partial least square structural equation modelling was used to analyse the proposed relationships.

The findings indicated that financial benefits (ß = 0.169, t = 3.930), social influence (ß = 0.099, t = 2.605), range consciousness (ß = 0.239, t = 3.983) and charging infrastructure (ß = 0.142, t = 4.8) significantly impact EV adoption. Family income was the most significant moderator with a large effect size (F square = 0.224), followed by environmental concern (F square = 0.182) and age (F square = 0.042) having a medium moderation effect and, subsequently, gender (F square = 0.010) as a mild moderator.

By analysing environmental concerns as a moderator, this study fosters a novel understanding of how environmental concerns impact EV adoption, which has not been explored. Additionally, the empirical assessment of the socio-economic and socio-demographic factors of EV adoption helps to offer a consumer perspective to the government and policymakers in undertaking initiatives to promote EV adoption.

This research aims to combine and extend the literature on the self-monitoring approach used by faculty members in online teaching during the COVID-19 pandemic using the Technology Acceptance Model (TAM) model. The study also highlights the challenges faced by faculty members in online teaching.

Based on a mixed methodology approach, the primary data was obtained from the faculty members of the post-graduate business schools. This data enabled the measurement of self-monitoring adopted by the faculty members and the relationship of the factors by using the TAM model. Multivariate regression was adopted to study the relationships between the elements in the TAM model and faculty members’ self-monitoring. Secondly, a few exploratory questions were asked to the respondents about the challenges faced by them during online teaching.

The quantitative analysis conducted using multiple regression directed that the faculty’s contentment with any digital platform influenced their engagement, attention and participation while taking an online class as a part of the self-monitoring process. The perception of the technology platforms used for online teaching affected the faculty members’ self-monitoring dimensions: attention, participation and engagement. Based on the qualitative approach, the thematic analysis pointed out five major challenges for faculty members in conducting online classes: I.T. support, hesitation, interaction with peers and students, proficiency with an online platform and evaluation challenges.

This study was conducted during the complete lockdown of the COVID-19 pandemic; many faculty members were initially trained to get familiarized with the online teaching platforms and educate students. Hence, this study enriches the literature on online teaching during pandemic times.

To ensure that the faculty impacts quality online education and the students obtain the knowledge and skills required, faculty need to alter their pedagogy based on the technology they use to focus on their students’ teaching, learning and needs.

This study measures self-monitoring and its dimensions for faculty members, which is unique in nature. This was the first time the faculty members were imposed with the responsibility of online teaching and ensuring that the learning-teaching process was fruitful. This study has both-theoretical and practical implications as the paper focuses on various insights which can make online teaching-learning more effective.

The crux of this paper is to unveil efficient features and practical tools that can predict credit default.

Annual data of non-financial listed companies were taken from 2000 to 2020, along with 71 financial ratios. The dataset was bifurcated into three panels with three default assumptions. Logistic regression (LR) and k-nearest neighbor (KNN) binary classification algorithms were used to estimate credit default in this research.

The study’s findings revealed that features used in Model 3 (Case 3) were the efficient and best features comparatively. Results also showcased that KNN exposed higher accuracy than LR, which proves the supremacy of KNN on LR.

Using only two classifiers limits this research for a comprehensive comparison of results; this research was based on only financial data, which exhibits a sizeable room for including non-financial parameters in default estimation. Both limitations may be a direction for future research in this domain.

This study introduces efficient features and tools for credit default prediction using financial data, demonstrating KNN’s superior accuracy over LR and suggesting future research directions.

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.

In the past decade, the biopolymeric properties of chitosan (CH) have been largely exploited for various applications. This paper aims to study the use of CH in its nanoform, i.e. as nanofibers blended with polyvinyl alcohol (PVA) for various antimicrobial applications in detail. In particular, their ability toward bacterial growth inhibition, in vitro drug release and their biocompatibility toward tissue growth have been investigated in detail.

Electrospinning technique was adapted for depositing CH/PVA blended nanofilms on the silver foil under optimized conditions of high voltage. Three different concentrations of blended nanofiber samples were prepared and their antimicrobial properties were studied.

The bead diameter and average diameter of blended nanofibers increase with CH concentration. Antibacterial activity increases as CH concentration increases. Increased hydrophilicity in CH-enriched samples contributes to a higher drug release profile.

To the best of the authors’ knowledge, chick chorioallantoic membrane assay analysis has been carried out for the first time for CH/PVA films which shows that CH/PVA blends are biocompatible. CH after being converted as nanoparticles exhibits higher drug release rate by in vitro method.

The banking sector requires a major comeback with the series of bank frauds that has shook the nation. The rising non-performing assets (NPAs) and corporate frauds find their roots in the top-level management or executive levels. The purpose of this study to analyse the behavioural component with corporate governance lapses for creating a trail and to what extent it can contribute to forensic analysis to help reduce and prevent fraud in the future.

This study is investigative in nature. This study uses case study approach by taking into account the major Advance–NPA–Fraud cases over period of 2010–2022. RBI data for bank advances, NPAs and advances-relate frauds from 2005 to 2019 were studies and interpreted for creating a trend and pattern for the reduction and prevention of frauds.

The authors found that behavioural factors and personalities affect the systems and culture of the company, thereby giving a jolt to the corporate governance mechanisms along with various entities like depositors, consumers and shareholders.

Assessing the behavioural aspects for risk mitigation remains unexplored in the banking sector. The personality dimension can help in contributing to comprehending the mental aspects and the reasons behind the combination of dark triads with economic offences.

This study is beneficial to all the beneficiaries of the banking sector and the economy at large in understanding the implications of risks because of patterns formed by emotions and vulnerability towards economic and fugitive economic crimes.