Search results

The purpose of this paper is to analyze various properties of anatase titanium dioxide (TiO₂) nanoparticles. Further, it proposes to implement Linear Combinations of Atomic Orbitals (LCAO) basis set under the framework of density functional theory and outline how LCAO is able to provide improved results in terms of various mechanical properties rather than plane wave and other theoretical results.

This paper provides an exploratory study on anatase TiO₂ by implementing OLCAO–DFT–LDA–LBFGS–EOS–PZ algorithms to find out various ground-level properties. The data so obtained are complemented by various analysis using mathematical expressions, description of internal processes occurred and comparison to others’ analytical results.

The paper provides some empirical insights on how mechanical properties of anatase TiO₂ improved by implementing LCAO methodology. From the analysis of electronic properties, it is seen that the anatase TiO₂ supports the inter band indirect transition from O-2p in valence region to Ti-3d in the conduction region.

Most of the electronic properties are underestimated because a single exchange-correlation potential is not continuous across the gap. This gap can be enhanced by implementing Green’s function in place of DFT and the other way is to implement self-interaction correction.

The use of anatase TiO₂ is primarily used for catalytic applications. This is also used to enhance the quality of paper in the paper industry. Additionally, this is used as a prime ingredient in cosmetic industry.

This paper fulfills an identified need to study how LCAO, another basis set, plays an important role in improving material properties.

This paper provides new evidence on Indian tourism firms by investigating the role of a firm's financial conditions typified by its leverage, earnings, size, cash holdings, and excess cash in moderating the pandemic-led idiosyncratic volatility in its stock prices.

The authors employ a firm-level panel comprising 82 publicly-listed tourism firms from India. Firm risk is estimated for the period beginning January 2020 to December 2020.

This paper finds non-linear effects of the pandemic on the idiosyncratic risk of the sample firms. Precisely, stock price volatility rises, but as the market absorbs this information, volatility subsides even as the disease spreads further. Further, lower levels of past debt and earnings and higher cash holdings ameliorate the pandemic's effects on tourism firms' risk. Contrasting the view that “excess” cash reflects poor operational performance, we show that “excess” cash firms are better prepared to face the adverse effects of the pandemic.

This study’s sample period fully encompasses the first wave of the pandemic (January–December 2020) of the novel coronavirus infection spread.

To the best of the authors’ knowledge, this is the first study to assess the moderating effects of company fundamentals on the risk of Indian tourism firms. In doing so, the authors account for non-linear effects of the pandemic on firms' idiosyncratic volatility over time.

To calculate the volume deviation between a CAD model and built‐up part in 5‐axis laminated object manufacturing employing direct slicing with first‐order approximation.

It is proposed here that the deviation between the CAD model and the built‐up part, which is normally calculated as a linear dimension in specific 2D sections of the CAD model, be treated as a volume (as it actually is), for higher accuracy in subsequent calculations. An algorithm has been developed and implemented for identification and calculation of volume deviation, considering all possibilities.

It has been conclusively shown that volume deviation consideration results in improved feature recognition and less approximation.

Increase in complexity of the CAD model leads to a considerable increase in the volume deviation computation time. Future research in this area would focus on optimization and calculation of the slice heights based on volume deviation.

Calculation of volume deviation would help eliminate the loss of intricate features in a complex surface and thus improve feature recognition. Slice height calculations based on volume deviation would reduce the deviation between the actual model and the built‐up part.

A new method has been developed for the calculation of volume deviation that could be implemented in the rapid prototyping software packages so as to build prototypes with higher accuracy.

In recent years, organizational agility (OA) has garnered significant attention from the academic community. Despite a substantial rise in the academic literature on OA, the nuanced understanding of OA among academicians, practitioners and policymakers is limited. To address this research gap, the current study attempts to synthesize the academic literature on organizational literature, understand the evolution of OA literature and state the potential research gaps that may open multiple research avenues.

The current study critically evaluates academic literature published in peer-reviewed journals using the bibliometric approach to map the intellectual structure of identified 224 articles on published literature on OA between 2001 and 2022.

The findings outline OA's evolutionary trend, most prolific authors, journals, affiliations and countries. Further, network analysis is deployed to unearth prominent OA themes. After that, four key themes of OA from each cluster have been identified and evaluated.

The study is based on the literature drawn from the SCOPUS database. Although the SCOPUS database is one of the largest databases, the authors believe that the SCOPUS does not contain some publications that might have offered some different insights. Secondly, the bibliometric analysis does not offer the opportunity to provide critical insights into published literature, which is one of the main limitations of bibliometric-based studies. However, despite some of these limitations, the authors believe that the study is a useful guide for scholars, practitioners and policymakers who do not have much information related to OA literature.

This article provides a pioneering review of the OA literature using bibliometrics and network analysis. The results and potential directions for further research may assist researchers in increasing the relevance of OA in the current uncertain and ambiguous environment.

Environmental pollution and corresponding adverse health impacts have now become a significant concern for the entire planet. In this regard, analysts and experts are continually formulating policies to reduce environmental pollution and improve natural ecological conditions. To aid in coping with the ecological predicament, a framework has been developed in the present study to inspect the adverse environmental impacts and related health issues of coal mining.

The parameters for this study have been identified through a review of the literature and finalized 23 critical parameters of air, water, land and soil, and noise related to coal mining by consultation with experts from industry and academia. Finally, the parameters have been categorized in accordance with the level of threat they pose to the environment by assigning weight using the Bradley–Terry model considering attitudinal data acquired by a questionnaire survey.

It is found that coal mining has a relatively higher impact on four attributes of “air pollution” (suspended particulate matter [SPM], respiratory particulate matter [RPM], sulfur dioxide [SO₂] and oxides of nitrogen [NO_x]), followed by “land and soil pollution” (deforestation and surface structure diversion), “noise pollution” (vehicle movement) and “water pollution” (water hardness, total solids (TSS/TDS) and iron content). It is also found that raising the air concentration of SPM and RPM results in increased respiratory and cardiopulmonary mortality. Therefore, reducing dust concentrations into the air generated during coal mining is recommended to reduce air pollution caused by coal mining, which will reduce contamination of water and land and soil.

The model built in this study is a hypothesized model that relied on the experts' opinions considering the parameters of coal production only. However, the parameters related to the usage of coal and its consequences have been excluded. Further, only industrial and academic experts were considered for this study; however, they excluded local people, coal mining personnel, policy authorities, etc. Therefore, the study findings might differ in real circumstances. The research can further be reproduced by considering the parameters related to the use of coal and its consequences, considering the opinions of the local people, coal mining personnel and policy authorities.

Categorizing the parameters according to the threat they pose to the environment due to coal mining can help the decision-maker develop an effective policy to reduce environmental pollution due to coal mining by considering the parameters on a priority basis. In addition, the results further help the decision-makers to assess the environmental impact of coal mining and take necessary action.

The study has developed a framework using the Bradley–Terry model to categorize the environmental parameters of coal mining to develop effective environmental policies, which are original and unique in nature.

This paper examines the current state of blockchain governance research. The study’s findings also propose a conceptual framework for the use of blockchain in governance and global governance and provide a global look at how public and private sectors alike are implementing new technologies.

The study is qualitative as well as quantitative in nature. The authors used Preferred Reporting Items for Systematic and Meta-Analysis (PRISMA) to gather data for the study. Furthermore, a bibliometric analysis using VOSviewer visualization tool and R Studio was carried out to attain the research objectives.

Many scholars and practitioners from around the world are interested in the topic, according to the analysis. This is a multidisciplinary study, so researchers have looked at how the blockchain can be used to govern countries, public utilities and global facilities, including corporations. There are numerous examples of how technology has been used in global governance, and the authors found that governments, as well as corporations around the world, have implemented technology in a variety of areas that affect the public and other stakeholders.

This study makes numerous contributions. In the first place, it presents the complex concept of blockchain in an easier to understand way. The numerous governmental and commercial initiatives that have made use of blockchain are also highlighted. As a result, the use of technology in corporate and social governance will continue to grow. Finally, the research will inform the academic community on the current state of the topic and potential future directions.

As a result of this research, academics and scholars can better understand the potential of blockchain in various governance models, ranging from developed to developing economies. The general public, as well as organizations, will benefit from the decentralized nature of the blockchain in a variety of ways related to their day-to-day governance. To the best of authors’ knowledge, this is a first kind of research on blockchain in governance using PRISMA and bibliometrics tools.

The new technology aspects of Industry 4.0 (I4.0), such as digital technologies including artificial intelligence (AI), block chain, big data analysis and the internet of things (IoT) as a digital cosmos, have the potential to fundamentally transform the future of business and supply chain management. By augmenting the functional components of the food supply chain (FSC), these technologies can transform it into an intelligent food supply chain (iFSC). The purpose of this study is to identify the I4.0 utilization for FSC to become an iFSC. Additionally, it suggests future research agendas to bridge the academic knowledge gaps.

This study utilizes the bibliometric analysis methodology to investigate the techno-functional components of iFSC in the context of I4.0. The study followed steps of bibliometric analysis to assess existing components’ knowledge in the area of intelligent food supply chain management. It further reviews the selected articles to explore the need for I4.0 technologies’ adoption as well as its barriers and challenges for iFSC.

This study examines the integration of emerging technologies in FSC and concludes that the main emphasis is on the adoption of blockchain and internet of things technology. To convert it into iFSC, it should be integrated with I4.0 and AI-driven FSC systems. In addition to traditional responsibilities, emerging technologies are acknowledged that are relatively uncommon but possess significant potential for implementation in FSC. This study further outlines the challenges and barriers to the adoption of new technologies and presents a comprehensive research plan or collection of topics for future investigations on the transition from FSC to iFSC. Utilizing artificial intelligence techniques to enhance performance, decision-making, risk evaluation, real-time safety, and quality analysis, and prioritizing the elimination of barriers for new technologies.

The uniqueness of this study lies in the provision of an up-to-date review of the food supply chain. In doing so, the authors have expanded the current knowledge base on the utilization of all I4.0 technologies in FSC. The review of designated publications yield a distinctive contribution by highlighting hurdles and challenges for iFSC. This information is valuable for operations managers and policymakers to consider.

One of the most decisive objectives of human resource management (HRM), essential for business performance, is to attract, maintain and engage a qualified workforce. This study aims to identify and prioritize the antecedents of employer branding, which are considered extremely important by potential applicants when they choose to join a particular employer.

The authors have adopted a popular multicriteria decision-making technique fuzzy analytical hierarchy process, to prioritize the identified antecedents. The modified Delphi techniques with the 22 experts have been conducted to validate the identified antecedents. Structured questionnaires were discussed, and their reliability was assessed using the expert’s opinion.

Results of this study indicate that potential applicants consider career advancement opportunities as the most important enabler that persuades them to join a particular employer. Future employees are also motivated to join if they are offered attractive compensation packages, which are distinct from competitors. Furthermore, corporate social responsibility is evolving as an antecedent of employer branding as potential candidates are attracted to employers who are socially responsible.

Employer branding can serve as a strategic HRM technique for any business seeking to attract, recruit, retain and involve outstanding employees, as the success of the organization is determined by how its image is built, communicated and promoted. This study provides insights for HR managers and practitioners who can think of developing an effective employer brand communication that offers a distinct and in-imitable image and reputation as an employer of choice.

This study is unique, as it offers meaningful visions to HR practitioners and experts for designing employer branding strategies for attracting potential applicants to join their organizations.