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Article
Publication date: 30 April 2024

K.M. Priya and Sivakumar Alur

This study examines how health-conscious consumers utilize nutrition facts panel labels when purchasing food products, focusing specifically on the dimension of ethical…

167

Abstract

Purpose

This study examines how health-conscious consumers utilize nutrition facts panel labels when purchasing food products, focusing specifically on the dimension of ethical evaluation. It aims to understand how ethical considerations influence the decision-making process of consumers who prioritize health. By analyzing the impact of ethical evaluation on label usage, the study sheds light on the significance of ethics in consumer behavior in the context of purchasing packaged edible oil.

Design/methodology/approach

Empirical data were collected using an online survey and a non-ordered questionnaire. In total, 469 valid responses were obtained. The study used SPSS version 27.0 and SmartPLS version 3 for demographic analysis and structural equation modeling.

Findings

The findings suggest that three factors – perceived benefits, perceived threats, and nutrition self-efficacy, positively impact the use of NFP labels. However, perceived barriers negatively influence the use of NFP labels. In additionally, ethical evaluation mediates the usage of NFP labels.

Practical implications

In the health belief model, ethical evaluation functions as a mediator and has a greater influence on NFP label use. This study provides a framework for marketers to promote consumer health consciousness by encouraging them to incorporate NFP labels.

Originality/value

This study is one of the first attempts to demonstrate that ethical evaluation mediate health beliefs and the use of nutrition labels.

Details

Benchmarking: An International Journal, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1463-5771

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Article
Publication date: 11 July 2019

M. Priya and Aswani Kumar Ch.

The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras is…

273

Abstract

Purpose

The purpose of this paper is to merge the ontologies that remove the redundancy and improve the storage efficiency. The count of ontologies developed in the past few eras is noticeably very high. With the availability of these ontologies, the needed information can be smoothly attained, but the presence of comparably varied ontologies nurtures the dispute of rework and merging of data. The assessment of the existing ontologies exposes the existence of the superfluous information; hence, ontology merging is the only solution. The existing ontology merging methods focus only on highly relevant classes and instances, whereas somewhat relevant classes and instances have been simply dropped. Those somewhat relevant classes and instances may also be useful or relevant to the given domain. In this paper, we propose a new method called hybrid semantic similarity measure (HSSM)-based ontology merging using formal concept analysis (FCA) and semantic similarity measure.

Design/methodology/approach

The HSSM categorizes the relevancy into three classes, namely highly relevant, moderate relevant and least relevant classes and instances. To achieve high efficiency in merging, HSSM performs both FCA part and the semantic similarity part.

Findings

The experimental results proved that the HSSM produced better results compared with existing algorithms in terms of similarity distance and time. An inconsistency check can also be done for the dissimilar classes and instances within an ontology. The output ontology will have set of highly relevant and moderate classes and instances as well as few least relevant classes and instances that will eventually lead to exhaustive ontology for the particular domain.

Practical implications

In this paper, a HSSM method is proposed and used to merge the academic social network ontologies; this is observed to be an extremely powerful methodology compared with other former studies. This HSSM approach can be applied for various domain ontologies and it may deliver a novel vision to the researchers.

Originality/value

The HSSM is not applied for merging the ontologies in any former studies up to the knowledge of authors.

Details

Library Hi Tech, vol. 38 no. 2
Type: Research Article
ISSN: 0737-8831

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Article
Publication date: 16 January 2024

Soundarya Priya M.G., Anandh K.S., Sathyanarayanan Rajendran and Krishna Nirmalya Sen

This study aims to explore the “psychological contract of safety” (PCS), a key factor in the safety climate (SC), which relies on the behavioral safety actions of workers at…

328

Abstract

Purpose

This study aims to explore the “psychological contract of safety” (PCS), a key factor in the safety climate (SC), which relies on the behavioral safety actions of workers at construction sites. While numerous factors have been identified in various sectors across different countries, there is a consensus among researchers that there is a dearth of common assessment factors specifically for the Indian construction industry (ICI). Therefore, this study undertakes a systematic review of existing literature to identify the factors that determine PCS in construction and to ascertain the relative importance index (RII) of these variables and their interrelationships using structural equation modelling (SEM).

Design/methodology/approach

A structured survey was conducted among 420 professionals in the ICI to collect data. This data was then analyzed using descriptive and inferential statistical methods to derive results.

Findings

The findings of the study indicate that PCS factors have a significant impact on the construction industry (CI). The inferential analysis ranks “Safety System” as the top factor with the highest RII value. The chi-square results highlight two key SC factors that enhance and regulate an organization’s safety performance. The SEM results reveal that SC factors contribute to the improvement of PCS and influence worker safety behavior.

Originality/value

The outcomes of this study will be beneficial for stakeholders aiming to improve safety at construction sites and enhance safety performance by fulfilling the mutual safety obligations of employers and employees and by improving safety norms, procedures and policy-making. This paper also provides a theoretical framework for scholars to reassess the results in various contexts.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

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Article
Publication date: 7 February 2021

Sengathir Janakiraman, Deva Priya M., Christy Jeba Malar A., Karthick S. and Anitha Rajakumari P.

The purpose of this paper is to design an Internet-of-Things (IoT) architecture-based Diabetic Retinopathy Detection Scheme (DRDS) proposed for identifying Type-I or Type-II…

85

Abstract

Purpose

The purpose of this paper is to design an Internet-of-Things (IoT) architecture-based Diabetic Retinopathy Detection Scheme (DRDS) proposed for identifying Type-I or Type-II diabetes and to specifically advise the Type-II diabetic patients about the possibility of vision loss.

Design/methodology/approach

The proposed DRDS includes the benefits of automatic calculation of clip limit parameters and sub-window for making the detection process completely adaptive. It uses the advantages of extended 5 × 5 Sobels operator for estimating the maximum edges determined through the convolution of 24 pixels with eight templates to achieve 24 outputs corresponding to individual pixels for finding the maximum magnitude. It enhances the probability of connecting pixels in the vascular map with its closely located neighbourhood points in the fundus images. Then, the spatial information and kernel of the neighbourhood pixels are integrated through the Robust Semi-supervised Kernelized Fuzzy Local information C-Means Clustering (RSKFL-CMC) method to attain significant clustering process.

Findings

The results of the proposed DRDS architecture confirm the predominance in terms of accuracy, specificity and sensitivity. The proposed DRDS technique facilitates superior performance at an average of 99.64% accuracy, 76.84% sensitivity and 99.93% specificity.

Research limitations/implications

DRDS is proposed as a comfortable, pain-free and harmless diagnosis system using the merits of Dexcom G4 Plantinum sensors for estimating blood glucose level in diabetic patients. It uses the merits of RSKFL-CMC method to estimate the spatial information and kernel of the neighborhood pixels for attaining significant clustering process.

Practical implications

The IoT architecture comprises of the application layer that inherits the DR application enabled Graphical User Interface (GUI) which is combined for processing of fundus images by using MATLAB applications. This layer aids the patients in storing the capture fundus images in the database for future diagnosis.

Social implications

This proposed DRDS method plays a vital role in the detection of DR and categorization based on the intensity of disease into severe, moderate and mild grades. The proposed DRDS is responsible for preventing vision loss of diabetic Type-II patients by accurate and potential detection achieved through the utilization of IoT architecture.

Originality/value

The performance of the proposed scheme with the benchmarked approaches of the literature is implemented using MATLAB R2010a. The complete evaluations of the proposed scheme are conducted using HRF, REVIEW, STARE and DRIVE data sets with subjective quantification provided by the experts for the purpose of potential retinal blood vessel segmentation.

Details

International Journal of Pervasive Computing and Communications, vol. 17 no. 2
Type: Research Article
ISSN: 1742-7371

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Article
Publication date: 6 April 2023

Akanksha Jumde and Nishant Kumar

This paper aims to focus on compliance of workplace sexual harassment-related provisions under Indian companies and securities law, based on an empirical analysis of companies’…

273

Abstract

Purpose

This paper aims to focus on compliance of workplace sexual harassment-related provisions under Indian companies and securities law, based on an empirical analysis of companies’ sexual harassment-related disclosures contained within their directors’ annual reports (ARs). Specifically, sections devoted to sexual harassment-related disclosures, inbuilt within directors’ ARs for the financial year 2019–2020 for a selected sample of companies listed under the National Stock Exchange, have been analysed.

Design/methodology/approach

To examine the nature of companies’ disclosures to demonstrate their compliance with statutory requirements under the POSH law, aligned with the Companies (Accounts) Rules, 2014 and Securities and Exchange Board of India’s regulations, an empirical-based, descriptive content analysis of ARs of 200 listed companies were used.

Findings

This study primarily finds that the majority of companies from the sample have disclosed to have prepared a corporate-level policy, as required under the POSH law. As also required under the POSH law, companies, reportedly, have constituted an Internal Complaints Committee to adjudicate and dispose of incidents related to sexual misconduct reported at their workplaces. However, companies lack in disclosing qualitative information, with sufficient detail, on many important aspects related to prevention and resolution of reported cases of workplace sexual harassment.

Originality/value

This paper adds to the broader narrative of the lacunae within the disclosure and reporting requirements on enhancing the liabilities of the companies to prevent and address sexual harassment under India’s corporate and securities regulations.

Details

International Journal of Law and Management, vol. 65 no. 4
Type: Research Article
ISSN: 1754-243X

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Article
Publication date: 17 March 2022

Samant Shant Priya, Vineet Jain, Meenu Shant Priya, Sushil Kumar Dixit and Gaurav Joshi

This study aims to examine which organisational and other factors can facilitate the adoption of artificial intelligence (AI) in Indian management institutes and their…

1028

Abstract

Purpose

This study aims to examine which organisational and other factors can facilitate the adoption of artificial intelligence (AI) in Indian management institutes and their interrelationship.

Design/methodology/approach

To determine the factors influencing AI adoption, a synthesis-based examination of the literature was used. The interpretative structural modelling (ISM) method is used to determine the most effective factors among the identified ones and the inter-relationship among the factors, while the Decision-Making Trial and Evaluation Laboratory (DEMATEL) method is used to analyse the cause-and-effect relationships among the factors in a quantitative manner. The approaches used in the analysis aid in understanding the relationship among the factors affecting AI adoption in management institutes of India.

Findings

This study concludes that leadership support plays the most significant role in the adoption of AI in Indian management institutes. The results from the DEMATEL analysis also confirmed the findings from the ISM and Matrice d’ Impacts croises- multiplication applique and classment (MICMAC) analyses. Remarkably, no linkage factor (unstable one) was reported in the research. Leadership support, technological context, financial consideration, organizational context and human resource readiness are reported as independent factors.

Practical implications

This study provides a listing of the important factors affecting the adoption of AI in Indian management institutes with their structural relationships. The findings provide a deeper insight about AI adoption. The study's societal implications include the delivery of better outcomes by Indian management institutes.

Originality/value

According to the authors, this study is a one-of-a-kind effort that involves the synthesis of several validated models and frameworks and uncovers the key elements and their connections in the adoption of AI in Indian management institutes.

Details

foresight, vol. 25 no. 1
Type: Research Article
ISSN: 1463-6689

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Article
Publication date: 14 November 2024

Neeraj Kumar, Rama Tyagi, Sahaya Mercy Jaquline Robert, Akanksha  , Mohd. Aqil, Mohd. Vaseem Ismail, Abul Kalam Najmi and Mohd Mujeeb

This study aims to present a great deal of interest in researching plant-based phytopharmaceuticals and nutraceuticals as a possible alternative to synthetic medication, both to…

14

Abstract

Purpose

This study aims to present a great deal of interest in researching plant-based phytopharmaceuticals and nutraceuticals as a possible alternative to synthetic medication, both to avoid their side effects and for financial reasons.

Design/methodology/approach

Mankind has used medicinal plants since the beginning of civilization. Nature has been explored as a source of therapeutic chemicals for thousands of years, and many modern drugs have been discovered from natural sources. The primary medical care system of resource-poor areas in India has continued to rely on traditional medicine as the most accessible and reasonably priced form of treatment.

Findings

Tinospora cordifolia is a plant that is frequently used in Ayurvedic and traditional medicine throughout India. Although almost all of its parts are used in conventional medical systems, the leaves, stems and roots are the most significant ones used medicinally. All forms of existence can benefit from the versatility of T. cordifolia. It includes a wide variety of compounds that impact the body.

Originality/value

The goal of this review is to provide a concise summary of the knowledge about the pharmacological, phytochemistry, botanical, ethnopharmacology, toxicity study, marketed products and patents of the T. cordifolia plant.

Details

Nutrition & Food Science , vol. 55 no. 2
Type: Research Article
ISSN: 0034-6659

Keywords

Available. Open Access. Open Access
Article
Publication date: 12 January 2024

B.S. Patil and M.R. Suji Raga Priya

The purpose of this study is to target utilizing Human resources (HRs) data analytics that may enhance strategic business, but little study has examined how it affects components…

4613

Abstract

Purpose

The purpose of this study is to target utilizing Human resources (HRs) data analytics that may enhance strategic business, but little study has examined how it affects components. Data analytics, HRM and strategic business require empirical investigations and how to over come HR data analytics implementation issues.

Design/methodology/approach

A semi-systematic methodology for its evaluation allows for a more complete examination of the literature that emerges theoretical framework and a structured survey questionnaire for quantitative data collection from IT sector personnel. SPSS analyses data.

Findings

Future research is essential for organisations to exploit HR data analytics’ performance-enhancing potential. Data analytics should complement human judgment, not replace it. This paper details these transitions, the important contributions to theory and practice and future research.

Research limitations/implications

Data analytics has grown rapidly and might make HRM practices faster, more efficient and data-driven. HR data analytics may improve strategic business. HR data analytics on employee retention, engagement and organisational success is insufficient. HR data analytics may boost performance, but there is limited proof. The authors do not know how HRM data analytics influences firms and employees.

Originality/value

Data analytics offers HRM new opportunities, along with technical and ethical challenges. This study makes a significant contribution to HR data analytics, evidence-based practice and strategic business literature. In addition to estimating turnover risk, identifying engagement factors and planning interventions to increase retention and engagement, HR data analytics can also estimate the risk of employee attrition.

Details

Vilakshan - XIMB Journal of Management, vol. 21 no. 1
Type: Research Article
ISSN: 0973-1954

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Article
Publication date: 24 June 2022

Aniekan Essien and Godwin Chukwukelu

This study aims to provide a systematic review of the existing literature on the applications of deep learning (DL) in hospitality, tourism and travel as well as an agenda for…

1538

Abstract

Purpose

This study aims to provide a systematic review of the existing literature on the applications of deep learning (DL) in hospitality, tourism and travel as well as an agenda for future research.

Design/methodology/approach

Covering a five-year time span (2017–2021), this study systematically reviews journal articles archived in four academic databases: Emerald Insight, Springer, Wiley Online Library and ScienceDirect. All 159 articles reviewed were characterised using six attributes: publisher, year of publication, country studied, type of value created, application area and future suggestions (and/or limitations).

Findings

Five application areas and six challenge areas are identified, which characterise the application of DL in hospitality, tourism and travel. In addition, it is observed that DL is mainly used to develop novel models that are creating business value by forecasting (or projecting) some parameter(s) and promoting better offerings to tourists.

Research limitations/implications

Although a few prior papers have provided a literature review of artificial intelligence in tourism and hospitality, none have drilled-down to the specific area of DL applications within the context of hospitality, tourism and travel.

Originality/value

To the best of the authors’ knowledge, this paper represents the first theoretical review of academic research on DL applications in hospitality, tourism and travel. An integrated framework is proposed to expose future research trajectories wherein scholars can contribute significant value. The exploration of the DL literature has significant implications for industry and practice, given that this, as far as the authors know, is the first systematic review of existing literature in this research area.

Details

International Journal of Contemporary Hospitality Management, vol. 34 no. 12
Type: Research Article
ISSN: 0959-6119

Keywords

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Publication date: 25 July 2024

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