Devendra Dhagarra, Mohit Goswami, P.R.S. Sarma and Abhijit Choudhury
Significant advances have been made in the field of healthcare service delivery across the world; however, health coverage particular for the poor and disadvantaged still remains…
Abstract
Purpose
Significant advances have been made in the field of healthcare service delivery across the world; however, health coverage particular for the poor and disadvantaged still remains a distant dream in developing world. In large developing countries like India, disparities in access to healthcare are pervasive. Despite recent progress in ensuring improved access to health care in past decade or so, disparities across gender, geography and socioeconomic status continue to persist. Fragmented and scattered health records and lack of integration are some of the primary causes leading to uneven healthcare service delivery. The devised framework is intended to address these challenges. The paper aims to discuss these issues.
Design/methodology/approach
In view of such challenges, in this research a Big Data and blockchain anchored integrative healthcare framework is proposed focusing upon providing timely and appropriate healthcare services to every citizen of the country. The framework uses unique identification number (UID) system as formalized and implemented by the Government of India for identification of the patients, their specific case histories and so forth.
Findings
The key characteristic of our proposed framework is that it provides easy access to secure, immutable and comprehensive medical records of patients across all treatment centers within the country. The model also ensures security and privacy of the medical records based upon the incorporation of biometric authentication by the patients for access of their records to healthcare providers.
Originality/value
A key component of our evolved framework is the Big Data analytics-based framework that seeks to provide structured health data to concerned stakeholders in healthcare services. The model entails all pertinent stakeholders starting from patients to healthcare service providers.
Details
Keywords
Abhijit Mitra, Sufia Zaman and Subhra Bikash Bhattacharyya
The Gangetic delta, sustaining the Sundarbans mangrove forest at the apex of the Bay of Bengal is recognized as one of the most diversified and productive ecosystems in the Indian…
Abstract
The Gangetic delta, sustaining the Sundarbans mangrove forest at the apex of the Bay of Bengal is recognized as one of the most diversified and productive ecosystems in the Indian subcontinent. The deltaic lobe is unique for its wilderness, mangrove gene pool and tiger habitat. However, due to intense industrial activities in the upstream zone, and several anthropogenic factors, the aquatic phase in the western part of the deltaic complex is exposed to pollution from domestic sewage and industrial effluents leading to serious impacts on biota. The presence of Haldia port-cum-industrial complex in the upstream region of the lower Gangetic delta (adjacent to western sector of Indian Sundarbans) has accelerated the pollution problem to a much greater dimension. The organic and inorganic wastes released from industries and urban units contain substantial concentrations of heavy metals. The present article aims to highlight the level of selective heavy metals (zinc, copper, and lead) in the water and muscle of a commercially important shellfish species (Penaeus monodon, commonly known as tiger prawn) collected from two sectors (western and central) in the Indian Sundarbans. Heavy metals are accumulated in the prawn muscle in the following order – zinc > copper > lead – which is similar to the order in the ambient estuarine water. Significant spatial variations of heavy metal concentrations in estuarine water and prawn muscle were observed between the selected sectors, which reflect the adverse impact of intense industrialization, unplanned tourism, and rapid urbanization on the mangrove ecosystem and its biotic community, particularly in the western Indian Sundarbans.
Details
Keywords
Barnali Biswas, Piyal Basu Roy, Ankita Saha and Abhijit Sarkar
The locational disadvantage of a health-care centre often restricts adequate delivery of health-care services in an area. The purpose of this study is to examine the status of…
Abstract
Purpose
The locational disadvantage of a health-care centre often restricts adequate delivery of health-care services in an area. The purpose of this study is to examine the status of primary health-care services in such a geographically disadvantageous area which is confined by forests, tea gardens and undulating topography.
Design/methodology/approach
Necessary secondary data of 13 primary health centres and 236 sub-centres has been collected from the Office of the Chief Medical Officer of Health. Based on obtained data, Health-care Infrastructure Index has been prepared which has been validated by an expert panel, and subsequently, the Thiessen Polygon method has been applied through Arc GIS software to show spatial variation of health-care services delivered by different health-care centres.
Findings
In the study area, there is wide variation found in the case of physical facilities, caregivers and connectivity of road networks, which altogether affect the overall status of health-care services. Among all the indicators, some health-care centres experience staff shortages for prolonged non-recruitment, inaccessibility and inconsistent patient load in different health centres.
Originality/value
In spite of the unfavourable geographical landscape, health-care centres have to be set up wherever possible. There is a need to make new roads and simultaneously the existing road connectivity should be improved so that patients and caregivers can move quickly whenever required. Existing physical facilities need to be renewed or redeveloped along with increasing the number of doctors and other health-care providers as per the need of people with an adequate and optimum level of services.
Details
Keywords
Sufia Zaman, Subhra Bikash Bhattacharyya, Prosenjit Pramanick, Atanu Kumar Raha, Shankhadeep Chakraborty and Abhijit Mitra
Mangroves constitute an important ecosystem because of their global extent and high productivity. These plants thrive in the intertidal zones of the tropics and subtropics that…
Abstract
Mangroves constitute an important ecosystem because of their global extent and high productivity. These plants thrive in the intertidal zones of the tropics and subtropics that are characterized by regular tidal inundation and fluctuating salinity. Mangrove species are well adapted, both morphologically and physiologically, to survive under saline conditions, but in hypersaline environment their growth is reduced. The present chapter is a critical analysis on the impact of salinity on the growth of a common mangrove species (Hertiera fomes). The analysis has been carried out in the framework of Indian Sundarbans, which has contrasting salinity profiles in different segments owing to barrage discharge and siltation phenomena. Analysis of the decadal profile of salinity indicates a gradual lowering in the western Indian Sundarbans due to Farrakka barrage discharge and run-off from catchments. The central sector, however, exhibits a contrasting picture of increment of aquatic salinity through time, mainly due to disconnection of the Bidyadhari River with the Ganga–Bhagrirathi–Hooghly River system (in the western part). This has made the Matla River in the central Indian Sundarbans hypersaline in nature (that used to get water from the Bidyadhari River) finally leading to an insecure ecological condition for the growth and survival of mangroves. The possible remedial measures to combat the situation have also been listed considering the ecological framework of the study zone.
Details
Keywords
Smita Abhijit Ganjare, Sunil M. Satao and Vaibhav Narwane
In today's fast developing era, the volume of data is increasing day by day. The traditional methods are lagging for efficiently managing the huge amount of data. The adoption of…
Abstract
Purpose
In today's fast developing era, the volume of data is increasing day by day. The traditional methods are lagging for efficiently managing the huge amount of data. The adoption of machine learning techniques helps in efficient management of data and draws relevant patterns from that data. The main aim of this research paper is to provide brief information about the proposed adoption of machine learning techniques in different sectors of manufacturing supply chain.
Design/methodology/approach
This research paper has done rigorous systematic literature review of adoption of machine learning techniques in manufacturing supply chain from year 2015 to 2023. Out of 511 papers, 74 papers are shortlisted for detailed analysis.
Findings
The papers are subcategorised into 8 sections which helps in scrutinizing the work done in manufacturing supply chain. This paper helps in finding out the contribution of application of machine learning techniques in manufacturing field mostly in automotive sector.
Practical implications
The research is limited to papers published from year 2015 to year 2023. The limitation of the current research that book chapters, unpublished work, white papers and conference papers are not considered for study. Only English language articles and review papers are studied in brief. This study helps in adoption of machine learning techniques in manufacturing supply chain.
Originality/value
This study is one of the few studies which investigate machine learning techniques in manufacturing sector and supply chain through systematic literature survey.
Highlights
A comprehensive understanding of Machine Learning techniques is presented.
The state of art of adoption of Machine Learning techniques are investigated.
The methodology of (SLR) is proposed.
An innovative study of Machine Learning techniques in manufacturing supply chain.
A comprehensive understanding of Machine Learning techniques is presented.
The state of art of adoption of Machine Learning techniques are investigated.
The methodology of (SLR) is proposed.
An innovative study of Machine Learning techniques in manufacturing supply chain.
Details
Keywords
Ali Jaber Naeemah and Kuan Yew Wong
The purpose of this paper is (1) to review, analyze and assess the existing literature on lean tools selection studies published from 2005 to 2021; (2) to identify the limitations…
Abstract
Purpose
The purpose of this paper is (1) to review, analyze and assess the existing literature on lean tools selection studies published from 2005 to 2021; (2) to identify the limitations faced by previous studies; and (3) to suggest future works that are necessary to facilitate the selection of lean tools.
Design/methodology/approach
A systematic approach was used in order to identify, collect and select the articles. Several keywords related to the selection of lean tools were used to collect articles from different Scopus indexed journals. Next, the study systematically reviewed and analyzed the selected papers to identify the lean tools' selection method and discussed its features and limitations.
Findings
An analysis of the results showed that previous studies have adopted two types of methods for selecting lean tools. First, there are various traditional methods being used. Second, multi-criteria decision-making (MCDM) methods were commonly used in previous studies, such as the multi-objective decision-making method (MODM), single multi-attribute decision-making (MADM) methods and hybrid (MCDM). Moreover, the study revealed that the lean tools' selection methods in previous studies were based on evaluating the relationship between either lean tools and performance metrics or lean tools and waste, or both.
Research limitations/implications
In terms of its theoretical value, the study is considered as an extension of the previous researches performed on this topic by determining and analyzing the features of the most selection methods of lean tools. Unlike previous review papers, this review had considered discussing and analyzing the characteristics and limitations of these methods. Section 2.2 of this paper reviewed some of the categories of MCDM methods as well as some of the traditional methods used in the selected previous studies. Section 2.1 of this paper explained the concept of lean management and its application benefits. Further, only three sectors were covered by the previous studies in this review paper. This study also provided recommendations for future research. Therefore, it provided researchers with a good conception of how to conduct the studies on lean tools selection. Besides, knowing the methods used in previous studies can help researchers develop new methods to select the best set of lean tools. That is, this study provided and advanced the existing knowledge base for researchers concerning lean tools selection, especially there is limited availability of review papers on this topic. Moreover, the study showed researchers the importance of the relationship between lean tools and indicators or/and performance indicators to determine the appropriate set of lean tools so that the results of future studies will be more realistic and acceptable.
Practical implications
Practically, manufacturers face a significant challenge when selecting proper lean tools. This study may enhance managers, manufacturers and company's knowledge to identify most of the methods used to choose the best set of lean tools and what are the advantages, disadvantages and limitations of these methods as well as the latest studies that have been adopted in this topic. That means this study can direct companies to prioritize the application of lean tools depending on either the manufacturing performance metrics or/and manufacturing wastes so that they avoid incorrect application of lean tools, which will add more non-value added activities to operations. Therefore companies can decrease the time and cost losses and enhancing the quality and efficiency of the performance. Correctly implementing the best set of lean tools in companies will lead in general to correctly applying lean management in corporations. Therefore, these lean tools can boost the economic aspect of companies and society through reducing waste, improving performance indicators, preserving time and cost, achieving quality, efficiency, competitiveness, boosting employee income and improving the gross domestic product. The correct lean tool selection reduces customer complaints and employee stress and improves work conditions, health, safety and labor wellbeing. Besides, the correct lean tools selection improves materials usage, energy usage, water usage and decreases liquid wastes, solid wastes and air emissions. As a result, the right selection of lean tools will have positive effects on both the environment and society. The study may also encourage manufacturers and researchers to adopt studies on lean tools selection in small- and medium-sized companies because the study referred to the importance and participation of these kinds of companies in a large proportion of the economy of developing countries. Further, the study may encourage some countries that have not previously adopted this type of study, academically and industrially to conduct lean tools selection studies.
Social implications
As mentioned previously, the correct lean tool selection reduces customer complaints and employee stress and improves work conditions, health, safety and labor wellbeing. The proper lean tools selection improves materials usage, energy usage, water usage and decreases liquid wastes, solid wastes and air emissions. As a result, the right choice of lean tools will positively affect both the environment and society.
Originality/value
The study expanded the efforts of previous studies concerning lean management features. It provided an accurate review of most lean tools selection studies published from 2005 to 2021 and was not limited to the manufacturing sector. It further identified and briefly described the selection methods concerning lean tools adopted in each paper.
Details
Keywords
Ibrahim Abiodun Oladapo and Asmak Ab Rahman
One area of concern for Islamic economics is the challenges and discrimination experienced in Muslim societies and the lower human development indices compared to the Western…
Abstract
Purpose
One area of concern for Islamic economics is the challenges and discrimination experienced in Muslim societies and the lower human development indices compared to the Western counterparts. It is possible that the application of the theory of Maqāsid al Sharī’ah (TMS) could provide some insight on the problems and probably offer some support to the policymaker on the direction to take. The purpose of this paper is to apply TMS to validate the factors of human development.
Design/methodology/approach
The primary data were collected using a questionnaire. The target respondents were Muslims from Nigeria. Both stratified and purposeful random sampling techniques were used to collect the data, and the analyses were done by SPSS and AMOS statistical software.
Findings
In validating factors that contribute to human development, TMS framework is used, and the model integrates five factors which are considered most likely to have influence on human development. The model proposes that individual factors such social justice and human rights have effects on the factors of human development.
Originality value
This study provides understanding on the contributing factors to the persistent challenges of human development in predominantly Muslim settings. Previous research which has applied TMS focused more on its financial relevance and has not attempted to understand the situation and proffer solution.
Details
Keywords
Satyender Jaglan, Sanjeev Kumar Dhull and Krishna Kant Singh
This work proposes a tertiary wavelet model based automatic epilepsy classification system using electroencephalogram (EEG) signals.
Abstract
Purpose
This work proposes a tertiary wavelet model based automatic epilepsy classification system using electroencephalogram (EEG) signals.
Design/methodology/approach
In this paper, a three-stage system has been proposed for automated classification of epilepsy signals. In the first stage, a tertiary wavelet model uses the orthonormal M-band wavelet transform. This model decomposes EEG signals into three bands of different frequencies. In the second stage, the decomposed EEG signals are analyzed to find novel statistical features. The statistical values of the features are demonstrated using multi-parameters graph comparing normal and epileptic signals. In the last stage, the features are inputted to different conventional classifiers that classify pre-ictal, inter-ictal (epileptic with seizure-free interval) and ictal (seizure) EEG segments.
Findings
For the proposed system the performance of five different classifiers, namely, KNN, DT, XGBoost, SVM and RF is evaluated for the University of BONN data set using different performance parameters. It is observed that RF classifier gives the best performance among the above said classifiers, with an average accuracy of 99.47%.
Originality/value
Epilepsy is a neurological condition in which two or more spontaneous seizures occur repeatedly. EEG signals are widely used and it is an important method for detecting epilepsy. EEG signals contain information about the brain's electrical activity. Clinicians manually examine the EEG waveforms to detect epileptic anomalies, which is a time-consuming and error-prone process. An automated epilepsy classification system is proposed in this paper based on combination of signal processing (tertiary wavelet model) and novel features-based classification using the EEG signals.
Details
Keywords
The purpose of this paper is to provide an overview of behavioral pricing research, including the identification of the primary areas studied and a summary of the core findings in…
Abstract
Purpose
The purpose of this paper is to provide an overview of behavioral pricing research, including the identification of the primary areas studied and a summary of the core findings in each based on previous literature.
Design/methodology/approach
This research examines 613 articles on the ISI Web of Science database and focuses on marketing journals that discuss behavioral pricing. The reviews of these articles use traditional literature review and research profiling methods.
Findings
The main subareas in behavioral pricing this study identifies are the price–quality relationship, reference price, price awareness, price elasticity estimation and price fairness. In general, the behavioral pricing field is relatively new, and all subareas would benefit from additional research.
Originality/value
For pricing researchers, this study offers integrative insights into the field based on previous literature and identifies the main contribution and main topic of each. The study also offers suggestions for new research ideas.