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Achieving organizational performance by integrating industrial Internet of things in the SMEs: a developing country perspective
Purpose: This research investigates the adoption of the industrial Internet of things (IIoT) in SMEs to achieve and increase organizational performance. With the latest technology, small and medium-sized enterprises (SMEs) can create a competitive edge in the market and better serve customers. Design/methodology/approach: Twelve hypotheses are proposed for this study. This study constructed a questionnaire based on technological, organizational, environmental and human perspectives. A survey is conducted on the SMEs of India using the questionnaire. Findings: Eight hypotheses were accepted, and four hypotheses were not supported. The hypotheses rejected are infrastructure, organizational readiness, internal excellence and prior experience. The findings suggested that adopting IIoT in SMEs will increase organizational performance. Research limitations/implications: This study will be helpful for the manager, top management and policymakers. This study identified the areas SMEs need to work on to adopt the technologies. Originality/value: In the literature, no article considered IIoT adoption in SME firms as a human factor. Therefore, this study is unique, including human, technological, organizational and environmental factors. 2023, Emerald Publishing Limited. -
Investigating sustainable development for the COVID-19 vaccine supply chain: a structural equation modelling approach
Purpose: Immunization is one of the most cost-effective ways to save lives while promoting good health and happiness. The coronavirus disease 2019 (COVID-19) pandemic has served as a stark reminder of vaccines' ability to prevent transmission, save lives, and have a healthier, safer and more prosperous future. This research investigates the sustainable development (SD) of the COVID-19 vaccine supply chain (VSC). Design/methodology/approach: This study investigates the relationship between internal process, organizational growth, and its three pillars of SD environmental sustainability, economic sustainability and social sustainability. Survey-based research is carried out in the hospitals providing COVID-19 vaccines. Nine hypotheses are proposed for the study, and all the hypotheses got accepted. The survey was sent to 428 respondents and received 291 responses from health professionals with a response rate of 68%. For the study, the healthcare professionals working in both private and public hospitals across India were selected. Findings: The structural equation modelling (SEM) approach is used to test the hypothesis. All nine hypotheses are supported. This study examines a link between internal processes and organizational learning and the three sustainability pillars (environmental sustainability, economic sustainability and social sustainability). Practical implications: This study will help the management and the policymakers to think and adopt SD in the COVID-19 VSC. This paper also implies that robust immunization systems will be required in the future to ensure that people worldwide are protected from COVID-19 and other diseases. Originality/value: This paper shows the relationship between organizational learning and internal process with environmental sustainability, economic sustainability and social sustainability for the COVID-19. Studies on VSC of COVID-19 are not evident in any previous literature. 2022, Subhodeep Mukherjee, Manish Mohan Baral, Venkataiah Chittipaka, Surya Kant Pal and Ramji Nagariya. -
Intentions to adopt the blockchain: investigation of the retail supply chain
Purpose: Blockchain can track the material from the manufacturer to the end customers. Therefore, it can ensure the product's authenticity, transparency and trust in the retail supply chain (SC). There is a need to trace and track the retail products before it reaches the customers to check the quality of the products so that expired products can be recycled and reused, which in turn will help gain customers' trust. This research aims to investigate retail employees' behavioural intention to adopt blockchain in the retail SC. Design/methodology/approach: To examine the behavioural intention of employees in the retail SC, the research uses three theories the technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour. The technology acceptance model measures the employee's acceptance of blockchain in the retail SC. The unified theory of acceptance is used in this research to measure how blockchain adoption will improve the performance of the employees. The theory of planned behaviour is used in this research to measure whether the employees intend to adopt blockchain. A survey was carried out in the retail stores of India. Exploratory factor analysis and structural equation modelling were used for data analysis. Findings: This study found that the employees of the retail stores have a positive intention and attitude to adopt blockchain technology. Further, it was found that perceived behavioural control and effort expectancy was not promoting blockchain adoption in the retail sector. Practical implications: This study will help the retail stores' employees understand the blockchain in their operations and will motivate the top management of the retail companies to adopt this technology. The study is limited to the retail SC in India only. Originality/value: This study uses three theories technology acceptance model; the unified theory of acceptance and use of technology; and the theory of planned behaviour, which were not used in earlier studies of blockchain adoption in the retail SC. 2023, Emerald Publishing Limited. -
Systematic literature review and future research directions for service robots in hospitality and tourism industries; [????????????????????????]
Service robots create a touchless experience for travellers; therefore, this research aims to conduct a systematic literature review (SLR) of service robots in the tourism and hospitality sector. This study used the Scientific Procedures and Rationales for Systematic Literature Reviews (SPAR-4-SLR) approach for reviewing the articles. One hundred eighteen articles are selected for the final review. A thematic analysis divided the articles into three themes and nine sub-themes. For establishing the future research directions Theory, Methodology, and Context (TMC) framework was used and forty-one future research questions are proposed. The study provides various research implications concerning theory and practical perspective. Different management theories are linked with future research questions. Few review papers discussed the service robot in the context of the tourism sector, but none of these studies used the SPAR-4-SLR and TMC framework. This study comprehensively reviews the articles and provides potential future research directions. 2023 Informa UK Limited, trading as Taylor & Francis Group. -
Blockchain-based circular economy for achieving environmental sustainability in the Indian electronic MSMEs
Purpose: The circular economy is a production and consumption model that encourages people to share, lease, reuse, repair, refurbish and recycle existing materials and products for as long as possible. The blockchain-based circular economy is being used in many industries worldwide, but Indian electronic MSMEs face many problems in adopting a blockchain-based circular economy. The research aims to discover the barriers the electronic MSMEs face in adopting a blockchain-based circular economy and pull back from achieving environmental sustainability in their operations. Design/methodology/approach: Fifteen barriers are identified from the literature review and finalized with experts' opinions. These barriers are evaluated by using interpretive structural modeling (ISM), MICMAC analysis and fuzzy TOPSIS method. Findings: Lack of support from distribution channels, lack of traceability mechanism and customer attitudes toward purchasing remanufactured goods are identified as the most critical barriers. Practical implications: The study will benchmark the electronic MSMEs in achieving environmental sustainability in the blockchain-based circular economy. Originality/value: It is a study that not only establishes a hierarchical relationship among the barriers of blockchain adoption in Indian electronic MSMEs but also verifies the results with fuzzy TOPSIS method. 2022, Emerald Publishing Limited. -
Artificial intelligence-based reverse logistics for improving circular economy performance: adeveloping country perspective
Purpose: Reverse logistics services are designed to move goods from their point of consumption to an endpoint to capture value or properly dispose of products and materials. Artificial intelligence (AI)-based reverse logistics will help Micro, Small, and medium Enterprises (MSMEs) adequately recycle and reuse the materials in the firms. This research aims to measure the adoption of AI-based reverse logistics to improve circular economy (CE) performance. Design/methodology/approach: In this study, we proposed ten hypotheses using the theory of natural resource-based view and technology, organizational and environmental framework. Data are collected from 363 Indian MSMEs as they are the backbone of the Indian economy, and there is a need for digital transformation in MSMEs. A structural equation modeling approach is applied to analyze and test the hypothesis. Findings: Nine of the ten proposed hypotheses were accepted, and one was rejected. The results revealed that the relative advantage (RA), trust (TR), top management support (TMS), environmental regulations, industry dynamism (ID), compatibility, technology readiness and government support (GS) positively relate to AI-based reverse logistics adoption. AI-based reverse logistics indicated a positive relationship with CE performance. For mediation analysis, the results revealed that RA, TR, TMS and technological readiness are complementary mediation. Still, GS, ID, organizational flexibility, environmental uncertainty and technical capability have no mediation. Practical implications: The study contributed to the CE performance and AI-based reverse logistics literature. The study will help managers understand the importance of AI-based reverse logistics for improving the performance of the CE in MSMEs. This study will help firms reduce their carbon footprint and achieve sustainable development goals. Originality/value: Few studies focused on CE performance, but none measured the adoption of AI-based reverse logistics to enhance MSMEs CE performance. 2024, Emerald Publishing Limited. -
Linking supply chain resilience with knowledge management for achieving supply chain performance
Purpose: Supply chain (SC) and knowledge management (KM) have been studied; still, there is a need to understand how KM can be used for SC resilience and improving the firms performance. The purpose of the paper is to study and analyze SC resilience strategies based on KM processes to enhance SC performance considering six SC strategies: SC reengineering, collaboration, SC innovation, SC integration, SC agility and SC risk management. Design/methodology/approach: By adopting the dynamic capability theory, the empirical research is conducted on a sample of 312 Indian micro, small to medium enterprises. To evaluate 312 samples, the structural equation modeling approach is adopted. Findings: The study found a is a positive relationship between SC reengineering, SC collaboration, SC integration, SC agility, SC risk management and KM. Nevertheless, the relationship between SC innovation and KM is not significant. This study also found the mediating effect of KM on SC performance, and the results shows that SC reengineering, SC collaboration, SC agility and SC risk management are having complementary mediation, while SC innovation and SC integration did not show any mediation. Originality/value: This is the only research that integrates resilience strategies and KM for improving SC performance. Using KM, SC reengineering will improve SC performance by enhancing readiness and recovery strategies to avoid SC disruption. KM will improve SC collaboration. It will enhance the SC process overall visibility, transparency and so on. Agility leads to increased speed, visibility and flexibility, which aids in dealing with uncertainty in the environment. SCRM entails investments and additional resources (such as equipment and labor) to navigate uncertainty and risks in the SC and improve SC performance. 2023, Emerald Publishing Limited. -
Smart Mobile Device to Trace Moving Rogue Objects in Smart City Utilizing Dynamic Source Dynamic Destination Tracking Algorithm
In the present literature, various algorithms are available for computing the shortest path between two objects. The maximum number of these algorithms compute the shortest path either between two static objects or one static object and one dynamic object. This article presents an insight to integrated Mobile Edge Computing (MEC) based smart devices for tracking mobile rogue objects based on dynamic source and dynamic destination optimal cost estimation. This device considers any two mobile objects to estimate the shortest path between them. The proposed Ant Colony Optimization (ACO) based algorithm considers the property of dead-end removal and nth path exploration with efficient self-loop removal strategy. To review the performance of the proposed algorithm, experimentations are carried out and compared with several well-established shortest cost estimation techniques available in the literatureFloyd Warshall, Bellman Ford, Dijkstra, A* algorithms and the only dynamic shortest path algorithm. The detailed algorithmic comparisons clearly indicate the superiority of the proposed one over the existing dynamic and present state-of-the-art shortest path estimation methodologies. 2023 IETE. -
Tunable Capacitive Behavior in Metallopolymer-based Electrochromic Thin Film Supercapacitors
Volumetric capacitance is a more critical performance parameter for rechargeable power supply in lightweight and microelectronic devices as compared to gravimetric capacitance in larger devices. To this end, we report three electrochromic metallopolymer-based electrode materials containing Fe2+as the coordinating metal ion with high volumetric capacitance and energy densities in a symmetric two-electrode supercapacitor setup. These metallopolymers exhibited volumetric capacitance up to 866.2 F cm-3at a constant current density of 0.25 A g-1. The volumetric capacitance (poly-Fe-L2: 544.6 F cm-3> poly-Fe-L1: 313.8 F cm-3> poly-Fe-L3: 230.8 F cm-3at 1 A g-1) and energy densities (poly-Fe-L2: 75.5 mWh cm-3> poly-Fe-L1: 43.6 mWh cm-3> poly-Fe-L3: 31.2 mWh cm-3) followed the order of the electrical conductivity of the metallopolymers and are among the best values reported for metal-organic systems. The variation in the ligand structure was key toward achieving different electrical conductivities in these metallopolymers with excellent operational stability under continuous cycling. High volumetric capacitances and energy densities combined with tunable electro-optical properties and electrochromic behavior of these metallopolymers are expected to contribute to high performance and compact microenergy storage systems. We envision that the integration of smart functionalities with thin film supercapacitors would warrant the surge of miniaturized on-chip microsupercapacitors integrated in-plane with other microelectronic devices for wearable applications. 2022 American Chemical Society. All rights reserved. -
CMT-CNN: colposcopic multimodal temporal hybrid deep learning model to detect cervical intraepithelial neoplasia
Cervical cancer poses a significant threat to women's health in developing countries, necessitating effective early detection methods. In this study, we introduce the Colposcopic Multimodal Temporal Convolution Neural Network (CMT-CNN), a novel model designed for classifying cervical intraepithelial neoplasia by leveraging sequential colposcope images and integrating extracted features with clinical data. Our approach incorporates Mask R-CNN for precise cervix region segmentation and deploys the EfficientNet B7 architecture to extract features from saline, iodine, and acetic acid images. The fusion of clinical data at the decision level, coupled with Atrous Spatial Pyramid Pooling-based classification, yields remarkable results: an accuracy of 92.31%, precision of 90.19%, recall of 89.63%, and an F-1 score of 90.72. This achievement not only establishes the superiority of the CMT-CNN model over baselines but also paves the way for future research endeavours aiming to harness heterogeneous data types in the development of deep learning models for cervical cancer screening. The implications of this work are profound, offering a potent tool for early cervical cancer detection that combines multimodal data and clinical insights, potentially saving countless lives. 2024, Universitas Ahmad Dahlan. All rights reserved. -
EGMM: removal of specular reflection with cervical region segmentation using enhanced Gaussian mixture model in cervix images
Colposcopy is a crucial imaging technique for finding cervical abnormalities. Colposcopic image evaluation, particularly the accurate delineation of the cervix region, has considerable medical significance.Before segmenting the cervical region, specular reflection removal is an efficient one. Because, cervical cancer can be found using a visual check with acetic acid, which turns precancerous and cancerous areas whiteand these could be viewed as signs of abnormalities. Similarly, bright white regions known as specular reflections obstruct the identification of aceto-whiteareas and should therefore be removed. So, in this paper, specular reflection removal with segmentingthe cervix region ina colposcopy image is proposed. The proposed approach consists of two main stages, namely, pre-processing and segmentation. In the pre-processing stage, specular reflections are detected and removed using a swin transformer. After that, cervical regions are segmented using an enhanced Gaussian mixture model (EGMM). For better segmentation accuracy, the best parameters of GMM are chosen via the adaptive Mexican Axolotl Optimization (AMAO) algorithm. The performance of the proposed approach is analyzed based on accuracy, sensitivity, specificity, Jaccard index, and dice coefficient, and the efficiency of the suggested strategy is compared with various methods. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Media's influence on suicide: Building a safer online world for all
In 1999, World Health Organization (WHO) initiated a global campaign focused on suicide prevention. In collaboration with International Association for Suicide Prevention, WHO compiled recommendations and resources intended to educate various societal and groups with the potential to impact suicide prevention, and this included the media. In order to combat the alarmingly high incidence of suicides (Tandon and Nathani, 2018), it is imperative to institute guidelines outlining how the social media forums ought to disseminate altruistic, essential educational content while. This work is a step toward achieving the same by laying down guidelines that could potentially reduce the suicide rate. 2023 Elsevier B.V. -
TelsNet: temporal lesion network embedding in a transformer model to detect cervical cancer through colposcope images
Cervical cancer ranks as the fourth most prevalent malignancy among women globally. Timely identification and intervention in cases of cervical cancer hold the potential for achieving complete remission and cure. In this study, we built a deep learning model based on self-attention mechanism using transformer architecture to classify the cervix images to help in diagnosis of cervical cancer. We have used techniques like an enhanced multivariate gaussian mixture model optimized with mexican axolotl algorithm for segmenting the colposcope images prior to the Temporal Lesion Convolution Neural Network (TelsNet) classifying the images. TelsNet is a transformer-based neural network that uses temporal convolutional neural networks to identify cancerous regions in colposcope images. Our experiments show that TelsNet achieved an accuracy of 92.7%, with a sensitivity of 73.4% and a specificity of 82.1%. We compared the performance of our model with various state-of-the-art methods, and our results demonstrate that TelsNet outperformed the other methods. The findings have the potential to significantly simplify the process of detecting and accurately classifying cervical cancers at an early stage, leading to improved rates of remission and better overall outcomes for patients globally. 2023, Universitas Ahmad Dahlan. All rights reserved. -
Predicting the financial behavior of Indian salaried-class individuals
COVID-19 has caused not only unprecedented health crises but also economic crises among individuals across the world. White-collar (salaried-class) employees with a fixed salary face financial insecurity due to job loss, pay cuts and uncertainty in retaining a job. This study examines the financial behavior of Indian white-collar salariedclass investors to their cognitive biases. In addition, the mediating effect of financial self-efficacy on cognitive biases and financial behavior is examined. Respondents were given structured questionnaires (google forms) through emails and WhatsApp for data collection. SPSS and R-PLS are used to analyze the data. Conservatism (r = -.603, p < 0.05) and herding bias (r = -.703, p < 0.05) have a significant negative correlation with financial behavior. Financial self-efficacy has a significant positive correlation (r =.621. p < 0.050). Conservatism and herding predicted 60.5% and 62.2% of the variance, respectively. The direct and indirect paths between conservatism bias, financial self-efficacy, and financial behavior are significant. The paths between herding, financial self-efficacy and financial behavior are also significant. Ankita Mulasi, Jain Mathew, Kavitha Desai, 2022. -
JP-DAP: An Intelligent Data Analytics Platform for Metro Rail Transport Systems
This paper deals with an intelligent data analytics platform-Jaison-Paul Data Analytics Platform (JP-DAP)-for metro rail transport systems. JP-DAP is intended to ensure smooth functioning, improved customer experience, ridership forecasting, and efficient administration of metro rail transportation systems by integrating and analysing its many data sources. It consists of a middleware which is built on the top of a Hadoop Distributed File System (HDFS) and Spark framework, along with a set of open-source software tools like Apache Hive, Pandas, Google TensorFlow and Spark ML-lib for real-time and legacy data processing. The benchmarking of JP-DAP was conducted using TestDFSIO and have found that it performs well according to industry standards. The specific use case for this project is Kochi Metro Rail Limited (KMRL). The analysis of Automated Fare Collection data from KMRL on JP-DAP framework have produced descriptive statistics visualisation of inflow and outflow analysis, travel patterns during weekdays and weekends, origin-destination matrix, etc.. Moreover JP-DAP framework is capable of producing short term passenger flow predictions using SVR machine learning algorithm with linear, radial basis function and polynomial kernels. Our experiments have shown that SVR linear kernel gives the most accurate results with the least errors in predicting the next day's passenger count using the previous five weekdays data. The station usage (one-to-all) prediction using Long Short-Term Memory (LSTM) is also integrated to this framework. The visualisation as well as analytical outcomes of JP-DAP framework have also been made available to the external world using a rich set of REST APIs and are projected on to a web-dashboard. 2000-2011 IEEE. -
Restrained geodetic domination of edge subdivision graph
For a connected graph G = (V,E), a set S subset of V (G) is said to be a geodetic set if all vertices in G should lie in some u-v geodesic for some u,v S. The minimum cardinality of the geodetic set is the geodetic number. In this paper, the authors discussed the geodetic number, geodetic domination number, and the restrained geodetic domination of the edge subdivision graph. 2022 World Scientific Publishing Company. -
Restrained geodetic domination in graphs
Let G = (V,E) be a graph with edge set E and vertex set V. For a connected graph G, a vertex set S of G is said to be a geodetic set if every vertex in G lies in a shortest path between any pair of vertices in S. If the geodetic set S is dominating, then S is geodetic dominating set. A vertex set S of G is said to be a restrained geodetic dominating set if S is geodetic, dominating and the subgraph induced by V - S has no isolated vertex. The minimum cardinality of such set is called restrained geodetic domination (rgd) number. In this paper, rgd number of certain classes of graphs and 2-self-centered graphs was discussed. The restrained geodetic domination is discussed in graph operations such as Cartesian product and join of graphs. Restrained geodetic domination in corona product between a general connected graph and some classes of graphs is also discussed in this paper. 2020 World Scientific Publishing Company. -
Process scheduling in heterogeneous multicore system using agent based graph coloring algorithm
In any heterogeneous multicore system, there are numerous amount of processors with different platform and all the processing units are fabricated on a common single unit preferably on a System on Chip. As there is a tremendous amount of parallelism encompassed in a multicore system, proper utilization of the cores is a big challenge in the current era. Hence a more automated software approach is required like an agent based graph coloring algorithm to find the free processor and schedule the tasks on the respective cores. Predominantly the entire process of scheduling the tasks on multicore system is based on arrival time of process. This paper incorporates the scheduling on the linux 2.6.11 kernel and GEMS simulator for multicore implementation. The core utilization in this type of agent scheduling is 50% more than the existing scheduling mechanism. BEIESP. -
Comparative Study on the Experimental Results on Low-Velocity Impact Characteristics of GLARE Laminates with Simulation Results from LS Dyna
Fiber reinforcement with metallic face sheets is one of the recently implemented materials for distinctive applications in automotive and aerospace sectors. While the reinforcement enhances the sustenance property of the laminate, the face sheets provide resistance to impact force. In most automotive sectors, drop weight analysis at varying velocity ranges is performed to evaluate the damage characteristics of the vehicle body. The present work is aimed at studying the influence of low-velocity impact (LVI) on Glass Laminate Aluminum-Reinforced Epoxy (GLARE) laminate. Three distinct thicknesses of Al-2024 T3 aluminum alloy (0.2, 0.3 and 0.4mm) were chosen as the face sheet and E-glass fiber was used as intermediate layers. Epoxy resin LY556 with a HY951 hardener was used to fabricate the GLARE structure and the overall thickness was maintained at 2.0mm for all the cases. Energy absorbed by GLARE laminates for different energy was determined using Drop weight Impact test experimentally and analytically. The laminate and the dart were modeled by ANSYS ACP tool and the simulation was performed using LS Dyna software. It was evident that laminate can sustain impact at a velocity of 3.13m/s and beyond which leads to surface delamination. The simulation results were in close agreement with the experimental values for the absorbed energy, with less than 10% error. 2022, The Institution of Engineers (India). -
A Statistical Analysis and Comparison of the spread of Swine Flu and COVID-19 in India
Introduction: The world is currently experiencing the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) [COVID-19], however, this is not a new phenomenon; it occurred in 2009-2010 in the form of novel influenza A. (H1N1). The H1N1 virus primarily afflicted people between the ages of 26 and 50, but SARS-CoV-2 primarily afflicted those over the age of 60, increasing the number of deaths owing to their weakened immunity. The report provides a case study of the impact of H1N1 and SARS-CoV-2 in India. Methods: Data is obtained from The Hindustan Times newspaper, GoI press releases and World Health Organization (WHO) reports. Results: The incidence rate was initially low and it was only by the 10-15th week that it started increasing. There is an initial upward trend before levelling out followed by a second wave and third wave. COVID-19 exhibited a steeper growth, where the steps taken by the Government were ineffective leading to higher death cases. Kerala was affected due to the travellers returning from the Middle East, while Maharashtra and Delhi saw large incidence rates due to the migrant influx and communal gathering. Conclusion: The most effective and practical approach is to test the symptomatic patients and aggressive testing to contain the transmission. Awareness campaigns to educate the public about social distancing and personal hygiene is more practical. There is still scope of improvement with regards to the public health care support, preparedness and response. Lockdown measures could have been avoided if the initial screening was conducted properly. 2022 UPM Press. All rights reserved.