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Increasing safety in residential construction through a simplified earthquake- and typhoon-resistant guidelines
, Pages: 119-124 Linnel Marie S. Ballesteros, Shiva Ourang, Jennifer Pazdon and Karin Kuffel PDF (650K) |
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Abstract: This paper presents the engineering basis for a document, Residential Design and Construction Guidelines (hereafter, Guidelines). The Guidelines is developed by the engineers of Build Change and its partners based on their technical reconnaissance after the 2013 earthquake in Bohol on October 15, 2013, and Typhoon Haiyan on November 8, 2013. The Guidelines are centered on the observations of typical residential construction and damage in these areas and the requirements of the 2010 National Structural Code of the Philippines. The Guidelines provide illustrated and simple instructions on residential construction, making them accessible to homeowners and local builders. The Guidelines are designed for disaster-resistant, permanent low-rise housing construction, endorsed by the Department of Public Works and Highways of the Philippines (in March 2016). Increasing understanding and application of the Guidelines in residential construction in earthquake- and typhoon-prone areas will increase the structural safety of houses and the country's resiliency. DOI: 10.5267/j.jfs.2023.1.001 Keywords: Residential construction, Sustainability, Capacity building, Housing, Resilience
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The effect of digital communication technologies in retail supply chain management: Evidence from Indian small retailers
, Pages: 125-132 M. Karthik Ram, S. Selvabaskar, R. Guhan and K. Rajarathi PDF (650K) |
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Abstract: Indian retail industry held the second rank in A.T. Kearney's Global retail development index in 2021 and ranked 16th FDI confidence index. The retail industry provides ample job opportunities and contributes to the economic progress of the nation. After the advent of new innovation there are new technologies which have emerged in business and it also substantially changed consumer behavior. Digital communication allows the user to transfer data from one end to another using digital technologies like e-mail, phone calls, video conferencing, and several instant message applications. Digital communication allows retailers to send personalized business information to their loyal customers and the customers respond to those messages, which in turn generate business for unorganized retailers. Digital communication not only improves the business of unorganized retailers but also the business image, Geographical spread, profitability, new customer acquisition, customer retention, and the like. Digital communication will transform the traditional unorganized retailer into an offline-to-online commerce model. Based on theoretical review this study identified constructs and proposed major determinants which influence technology adoption and its continuance among the unorganized retailers. This study assesses the digital communication technology usage in supply chain management among unorganized retailers with the constructs like experience, effortlessness, efficiency, enrichment, trust, security, digital infrastructure, satisfaction, and continuous intention to use. The results show that digital communication technology's effort, experience, and efficiency influence satisfaction. However, enrichment failed to influence satisfaction. Further, the results show that satisfaction and security influence continuous intention to use. However, trust and digital infrastructure failed to influence. Therefore, digital communication technology usage in supply chain management among unorganized retailers is substantially influenced by constructs like effort, experience, efficiency, satisfaction, and security. DOI: 10.5267/j.jfs.2023.1.002 Keywords: Digital Communication technology, Supply chain management, Unorganized retailers, Effortlessness, Enrichment, Satisfaction
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Impact of global supply chain disruption on global supply chain resilience during pandemic like COVID-19
, Pages: 133-142 Syed Danish Bukhari and Irfan Zafar PDF (650K) |
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Abstract: During a pandemic like COVID-19, the country adopted a lockdown to minizine the spread of the pandemic which disrupted the global supply chain and supply chain resilience failed to minimize disruption. In this regard, this study aims to explore the resilience system among countries during a global disruption and the impact of supply chain disruption on supply chain resilience through misinformation/fake news, panic buying behavior, and inflation factors. For this purpose, the analytical study has been selected to predict the impact of supply chain disruption on supply chain resilience through misinformation/fake news, panic buying behavior, and inflation and propose a solution accordingly. The data from 89 countries are collected on various factors for the year 2020 and mediating analysis is selected to test the hypothesis through regression and correlation. They illustrate that there is a 46% correlation and 21% dependency between supply chain disruption and supply chain resilience through misinformation/fake news, panic buying behavior, supply chain disruption & inflation. The criterion validity of convergence validity and Cronbach of homogeneity test are applied. It has been found that panic buying behavior & supply chain disruption has a 71% strong correlation as compared to other factors and the reliability is 69% which is highly reliable and acceptable. In the end, it is concluded that strong coordination among countries will minimize global supply chain disruption through supply chain resilience for continuing supply chain activities and supply chain organizations & mass media organizations coordination with each other for minimizing misinformation/fake news, panic buying behavior supply chain disruption, and inflation factors to improve supply chain resilience by using artificial intelligence technology. DOI: 10.5267/j.jfs.2023.1.003 Keywords: Supply Chain Resilience, Global Disruption, Lockdown, Global Supply Chain
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Nature inspired firefighter assistant by unmanned aerial vehicle (UAV) data
, Pages: 143-166 Seyed Muhammad Hossein Mousavi and Atiye Ilanloo PDF (650K) |
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Abstract: One of the most hazardous phenomena in forests is wildfire or bush fire and early detection of massive damage prevention is vital. Employing Unmanned Aerial Vehicles (UAV) as a visual and extinguisher tool in order to prevent this tragedy which brings fatal effects on humans and wildlife has high importance. Additionally, using aerial imagery could assist firefighters to recognize fire intensity and localize and route the fire in the forest which shrinks down casualties of firefighters. All these benefits and more is just possible by employing cheap UAVs. The proposed research uses nature-inspired image processing techniques in order to segment and classify fire in color and thermal images. Multiple nature-inspired and traditional computer vision techniques, including Chicken Swarm Algorithm (CSA) intensity adjustment (contrast enhancement), Denoising Convolutional Neural Network (DnCNN), Local Phase Quantization (LPQ) feature extraction, Bees Image Segmentation, Biogeography-Based Optimization (BBO) feature selection, Firefly Algorithm (FA) classification and more are employed to achieve high classification and segmentation accuracy. The system evaluates nine performance metrics including, F-Score, Accuracy, and Jaccard for the segmentation stage and four performance metrics for the classification stage. All experiments are conducted on the two most recent UAV fire datasets of FLAME (2021) and DeepFire (2022). Additionally, fire intensity, fire direction, and fire geometrical calculation are calculated which assists firefighters even more. As smoke shows the location of the fire, a smoke detection workflow is proposed, too. Proposed system Compared with traditional and novel methods for segmentation and classification leading to satisfactory and promising results for almost all metrics. The trained model of this system could be used in most of the current rescue UAVs in real-time applications. For the FLAME dataset (color data), segmentation precision is 95.57 % and classification accuracy is 91.33 %. Also, For the DeepFire dataset segmentation precision is 91.74 % and classification accuracy is 96.88 %. DOI: 10.5267/j.jfs.2023.1.004 Keywords: Unmanned Aerial Vehicle (UAV), Forest Fire Detection, Nature Inspired Image Processing, Image Segmentation, Classification
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Selection of sustainable and green suppliers using a fuzzy R-method in group decision-making situations
, Pages: 167-182 Ravipudi Venkata Rao and Sarthakkumar Patel PDF (650K) |
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Abstract: A growing number of companies treat "sustainability" as an important objective in their strategy. Sustainable and green suppliers increase efficiency by reducing costs and waste in industries. Sustainable and green supplier selection is a critically important factor in moving forward along the path of sustainability. A fuzzy R-method is proposed in this paper based on ranking the fuzzy numbers of alternative suppliers and criteria. Triangular fuzzy membership function and different fuzzy scales are presented to demonstrate and validate the proposed method. Fuzzy composite scores are generated, and these scores are converted into crisp forms to evaluate the alternative suppliers. The novelty of the proposed method is that it is simple, can deal with qualitative and quantitative criteria of supplier selection, and requires less computational effort for evaluating and ranking the green and sustainable suppliers in fuzzy group decision-making situations. The weights of the criteria and alternative suppliers are generated using a simple equation and hence there is no need to apply different methods for weights generation and ranking. Furthermore, this method does not require normalization of the data. Two realistic group decision-making problems of green and sustainable supplier selection to test the method. Sensitivity analysis for the proposed method is also conducted to check the consistency of the proposed method to different weights of the criteria. The proposed method is effective, robust, and competitive to the existing multi-criteria decision making (MCDM) methods of sustainable supplier selection. DOI: 10.5267/j.jfs.2023.1.005 Keywords: Sustainability, Green supplier selection, Fuzzy scale, Multi-criteria decision making, R-method
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