Effects of climate change can already be observed in many regions of the world. The basin of the Paraná River, in South America, has been suffering an important drought since 2019 in the whole region. The extension of the crisis has increased the risks in the flora and fauna, losses in logistics of navigation, besides the problems of urban water cleansing. In this regard, the novel proposal presents a new mathematical model to study the impact of this crisis. Besides the traditional constraints of the literature for hydraulic systems, this paper enhances inventory constraints, connections with electric systems, and other considerations as the head effects in electricity generation. Because several equations related to electricity generation are nonlinear (which the subsequent computational effort impacts), this proposal applies linearization techniques to reduce CPU times. The core is related to hydropower production, and the consequences of the water crisis in the regional markets. The mathematical model analyzes the interrelationships between reservoirs and water flows of the basin. To study the effectiveness of the novel proposal, the reported situation of the basin of the Paraná River is studied by considering two scenarios (normal conditions of the river flow and the conditions related to the drought). Results show that the crisis implies daily net economic losses of about 7 million USD for the operators of the power plants. Other problems (different from the ones related to the energy field) are also mentioned and analyzed.

In this article, a multi-echelon supply chain for growing and deteriorating items, where the grower has a lot of live newborn items (growing) is discussed. The grower transfers the matured inventory to the processor in each shipment. The processor begins to process the stock as a ready-sale product in the market. The processor also delivers the processed inventory to the retailer in each shipment in the non-processing period of his cycle length. Then the processor offers trade credit to the retailer and makes the retailer agree to share a portion of his profit with him. The product’s life cycle when in the hand of the retailer is certain and it expires after some time t. Carbon emission during processing is considered while packing and preserving the livestock for sale. Depending on these assumptions, there are six possibilities to discuss profit values. Sensitivity analysis was also brought to verify the optimal determined values. The profit-sharing sharing method’s outcome benefits the processor and the retailer more.

This study sought to determine whether farm categories influence the key agro business supply chain metric of crop yield. The investigated farm categories are the communal farms, A1 farms, A2 farms, and commercial farms that reflect the agricultural structure that emerged from the post-fast-track land reform programme in Zimbabwe. Secondary data for crop yield was collected from the Tobacco Industry and Marketing Board publications of a five-year period spanning from 2014-2018. Tobacco Industry and Marketing Board is the regulatory authority of the Zimbabwean tobacco industry. The study used One-way ANOVA to test the specified hypotheses. A post hoc test was conducted using the Bonferroni procedure. The results indicated that crop yield is a function of the farm category. Communal farms had low crop yield, while A1 farm models proved to be very productive as evidenced by higher crop yield than any other farm category. A2 farms and commercial farms had unexpectedly low crop yield. The study recommended consolidation and transformation of communal areas into small-to-medium plots for the purposes of improving their agricultural viability, while at the same time downsizing the redundant A2 and commercial farms into small scale plots for the purposes of improving their efficiency. The study also recommended entering into resource-providing contract farming with A2 farmers whose current low yield might be due to lack of adequate input resources.

The purpose of the study is to examine the effects of supplier relationship management practices on organizational performance and competitive advantage of large manufacturing companies in Bahir Dar, Ethiopia. The study employed an explanatory research design. A standardized five-point Likert scale questionnaire was administered to manufacturing companies' executives, top managers, and procurement managers. Structural equation modeling with the help of analysis of moment structure 23 is used to analyze the relationship between variables. The result reveals that supplier relationship management practices lead to enhancing organizational performance and competitive advantage. Also, competitive advantage significantly affects the performance of manufacturing companies. The study is limited by the effects of supplier relationship management practices on organization performance and competitive advantage over a quantitative research approach. Further, it only focused on large manufacturing companies in Bahir Dar, Ethiopia. The study contributes evidence on the effects of supplier relationship management practices on organization performance and competitive advantage. Moreover, it helps the supply chain managers in large manufacturing companies to have a deeper understanding of supplier relationship management and its importance to organizational performance and competitive advantage.

To date, the use of three key aspects together has received little attention in studies on sustainable business models (SBMs). These aspects are a) the qualitative design of SBMs based on a valid sustainable business model canvas presented so far, b) the dynamic quantitative analysis of the designed SBMs, and c) the identification of appropriate business policies for different future scenarios, not just for one. Therefore, in this research, an attempt is made to study all three aspects by proposing a new practical framework based on one of the latest SBMs, called value triangular business model canvas (VTBMC), and system dynamics. To evaluate the proposed framework in the real world, it was implemented as a case study in Farassan Industrial and Manufacturing Company, one of the companies producing composite pipes. The results showed that the proposed framework helps business owners and managers identify the proper policies to achieve their key business objectives in the future under critical uncertainties and also create appropriate balanced values for a wide range of stakeholders, rather than just for shareholders.

The rapid expansion of Dubai and the United Arab United infrastructure in the Middle East over the past twenty years has resulted in a large accumulation of concrete waste in landfills and dumping sites. The subsequent hasty increase in the construction and demolition of the infrastructure has outstripped effective waste management facilities, posing a serious natural challenge. This concrete waste greatly endangers human health, property, and biological systems when buried. To find effective solutions to this issue, different waste management methods were researched and compared to find the most effective. This paper aims to differentiate the most appropriate waste management strategies and determine their impact on the environment. These methods included reducing the waste, reusing those wastes that can be reused, recycling, and disposal in landfills and government dumping sites. This paper opens the door for future studies to determine the impact indicators and specific waste management methods that substantially influence the environment and the cost of damage. In addition, a Life Cycle Cost Assessment (LCA) may be carried out to supplement this research and determine the financial benefits of the various specific waste management options and the cost of damages. The study predominantly assesses the different construction and demolition waste management strategies. It primarily adds valuable knowledge concerning these waste recycling management techniques and their environmental effect. This study also suggests directions for future exploration, such as identifying key impact indicators and management strategies that have a significant impact on the environment. Alternatively, LCA can complement the results by assessing the financial benefits of different physical waste management options. To sum up, the exponential growth of infrastructure in Dubai has led to a considerable challenge regarding concrete waste. The LCA-based comparison between landfill and recycling methods highlights the urgency of adopting sustainable waste management practices. This study not only broadens the understanding of damage cost models but also provides a comprehensive assessment of practical waste management options, contributing to informed decision-making to minimize environmental impact.

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.

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.

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.

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 %.