Search results for: electricity market

Authors: Josué Alfredo Tomas Machaca Fajardo, Jhon Elvis Chahua Janampa, Pedro Rau Lavado

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A flood vulnerability index was developed for the Piura River watershed in northern Peru using Principal Component Analysis (PCA) to assess flood risk. The official methodology to assess risk from natural hazards in Peru was introduced in 1980 and proved effective for aiding complex decision-making. This method relies in part on decision-makers defining subjective correlations between variables to identify high-risk areas. While risk identification and ensuing response activities benefit from a qualitative understanding of influences, this method does not take advantage of the advent of national and international data collection efforts, which can supplement our understanding of risk. Furthermore, this method does not take advantage of broadly applied statistical methods such as PCA, which highlight central indicators of vulnerability. Nowadays, information processing is much faster and allows for more objective decision-making tools, such as PCA. The approach presented here develops a tool to improve the current flood risk assessment in the Peruvian basin. Hence, the spatial analysis of the census and other datasets provides a better understanding of the current land occupation and a basin-wide distribution of services and human populations, a necessary step toward ultimately reducing flood risk in Peru. PCA allows the simplification of a large number of variables into a few factors regarding social, economic, physical and environmental dimensions of vulnerability. There is a correlation between the location of people and the water availability mainly found in rivers. For this reason, a comprehensive vision of the population location around the river basin is necessary to establish flood prevention policies. The grouping of 5x5 km gridded areas allows the spatial analysis of flood risk rather than assessing political divisions of the territory. The index was applied to the Peruvian region of Piura, where several flood events occurred in recent past years, being one of the most affected regions during the ENSO events in Peru. The analysis evidenced inequalities for the access to basic services, such as water, electricity, internet and sewage, between rural and urban areas.

Keywords: assess risk, flood risk, indicators of vulnerability, principal component analysis

Procedia PDF Downloads 186

Authors: Thiago Ribeiro de Alencar, Jacyro Gramulia Junior, Patricia Teixeira Leite

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The area of the electricity sector that deals with energy needs by the hydroelectric in a coordinated manner is called Operation Planning of Hydrothermal Power Systems (OPHPS). The purpose of this is to find a political operative to provide electrical power to the system in a given period, with reliability and minimal cost. Therefore, it is necessary to determine an optimal schedule of generation for each hydroelectric, each range, so that the system meets the demand reliably, avoiding rationing in years of severe drought, and that minimizes the expected cost of operation during the planning, defining an appropriate strategy for thermal complementation. Several optimization algorithms specifically applied to this problem have been developed and are used. Although providing solutions to various problems encountered, these algorithms have some weaknesses, difficulties in convergence, simplification of the original formulation of the problem, or owing to the complexity of the objective function. An alternative to these challenges is the development of techniques for simulation optimization and more sophisticated and reliable, it can assist the planning of the operation. Thus, this paper presents the development of a computational tool, namely Hydro-IA for solving optimization problem identified and to provide the User an easy handling. Adopted as intelligent optimization technique is Genetic Algorithm (GA) and programming language is Java. First made the modeling of the chromosomes, then implemented the function assessment of the problem and the operators involved, and finally the drafting of the graphical interfaces for access to the User. The results with the Genetic Algorithms were compared with the optimization technique nonlinear programming (NLP). Tests were conducted with seven hydroelectric plants interconnected hydraulically with historical stream flow from 1953 to 1955. The results of comparison between the GA and NLP techniques shows that the cost of operating the GA becomes increasingly smaller than the NLP when the number of hydroelectric plants interconnected increases. The program has managed to relate a coherent performance in problem resolution without the need for simplification of the calculations together with the ease of manipulating the parameters of simulation and visualization of output results.

Keywords: energy, optimization, hydrothermal power systems, artificial intelligence and genetic algorithms

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Authors: Yosr Ghozzi

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The Cyber-Physical Systems terminology has been well received by the industrial community and specifically appropriated in educational settings. Indeed, our latest educational activities are based on the development of experimental platforms on an industrial scale. In fact, we built a collaborative learning model because of an international market study that led us to place ourselves at the heart of this technology. To align with these findings, a competency-based approach study was conducted, and program content was revised by reflecting the projectbased approach. Thus, this article deals with the development of educational devices according to a generated curriculum and specific educational activities while respecting the repository of skills adopted from what constitutes the educational cyber-physical production systems and the laboratories that are compliant and adapted to them. The implementation of these platforms was systematically carried out in the school's workshops spaces. The objective has been twofold, both research and teaching for the students in mechatronics and logistics of the electromechanical department. We act as trainers and industrial experts to involve students in the implementation of possible extension systems around multidisciplinary projects and reconnect with industrial projects for better professional integration.

Keywords: education 4.0, competency-based learning, teaching factory, project-based learning, cyber-physical systems, industry 4.0

Procedia PDF Downloads 107

Authors: Habtamu Ayenew Asegie

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Wealth, as opposed to income or consumption, implies a more stable and permanent status. Due to natural and human-made difficulties, households' economies will be diminished, and their well-being will fall into trouble. Hence, governments and humanitarian agencies offer considerable resources for poverty and malnutrition reduction efforts. One key factor in the effectiveness of such efforts is the accuracy with which low-income or poor populations can be identified. As a result, this study aims to predict a household’s wealth status using ensemble Machine learning (ML) algorithms. In this study, design science research methodology (DSRM) is employed, and four ML algorithms, Random Forest (RF), Adaptive Boosting (AdaBoost), Light Gradient Boosted Machine (LightGBM), and Extreme Gradient Boosting (XGBoost), have been used to train models. The Ethiopian Demographic and Health Survey (EDHS) dataset is accessed for this purpose from the Central Statistical Agency (CSA)'s database. Various data pre-processing techniques were employed, and the model training has been conducted using the scikit learn Python library functions. Model evaluation is executed using various metrics like Accuracy, Precision, Recall, F1-score, area under curve-the receiver operating characteristics (AUC-ROC), and subjective evaluations of domain experts. An optimal subset of hyper-parameters for the algorithms was selected through the grid search function for the best prediction. The RF model has performed better than the rest of the algorithms by achieving an accuracy of 96.06% and is better suited as a solution model for our purpose. Following RF, LightGBM, XGBoost, and AdaBoost algorithms have an accuracy of 91.53%, 88.44%, and 58.55%, respectively. The findings suggest that some of the features like ‘Age of household head’, ‘Total children ever born’ in a family, ‘Main roof material’ of their house, ‘Region’ they lived in, whether a household uses ‘Electricity’ or not, and ‘Type of toilet facility’ of a household are determinant factors to be a focal point for economic policymakers. The determinant risk factors, extracted rules, and designed artifact achieved 82.28% of the domain expert’s evaluation. Overall, the study shows ML techniques are effective in predicting the wealth status of households.

Keywords: ensemble machine learning, households wealth status, predictive model, wealth status prediction

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Authors: Jonghae Park, Daesung Kim

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The impact of aggressive and conservative working capital‘s strategies on the value and profitability of the firms has been evaluated by applying the panel data regression analysis. The control variables used in the regression models are natural log of firm size, sales growth, and debt. We collected a panel of 13,988 companies listed on the Korea stock market covering the period 2000-2016. The major findings of this study are as follow: 1) We find a significant negative correlation between firm profitability and the number of days inventory (INV) and days accounts payable (AP). The firm’s profitability can also be improved by reducing the number of days of inventory and days accounts payable. 2) We also find a significant positive correlation between firm profitability and the number of days accounts receivable (AR) and cash ratios (CR). In other words, the cash is associated with high corporate profitability. 3) Tobin's analysis showed that only the number of days accounts receivable (AR) and cash ratios (CR) had a significant relationship. In conclusion, companies can increase profitability by reducing INV and increasing AP, but INV and AP did not affect corporate value. In particular, it is necessary to increase CA and decrease AR in order to increase Firm’s profitability and value.

Keywords: working capital, working capital management, firm value, profitability

Procedia PDF Downloads 189

Authors: Farah Kanani

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Blue Tide Environmental is a company focused on developing a network of used motor oil recycling facilities across the U.S. They initiated the redesign of its recycling plant in Texas, and aimed to establish an updated carbon footprint of re-refined used motor oils compared to an equivalent product derived from virgin stock that is not re-refined. The aim was to quantify emissions savings of a circular alternative to conventional end-of-life combustion of used motor oil (UMO). To do so, they mandated an ISO-compliant carbon footprint, utilizing complex models requiring geographical and temporal accuracy to accommodate the U.S. refinery market. The quantification of linear and circular flows, proxies for fuel substitution and system expansion for multi-product outputs were all critical methodological choices and were tested through sensitivity analyses. The re-refined system consisted of continuous recycling of UMO and thus, end-of-life is considered non-existent. The unique perspective to this topic will be from a life cycle i.e. holistic one and essentially demonstrate using this example of how a cradle-to-cradle model can be used to quantify a comparative carbon footprint. The intended audience is lubricant manufacturers as the consumers, motor oil industry professionals and other industry members interested in performing a cradle-to-cradle modeling.

Keywords: circularity, used motor oil, re-refining, systems expansion

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Authors: Ayat-Allah Bouramdane

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Since 2010, there have been sustained decreases in the unit costs of onshore wind energy and large increases in its deployment, varying widely across regions. In fact, the onshore wind production is affected by air density— because cold air is more dense and therefore more effective at producing wind power— and by wind speed—as wind turbines cannot operate in very low or extreme stormy winds. The wind speed is essentially affected by the surface friction or the roughness and other topographic features of the land, which slow down winds significantly over the continent. Hence, the identification of the most appropriate locations of onshore wind systems is crucial to maximize their energy output and therefore minimize their Levelized Cost of Electricity (LCOE). This study focuses on the preliminary assessment of onshore wind energy potential, in several areas in Morocco with a particular focus on the Dakhla city, by analyzing the diurnal and seasonal variability of wind speed for different hub heights, the frequency distribution of wind speed, the wind rose and the wind performance indicators such as wind power density, capacity factor, and LCOE. In addition to climate criterion, other criteria (i.e., topography, location, environment) were selected fromGeographic Referenced Information (GRI), reflecting different considerations. The impact of each criterion on the suitability map of onshore wind farms was identified using the Analytic Hierarchy Process (AHP). We find that the majority of suitable zones are located along the Atlantic Ocean and the Mediterranean Sea. We discuss the sensitivity of the onshore wind site suitability to different aspects such as the methodology—by comparing the Multi-Criteria Decision-Making (MCDM)-AHP results to the Mean-Variance Portfolio optimization framework—and the potential impact of climate change on this suitability map, and provide the final recommendations to the Moroccan energy strategy by analyzing if the actual Morocco's onshore wind installations are located within areas deemed suitable. This analysis may serve as a decision-making framework for cost-effective investment in onshore wind power in Morocco and to shape the future sustainable development of the Dakhla city.

Keywords: analytic hierarchy process (ahp), dakhla, geographic referenced information, morocco, multi-criteria decision-making, onshore wind, site suitability.

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Authors: Faris Algarni

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The Kingdom of Saudi Arabia adopted a new law of e-commerce on July 10, 2019, which is the first Saudi law regarding e-commerce. The practice of e-commerce has been started in Saudi Arabia a few years ago with no specific rules to govern e-commerce in the Kingdom. The adoption of the law raises the concern of the ability of the law to provide real protection to both the investors and the customers. Based on that, this article seeks to respond to some questions related to the protection of investors of e-commerce in Saudi Arabia, using a quantitative method through questionnaires to gather primary data. The study tried to find the impact of adopting a new Saudi law of e-commerce on the protection of the investors from the point of view of those investors. By answering this main question, this article provides an answer to the question of whether there is a need to reform the Saudi law of e-commerce to convince existing and potential foreign investors to invest in the Kingdom through e-commerce. Questions were put to the respondents to determine their level of satisfaction with the Saudi law of e-commerce and what reforms to that system would enhance the attractiveness of the Kingdom as an investment environment for e-commerce investors, based on the information gathered and the analysis of them. A key finding is that the law of e-commerce is a core factor in the decision of investors to continue investing in the e-commerce market in Saudi Arabia. A subsequent finding is that some of the respondents are not fully satisfied with the new law and think that the law provides more protection to the customers than the investors. So, they are suggesting some legal reforms to be implemented in the bylaw of e-commerce, which is not adopted yet in order to attract them to continue investing in the Kingdom.

Keywords: e-commerce, law, investors, protection, Saudi Arabia

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Authors: Yuyang Cheng, Marcos Escobar-Anel

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This paper introduces a multivariate 4/2 stochastic covariance process generalizing the one-dimensional counterparts presented in Grasselli (2017). Our construction permits stochastic correlation not only among stocks but also among volatilities, also known as co-volatility movements, both driven by more convenient 4/2 stochastic structures. The parametrization is flexible enough to separate these types of correlation, permitting their individual study. Conditions for proper changes of measure and closed-form characteristic functions under risk-neutral and historical measures are provided, allowing for applications of the model to risk management and derivative pricing. We apply the model to an expected utility theory problem in incomplete markets. Our analysis leads to closed-form solutions for the optimal allocation and value function. Conditions are provided for well-defined solutions together with a verification theorem. Our numerical analysis highlights and separates the impact of key statistics on equity portfolio decisions, in particular, volatility, correlation, and co-volatility movements, with the latter being the least important in an incomplete market.

Keywords: stochastic covariance process, 4/2 stochastic volatility model, stochastic co-volatility movements, characteristic function, expected utility theory, verication theorem

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Authors: Suzanne Bouma

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In the Netherlands, the assumed causal relationship between employment, economic independence and individual freedom of choice has been extended to the approach of intimate partner violence (IPV). In the interests of combating IPV, it is crucial to further investigate this relationship. Based on a literature review, this article shows that the relationship between economic independence and IPV is highly complex. To unravel this complex relationship, a socio-ecological analysis framework has been applied. First, it is a layered relation, in where employment does not necessarily lead to economic independence, which can be explained by social inequalities. Second, the relation is bidirectional, where women do not by definition have access to their own financial recourses due to tactics of financial control by the intimate partner. This reveals the coexistence of IPV and economic abuse and the extent to which an intimate relationship affects the scope for individual choice. Third, there is a paradoxical relationship in which employment is both a protective and risk factor for IPV. This, in turn, cannot be separated from traditional norms about masculinity and femininity, where men occupy a position of power and derive status from being the breadwinner. These findings imply that not only the approach to IPV but also the labor market policy requires a gender-sensitive approach.

Keywords: intimate partner violence, economic independence, literature review, socio-ecological analysis framework

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Authors: Ijaz Ahmad

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Weed competition is one of the major biotic constraints in wheat crop productivity. Avena fatua L. and Silybum marianum (L.) Gaertn. are among the worst weeds of wheat, greatly deteriorating wheat quality subsequently reducing its market value. In this connection, two-year experiments were conducted in 2018 & 2019. Different seeding rate wheat viz; 80, 100, 120 and 140 kg ha-1 and different weeds ratio (A. fatua: S. marianum ) sown at the rate 1:8, 2:7, 3:6, 4:5, 5:4, 6:3, 7:2, 8:1 and 0:0 respectively. The weeds ratio and wheat densities are indirectly proportional. However, the wheat seed at the rate of 140 kg ha-1 has minimal weeds interference. Yield losses were 17.5% at weeds density 1:8 while 7.2% at 8:1. However, in wheat density, the highest percent losses were computed on 80 kg ha-1 while the lowest was recorded on 140 kg ha-1. Since due to the large leaf canopy of S. marianum other species can't sustain their growth. Hence, it has been concluded that S. marianum is the hotspot that causes reduction to the yield-related parameters, followed by A. fatua and the other weeds. Due to the morphological mimicry of A. fatua with wheat crop during the vegetative growth stage, it cannot be easily distinguished. Therefore, managing A. fatua and S. marianum before seed setting is recommended for reducing the future weed problem. Based on current studies, it is suggested that sowing wheat seed at the rate of 140 kg ha-1 is recommended to better compete with all the field weeds.

Keywords: fat content, holly thistle, protein content, weed competition, wheat, wild oat

Procedia PDF Downloads 207

Authors: Olukayode Bamgbose, Feyisola Agboola, Adewale M. Taiwo, Olanrewaju Olujimi Oluwole Terebo, Azeez Soyingbe, Akeem Bamgbade

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The present study evaluated the contents and health risk assessment of metals determined in milk and milk product samples collected from the Abeokuta market. Forty-five milk and milk product (yoghurt) samples were digested and analysed for selected metals using Atomic Absorption Spectrophotometric method. Health risk assessment was evaluated for hazard quotient (HQ), hazard index (HI), and cancer risk (CR). Data were subjected to descriptive and inferential statistics. The concentrations of Zn, which ranged from 3.24±0.59 to 4.35±0.59 mg/kg, were the highest in the samples. Cr and Cd were measured below the detection limit of the analytical instrument, while the Pb level was higher than the Codex Alimentarius Commission value of 0.02 mg/kg, indicating unsafe for consumption. However, the HQ of Pb and other metals in milk and milk product samples was less than 1.0, thereby establishing no adverse health effects for Pb and other metals. The distribution pattern of metals in milk and milk product samples followed the decreasing order of Zn > Fe > Ni > Co > Cu > Mn > Pb > Cd/Cr. The CR levels of meals were also less than the permissible limit of 1.0 x 10-4, establishing no possible development of cancer. Keywords: adverse effects, cancer, metals, milk, milk product, the permissible limit.

Keywords: adverse effects, cancer, metals, milk, milk product, permissible limit

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Authors: Saira Naeem, Rana Muhammad Ayyub

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The main objective of this study is to empirically study the antecedents of perceptions of non-Muslim consumers towards Halal foods. The questionnaire survey was conducted through surveymonkey.com from non-Muslims (n=222) of USA. The validated scales of knowledge about Halal foods, animal welfare concerns, acculturation and perception about Halal foods were adopted after necessary adaptation as measures. The structural equation modelling (SEM) approach was used to study the structural model. It was found that Knowledge about Halal foods and ongoing acculturation among non-Muslims has a positive effect on perception about Halal food whereas; animal welfare concerns have negative effect on it. Furthermore, the acculturation has moderating effects but it was found non-significant. It is recommended that Halal food marketers should increase their efforts to educate customers by updating their knowledge about it. Furthermore, it is recommended that the non-Muslim consumers must be apprised of the fact that their animal welfare concerns are adequately addressed while Halal food production and supply chain. Online data collection is the only limitation of this study. This study will guide the Halal marketers of western countries about how to market the Halal food products and services to serve the non-Muslim customers.

Keywords: non-Muslims, consumer perceptions, animal welfare concerns, acculturation, knowledge about Halal

Procedia PDF Downloads 116

Authors: Ali R. Alshawawreh, Francisco Liébana-Cabanillas, Francisco J. Blanco-Encomienda

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Collaboration between marketing and business intelligence (BI) is crucial in today's ever-evolving business landscape. These two domains play pivotal roles in molding customers' experiential knowledge. Marketing insights offer valuable information regarding customer needs, preferences, and behaviors. Conversely, BI facilitates data-driven decision-making, leading to heightened operational efficiency, product quality, and customer satisfaction. Customer experiential knowledge (CEK) encompasses customers' implicit comprehension of consumption experiences influenced by diverse factors, including social and cultural influences. This study primarily focuses on telecommunications companies in Jordan, scrutinizing how experiential customer knowledge mediates the relationship between marketing intelligence and business intelligence. Drawing on theoretical frameworks such as the resource-based view (RBV) and service-dominant logic (SDL), the research aims to comprehend how organizations utilize their resources, particularly knowledge, to foster Evolution. Employing a quantitative research approach, the study collected and analyzed primary data to explore hypotheses. Structural equation modeling (SEM) facilitated by Smart PLS software evaluated the relationships between the constructs, followed by mediation analysis to assess the indirect associations in the model. The study findings offer insights into the intricate dynamics of organizational Creation, uncovering the interconnected relationships between business intelligence, customer experiential knowledge-based innovation (CEK-DI), marketing intelligence (MI), and product and service innovation (PSI), underscoring the pivotal role of advanced intelligence capabilities in developing innovative practices rooted in a profound understanding of customer experiences. Furthermore, the positive impact of BI on PSI reaffirms the significance of data-driven decision-making in shaping the innovation landscape. The significant impact of CEK-DI on PSI highlights the critical role of customer experiences in driving an organization. Companies that actively integrate customer insights into their opportunity creation processes are more likely to create offerings that match customer expectations, which drives higher levels of product and service sophistication. Additionally, the positive and significant impact of MI on CEK-DI underscores the critical role of market insights in shaping evolutionary strategies. While the relationship between MI and PSI is positive, the slightly weaker significance level indicates a subtle association, suggesting that while MI contributes to the development of ideas, In conclusion, the study emphasizes the fundamental role of intelligence capabilities, especially artificial intelligence, emphasizing the need for organizations to leverage market and customer intelligence to achieve effective and competitive innovation practices. Collaborative efforts between marketing and business intelligence serve as pivotal drivers of development, influencing customer experiential knowledge and shaping organizational strategies and practices. Future research could adopt longitudinal designs and gather data from various sectors to offer broader insights. Additionally, the study focuses on the effects of marketing intelligence, business intelligence, customer experiential knowledge, and innovation, but other unexamined variables may also influence innovation processes. Future studies could investigate additional factors, mediators, or moderators, including the role of emerging technologies like AI and machine learning in driving innovation.

Keywords: marketing intelligence, business intelligence, product, customer experiential knowledge-driven innovation

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Authors: Srushti Bhatt, M. B. Kiran

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Two-sided assembly line balancing problem is yet to be addressed simply to compete for the global market for manufacturers. The task assigned in an ordered sequence to get optimum performance of the system is known as assembly line balancing problem mainly classified as single and two sided. It is very challenging in manufacturing industries to balance two-sided assembly line, wherein the set of sequential workstations the task operations are performed in two sides of the line. The conflicting major objective in two-sided assembly line balancing problem is either to maximize /minimize the performance parameters. The present study emphases on combining different evolutionary algorithm; ant colony, Tabu search and petri net method; and compares their results of an algorithm for solving two-sided assembly line balancing problem. The concept of multi objective optimization of performance parameters is now a day adopted to make a decision involving more than one objective function to be simultaneously optimized. The optimum result can be expected among the selected methods using multi-objective optimization. The performance parameters considered in the present study are a number of workstation, slickness and smoothness index. The simulation of the assembly line balancing problem provides optimal results of classical and practical problems.

Keywords: Ant colony, petri net, tabu search, two sided ALBP

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Authors: Nikolaos Georgantzis, Efi Vasileiou

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We present results from experimental price-setting oligopolies in which green firms undertake different levels of energy-saving investments motivated by public subsidies and demand-side advantages. We find that consumers reveal higher willingness to pay for greener sellers’ products. This observation in conjunction to the fact that greener sellers set higher prices is compatible with the use and interpretation of energy-saving behaviour as a differentiation strategy. However, sellers do not exploit the resulting advantage through sufficiently high price-cost margins, because they seem trapped into “run to stay still” competition. Regarding the use of public subsidies to energy-saving sellers we uncover an undesirable crowding-out effect of consumers’ intrinsic tendency to support green manufacturers. Namely, consumers may be less willing to support a green seller whose energy-saving strategy entails a direct financial benefit. Finally, we disentangle two alternative motivations for consumer’s attractions to pro-social firms; first, the self-interested recognition of the firm’s contribution to the public and private welfare and, second, the need to compensate a firm for the cost entailed in each pro-social action. Our results show the prevalence of the former over the latter.

Keywords: corporate social responsibility, energy savings, public good, experiments, vertical differentiation, altruism

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Authors: Alexandra-Veronica Luca, Letitia Petrescu

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Steel production is a major contributor to global warming potential. An average value of 1.83 tons of CO₂ is emitted for every ton of steel produced, resulting in over 3.3 Mt of CO₂ emissions each year. The present paper is focused on the investigation and comparison of two O₂ separation methods and two CO₂ capture technologies applicable to iron and steel industry. The O₂ used in steel production comes from an Air Separation Unit (ASU) using distillation or from air separation using membranes. The CO₂ capture technologies are represented by a two-stage membrane separation process and the gas-liquid absorption using methyl di-ethanol amine (MDEA). Process modelling and simulation tools, as well as environmental tools, are used in the present study. The production capacity of the steel mill is 4,000,000 tones/year. In order to compare the two CO₂ capture technologies in terms of efficiency, performance, and sustainability, the following cases have been investigated: Case 1: steel production using O₂ from ASU and no CO₂ capture; Case 2: steel production using O₂ from ASU and gas-liquid absorption for CO₂ capture; Case 3: steel production using O₂ from ASU and membranes for CO₂ capture; Case 4: steel production using O₂ from membrane separation method and gas-liquid absorption for CO₂ capture and Case-5: steel production using membranes for air separation and CO₂ capture. The O₂ separation rate obtained in the distillation technology was about 96%, and about 33% in the membrane technology. Similarly, the O₂ purity resulting in the conventional process (i.e. distillation) is higher compared to the O₂ purity obtained in the membrane unit (e.g., 99.50% vs. 73.66%). The air flow-rate required for membrane separation is about three times higher compared to the air flow-rate for cryogenic distillation (e.g., 549,096.93 kg/h vs. 189,743.82 kg/h). A CO₂ capture rate of 93.97% was obtained in the membrane case, while the CO₂ capture rate for the gas-liquid absorption was 89.97%. A quantity of 6,626.49 kg/h CO₂ with a purity of 95.45% is separated from the total 23,352.83 kg/h flue-gas in the membrane process, while with absorption of 6,173.94 kg/h CO₂ with a purity of 98.79% is obtained from 21,902.04 kg/h flue-gas and 156,041.80 kg/h MDEA is recycled. The simulation results, performed using ChemCAD process simulator software, lead to the conclusion that membrane-based technology can be a suitable alternative for CO₂ removal for steel production. An environmental evaluation using Life Cycle Assessment (LCA) methodology was also performed. Considering the electricity consumption, the performance, and environmental indicators, Case 3 can be considered the most effective. The environmental evaluation, performed using GaBi software, shows that membrane technology can lead to lower environmental emissions if membrane production is based on benzene derived from toluene hydrodealkilation and chlorine and sodium hydroxide are produced using mixed technologies.

Keywords: CO₂ capture, gas-liquid absorption, Life Cycle Assessment, membrane separation, steel production

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Authors: Mnisi Blessing, Christopher Amoah

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Purpose: The usage of modern technology is widespread in industrialised nations. The issue still pertains to developing countries since they struggle to use technology in the building sector. The study aims to identify the barriers to technology usage in quantity surveying firms. Methodology: Quantity Surveyors were interviewed via Microsoft teams due to the dispersed nature of the participants. However, where the interview was not possible, the interview guide was emailed to the participants to fill in. In all, 12 participants were interviewed out of the 25 participants contacted. The data received were analysed using the content analysis process. Findings: The study's findings demonstrate that quantity surveyors have access to a wide range of technology that significantly enhances their project activities. However, quantity surveying companies are hesitant to use technology for several reasons, including the cost and maintenance associated with it. Other obstacles include a lack of knowledge, poor market acceptance, legal obstacles, and budgetary constraints. Implication: Despite the advantages associated with modern technology applications, quantity surveying firms are not using them, which may ultimately affect their work output. Therefore, firms need to re-examine these obstacles, inhibiting their adoption of technology in the work process to enhance their production. Value of the Paper: The study reveals the main hindrances to technology usage, which may help firms institute measures to address them.

Keywords: barriers, implementation, technology, quantity surveying

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Authors: Hadia Abdel Aziz, Raghda El Ebrashi

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Business models are shaped by their design space or the environment they are designed to be implemented in. The rapidly changing economic, technological, political, regulatory and market external environment severely affects business logic. This is particularly true for social enterprises whose core mission is to transform their environments, and thus, their whole business logic revolves around the interchange between the enterprise and the environment. The context in which social business operates imposes different business design constraints while at the same time, open up new design opportunities. It is also affected to a great extent by the impact that successful enterprises generate; a continuous loop of interaction that needs to be managed through a dynamic capability in order to generate a lasting powerful impact. This conceptual research synthesizes and analyzes literature on social enterprise, social enterprise business models, business model innovation, business model design, and the open system view theory to propose a new business model design process for social enterprises that takes into account the critical role of environmental factors. This process would help the social enterprise develop a dynamic capability that ensures the alignment of its business model to its environmental context, thus, maximizing its probability of success.

Keywords: social enterprise, business model, business model design, business model environment

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Authors: Andrew John Zeller, Artjoms Formulevics

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Banking and financial services are rapidly transitioning from being monolithic structures focusing merely on their own financial offerings to becoming integrated players in multiple customer journeys and supply chains. Banks themselves are refocusing on being liquidity providers and underwriters in these networks, while the general concept of ‘embeddedness’ builds on the market readily available API (Application Programming Interface) architectures to flexibly deliver services to various requestors, i.e., online retailers who need finance and insurance products to better serve their customers, respectively. With this new flexibility come new requirements for enhanced cybersecurity. API structures are more decentralized and inherently prone to change. Unfortunately, this has not been comprehensively addressed in the literature. This paper tries to fill this gap by looking at security approaches and technologies relevant to API architectures found in embedded finance. After presenting the research methodology applied and introducing the major bodies of knowledge involved, the paper will discuss six dominating technology trends shaping high-level financial services architectures. Subsequently, embedded finance and the respective usage of API strategies will be described. Building on this, security considerations for APIs in financial and insurance services will be elaborated on before concluding with some ideas for possible further research.

Keywords: embedded finance, embedded banking strategy, cybersecurity, API management, data security, cybersecurity, IT management

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Authors: Merih Welay Welesilassie

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This research investigated the factors influencing digital inclusion for young students with disabilities in Ethiopian schools. In this context, socio-economic, infrastructural, and cultural challenges amplify educational disparities. In the era of digital technology's pivotal role in education, it is crucial to ensure equitable access for students with disabilities. Nevertheless, obstacles like inadequate infrastructure, insufficient teacher training, and economic constraints impede the incorporation of digital tools in educational environments, especially for marginalised groups. This study employed an explanatory sequential mixed-methods approach involving data collection through a survey administered to 300 students. Subsequently, in-depth interviews were conducted with 30 participants to provide comprehensive insights into their experiences. The quantitative analysis uncovered that students with disabilities have limited support for digital readiness, find digital technologies less accessible, and perceive digital tools as less easy to use. The study revealed that economic barriers, such as the high cost of devices and limited internet access, prevent students from fully utilising digital resources. Furthermore, infrastructural challenges, such as unreliable electricity and poor internet connectivity, exacerbate the issue. The qualitative data provided a more profound understanding by emphasising social and attitudinal obstacles, including a lack of empathy from both peers and educators, exclusion from participatory digital tasks, and enduring negative stereotypes regarding disabilities. The research highlights the importance of implementing interventions to enhance digital accessibility for students with disabilities. Essential suggestions encompass refining teacher training programs to effectively facilitate inclusive education, improving digital infrastructure, and offering financial assistance to procure digital tools. Furthermore, implementing policy reforms and public awareness campaigns is crucial to cultivate a cultural shift and nurture a more inclusive societal atmosphere. This study yields valuable perspectives on the digital inclusion scenario in Ethiopia, laying the groundwork for prospective research endeavours to narrow the digital gap for students with disabilities.

Keywords: digital inclussion, students with disabilities, ethiopian education, barries and access

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Authors: Mohammed Ibrahim Bu Haya, Abdelmoneim Bahyeldin Mohamed Metwally

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This paper examines the impact of Green Intellectual Capital (GIC) on Green Supply Chain Performance (GSCP). Further, the study examines the moderating role of external pressures (EP) on the relationship between GIC and GSCP. Data were collected from employees working in Egyptian hotels and tourism companies (N= 366). The collected data were analyzed using smart partial least squares (Smart-PLS) software. The current research indicated that there is a positive and significant impact of all GIC components on GSCP. The results also revealed that EP were found to moderate the relationship between GIC and GSCP. The study model was able to explain 63.1% of the variance in GSCP. The findings of this study serve as a pivotal yardstick for guiding corporate policy formulation, offering valuable insights to drive continuous improvements in supply chain management and performance. Furthermore, the research holds substantial implications for managerial strategies by shedding light on the potential of GIC and EP to elevate GSCP. Positioned as one of the initial studies to delve into the moderating role of EP in the relationship between GIC and GSCP, this research offers insights within an emerging market context.

Keywords: green intellectual capital, green supply chain, supply chain performance, external pressures, emerging economy, Egypt

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Authors: Mei-Fang Wu, Shu-Li Wang, Tsung-Yueh Lu, Feng-Tsung Cheng

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Strengthening core competitiveness is the main goal of enterprises in a fierce competitive environment. Accurate cost information is a great help for managers in dealing with operation strategies. This paper establishes a profitability management mechanism that applies the Activity-Based Benefit approach (ABBA) to solve the profitability for each customer from the market. ABBA provides financial and non-financial information for the operation, but also indicates what resources have expired in the operational process. The customer profit management model shows the level of profitability of each customer for the company. The empirical data were gathered from a case company operating in the leather industry in Taiwan. The research findings indicate that 30% of customers create little profit for the company as a result of asking for over 5% of sales discounts. Those customers ask for sales discount because of color differences of leather products. This paper provides a customer’s profitability evaluation mechanism to help enterprises to greatly improve operating effectiveness and promote operational activity efficiency and overall operation profitability.

Keywords: activity-based benefit approach, customer profit analysis, leather industry, profitability management mechanism

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Authors: Dalia Suša Vugec, Ana-Marija Stjepić, Darija Ivandić Vidović

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Digital transformation is one of the latest trends on the global market. In order to maintain the competitive advantage and sustainability, increasing number of organizations are conducting digital transformation processes. Those organizations are changing their business processes and creating new business models with the help of digital technologies. In that sense, one should also observe the role of business process management (BPM) and its maturity in driving digital transformation. Therefore, the goal of this paper is to investigate the role of BPM in digital transformation process within one organization. Since experiences from practice show that organizations from financial sector could be observed as leaders in digital transformation, an insurance company has been selected to participate in the study. That company has been selected due to the high level of its BPM maturity and the fact that it has previously been through a digital transformation process. In order to fulfill the goals of the paper, several interviews, as well as questionnaires, have been conducted within the selected company. The results are presented in a form of a case study. Results indicate that digital transformation process within the observed company has been successful, with special focus on the development of digital strategy, BPM and change management. The role of BPM in the digital transformation of the observed company is further discussed in the paper.

Keywords: business process management, case study, Croatia, digital transformation, insurance company

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Authors: Shafaq Rana, Hina Ansar

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Projectification is an emerging phenomenon in Western economies. The projects have become the key driver of the economic actions. The impact of projectification is understudy for over a decade. A methodology was developed to measure the degree of projectification at economical level, which was later adapted to measure the degree of projectification in Germany, Norway, and Iceland; and compared the differences in these project societies, considering their industrial structure, organizational size, and the share of project work. Using the same methodology, this study aims to provide empirical evidence of the project work in the context of Pakistan –a developing nation, keeping into consideration the macroeconomic measures, qualitative and quantitative measures of the project i/c GDP, monetary measures, and project success. The research includes a qualitative pre-study to define these macro-measures in the country-specific context and a quantitative study to measure the project work w.r.t hours working in the organizations on projects. The outcome of this study provides the key data on the projectification in a developing economy, which will help industry practitioners and decision-makers to examine the consequences of projectification and strategize, respectively. This study also provides a foundation for further research in individual sectors of the country while exploring different macroeconomic questions, including the effect of projectification on project productivity, income effects, and labor market.

Keywords: developing economy, Pakistan, project work, projectification

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Authors: Hema Bhardwaj, D. Srinivasa Rao

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Technology for analysing, processing, and extracting meaningful data from enormous and complicated datasets can be termed as "big data." The technique of big data mining and big data analysis is extremely helpful for business movements such as making decisions, building organisational plans, researching the market efficiently, improving sales, etc., because typical management tools cannot handle such complicated datasets. Special computational and statistical issues, such as measurement errors, noise accumulation, spurious correlation, and storage and scalability limitations, are brought on by big data. These unique problems call for new computational and statistical paradigms. This research paper offers an overview of the literature on big data mining, its process, along with problems and difficulties, with a focus on the unique characteristics of big data. Organizations have several difficulties when undertaking data mining, which has an impact on their decision-making. Every day, terabytes of data are produced, yet only around 1% of that data is really analyzed. The idea of the mining and analysis of data and knowledge discovery techniques that have recently been created with practical application systems is presented in this study. This article's conclusion also includes a list of issues and difficulties for further research in the area. The report discusses the management's main big data and data mining challenges.

Keywords: big data, data mining, data analysis, knowledge discovery techniques, data mining challenges

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Authors: Hideki Kitamura

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Since Islamic banking has broadly started in the late 1970s, Islamic economy has been paid much attention by both academia and the business world. However, despite abundant studies, descriptive exploration of practices of Islamic economy from a sociological/anthropological perspective is underrepresented, and most are basically designed for evaluating current practice or proposing ideal types of Islamic economy in accordance with their religious conviction. Overall, their interest is not paid to actors of Islamic economy such as practitioner’s decision-making and thought, while sociological/anthropological studies on Muslim’s religious life can be observed well. Herein, the paper aims to look into the possibilities of sociology/anthropology for exploration of the role of actors of Islamic economy, by revisiting the benefit of sociological/anthropological studies on the religion of Islam and its adaptability to the research on Islamic economy. The paper suggests that practices of Islamic economy can be assumed as results of practitioner’s dilemma between Islamic ideals and market realities in each society, by applying the perspective of social constructivism. The paper then proposes focusing on the human agency of practitioners in translating Islamic principles into economic behavior, thereby enabling a more descriptive inquiry into how Islamic economy is produced and operated.

Keywords: Islamic economy, economic sociology/anthropology, human agency, social constructivism

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Authors: Samuele Abagnato, Lucia Rigamonti

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Life-Cycle-Assessment (LCA) is an effective tool to quantify the environmental impacts of reuse models and recycling technologies for textiles. In this work, publications in the last ten years about LCA on textile waste are classified according to location, goal and scope, functional unit, waste composition, impact assessment method, impact categories, and sensitivity analysis. Twenty papers have been selected: 50% are focused only on recycling, 30% only on reuse, the 15% on both, while only one paper considers only the final disposal of the waste. It is found that reuse is generally the best way to decrease the environmental impacts of textiles waste management because of the avoided impacts of manufacturing a new item. In the comparison between a product made with recycled yarns and a product from virgin materials, in general, the first option is less impact, especially for the categories of climate change, water depletion, and land occupation, while for other categories, such as eutrophication or ecotoxicity, under certain conditions the impacts of the recycled fibres can be higher. Cultivation seems to have quite high impacts when natural fibres are involved, especially in the land use and water depletion categories, while manufacturing requires a remarkable amount of electricity, with its associated impact on climate change. In the analysis of the reuse processes, relevant importance is covered by the laundry phase, with water consumption and impacts related to the use of detergents. About the sensitivity analysis, it can be stated that one of the main variables that influence the LCA results and that needs to be further investigated in the modeling of the LCA system about this topic is the substitution rate between recycled and virgin fibres, that is the amount of recycled material that can be used in place of virgin one. Related to this, also the yield of the recycling processes has a strong influence on the results of the impact. The substitution rate is also important in the modeling of the reuse processes because it represents the number of avoided new items bought in place of the reused ones. Another aspect that appears to have a large influence on the impacts is consumer behaviour during the use phase (for example, the number of uses between two laundry cycles). In conclusion, to have a deeper knowledge of the impacts of a life-cycle approach of textile waste, further data and research are needed in the modeling of the substitution rate and of the use phase habits of the consumers.

Keywords: environmental impacts, life-cycle-assessment, textiles recycling, textiles reuse, textiles waste management

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Authors: Hubert Pun

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When a manufacturer outsources the production of a product, it distributes its intellectual property (IP) into a supply chain that it may not be able to fully control. An IP agreement between a manufacturer and its suppliers is a popular solution to address the challenge of supplier-copycatting. The goal of this paper is to examine the impact of copycatting, from both the supplier and third-party firms, and the effectiveness of an IP agreement. Specifically, we use a game-theoretic approach to examine a system where a manufacturer outsources to a supplier. The supplier and a third-party firm decide whether or not to enter the market with copycat products while the manufacturer selects the level of marketing investment. The manufacturer can reduce the threat of supplier-copycatting by signing an IP agreement. We find that the manufacturer can be worse off from signing an IP agreement with its supplier, even if the IP agreement is costless and perfectly enforceable. We show that a manufacturer can deter copycat products through vertical integration and IP agreements and we outline the instances where each method is preferred. Furthermore, we find that the manufacturer may choose not to invest in quality improvements as a copycat deterrence strategy. We show that the supplier can benefit from the manufacturer’s decision to sign an IP agreement and that the supplier and the consumers can benefit from government regulations against copycat products. Our paper demonstrates the strengths and limitations of various copycat deterrence strategies when a supplier and third-party may produce copycat products.

Keywords: coopetitive supply chain, copycat, government regulation, intellectual property

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Authors: Dipti Yadav, Latha Rangan, Pinakeswar Mahanta

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Recent fuel-development strategies to reduce oil dependency, mitigate greenhouse gas emissions, and utilize domestic resources have generated interest in the search for alternative sources of fuel supplies. Bioenergy production from lignocellulosic biomass has a great potential. Cellulose, hemicellulose and Lignin are main constituent of woods or agrowaste. In all the industries there are always left over or waste products mainly lignin, due to the heterogeneous nature of wood and pulp fibers and the heterogeneity that exists between individual fibers, no method is currently available for the quantitative isolation of native or residual lignin without the risk of structural changes during the isolation. The potential benefits from finding alternative uses of lignin are extensive, and with a double effect. Lignin can be used to replace fossil-based raw materials in a wide range of products, from plastics to individual chemical products, activated carbon, motor fuels and carbon fibers. Furthermore, if there is a market for lignin for such value-added products, the mills will also have an additional economic incentive to take measures for higher energy efficiency. In this study residual lignin were isolated from areca nut shells by acid hydrolysis and were analyzed and characterized by Fourier Transform Infrared (FTIR), LCMS and complexity of its structure investigated by NMR.

Keywords: Areca nut, Lignin, wood, bioenergy

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