Search results for: pre-allocation decisions

Authors: Mirjana Dragas, Marli Gonan Bozac, Morena Paulisic

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Corporate social responsibility (CSR) is a balance between strategic and financial goals of companies, as well as social needs. The integration of competitive strategy and CSR in food and beverage industry has allowed companies to find new sources of competitive advantage. The paper discusses the fact that socially responsible companies encourage co-operation with socially responsible suppliers in order to strengthen market competitiveness. In addition to the descriptive interpretation of the results obtained by a questionnaire, factor analysis was used, while principal components analysis was applied as a factor extraction method. The research results based on two multiple regression analyses show that: (1) selecting the CSR supplier explains a statistically significant part of the variance of the results on the scale of financial aspects of competitiveness (as much as 44.7% of the explained variance); and (2) selecting the CSR supplier is a significant predictor of non-financial aspects of competitiveness (explains 43.9% of the variance of the results on the scale of non-financial aspects of competitiveness). A successful competitive strategy must ultimately support the growth strategy. This implies an analytical approach to finding factors that influence competitiveness through socially sustainable solutions and satisfactory top management decisions.

Keywords: competitiveness, corporate social responsibility, food and beverage industry, supply chain decision making

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Authors: Asma Righi

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After the global financial crisis of 2008, interest in ethical economics increased, particularly in the field of finance in general and commercial banks in particular. Indeed, it has become imperative for them to move from an institution that aims to make a profit to a community partner that takes the environmental aspect into account in its funding, rationalizes its decisions and adheres to ethics in its dealings. This leads it to the need of adopting the concept of ethical finance and standing on its most important principles and dimensions to realize profits on the one hand and to serve its society and its economy on the other hand. The objective of this research is centered on knowing the reality of the Algerian commercial banks’ adoption of the dimensions and principles of ethical finance. The quantitative methodology used is based on a questionnaire survey of twenty-four banking agencies in the states of Bordj Bou Arreridj and Setif. The data obtained were processed using the Statistical Package for the Social Sciences (SPSS) program. This research led to two main results: first, the author observed a limited application of the principles of ethical finance in commercial banks active in Algeria. This application is particularly in line with the implementation of the directives of the Central Bank and the imposed monetary policy. Second, the results showed that there is a significant difference in the application of ethical financial dimensions and principles between government and foreign banks.

Keywords: Algerian commercial banks, ethical banking, ethical finance, socially responsible investment

Procedia PDF Downloads 142

Authors: Itamir de Morais Barroca Filho, Cephas A. S. Barreto, Ramon Malaquias, Cezar Miranda Paula de Souza, Arthur Costa Gorgônio, João C. Xavier-Júnior, Mateus Firmino, Fellipe Matheus Costa Barbosa

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Information and Communication Technologies (ICT) in healthcare are crucial for efficiently delivering medical healthcare services to patients. These ICTs are also known as e-health and comprise technologies such as electronic record systems, telemedicine systems, and personalized devices for diagnosis. The focus of e-health is to improve the quality of health information, strengthen national health systems, and ensure accessible, high-quality health care for all. All the data gathered by these technologies make it possible to help clinical staff with automated decisions using machine learning. In this context, we collected patient data, such as heart rate, oxygen saturation (SpO2), blood pressure, respiration, and others. With this data, we were able to develop machine learning models for patients’ risk of death and estimate the length of stay in ICU beds. Thus, this paper presents the methodology for applying machine learning techniques to develop these models. As a result, although we implemented these models on an IoT healthcare platform, helping clinical staff in healthcare in an ICU, it is essential to create a robust clinical validation process and monitoring of the proposed models.

Keywords: ICT, e-health, machine learning, ICU, healthcare

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Authors: Reza Alikhani

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This research focuses on the establishment of horizontal cooperation among companies to enhance their operational efficiency and competitiveness. The study proposes an approach to horizontal collaboration, called coalition configuration, which involves partnering companies sharing distribution centers in a network design problem. The paper investigates which coalition should be formed in each distribution center to minimize the total cost of the network. Moreover, potential uncertainties, such as operational and disruption risks, are considered during the collaborative design phase. To address this problem, a two-stage robust optimization model for collaborative distribution network design under surging demand and facility disruptions is presented, along with a column-and-constraint generation algorithm to obtain exact solutions tailored to the proposed formulation. Extensive numerical experiments are conducted to analyze solutions obtained by the model in various scenarios, including decisions ranging from fully centralized to fully decentralized settings, collaborative versus non-collaborative approaches, and different amounts of uncertainty budgets. The results show that the coalition formation mechanism proposes some solutions that are competitive with the savings of the grand coalition. The research also highlights that collaboration increases network flexibility and resilience while reducing costs associated with demand and capacity uncertainties.

Keywords: logistics, warehouse sharing, robust facility location, collaboration for resilience

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Authors: Vladimir A. Todiras

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Spatio-temporal models provide new possibilities for real-time action in pest risk analysis. It should be noted that estimation of the possibility and probability of introduction of a pest and of its economic consequences involves many uncertainties. We present a new mapping technique that assesses pest invasion risk using online BioClass software. BioClass is a GIS tool designed to solve multiple-criteria classification and optimization problems based on fuzzy logic and level set methods. This research describes a method for predicting the potential establishment and spread of a plant pest into new areas using a case study: corn rootworm (Diabrotica spp.), tomato leaf miner (Tuta absoluta) and plum fruit moth (Grapholita funebrana). Our study demonstrated that in BioClass we can combine fuzzy logic and geographic information systems with knowledge of pest biology and environmental data to derive new information for decision making. Pests are sensitive to a warming climate, as temperature greatly affects their survival and reproductive rate and capacity. Changes have been observed in the distribution, frequency and severity of outbreaks of Helicoverpa armigera on tomato. BioClass has demonstrated to be a powerful tool for applying dynamic models and map the potential future distribution of a species, enable resource to make decisions about dangerous and invasive species management and control.

Keywords: classification, model, pest, risk

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Authors: Sabiha S. Marine, Nicole Flint, John Rolfe

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The Queensland state government introduced commercial gill net fishing closures in Cairns, Mackay, and Rockhampton in November 2015 to increase the recreational fishing opportunities, nature-based tourism, and economic benefits in these three regional areas. This management change is likely to improve the potential for more desirable stock structures through natural recruitment. Barramundi (Lates calcarifer) is one of the popular target fish for recreational and commercial fishers in Northern Australia. This investigation examines the effects of reduced commercial fishing from both biological and economic perspectives, particularly on the local Barramundi population of the Fitzroy River in Rockhampton, the largest river catchment flowing to the eastern coast of Australia. Data on different parameters of biological and economic aspects have been collated from secondary sources for analysis through a system simulation approach to identify the effectiveness of the commercial netting closures on recreational fishing effort, especially for the Barramundi population. The results have the potential to explain certain consequences of the netting closures in Queensland, which could serve to inform future fisheries management decisions. The study output as a whole will help in the better management of fisheries resources by evaluating recreational fishing opportunities in Queensland, where the potential for increases in recreation is high.

Keywords: Barramundi, bioeconomic model, fishery management, recreational fishing

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Authors: Alvaro Javier Ortega

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A large number of companies face the challenge of matching highly-skilled professionals to high-end positions by human resource deployment professionals. However, when the professional list and tasks to be matched are larger than a few dozens, this process result is far from optimal and takes a long time to be made. Therefore, an automated assignment algorithm for this workforce management problem is needed. The majority of companies are divided into several sectors or departments, where trained employees with different experience levels deal with a large number of tasks daily. Also, the execution order of all tasks is of mater consequence, due to some of these tasks just can be run it if the result of another task is provided. Thus, a wrong execution order leads to large waiting times between consecutive tasks. The desired goal is, therefore, creating accurate matches and a near-optimal execution order that maximizes the number of tasks performed and minimizes the idle time of the expensive skilled employees. The problem described before can be model as a mixed-integer non-linear programming (MINLP) as it will be shown in detail through this paper. A large number of MINLP algorithms have been proposed in the literature. Here, genetic algorithm solutions are considered and a comparison between two different mutation approaches is presented. The simulated results considering different complexity levels of assignment decisions show the appropriateness of the proposed model.

Keywords: employees, genetic algorithm, industry management, workforce

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Authors: Walid Moudani

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The healthcare environment is generally perceived as being information rich yet knowledge poor. However, there is a lack of effective analysis tools to discover hidden relationships and trends in data. In fact, valuable knowledge can be discovered from application of data mining techniques in healthcare system. In this study, a proficient methodology for the extraction of significant patterns from the coronary heart disease warehouses for heart attack prediction, which unfortunately continues to be a leading cause of mortality in the whole world, has been presented. For this purpose, we propose to enumerate dynamically the optimal subsets of the reduced features of high interest by using rough sets technique associated to dynamic programming. Therefore, we propose to validate the classification using Random Forest (RF) decision tree to identify the risky heart disease cases. This work is based on a large amount of data collected from several clinical institutions based on the medical profile of patient. Moreover, the experts’ knowledge in this field has been taken into consideration in order to define the disease, its risk factors, and to establish significant knowledge relationships among the medical factors. A computer-aided system is developed for this purpose based on a population of 525 adults. The performance of the proposed model is analyzed and evaluated based on set of benchmark techniques applied in this classification problem.

Keywords: multi-classifier decisions tree, features reduction, dynamic programming, rough sets

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Authors: Lucia Mavudzi

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Socioeconomic and demographic factors influence male attendance of antenatal care (ANC) activities which are beneficial in improving maternal health and birth outcome. When a male, as the head of the family is expected to solely make decisions of how finances are managed, when and where health services are sought, it impacts on the woman’s health seeking behavior. Using the data from the Zimbabwe Demographic and Health Survey 2010-2011 this paper seeks to assess the prevalence of male ANC attendance in Zimbabwe and factors that influence male ANC attendance. We hypothesized that socioeconomic and demographic factors do not influence male ANC attendance. To achieve the objectives of this paper, descriptive analysis was used to describe the characteristics of men and the Binomial logistic modelling was used to assess the relationship between male ANC attendance and selected socioeconomic and demographic factors. Male ANC attendance was used as the dependent variable, and the independent variables are age, marital status, place of residence, wealth, education, religion and employment. A high percentage of males did not attend ANC with their pregnant partners. Religion, education, and place of residence were found to be significantly associated with male ANC attendance. There was no evidence to show that there was a difference in male ANC attendance by employment, marital status, and age. Findings from this paper are relevant to public health. They will be used to develop strategies and intervention programs to improve pregnant women’s attendance of ANC attendance by involving men in maternal health.

Keywords: antenatal care, male participation, maternal health, socio-economic and demographic factors

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Authors: Bekir O. Bartin, Kaan Ozbay, Sandeep Mudigonda, Hong Yang

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The use of microscopic traffic simulation in evaluating the operational and safety conditions at toll plazas is demonstrated. Two toll plazas in New Jersey are selected as case studies and were developed and validated in Paramics traffic simulation software. In order to simulate drivers’ lane selection behavior in Paramics, a utility-based lane selection approach is implemented in Paramics Application Programming Interface (API). For each vehicle approaching the toll plaza, a utility value is assigned to each toll lane by taking into account the factors that are likely to impact drivers’ lane selection behavior, such as approach lane, exit lane and queue lengths. The results demonstrate that similar operational conditions, such as lane-by-lane toll plaza traffic volume can be attained using this approach. In addition, assessment of safety at toll plazas is conducted via a surrogate safety measure. In particular, the crash index (CI), an improved surrogate measure of time-to-collision (TTC), which reflects the severity of a crash is used in the simulation analyses. The results indicate that the spatial and temporal frequency of observed crashes can be simulated using the proposed methodology. Further analyses can be conducted to evaluate and compare various different operational decisions and safety measures using microscopic simulation models.

Keywords: microscopic simulation, toll plaza, surrogate safety, application programming interface

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Authors: Mohamed Al-Badrashiny, Abdelghani Bellaachia

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This paper presents a classifier ensemble approach for predicting the survivability of the breast cancer patients using the latest database version of the Surveillance, Epidemiology, and End Results (SEER) Program of the National Cancer Institute. The system consists of two main components; features selection and classifier ensemble components. The features selection component divides the features in SEER database into four groups. After that it tries to find the most important features among the four groups that maximizes the weighted average F-score of a certain classification algorithm. The ensemble component uses three different classifiers, each of which models different set of features from SEER through the features selection module. On top of them, another classifier is used to give the final decision based on the output decisions and confidence scores from each of the underlying classifiers. Different classification algorithms have been examined; the best setup found is by using the decision tree, Bayesian network, and Na¨ıve Bayes algorithms for the underlying classifiers and Na¨ıve Bayes for the classifier ensemble step. The system outperforms all published systems to date when evaluated against the exact same data of SEER (period of 1973-2002). It gives 87.39% weighted average F-score compared to 85.82% and 81.34% of the other published systems. By increasing the data size to cover the whole database (period of 1973-2014), the overall weighted average F-score jumps to 92.4% on the held out unseen test set.

Keywords: classifier ensemble, breast cancer survivability, data mining, SEER

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Authors: Jamila Garba Audu, Shehu Usman Hassan

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The widespread failure in the financial information quality has created the need to improve the financial information quality and to strengthen the control of managers by setting up good firms structures. Published accounting information in financial statements is required to provide various users - shareholders, employees, suppliers, creditors, financial analysts, stockbrokers and government agencies – with timely and reliable information useful for making prudent, effective and efficient decisions. The relationship between corporate governance and performance to financial reporting quality is imperative; this is because despite rapid researches in this area the findings obtained from these studies are constantly inconclusive. Data for the study were extracted from the firms’ annual reports and accounts. After running the OLS regression, a robustness test was conducted for the validity of statistical inferences; the data was empirically tested. A multiple regression was employed to test the model as a technique for data analysis. The results from the analysis revealed a negative association between all the regressors and financial reporting quality except the performance of listed manufacturing firms in Nigeria. This indicates that corporate governance plays a significant role in mitigating earnings management and improving financial reporting quality while performance does not. The study recommended among others that the composition of audit committee should be made in accordance with the provision for code of corporate governance which is not more than six (6) members with at least one (1) financial expert.

Keywords: corporate governance, financial reporting quality, manufacturing firms, Nigeria, performance

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Authors: Omar A. Abuobidalla, Mingyuan Chen, Satyaveer S. Chauhan

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Railroad transportation of hazardous materials freights is important to the North America economics that supports the national’s supply chain. This paper introduces various extensions of the dynamic hazardous materials trip plan problems. The problem captures most of the operational features of a real-world railroad transportations systems that dynamically initiates a set of blocks and assigns each shipment to a single block path or multiple block paths. The dynamic hazardous materials trip plan policies have distinguishing features that are integrating the blocking plan, and the block activation decisions. We also present a non-linear mixed integer programming formulation for each variant and present managerial insights based on a hypothetical railroad network. The computation results reveal that the dynamic car scheduling policies are not only able to take advantage of the capacity of the network but also capable of diminishing the population, and environment risks by rerouting the active blocks along the least risky train services without sacrificing the cost advantage of the railroad. The empirical results of this research illustrate that the issue of integrating the blocking plan, and the train makeup of the hazardous materials freights must receive closer attentions.

Keywords: dynamic car scheduling, planning and scheduling hazardous materials freights, airborne hazardous materials, gaussian plume model, integrated blocking and routing plans, box model

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Authors: Reza Mohammadzadeh

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The major challenges in geotechnical engineering in underground spaces arise from uncertainties and different probabilities. The collection, collation, and collaboration of existing data to incorporate them in analysis and design for given prospect evaluation would be a reliable, practical problem solving method under uncertainty. Machine learning (ML) is a subfield of artificial intelligence in statistical science which applies different techniques (e.g., Regression, neural networks, support vector machines, decision trees, random forests, genetic programming, etc.) on data to automatically learn and improve from them without being explicitly programmed and make decisions and predictions. In this paper, a conceptual database schema of geotechnical risks in underground coal mining based on a cloud system architecture has been designed. A new approach of risk assessment using a three-dimensional risk matrix supported by the level of knowledge (LoK) has been proposed in this model. Subsequently, the model workflow methodology stages have been described. In order to train data and LoK models deployment, an ML platform has been implemented. IBM Watson Studio, as a leading data science tool and data-driven cloud integration ML platform, is employed in this study. As a Use case, a data set of geotechnical hazards and risk assessment in underground coal mining were prepared to demonstrate the performance of the model, and accordingly, the results have been outlined.

Keywords: data model, geotechnical risks, machine learning, underground coal mining

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Authors: Elisabeth Sundari, Anny Retnowati

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This research aims to examine the meaning of 'the best interests of the child' in Indonesia's rampant phenomenon of child marriage. The methodology used empirical and normative legal research by examining the parent's reason and the judges' considerations in granting child marriage dispensation applications. It takes data samples from judges' decisions purposively in two courts that differ in geographical and religious backgrounds to see data variation. Namely, the District Court and Religious Court of Yogyakarta City, as well as Gunung Kidul Regency, in the last three years (2020-2022). It analyses the data qualitatively to explore how judges interpreted 'the best interests of the child' in their decision. The results show that judges granted 100% of all child marriage dispensation applications filed by parents. The three reasons parents gave for applying for dispensation were that they were ashamed of having a pregnant child without being married, followed religious teachings, and obtained legal status for the baby. The judges supported those reasons by granting the dispensation application. The external factor of the child itself influenced the meaning of 'The best interests of the child' in marrying off children in Indonesia, such as cultural taboos, religious teachings, and obtaining legal status for the baby, rather than internal factors of the child, such as the will to marry, the mental and psychological readiness of the child to become a mother, as well as a wife. This research contributes to the finding that external factors, such as local culture and religion, can influence the meaning of 'the best interests of the child.'

Keywords: interests, child, Indonesia, marriage

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Authors: Lei Zhao, Zhe Yuan, Wenyue Kuang

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This paper studies two-warehouse inventory models for a deteriorating item considering that the demand is influenced by inventory levels. The problem mainly focuses on the optimal order policy and the optimal order cycle with inventory-level-dependent demand in two-warehouse system for retailers. It considers the different deterioration rates and the inventory holding costs in owned warehouse (OW) and rented warehouse (RW), and the conditions of transportation cost, allowed shortage and partial backlogging. Two inventory models are formulated: last-in first-out (LIFO) model and first-in-first-out (FIFO) model based on the policy choices of LIFO and FIFO, and a comparative analysis of LIFO model and FIFO model is made. The study finds that the FIFO policy is more in line with realistic operating conditions. Especially when the inventory holding cost of OW is high, and there is no difference or big difference between deterioration rates of OW and RW, the FIFO policy has better applicability. Meanwhile, this paper considers the differences between the effects of warehouse and shelf inventory levels on demand, and then builds retailers’ inventory decision model and studies the factors of the optimal order quantity, the optimal order cycle and the average inventory cost per unit time. To minimize the average total cost, the optimal dispatching policies are provided for retailers’ decisions.

Keywords: FIFO model, inventory-level-dependent, LIFO model, two-warehouse inventory

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Authors: Diana Bardhi

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Road safety is an essential part of the economic and social development of any industrialized country. Decisions to maintain and improve the reliability, functionality of infrastructure structures can only be achieved through integrated road life cycle planning and management. There has always been a tendency to review road maintenance strategies, but there is still no serious and reliable administration due to not only insufficient funds but also problems in the proper reorganization of this system. The safety and performance of the road system depend on the ongoing activity of road maintenance management. For it to be effective, it is necessary to intervene before the degradation has caused irreparable damage or damage with a high economic cost of repairs. Investments in road infrastructure during 2006-2014 show that the life of these projects presents problems related to the maintenance and management of life cycle performance in a wide range of constituent elements. Maintenance planning includes various problems that depend on the degree of degradation of asphalt layers, the degree of damage to road structures (bridges, tunnels, culverts, and the economic planning of resources for their repair). The purpose of this study is first to provide a brief overview of the problems in the field of maintenance and life cycle management of road infrastructure investments, proposing ways to reorganize the sector of administration and maintenance of ongoing roads and secondly testing and evaluating the work and nature of standards of different types of road infrastructure projects, through a methodology consisting of a) development, b) data collection, and c) analysis.

Keywords: infrastructure, maintenance, depreciation, efficiency

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Authors: Jacqueline Miller, Dongyuan Y. Wang, F. Dan Richard

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Before trying to make an ethical machine that holds a higher ethical standard than humans, a better understanding of human moral standards that could be used as a guide is crucial. How humans make decisions in dangerous driving situations like moral dilemmas can contribute to developing acceptable ethical principles for autonomous vehicles (AVs). This study uses a driving simulator to investigate whether drivers make utilitarian choices (choices that maximize lives saved and minimize harm) in unavoidable automobile accidents (moral dilemmas) with time pressure manipulated. This study also investigates how impulsiveness influences drivers’ behavior in moral dilemmas. Manipulating time pressure results in collisions that occur at varying time intervals (4 s, 5 s, 7s). Manipulating time pressure helps investigate how time pressure may influence drivers’ response behavior. Thirty-one undergraduates participated in this study using a STISM driving simulator to respond to driving moral dilemmas. The results indicated that the percentage of utilitarian choices generally increased when given more time to respond (from 4 s to 7 s). Additionally, participants in vehicle scenarios preferred responding right over responding left. Impulsiveness did not influence utilitarian choices. However, as time pressure decreased, response time increased. Findings have potential implications and applications on the regulation of driver assistance technologies and AVs.

Keywords: time pressure, automobile moral dilemmas, impulsiveness, reaction time

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Authors: Barbara Ballan

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Environmental Justice (EJ) and Environmental Social Governance (ESG) are trending terms used to address the impacts of corporate actions and environmental and social regulations on the people and the planet. ESG is a private governance invention (though increasingly required by public law) that aims to disclose environmental and social criteria while fostering value for businesses. On the other hand, EJ was borne as a social movement that evolved into a regulatory tool employed by EJ advocates and governmental agencies to assess inequalities in environmental impacts and regulations. However, EJ usage is expanding, and private environmental governance in the form of ESG disclosure frameworks is incorporating EJ criteria, indexes, and tools as part of its metric-driven approach. There is an existing tension between (1) the notion of social justice at the heart of the environmental justice movement and (2) the nature of for-profit corporations which generate value by externalizing costs, translated to environmental injustices. This study aims to explore the paradoxical relation of ESG, including EJ criteria, despite their opposing notions, in response to the need for innovative mechanisms to address today’s pressing social and environmental challenges. To that end, this study will evaluate and critically assess the inclusion of EJ in ESG reporting. Furthermore, it identifies gaps in ESG frameworks and proposes the integration of EJ tools to address these deficiencies. This work is intended to help both businesses looking to expand their ESG frameworks and include EJ criteria to inform corporate decisions and assure long-term corporate viability, as well as EJ supporters in understanding the complex dynamic of ESG disclosure for the pursuit of EJ objectives.

Keywords: environmental justice, ESG, sustainability reporting, corporate law, environmental law, social justice

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Authors: Alieu B. Sanneh

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In a country where there are minimal economic opportunities, with a declining living condition of the people, do electorates in Africa’s newest democracy reevaluate their support for a candidate based on issues or ethnicity. In the 2016 presidential election in The Gambia, the opposition coalition party had successfully managed to overthrow an authoritarian government, which has ruled the country for 22 years. The results of the election are not only surprising but also presented an interesting theoretical puzzle that raises important this paper is going to address. An important fact is that dictator had organized an election which he lost, and this paper will assess the voting decisions of Gambian electorates to determine whether they were more concerned with issues such as status of the economy, human rights abuses by the Jammeh administration or the ethnicities of the contestants who took part in the election. This study uses field survey data, conducted six months after this historic vote, to evaluate the opinion of the electorates. Contrary to the notion of the prevalence of ethnic voting in African elections, an argument made by many scholars, this study concluded that Gambian voters were more concerned with issues such as the economy and human rights under the Jammeh administration than they were for the ethnicities of the candidates. The election was issue-based, and that Jammeh lost the polls due to the concern the electorate had on human rights abuses by his government.

Keywords: election, issue, ethnicity, regime change

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Authors: Taghreed Abu-Salim

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This paper develops and investigates a framework for the assessment of customer involvement in the service design process of result oriented product-service systems in order to improve the service offering in a business to business (B2B) context. The framework comprises five main criteria and fifteen sub-criteria that contribute to customer involvement in a hierarchy using a maturity grid to highlight the strengths and weaknesses for each criterion. To develop the customer involvement framework, an extensive literature review related to service design, result oriented product-service system (PSS) and customer involvement in service design was carried out. Key factors that significantly influence customer involvement from industry and literature were identified to develop an initial framework. This framework was tested in six companies from four different sectors of industry: district cooling, medical equipment, transportation and oil storage. Validation of the framework was carried out using expert opinions and industrial case studies. A major contribution of the developed framework includes a hierarchy of appropriate criteria for assessing customer involvement in the service design process within results oriented PSS; the definition of four maturity levels which are suitable to describe the whole spectrum of customer involvement in the service design process; and finally, The paper concludes by enabling service providers to: take proactive decisions; screen and evaluate new services; improve perceived service quality; and provide barriers against imitation.

Keywords: customer involvement, maturity grid, new service development, result oriented product-service system, service design

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Authors: Claudeline D. Cellan

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Development is multifaceted, and efforts to hasten growth in all these facets have been gaining traction in recent years. Thus, producing a composite index that is reflective of these multidimensional impacts captures the interests of policymakers. The problem lies in going through a mixture of theoretical, methodological and empirical decisions and complexities which, when done carelessly, can lead to inconsistent and unreliable results. This study looks into index computation from a different and less complex perspective. Borrowing the idea of archetypes or ‘pure types’, archetypal analysis looks for points in the convex hull of the multivariate data set that captures as much information in the data as possible. The archetypes or 'pure types' are estimated such that they are convex combinations of all the observations, which in turn are convex combinations of the archetypes. This ensures that the archetypes are realistically observable, therefore achievable. In the sense of composite indices, we look for the best among these archetypes and use this as a benchmark for index computation. Its straightforward and simplistic approach does away with aggregation and substitutability problems which are commonly encountered in index computation. As an example of the application of archetypal analysis in index construction, the country data for the Human Development Index (HDI 2017) of the United Nations Development Programme (UNDP) is used. The goal of this exercise is not to replicate the result of the UNDP-computed HDI, but to illustrate the usability of archetypal analysis in index construction. Here best is defined in the context of life, education and gross national income sub-indices. Results show that the HDI from the archetypal analysis has a linear relationship with the UNDP-computed HDI.

Keywords: archetypes, composite index, convex combination, development

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Authors: Sultan Ghaleb Aldaihani

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- The environment in which educational leadership takes place is becoming increasingly complex due to factors like globalization and rapid technological change. - This is creating a "leadership gap" where the complexity of the environment outpaces the ability of leaders to effectively respond. - Educational leadership involves guiding teachers and the broader school system towards improved student learning and achievement. 2. Implications of Artificial Intelligence (AI) in Educational Leadership: - AI has great potential to enhance education, such as through intelligent tutoring systems and automating routine tasks to free up teachers. - AI can also have significant implications for educational leadership by providing better information and data-driven decision-making capabilities. - Computer-adaptive testing can provide detailed, individualized data on student learning that leaders can use for instructional decisions and accountability. 3. Enhancing Decision-Making Processes: - Statistical models and data mining techniques can help identify at-risk students earlier, allowing for targeted interventions. - Probability-based models can diagnose students likely to drop out, enabling proactive support. - These data-driven approaches can make resource allocation and decision-making more effective. 4. Improving Efficiency and Productivity: - AI systems can automate tasks and change processes to improve the efficiency of educational leadership and administration. - Integrating AI can free up leaders to focus more on their role's human, interactive elements.

Keywords: Education, Leadership, Technology, Artificial Intelligence

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Authors: Manveen Singh

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Since the very advent of law enforcement, eyewitness testimony has played a pivotal role in identifying, arresting and convicting suspects. Reliant heavily on the accuracy of human memory, nothing seems to carry more weight with the judiciary than the testimony of an actual witness. The acceptance of eyewitness testimony as a substantive piece of evidence lies embedded in the assumption that the human mind is adept at recording and storing events. Research though, has proven otherwise. Having carried out extensive study in the field of eyewitness testimony for the past 40 years, psychologists have concluded that human memory is fragile and needs to be treated carefully. The question that arises then, is how reliable is eyewitness testimony? The credibility of eyewitness testimony, simply put, depends on several factors leaving it reliable at times while not so much at others. This is further substantiated by the fact that as per scientific research, over 75 percent of all eyewitness testimonies may stand in error; quite a few of these cases resulting in life sentences. Although the advancement of scientific techniques, especially DNA testing, helped overturn many of these eyewitness testimony-based convictions, yet eyewitness identifications continue to form the backbone of most police investigations and courtroom decisions till date. What then is the solution to this long standing concern regarding the accuracy of eyewitness accounts? The present paper shall analyze the linkage between human memory and eyewitness identification as well as look at the various factors governing the credibility of eyewitness testimonies. Furthermore, it shall elaborate upon some best practices developed over the years to help reduce mistaken identifications. Thus, in the process, trace out the changing landscape of eyewitness testimony amidst the evolution of DNA and trace evidence.

Keywords: DNA, eyewitness, identification, testimony, evidence

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Authors: J. Vasauskaite

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From the perspective of Lithuanian furniture enterprises, the role of energy efficiency is significant as it leads to direct economic benefits, increased competitiveness and higher productivity. There are various possible improvements in energy efficiency in industry: changes in the production process, investment in R&D, implementation of energy-saving technologies or energy management systems. The research aims to contribute the understanding of energy efficiency importance in industry by presenting possible improvements of energy use in different manufacturing process of enterprises. The evaluation methodology included quantitative and qualitative research methods: the comparative and statistical analysis of primary and secondary sources of information. This paper provides the detailed analysis of the energy efficiency development opportunities and challenges in Lithuanian furniture industry. The results of the study show the importance of technological innovations, energy efficiency policies and environmental management strategies in developing energy efficiency within the wood and furniture industry. The analysis of energy efficiency development in Lithuanian furniture industry showed that the industrial activities are influenced by various internal and external factors such as increasing flows of products, human resources and overall management decisions; dynamic growth and increasing competition; emerging need for environmental information. In the light of these factors, Lithuanian furniture industry has undergone significant changes – restructuring, technological advances and business model innovations, allowing it to be more export-oriented and focus on upgrading quality, design and innovation.

Keywords: energy efficiency, energy policy, furniture industry, technological innovation

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Authors: Kika Ioannou Kazamia

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This paper examines the action research cycle of the second phase of longitudinal research on sustainable interior design practices, between two groups of stakeholders, designers and clients. During this phase of the action research, the second step - the change stage - of Lewin’s change management model has been utilized to change values, approaches, and attitudes toward sustainable design practices among the participants. Affective domain learning theory is utilized to attach new values. Learning with the use of information technology, collaborative learning, and problem-based learning are the learning methods implemented toward the acquisition of the objectives. Learning methods, and aims, require the design of interventions with participants' involvement in activities that would lead to the acknowledgment of the benefits of sustainable practices. Interventions are steered to measure participants’ decisions for the worth and relevance of ideas, and experiences; accept or commit to a particular stance or action. The data collection methods used in this action research are observers’ reports, participants' questionnaires, and interviews. The data analyses use both quantitative and qualitative methods. The main beneficial aspect of the quantitative method was to provide the means to separate many factors that obscured the main qualitative findings. The qualitative method allowed data to be categorized, to adapt the deductive approach, and then examine for commonalities that could reflect relevant categories or themes. The results from the data indicate that during the second phase, designers and clients' participants altered their behaviours.

Keywords: design, change, sustainability, learning, practices

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Authors: Aneta Nitsch-Osuch, Beata Pawlus, Maria Pawlak

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Introduction: Recently, the number of parents who refuse to vaccinate their children or present so-called hesitant behaviors has increased in many developed countries. The study aimed to analyze the completeness and timeliness of vaccinations against hepatitis B and tuberculosis in neonates in a single maternity hospital in Warsaw (Poland). Material and Methods: We analyzed medical records of children born in the hospital between 1st January 2015 and 31st December 2016 and calculated the proportion of newborns not vaccinated on time. Results: The percentage of unvaccinated newborns was similar in the analyzed years: 7.2% in 2015 and 6.7% in 2016. Parental decisions rather than medical contraindications caused non-immunization (4.3% vs. 2.9% in 2015, and 4.7% vs. 2% in 2016). Most parents refused both vaccinations (81%-84%), whereas 7-8% refused only hep B vaccination, and 9-11% refused alone tuberculosis vaccination. The majority of hesitant parents decided to delay both vaccinations (70-80%), while 10-11% of parents chose to delay only one vaccination (hep B). In consecutive years, an increase in the percentage of parents delaying tuberculosis vaccination was reported (10 vs. 19%). Discussion: The increase in the number of newborns who are not correctly vaccinated just after birth due to their parents' decision should be considered non-gradual, both for hepatitis B and tuberculosis. It is necessary to implement effective educational and informative measures targeted at future parents to reinforce positive attitudes towards vaccinations and to dispel doubts about them among parents who are hesitant.

Keywords: hepatitis B, tuberculosis, immunization, new-borns, coverage rate

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Authors: A. Buruzs, M. F. Hatwágner, A. Torma, L. T. Kóczy

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Recently, an increasing number of researchers have been focusing on working out realistic solutions to sustainability problems. As sustainability issues gain higher importance for organisations, the management of such decisions becomes critical. Knowledge representation is a fundamental issue of complex knowledge based systems. Many types of sustainability problems would benefit from models based on experts’ knowledge. Cognitive maps have been used for analyzing and aiding decision making. A cognitive map can be made of almost any system or problem. A fuzzy cognitive map (FCM) can successfully represent knowledge and human experience, introducing concepts to represent the essential elements and the cause and effect relationships among the concepts to model the behavior of any system. Integrated waste management systems (IWMS) are complex systems that can be decomposed to non-related and related subsystems and elements, where many factors have to be taken into consideration that may be complementary, contradictory, and competitive; these factors influence each other and determine the overall decision process of the system. The goal of the present paper is to construct an efficient IWMS which considers various factors. The authors’ intention is to propose an expert based system design approach for implementing expert decision support in the area of IWMSs and introduces an appropriate methodology for the development and analysis of group FCM. A framework for such a methodology consisting of the development and application phases is presented.

Keywords: factors, fuzzy cognitive map, group decision, integrated waste management system

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Authors: Laila Habiballah, Ahmad Tubaishat

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Background: with the development of information and communication technology, using the internet as a source to obtain health information is increasing. Nursing students as future health care providers should have the skills of locating, evaluating and using online health information. This will enable them to help their patients and families to make informed decisions. Aim: this study has a two-fold aim. The first is to assess the eHealth literacy among nursing students in Jordan. The second aim is to explore the factors that have an effect on the eHealth literacy. Methods: this is a descriptive cross-sectional survey that conducted in two universities in Jordan; public and private one. A number of 541 students from both universities were completed the eHEALS scale, which is an instrument designed to measure the eHealth literacy. Some additional personal and demographical variable were collected to explore its effect on eHealth literacy. Results: Students have a high perceived level of e-Health literacy (M=3.62, SD=0.58). They are aware of the available online health resources, know how to search, locate, and use these resources. But, they do not have the skills to evaluate these resources and cannot differentiate between the high and low-quality resources. The results showed as well that type of university, type of students' admission, academic level, students' skills of using the internet, and the perception of usefulness and importance of internet have an effect on the eHealth literacy. While the age, gender, GPA, and the frequency of using the internet was no significant factors. Conclusion: This study represents a baseline reference for the eHealth literacy in Jordan. Students have some skills of eHealth literacy and other skills need to be improved. Nursing educators and administrators should integrate and incorporate the skills of eHealth literacy in the curriculum.

Keywords: eHealth, literacy, nursing, students, Jordan

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Authors: Piyush Hajela

Abstract:

Public spaces within Indian markets are vibrant, colorful and contain dimensions that make them attractive and therefore act as popular gathering spaces. Most of these public spaces emerge as squares, plazas of varied shapes and sizes spread at different locations within the market. These public spaces grow organically and are discovered by the people themselves as they respond positively to the collective human senses. On the other hand, there are the planned and designed public spaces as well that are less active. This research evaluates both the planned and the organically transformed public spaces in Indian markets from an Urban Design point of view. The purpose of such research is to provide a basis for design solutions to ensure the success of designed public spaces. The evaluation is done for identified Attributes, namely Comfort, Protection, Familiarity, Activities, Form, Legibility, Engagement, Safety, Accessibility, Environment and Transformations by which a Public Space attains its recognition. The evaluation is based on a rating done for forty-four parameters falling under eleven attributes of public space. An opinion survey of professionals is conducted for their priorities of attributes while designing Public spaces. A comparison is made to rank these attributes between Planned and Organically transformed Public spaces and, opinion of the professionals. After dues analysis, the research suggests the learning from the organically transformed Public spaces for ensuring the success of designed public spaces. The suggestions may be in the form of Design decisions or administrative regulations, or both for achieving the desirables.

Keywords: assessment, attributes, engagement, interaction

Procedia PDF Downloads 193