Search results for: hiring decisions

Authors: Abdulqader Almasabe, Stephanie Ludi, Mohammed Alenazi

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Governments around the world have been increasingly introducing e-government services in order to make processes more efficient and accessible for their citizens. The government of Saudi Arabia has adopted E-Government for the effective delivery of services. However, the adoption rate of these services remains low in many countries. This paper aims to explore the determinants of citizens' intention to adopt and use e-government services, focusing on a model of factors influencing the adoption and utilization of e-government services (MFIAUEGS) that has been specially developed for this purpose. By analyzing the factors that influence citizens' decisions to use e-government services we hope to provide insights that help to increase adoption rates and improve the overall effectiveness of these services. In this paper, 562 valid responses were collected and analyzed to shed light on the issue. The results of the research showed that each of the proposed factors in the MFIAUEGS model played a significant role in influencing citizens' intentions to adopt and use e-government services.

Keywords: e-government, model acceptance, influencing factors, TAM

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Authors: Monica Lia

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This article presents a customer data analysis model using business intelligence tools for data modelling, transforming, data visualization and dynamic reports building. Economic organizational customer’s analysis is made based on the information from the transactional systems of the organization. The paper presents how to develop the data model starting for the data that companies have inside their own operational systems. The owned data can be transformed into useful information about customers using business intelligence tool. For a mature market, knowing the information inside the data and making forecast for strategic decision become more important. Business Intelligence tools are used in business organization as support for decision-making.

Keywords: customer analysis, business intelligence, data warehouse, data mining, decisions, self-service reports, interactive visual analysis, and dynamic dashboards, use cases diagram, process modelling, logical data model, data mart, ETL, star schema, OLAP, data universes

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Authors: Michel Patiño-Sáenz, Martín Haissiner, Jorge Martínez-Cotrina, Daniel Pastor, Hernando Santamaría-García, Maria-Alejandra Tangarife, Agustin Ibáñez, Sandra Baez

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It has been shown that gruesome descriptions of harm can increase the punishment given to a transgressor. This biasing effect is mediated by negative emotions, which are elicited upon the presentation of gruesome descriptions. However, there is a lack of studies inquiring the influence of such descriptions on moral decision-making in people involved in the criminal justice system. Such populations are of special interest since they have experience dealing with gruesome evidence, but also formal education on how to assess evidence and gauge the appropriate punishment according to the law. Likewise, they are expected to be objective and rational when performing their duty, because their decisions can impact profoundly people`s lives. Considering these antecedents, the objective of this study was to explore the influence gruesome written descriptions on moral decision-making in this group of people. To that end, we recruited attorneys, judges and public prosecutors (Criminal justice group, CJ, n=30) whose field of specialty is criminal law. In addition, we included a control group of people who did not have a formal education in law (n=30), but who were paired in age and years of education with the CJ group. All participants completed an online, Spanish-adapted version of a moral decision-making task, which was previously reported in the literature and also standardized and validated in the Latin-American context. A series of text-based stories describing two characters, one inflicting harm on the other, were presented to participants. Transgressor's intentionality (accidental vs. intentional harm) and language (gruesome vs. plain) used to describe harm were manipulated employing a within-subjects and a between-subjects design, respectively. After reading each story, participants were asked to rate (a) the harmful action's moral adequacy, (b) the amount of punishment deserving the transgressor and (c) how damaging was his behavior. Results showed main effects of group, intentionality and type of language on all dependent measures. In both groups, intentional harmful actions were rated as significantly less morally adequate, were punished more severely and were deemed as more damaging. Moreover, control subjects deemed more damaging and punished more severely any type of action than the CJ group. In addition, there was an interaction between intentionality and group. People in the control group rated harmful actions as less morally adequate than the CJ group, but only when the action was accidental. Also, there was an interaction between intentionality and language on punishment ratings. Controls punished more when harm was described using gruesome language. However, that was not the case of people in the CJ group, who assigned the same amount of punishment in both conditions. In conclusion, participants with job experience in the criminal justice system or criminal law differ in the way they make moral decisions. Particularly, it seems that they are less sensitive to the biasing effect of gruesome evidence, which is probably explained by their formal education or their experience in dealing with such evidence. Nonetheless, more studies are needed to determine the impact this phenomenon has on the fulfillment of their duty.

Keywords: criminal justice system, emotions, gruesome descriptions, intentionality, moral decision-making

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Authors: Ayesha Akbar

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Public service delivery has witnessed a significant improvement with the integration of information communication technology (ICT). It not only improves management structure with advanced technology for surveillance of service delivery but also provides evidence for informed decisions and policy. Pakistan’s public sector organizations have not been able to produce some good results to ensure service delivery. Notwithstanding, some of the public sector organizations in Pakistan has diffused modern technology and proved their credence by providing better service delivery standards. These good indicators provide sound basis to integrate technology in public sector organizations and shift of policy towards evidence based policy making. Rescue-1122 is a public sector organization which provides emergency services and proved to be a successful model for the provision of service delivery to save human lives and to ensure human development in Pakistan. The information about the organization has been received by employing qualitative research methodology. The information is broadly based on primary and secondary sources which includes Rescue-1122 website, official reports of organizations; UNDP (United Nation Development Program), WHO (World Health Organization) and by conducting 10 in-depth interviews with the high administrative staff of organizations who work in the Lahore offices. The information received has been incorporated with the study for the better understanding of the organization and their management procedures. Rescue-1122 represents a successful model in delivering the services in an efficient way to deal with the disaster management. The management of Rescue has strategized the policies and procedures in such a way to develop a comprehensive model with the integration of technology. This model provides efficient service delivery as well as maintains the standards of the organization. The service delivery model of rescue-1122 works on two fronts; front-office interface and the back-office interface. Back-office defines the procedures of operations and assures the compliance of the staff whereas, front-office equipped with the latest technology and good infrastructure handles the emergency calls. Both ends are integrated with satellite based vehicle tracking, wireless system, fleet monitoring system and IP camera which monitors every move of the staff to provide better services and to pinpoint the distortions in the services. The standard time of reaching to the emergency spot is 7 minutes, and during entertaining the case; driver‘s behavior, traffic volume and the technical assistance being provided to the emergency case is being monitored by front-office. Then the whole information get uploaded to the main dashboard of Lahore headquarter from the provincial offices. The latest technology is being materialized by Rescue-1122 for delivering the efficient services, investigating the flaws; if found, and to develop data to make informed decision making. The other public sector organizations of Pakistan can also develop such models to integrate technology for improving service delivery and to develop evidence for informed decisions and policy making.

Keywords: data, e-governance, evidence, policy

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Authors: I. Teotónio, C.O. Cruz, C.M. Silva, M. Manso

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Diverse stakeholders show different concerns when choosing green roof systems. Also, green roof solutions vary in their cost and performance. Therefore, decision-makers continually face the difficult task of balancing benefits against green roofs costs. Decision analysis methods, as multicriteria analysis, can be used when the decision‑making process includes different perspectives, multiple objectives, and uncertainty. The present study adopts a multicriteria decision model to evaluate the installation of green roofs in buildings, determining the solution with the best trade-off between costs and benefits in agreement with the preferences of the users/investors. This methodology was applied to a real decision problem, assessing the preferences between different green roof systems in an existing building in Lisbon. This approach supports the decision-making process on green roofs and enables robust and informed decisions on urban planning while optimizing buildings retrofitting.

Keywords: decision making, green roofs, investors preferences, multicriteria analysis, sustainable development

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Authors: R. M. P. C. Bandara, M. L. L. Weerasinghe, K. T. C. R. Kumari, A. G. D. R. Hansika, D. I. De Silva, D. M. T. H. Dias

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Software testing is an essential process in software development that aims to identify defects and ensure that software is functioning as intended. Various testing techniques are employed to achieve this goal, but the effectiveness of these techniques varies. This research paper analyzes the effectiveness of different testing techniques in ensuring software quality. The paper explores different testing techniques, including manual and automated testing, and evaluates their effectiveness in terms of identifying defects, reducing the number of defects in software, and ensuring that software meets its functional and non-functional requirements. Moreover, the paper will also investigate the impact of factors such as testing time, test coverage, and testing environment on the effectiveness of these techniques. This research aims to provide valuable insights into the effectiveness of different testing techniques, enabling software development teams to make informed decisions about the testing approach that is best suited to their needs. By improving testing techniques, the number of defects in software can be reduced, enhancing the quality of software and ultimately providing better software for users.

Keywords: software testing life cycle, software testing techniques, software testing strategies, effectiveness, software quality

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Authors: Hyun-Woo Cho

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Detection of incipient abnormal events in production processes is important to improve safety and reliability of manufacturing operations and reduce losses caused by failures. The construction of calibration models for predicting faulty conditions is quite essential in making decisions on when to perform preventive maintenance. This paper presents a multivariate calibration monitoring approach based on the statistical analysis of process measurement data. The calibration model is used to predict faulty conditions from historical reference data. This approach utilizes variable selection techniques, and the predictive performance of several prediction methods are evaluated using real data. The results shows that the calibration model based on supervised probabilistic model yielded best performance in this work. By adopting a proper variable selection scheme in calibration models, the prediction performance can be improved by excluding non-informative variables from their model building steps.

Keywords: calibration model, monitoring, quality improvement, feature selection

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Authors: Sherry Ann Ganase, Sandra Sookram

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This study examines adaptation measures and factors that influence adaptation decisions in Bequia by using multiple linear regression and a structural equation model. Using survey data, the results suggest that households are knowledgeable and concerned about climate change but lack knowledge about the measures needed to adapt. The findings from the SEM suggest that a positive relationship exist between vulnerability and adaptation, vulnerability and perception, along with a negative relationship between perception and adaptation. This suggests that being aware of the terms associated with climate change and knowledge about climate change is insufficient for implementing adaptation measures; instead the risk and importance placed on climate change, vulnerability experienced with household flooding, drainage and expected threat of future sea level are the main factors that influence the adaptation decision. The results obtained in this study are beneficial to all as adaptation requires a collective effort by stakeholders.

Keywords: adaptation, Bequia, multiple linear regression, structural equation model

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Authors: Rachel Nir, Tina Mckee

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In the UK, reliance has been placed on the professions to ‘heal themselves’ in improving equality and diversity. This approach has faltered, in part due to the global economic climate, and stimulus is needed to make faster equality progress. Recent empirical evidence has identified specific diversity barriers, namely: the cost of training; the use of high school grades as a primary selection criteria; the significance of prior work experience in recruitment decisions; and recruitment from elite universities. Students from majority groups and affluent backgrounds are advantaged over their counterparts. We as educators are passionate about resisting this. We believe that education can be a key agent of change. As part of this belief, the presenters have recently designed learning and teaching materials for the 2015/16 academic year. These are aimed at undergraduate law students for the purpose of 1) educating them on career barriers; 2) helping them to develop personal strategies to overcome them; and 3) encouraging them to address their own biases, both conscious and implicit, so that they, themselves, may be fairer employers and managers in the future.

Keywords: career barriers, challenging professional bias, education, elitism, personal student strategies

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Authors: Surita Maini, Sanjay Dhanka

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Machine learning (ML) involves developing algorithms and statistical models that enable computers to learn and make predictions or decisions based on data without being explicitly programmed. Because of its unlimited abilities ML is gaining popularity in medical sectors; Medical Imaging, Electronic Health Records, Genomic Data Analysis, Wearable Devices, Disease Outbreak Prediction, Disease Diagnosis, etc. In the last few decades, many researchers have tried to diagnose Breast Cancer (BC) using ML, because early detection of any disease can save millions of lives. Working in this direction, the authors have proposed a hybrid ML technique RBF SVM, to predict the BC in earlier the stage. The proposed method is implemented on the Breast Cancer UCI ML dataset with 569 instances and 32 attributes. The authors recorded performance metrics of the proposed model i.e., Accuracy 98.24%, Sensitivity 98.67%, Specificity 97.43%, F1 Score 98.67%, Precision 98.67%, and run time 0.044769 seconds. The proposed method is validated by K-Fold cross-validation.

Keywords: breast cancer, support vector classifier, machine learning, hyper parameter tunning

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Authors: Anuj Kumar Vaksha

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The research paper examines the trends and approaches of the international investment arbitral tribunals to the issues of environment and the exercise of states' regulatory power for the preservation of environment vis-à-vis the rights of the affected foreign investors. The paper analyses arbitral awards, decisions and orders in the leading cases of international investment arbitrations involving issues of environment and finds that there has been strong trend among the arbitral tribunals to balance the imperatives of the environmental regulation and the interest of the foreign investors. The arbitral tribunals have reflected deference to States' competence for regulation of environment to the extent they were genuine, relevant and in proportion to the legitimate objective sought to be achieved. The arbitral tribunals have at times been innovative and non-conservative in promoting the cause of environment through the mechanism of investor-state arbitration.

Keywords: International Investment Arbitration, environmental regulations, bilateral investment treaties, ICSID, NAFTA, amicus curiae, pollution havens hypothesis, environmental race to the bottom hypothesis

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Authors: Uyen Tran Tu

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The decision on capital structure is one of the most important and sophisticated decisions in financial management in order to improve firm performance. This article would study the two-way impact between capital structure and firm performance. The study use EVIEWS 6.0 software to determine a two-way relationship between the capital structure and firm performance based on two-stage regression (2SLS - Two-Stage Least Squares). The findings are: capital structure has the opposite effect on the business efficiency and vice versa, factors that effect on business efficiency include Size and Opportunities. Factors effects on the capital structure are size; liquidity. These factors also affect the ratio of capital structure (total debt/ total asset) of companies. In particular, liquidity has the opposite effect; and the size of the business has the same impact. The results of the study are in line with the theory and empirical studies presented, and the results of the study are unchanged for all three years 2015-2017.

Keywords: capital structure, firm performance, factors, two-way relationship

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Authors: Nguyen Thi Huong Nhai

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This paper examines how different motivations to engage in organic farming may impact the farmers’ subjective well-being using a survey database from the French Agence Bio. Three measures representing the subjective well-being of farmers brought by their involvement in organic farming are used in this study: feelings of pride, satisfaction, and feeling of happiness. We focus on the effects of two different types of motivations: intrinsic motivations, such as preservation of human health and public health, concern about the environment, and autonomy in farming decisions; extrinsic motivations, such as fair price, income, and demand incentives. Results show that not all intrinsic motivations can increase farmers’s well-being. The intrinsic motivation relating to environment concern and aspiration seems to have the highest positive impact on the three proxies of SWB in our study. It is interesting to find out that the two extrinsic motivations (profitable price, satisfying the incentive of consumer and cooperative) are proven to have a negative influence. Some comparisons, explanations, and practical implications are also indicated in this research.

Keywords: intrinsic otivation, extrinsic motivation, subjective wellbeing, organic farmers

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Authors: Kamalendu Pal

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Supply chains are the spinal cord of trade and commerce. Their logistics use different transport corridors on regular basis for operational purpose. The international supply chain transport corridors include different infrastructure elements (e.g. weighbridge, package handling equipment, border clearance authorities, and so on) in supply chains. This paper presents the use of multi-agent systems (MAS) to model and simulate some aspects of transportation corridors, and in particular the area of weighbridge resource optimization for operational profit generation purpose. An underlying multi-agent model provides a means of modeling the relationships among stakeholders in order to enable coordination in a transport corridor environment. Simulations of the costs of container unloading, reloading, and waiting time for queuing up tracks have been carried out using data sets. Results of the simulation provide the potential guidance in making decisions about optimal service resource allocation in a trade corridor.

Keywords: multi-agent systems, simulation, supply chain, transport corridor, weighbridge

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Authors: Md. Ahsan Ayub, Kazi A. Kalpoma, Humaira Tasnim Proma, Syed Mehrab Kabir, Rakib Ibna Hamid Chowdhury

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Constraint Satisfaction Problem (CSP) is observed in various applications, i.e., scheduling problems, timetabling problems, assignment problems, etc. Researchers adopt a CSP technique to tackle a certain problem; however, each technique follows different approaches and ways to solve a problem network. In our exhaustive study, it has been possible to visualize the processes of essential CSP algorithms from a very concrete constraint satisfaction example, NQueens Problem, in order to possess a deep understanding about how a particular constraint satisfaction problem will be dealt with by our studied and implemented techniques. Besides, benchmark results - time vs. value of N in N-Queens - have been generated from our implemented approaches, which help understand at what factor each algorithm produces solutions; especially, in N-Queens puzzle. Thus, extended decisions can be made to instantiate a real life problem within CSP’s framework.

Keywords: arc consistency (AC), backjumping algorithm (BJ), backtracking algorithm (BT), constraint satisfaction problem (CSP), forward checking (FC), least constrained values (LCV), maintaining arc consistency (MAC), minimum remaining values (MRV), N-Queens problem

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Authors: Sedigheh Zarei

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The aim of this research is to identify the key factors in shipping company’s port selection in order to providing their requirement. To identify and rank factors that are play the main role in selecting port for providing the ship supplies. At the first step, Data were collected via Semi-structured interviews, The aim was to generate knowledge on how shipping company select the port and suppliers for providing their needs. 37 port selection factors were chosen from the previous researches and field interviews and have been categorized into two groups of port's factor and the factors of services of suppliers companies. The current study adopts a questionnaire survey to the main shipping companies' operators in Iran. Their responses reveal that level of services of supplying companies and customs rules play the important role in selecting the ports. Our findings could affect decisions made by port authorities to consider that supporting the privet sections for ship chandelling business could have the best result in attracting ships.

Keywords: ship supplier, port selection, ship chandler, provision

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Authors: Neil Fourati

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Collaboration between public and private stakeholders for agricultural development are today lacking in Tunisia. The last dictatorship witnessed by the country has deteriorated the necessary trust between the state and small farmers for the realization of development projects, in particular in the interior, disadvantaged regions of the country. These regions, where the youth unemployment rate is above 30%, have been the heart of the uprising that preceded the revolution. The transitional period that the country is going through since 2011 is an opportunity for the emergence of new governance systems in the context of the decentralization. The latter is recognized in the 2nd Tunisian Republic constitution as the basis of regional management. Civil society participation to the decision-making process is considered as a mean to identify measures that are more coherent with local populations’ needs. The development of agriculture and food value chains in rural areas is relevant within the framework of the implementation of new decisions systems that require public-private collaborations. These new systems can lead to actions in favor of improving living conditions of rural populations. The diverisification of activities around agriculture can be a solution for job creation and local value creation. The project for the promotion of sustainable agriculture and rural development in Tunisia has designed and implemented a multi-stakeholder dialogue process for the development of local value chains platforms in disadvantaged areas of the country. The platforms gather public and private organizations ; as well civil society organizations ; that intervene in a locality in relation to the production transformation or product’s commercialization. The role of these platforms is to formulate realize and evaluate collaborative actions or projects for the promotion of the concerned product and territory. The dialogue process steps allow to create the necessary collaboration conditions in order to promote viable collectivities, dynamic economies and healthy environments. Effectively, the dialogue process steps allow to identify the local leaders. These leaders recognize the development constraints and opportunities. They deal with key and gathering subjects around the collaborative projects or actions. They take common decisions in order to create effective coalitions for the implementation of common actions. The plateforms realize quick success so as to build trust. The project has supported the formulation of 22 collaborative projects. Seven priority collaborative projects have been realized. Each collaborative project includes 3 parts : the signature of the collaboration conventions between public and private organizations, investment in the relevant material in order to increase productivity and the quality of local and products and finally management and technical training in favour of producers’ organizations for the promotion of local products. The implementation of this process has enabled to enhance the capacities of collaboration between local actors : producers, traders, processors and support structures from public sector and civil society. It also allowed to improve the efficiency and relevance of actions and measures for agriculture and rural development programs. Thus, the process for the development of local value chain platform is a basis for sustainable development of agriculture.

Keywords: governance, public private collaboration, rural development, value chains

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Authors: The Danh Phan

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House price forecasting is a main topic in the real estate market research. Effective house price prediction models could not only allow home buyers and real estate agents to make better data-driven decisions but may also be beneficial for the property policymaking process. This study investigates the housing market by using machine learning techniques to analyze real historical house sale transactions in Australia. It seeks useful models which could be deployed as an application for house buyers and sellers. Data analytics show a high discrepancy between the house price in the most expensive suburbs and the most affordable suburbs in the city of Melbourne. In addition, experiments demonstrate that the combination of Stepwise and Support Vector Machine (SVM), based on the Mean Squared Error (MSE) measurement, consistently outperforms other models in terms of prediction accuracy.

Keywords: house price prediction, regression trees, neural network, support vector machine, stepwise

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Authors: Zeba Mahmood

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The modern business organizations are adopting technological advancement to achieve competitive edge and satisfy their consumer. The development in the field of Information technology systems has changed the way of conducting business today. Business operations today rely more on the data they obtained and this data is continuously increasing in volume. The data stored in different locations is difficult to find and use without the effective implementation of Data mining and Knowledge management techniques. Organizations who smartly identify, obtain and then convert data in useful formats for their decision making and operational improvements create additional value for their customers and enhance their operational capabilities. Marketers and Customer relationship departments of firm use Data mining techniques to make relevant decisions, this paper emphasizes on the identification of different data mining and Knowledge management techniques that are applied to different business industries. The challenges and issues of execution of these techniques are also discussed and critically analyzed in this paper.

Keywords: knowledge, knowledge management, knowledge discovery in databases, business, operational, information, data mining

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Authors: Jingsi Li, Neil S. Ferguson

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Time pressure could have an influence on the productivity, quality of decision making, and the efficiency of problem-solving. This has been mostly stemmed from cognitive research or psychological literature. However, a salient scarce discussion has been held for transport adjacent fields. It is conceivable that in many activity-travel contexts, time pressure is a potentially important factor since an excessive amount of decision time may incur the risk of late arrival to the next activity. The activity-travel rescheduling behavior is commonly explained by costs and benefits of factors such as activity engagements, personal intentions, social requirements, etc. This paper hypothesizes that an additional factor of perceived time pressure could affect travelers’ rescheduling behavior, thus leading to an impact on travel demand management. Time pressure may arise from different ways and is assumed here to be essentially incurred due to travelers planning their schedules without an expectation of unforeseen elements, e.g., transport disruption. In addition to a linear-additive utility-maximization model, the less computationally compensatory heuristic models are considered as an alternative to simulate travelers’ responses. The paper will contribute to travel behavior modeling research by investigating the following questions: how to measure the time pressure properly in an activity-travel day plan context? How do travelers reschedule their plans to cope with the time pressure? How would the importance of the activity affect travelers’ rescheduling behavior? What will the behavioral model be identified to describe the process of making activity-travel rescheduling decisions? How do these identified coping strategies affect the transport network? In this paper, a Mixed Heuristic Model (MHM) is employed to identify the presence of different choice heuristics through a latent class approach. The data about travelers’ activity-travel rescheduling behavior is collected via a web-based interactive survey where a fictitious scenario is created comprising multiple uncertain events on the activity or travel. The experiments are conducted in order to gain a real picture of activity-travel reschedule, considering the factor of time pressure. The identified behavioral models are then integrated into a multi-agent transport simulation model to investigate the effect of the rescheduling strategy on the transport network. The results show that an increased proportion of travelers use simpler, non-compensatory choice strategies instead of compensatory methods to cope with time pressure. Specifically, satisfying - one of the heuristic decision-making strategies - is adopted commonly since travelers tend to abandon the less important activities and keep the important ones. Furthermore, the importance of the activity is found to increase the weight of negative information when making trip-related decisions, especially route choices. When incorporating the identified non-compensatory decision-making heuristic models into the agent-based transport model, the simulation results imply that neglecting the effect of perceived time pressure may result in an inaccurate forecast of choice probability and overestimate the affectability to the policy changes.

Keywords: activity-travel rescheduling, decision making under uncertainty, mixed heuristic model, perceived time pressure, travel demand management

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Authors: Evren Aysev Denec

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As an urban settlement dating as early as 8000 years and the capital for Byzantine and Ottoman empires; İstanbul has been a significant global city throughout history. The most drastic changes in the macro form of Istanbul have taken place in the last seven decades; starting from 1950’s with rapid industrialization and population growth; pacing up after the 1980’s with the efforts of integration to the global capitalist system; reaching to a climax in the 2000’s with the adaptation of a neoliberal urban regime. Today, the rate of urbanization together with land speculation and real estate investment has been growing enormously. Every inch of urban land is conceptualized as a commodity to be capitalized. This neoliberal mindset has many controversial implementations, from the privatization of public land to the urban transformation of historic neighbourhoods and consumption of natural resources. The planning decisions concerning the city have been mainly top down initiations; conceptualising historical, cultural and natural heritage as commodities to be capitalised and consumed in favour of creating rent value. One of the most crucial implementations of this neoliberal urban regime is the project of establishing a ‘new city’ around northern Istanbul; together with a number of large-scale infrastructural projects such as the Third Bosporus Bridge; a new highway system, a Third Airport Project and a secondary Bosporus project called the ‘Canal Istanbul’. Urbanizing northern Istanbul is highly controversial as this area consists of major natural resources of the city; being the northern forests, water supplies and wildlife; which are bound to be destroyed to a great extent following the implementations. The construction of the third bridge and the third airport has begun in 2013, despite environmental objections and protests. Over five hundred thousand trees are planned be cut for solely the construction of the bridge and the Northern Marmara Motorway. Yet the real damage will be the urbanization of the forest area; irreversibly corrupting the natural resources and attracting millions of additional population towards Istanbul. Furthermore, these projects lack an integrated planning scope as the plans prepared for Istanbul are constantly subjected to alterations forced by the central government. Urban interventions mentioned above are executed despite the rulings of Istanbul Environmental plan, due to top down planning decisions. Instead of an integrated action plan that prepares for the future of the city, Istanbul is governed by partial plans and projects that are issued by a profit based agenda; supported by legal alterations and laws issued by the central government. This paper aims to discuss the ongoing implementations with regards to northern Istanbul; claiming that they are not merely infrastructural interventions but parts of a greater neoliberal urbanization strategy. In the course of the study, firstly a brief account on the northern forests of Istanbul will be presented. Then, the projects will be discussed in detail, addressing how the current planning schemes deal with the natural heritage of the city. Lastly, concluding remarks on how the implementations could affect the future of Istanbul will be presented.

Keywords: Istanbul, urban design, urban planning, natural resources

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Authors: Lilia Righi

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Recently, the fashion industry has demonstrated a keen interest in sustainability and the environment. Sustainable fashion has huge potential and appeals to environmentally conscious Generation Z shoppers. Meanwhile, Generation Z customers have attracted researchers' interest due to their overconsumption of clothing. However, most studies in this area focus on designing or producing sustainable clothing, with little exploration of consumers. To fill this gap, the present study aims to determine the important factors influencing Generation Z consumers' decisions to purchase sustainable fashion by mobilizing the theory of planned behavior (TPB). It uses deductive qualitative research based on 18 semi-structured interviews with Generation Z consumers in France. Qualitative data will be analyzed using reflective thematic analysis. On a theoretical level, this research contributes to enriching the literature by mobilizing, for the first time, the theory of planned behavior in the context of sustainable fashion. On a practical level, the results can help practitioners determine effective marketing strategies to persuade Generation Z to consume sustainable clothing.

Keywords: generation Z, qualitative methodology, sustainable fashion, theory of planned behavior (TPB).

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Authors: Tyler Gill, Sophia Daniels

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The paper examines how accessing the spatial-temporal constrains of data will help inform policymakers and law enforcement officials. The authors utilize Chicago crime data from 2006-2016 to demonstrate how the Emerging Hot Spot Tool is an ideal hot spot clustering approach to analyze crime data. Traditional approaches include density maps or creating a spatial weights matrix to include the spatial-temporal constrains. This new approach utilizes a space-time implementation of the Getis-Ord Gi* statistic to visualize the data more quickly to make better decisions. The research will help complement socio-cultural research to find key patterns to help frame future policies and evaluate the implementation of prior strategies. Through this analysis, homicide trends and patterns are found more effectively and recommendations for use by non-traditional users of GIS are offered for real life implementation.

Keywords: crime mapping, emerging hot spot analysis, Getis-Ord Gi*, spatial-temporal analysis

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Authors: Hassam Muazzam

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This paper devises an autonomous self-driven vehicle that is capable of taking a disabled person to his/her desired location using three different power sources (gasoline, solar, electric) without any control from the user, avoiding the obstacles in the way. The GPS co-ordinates of the desired location are sent to the main processing board via a GSM module. After the GPS co-ordinates are sent, the path to be followed by the vehicle is devised by Pythagoras theorem. The distance and angle between the present location and the desired location is calculated and then the vehicle starts moving in the desired direction. Meanwhile real-time data from ultrasonic sensors is fed to the board for obstacle avoidance mechanism. Ultrasonic sensors are used to quantify the distance of the vehicle from the object. The distance and position of the object is then used to make decisions regarding the direction of vehicle in order to avoid the obstacles using artificial neural network which is implemented using ATmega1280. Also the vehicle provides the feedback location at remote location.

Keywords: autonomous self-driven vehicle, obstacle avoidance, desired location, pythagoras theorem, neural network, remote location

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Authors: Dimitriu Corneliu-Ioan, Gheorghe FrațIlă

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Romania has one of the highest rates of road deaths among European Union Member States, and there is a concern that the country will not meet its goal of "zero deaths" by 2050. The European Union also aims to halve the number of people seriously injured in road accidents by 2030. Therefore, there is a need to improve road infrastructure safety management in Romania. The aim of this study is to analyze road accident data through statistical methods to assess the current state of road infrastructure safety in Bucharest. The study also aims to identify trends and make forecasts regarding serious road accidents and their consequences. The objective is to provide insights that can help prioritize measures to increase road safety, particularly in urban areas. The research utilizes statistical analysis methods, including exploratory analysis and descriptive statistics. Databases from the Traffic Police and the Romanian Road Authority are analyzed using Excel. Road risks are compared with the main causes of road accidents to identify correlations. The study emphasizes the need for better quality and more diverse collection of road accident data for effective analysis in the field of road infrastructure engineering. The research findings highlight the importance of prioritizing measures to improve road safety in urban areas, where serious accidents and their consequences are more frequent. There is a correlation between the measures ordered by road safety auditors and the main causes of serious accidents in Bucharest. The study also reveals the significant social costs of road accidents, amounting to approximately 3% of GDP, emphasizing the need for collaboration between local and central administrations in allocating resources for road safety. This research contributes to a clearer understanding of the current road infrastructure safety situation in Romania. The findings provide critical insights that can aid decision-makers in allocating resources efficiently and institutionally cooperating to achieve sustainable road safety. The data used for this study are collected from the Traffic Police and the Romanian Road Authority. The data processing involves exploratory analysis and descriptive statistics using the Excel tool. The analysis allows for a better understanding of the factors contributing to the current road safety situation and helps inform managerial decisions to eliminate or reduce road risks. The study addresses the state of road infrastructure safety in Bucharest and analyzes the trends and forecasts regarding serious road accidents and their consequences. It studies the correlation between road safety measures and the main causes of serious accidents. To improve road safety, cooperation between local and central administrations towards joint financial efforts is important. This research highlights the need for statistical data processing methods to substantiate managerial decisions in road infrastructure management. It emphasizes the importance of improving the quality and diversity of road accident data collection. The research findings provide a critical perspective on the current road safety situation in Romania and offer insights to identify appropriate solutions to reduce the number of serious road accidents in the future.

Keywords: road death rate, strategic objective, serious road accidents, road safety, statistical analysis

Procedia PDF Downloads 62

Authors: B. Garfolo, L. Kelpsh, R. Roak, R. Kuck

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Often, student ratings of instructors play a significant role in the career path of an instructor in higher education. So then, how does a student view the effectiveness of instructor teaching? This question has been address by literally thousands of studies found in the literature. Yet, why does this question still persist? A literature review reveals that while it is true that student evaluations of instructors can be biased, there is still a considerable amount of work that needs to be done in understanding why. As student evaluations of instructors can be used in a variety of settings (formative or summative) it is critical to understand the nature of the bias. The authors believe that not only is some bias possible in student evaluations, it should be expected for the simple reason that a student evaluation is a human activity and as such, relies upon perception and interpersonal judgment. As such, student ratings are affected by the same factors that can potentially affect any rater’s judgment, such as stereotypes based on gender, culture, race, etc. Previous study findings suggest that student evaluations of teacher effectiveness differ between male and female raters. However, even though studies have shown that instructor gender does play an important role in influencing student ratings, the exact nature and extent of that role remains the subject of debate. Researchers, in their attempt to define good teaching, have looked for differences in student evaluations based on a variety of characteristics such as course type, class size, ability level of the student and grading practices in addition to instructor and student characteristics (gender, age, etc.) with inconsistent results. If a student evaluation represents more than an instructor’s teaching ability, for example, a physical characteristic such as gender, then this information must be taken into account if the evaluation is to have meaning with respect to instructor assessment. While the authors concede that it is difficult or nearly impossible to separate gender from student perception of teaching practices in person, it is, however, possible to shield an instructor’s gender identity with respect to an online teaching experience. The online teaching modality presents itself as a unique opportunity to experiment directly with gender identity. The analysis of the differences of online behavior of individuals when they perceive that they are interacting with a male or female could provide a wealth of data on how gender influences student perceptions of teaching effectiveness. Given the importance of the role student ratings play in hiring, retention, promotion, tenure, and salary deliberations in academic careers, this question warrants further attention as it is important to be aware of possible bias in student evaluations if they are to be used at all with respect to any academic considerations. For experimental purposes, the author’s constructed and online class where each instructors operate under two different gender identities. In this study, each instructor taught multiple sections of the same class using both a male identity and a female identity. The study examined student evaluations of teaching based on certain student and instructor characteristics in order to determine if and where male and female students might differ in their ratings of instructors based on instructor gender. Additionally, the authors examined if there are differences between undergraduate and graduate students' ratings with respect to the experimental criteria.

Keywords: gender bias, ethics, student evaluations, student perceptions, online instruction

Procedia PDF Downloads 248

Authors: Priya Nangia, Sanchita Bansal

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As fashion cycles become more rapid, some segments of the fashion industry have adopted increasingly unsustainable production processes to keep up with demand and enhance profit margins. The growing threat to environmental and social wellbeing posed by unethical fast fashion practices and the need to integrate the targets of SDGs into this industry necessitates a shift in the fashion industry's unsustainable nature, which can only be accomplished in the long run if consumers support sustainable fashion by purchasing it. Fast fashion is defined as low-cost, trendy apparel that takes inspiration from the catwalk or celebrity culture and rapidly transforms it into garments at high-street stores to meet consumer demand. Given the importance of identity formation to many consumers, the desire to be “fashionable” often outweighs the desire to be ethical or sustainable. This paradox exemplifies the tension between the human drive to consume and the will to do so in moderation. Previous research suggests that there is an attitude-behavior gap when it comes to determining consumer purchasing behavior, but to the best of our knowledge, no study has analysed how to encourage customers to shift from fast to slow fashion. Against this backdrop, the aim of this study is twofold: first, to identify and examine the factors that impact consumers' decisions to engage in sustainable fashion, and second, the authors develop a comprehensive framework for conceptualizing and encouraging researchers and practitioners to foster sustainable consumer behavior. This study used a systematic approach to collect data and analyse literature. The approach included three key steps: review planning, review execution, and findings reporting. Authors identified the keywords “sustainable consumption” and “sustainable fashion” and retrieved studies from the Web of Science (WoS) (126 records) and Scopus database (449 records). To make the study more specific, the authors refined the subject area to management, business, and economics in the second step, retrieving 265 records. In the third step, the authors removed the duplicate records and manually reviewed the articles to examine their relevance to the research issue. The final 96 research articles were used to develop this study's systematic scheme. The findings indicate that societal norms, demographics, positive emotions, self-efficacy, and awareness all have an effect on customers' decisions to purchase sustainable apparel. The authors propose a framework, denoted by the acronym SHIFT, in which consumers are more likely to engage in sustainable behaviors when the message or context leverages the following factors: (s)social influence, (h)habit formation, (i)individual self, (f)feelings, emotions, and cognition, and (t)tangibility. Furthermore, the authors identify five broad challenges that encourage sustainable consumer behavior and use them to develop novel propositions. Finally, the authors discuss how the SHIFT framework can be used in practice to drive sustainable consumer behaviors. This research sought to define the boundaries of existing research while also providing new perspectives on future research, with the goal of being useful for the development and discovery of new fields of study, thereby expanding knowledge.

Keywords: consumer behavior, fast fashion, sustainable consumption, sustainable fashion, systematic literature review

Procedia PDF Downloads 76

Authors: Ritsuko Kawasaki (Aiba), Takeshi Hiromatsu

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Management is required to understand all information security risks within an organization, and to make decisions on which information security risks should be treated in what level by allocating how much amount of cost. However, such decision-making is not usually easy, because various measures for risk treatment must be selected with the suitable application levels. In addition, some measures may have objectives conflicting with each other. It also makes the selection difficult. Moreover, risks generally have trends and it also should be considered in risk treatment. Therefore, this paper provides the extension of the model proposed in the previous study. The original model supports the selection of measures by applying a combination of weighted average method and goal programming method for multi-objective analysis to find an optimal solution. The extended model includes the notion of weights to the risks, and the larger weight means the priority of the risk.

Keywords: information security risk treatment, selection of risk measures, risk acceptance, multi-objective optimization

Procedia PDF Downloads 440

Authors: Ashiff Khan, A. Seetharaman, Abhijit Dasgupta

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The new era of big data (BD) is influencing chemical industries tremendously, providing several opportunities to reshape the way they operate and help them shift towards intelligent manufacturing. Given the availability of free software and the large amount of real-time data generated and stored in process plants, chemical industries are still in the early stages of big data adoption. The industry is just starting to realize the importance of the large amount of data it owns to make the right decisions and support its strategies. This article explores the importance of professional competencies and data science that influence BD in chemical industries to help it move towards intelligent manufacturing fast and reliable. This article utilizes a literature review and identifies potential applications in the chemical industry to move from conventional methods to a data-driven approach. The scope of this document is limited to the adoption of BD in chemical industries and the variables identified in this article. To achieve this objective, government, academia, and industry must work together to overcome all present and future challenges.

Keywords: chemical engineering, big data analytics, industrial revolution, professional competence, data science

Procedia PDF Downloads 66

Authors: Mouataz Zreika, Maria Estela Varua

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Stock investment decisions are often made based on current events of the global economy and the analysis of historical data. Conversely, visual representation could assist investors’ gain deeper understanding and better insight on stock market trends more efficiently. The trend analysis is based on long-term data collection. The study adopts a hybrid method that combines the Clustering algorithm and Force-directed algorithm to overcome the scalability problem when visualizing large data. This method exemplifies the potential relationships between each stock, as well as determining the degree of strength and connectivity, which will provide investors another understanding of the stock relationship for reference. Information derived from visualization will also help them make an informed decision. The results of the experiments show that the proposed method is able to produced visualized data aesthetically by providing clearer views for connectivity and edge weights.

Keywords: clustering, force-directed, graph drawing, stock investment analysis

Procedia PDF Downloads 288