Search results for: multi-criteria decision making methods

Authors: Katalin Kovacs

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In most forms of violence the perpetrators intend to hide their identities. Terrorism is different. Terrorist groups often take responsibility for their attacks, and consequently they reveal their identities. This unique characteristic of terrorism has been largely overlooked, and scholars are still puzzled as to why terrorist groups claim responsibility for their attacks. Certainly, the claim of responsibility is worth analysing. It would help to have a clearer picture of what terrorist groups try to achieve and how, but also to develop an understanding of the strategic planning of terrorist attacks and the message the terrorists intend to deliver. The research aims to answer the question why terrorist groups choose to claim responsibility for some of their attacks and not for others. In order to do so the claim of responsibility is considered to be a tactical choice, based on the assumption that terrorists weigh the costs and benefits of claiming responsibility. The main argument is that terrorist groups do not claim responsibility in cases when there is no tactical advantage gained from claiming responsibility. The idea that the claim of responsibility has tactical value offers the opportunity to test these assertions using a large scale empirical analysis. The claim of responsibility as a tactical choice depends on other tactical choices, such as the choice of target, the internationality of the attack, the number of victims and whether the group occupies territory or operates as an underground group. The structure of the terrorist groups and the level of decision making also affects the claim of responsibility. Terrorists on the lower level are less disciplined than the leaders. This means that the terrorists on lower levels pay less attention to the strategic objectives and engage easier in indiscriminate violence, and consequently they would less like to claim responsibility. Therefore, the research argues that terrorists, who are on a highest level of decision making would claim responsibility for the attacks as those are who takes into account the strategic objectives. As most studies on terrorism fail to provide definitions; therefore the researches are fragmented and incomparable. Separate, isolated researches do not support comprehensive thinking. It is also very important to note that there are only a few researches using quantitative methods. The aim of the research is to develop a new and comprehensive overview of the claim of responsibility based on strong quantitative evidence. By using well-established definitions and operationalisation the current research focuses on a broad range of attributes that can have tactical values in order to determine circumstances when terrorists are more likely to claim responsibility.

Keywords: claim of responsibility, leadership, tactical choice, terrorist group

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Authors: Madhurima S. Waghmare, Shaleen Singhal

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The concept of smartness, inclusion, sustainability is multidisciplinary and fuzzy, rooted in economic and social development theories and policies which get reflected in the spatial development of the cities. It is a challenge to convert these concepts from aspirations to transforming actions. There is a dearth of assessment and planning tools to support the city planners and administrators in developing smart, inclusive, and sustainable cities. To address this gap, this study develops an inclusive cities decision matrix based on an exploratory approach and using mixed methods. The matrix is soundly based on a review of multidisciplinary urban sector literature and refined and finalized based on inputs from experts and insights from case studies. The application of the decision matric on the case study cities in India suggests that the contemporary planning tools for cities need to be multidisciplinary and flexible to respond to the unique needs of the diverse contexts. The paper suggests that a multidimensional and inclusive approach to city planning can play an important role in building sustainable smart cities.

Keywords: inclusive-cities decision matrix, smart cities in India, city planning tools, sustainable cities

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Authors: Jeon Chi-Ho, Lee Jae-Bin, Shim Chang-Su

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National bridge inventory in Korea shows that the number of old prestressed concrete (PSC) bridgeover 30 years of service life is rapidly increasing. Recently tendon corrosion is one of the most critical issues in the maintenance of PSC bridges. In this paper, mechanical properties of corroded strands, which were removed from old bridges, were evaluated using tensile test. In the result, the equations to express the mechanical behavior of corroded strand were derived and compared to existing equation. For the decision of tendon replacement, it is necessary to evaluate the effect of corrosion level on strength and ductility of the structure. Considerations on analysis of PSC girders were introduced, and decision making on tendon replacement was also proposed.

Keywords: prestressed concrete bridge, tendon, corrosion, strength, ductility

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Authors: Sandesh Achar

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Personalized advertising holds greater potential for higher conversion rates compared to generic advertisements. However, its widespread application in the retail industry faces challenges due to complex implementation processes. These complexities impede the swift adoption of personalized advertisement on a large scale. Personalized advertisement, being a data-driven approach, necessitates consumer-related data, adding to its complexity. This paper introduces an innovative data-driven decision-making framework, D3Advert, which personalizes advertisements by analyzing personalities using a BiLSTM network. The framework utilizes the Myers–Briggs Type Indicator (MBTI) dataset for development. The employed BiLSTM network, specifically designed and optimized for D3Advert, classifies user personalities into one of the sixteen MBTI categories based on their social media posts. The classification accuracy is 86.42%, with precision, recall, and F1-Score values of 85.11%, 84.14%, and 83.89%, respectively. The D3Advert framework personalizes advertisements based on these personality classifications. Experimental implementation and performance analysis of D3Advert demonstrate a 40% improvement in impressions. D3Advert’s innovative and straightforward approach has the potential to transform personalized advertising and foster widespread personalized advertisement adoption in marketing.

Keywords: personalized advertisement, deep Learning, MBTI dataset, BiLSTM network, NLP.

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Authors: Klio Monokrousou, Maria Giannopoulou

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Urban areas, as they have been developed and operate today, are areas of accumulation of a significant amount of people and a large number of activities that generate desires and reasons for traveling. The territorial expansion of the cities as well as the need to preserve the importance of the central city areas lead to the continuous increase of transportation needs which in the limited urban space results in creating serious traffic and operational problems. The modern perception of urban planning is directed towards more holistic approaches and integrated policies that make it economically competitive, socially just and more environmentally friendly. Over the last 25 years, the goal of sustainable transport development has been central to the agenda of any plan or policy for the city. The modern planning of urban space takes into account the economic and social aspects of the city and the importance of the environment to sustainable urban development. In this context, the European Union promotes direct or indirect related interventions according to the cohesion and environmental policies; many countries even had the chance to actually test them. This paper is part of a wider research still in progress and it explores the methods and processes that have been developed towards this direction and presents a review and systematic presentation of this work. The ultimate purpose of this research is to effectively use this review to create a decision making methodological framework which can be the basis of a useful operational tool for sustainable urban planning.

Keywords: methods, sustainable urban development, urban mobility, methodological framework

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Authors: Peter Schnell, Phillip Haag

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In the course of the structural transformation of the construction industry, the integration of industrialization and digitization has led to the development of construction methods with an increased degree of prefabrication, such as system or modular construction. Compared to conventional construction, these innovative construction methods are characterized by modified structural and procedural properties and expand the range of construction services. Faced with the supply side, it is possible to identify construction-specific customer types with different characteristics and certain preferences as far as the choice of construction method is concerned. The basis for this finding was qualitative expert interviews. By evaluating the stereotypical customer needs, a corresponding segmentation of the demand side can be made along with the basic orientation and decision behavior. This demarcation supports the target- and needs-oriented customer approach and contributes to cooperative and successful project management.

Keywords: differentiation of customer types, modular construction methods, conventional construction methods, stereotypical customer types

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Authors: Zahra Ahmadi, Fazlollah Adibnia

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Scheduling of tasks and the optimal allocation of resources in the cloud are based on the dynamic nature of tasks and the heterogeneity of resources. Applications that are based on the scientific workflow are among the most widely used applications in this field, which are characterized by high processing power and storage capacity. In order to increase their efficiency, it is necessary to plan the tasks properly and select the best virtual machine in the cloud. The goals of the system are effective factors in scheduling tasks and resource selection, which depend on various criteria such as time, cost, current workload and processing power. Multi-criteria decision-making methods are a good choice in this field. In this research, a new method of work planning and resource allocation in a heterogeneous environment based on the modified AHP algorithm is proposed. In this method, the scheduling of input tasks is based on two criteria of execution time and size. Resource allocation is also a combination of the AHP algorithm and the first-input method of the first client. Resource prioritization is done with the criteria of main memory size, processor speed and bandwidth. What is considered in this system to modify the AHP algorithm Linear Max-Min and Linear Max normalization methods are the best choice for the mentioned algorithm, which have a great impact on the ranking. The simulation results show a decrease in the average response time, return time and execution time of input tasks in the proposed method compared to similar methods (basic methods).

Keywords: hierarchical analytical process, work prioritization, normalization, heterogeneous resource allocation, scientific workflow

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Authors: Dimitrios J. Dimitriou, Maria F. Sartzetaki

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The assessment variables of the accessibility and the sustainability of access infrastructure for remote regions may vary significant by location and a wide range of factors may affect the decision process. In this paper, the environmental disturbance implications of transportation system to key demand and supply variables impact the economic system in remote destination are descripted. According to a systemic approach, the key sustainability variables deals with decision making process that have to be included in strategic plan for the critical transport infrastructure development and their relationship to regional socioeconomic system are presented. The application deals with the development of railway in remote destinations, where the traditional CBA not include the external cost generated by the environmental impacts that may have a range of diverse impacts on transport infrastructure and services. The analysis output provides key messages to decision and policy makers towards sustainable development of transport infrastructure, especially for remote destinations where accessibility is a key factor of regional economic development and social stability. The key conclusion could be essential useful for relevant applications in remote regions in the same latitude.

Keywords: sustainable development in remote regions, transport infrastructure, strategic planning, sustainability variables

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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: Larisa Akhmylovskaia, Andriana Barysh

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The present paper is introducing the translation score developing methodology and methods in the cross-cultural communication. The ideas and examples presented by the authors illustrate the universal character of translation score developing methods under analysis. Personal experience in the international theatre-making projects, opera laboratories, cross-cultural master-classes give more opportunities to single out the conditions, forms, means and principles of translation score developing as well as the translator/interpreter’s functions as cultural liaison for multiethnic collaboration.

Keywords: methodology of translation score developing, pre-production, analysis, production, post-production, ethnic scene theory, theatre anthropology, laboratory, master-class, educational project, academic project, participant observation, super-objective

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Authors: Antonella Falanga, Armando Cartenì

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"Big data" refers to extremely vast and complex sets of data, encompassing extraordinarily large and intricate datasets that require specific tools for meaningful analysis and processing. These datasets can stem from diverse origins like sensors, mobile devices, online transactions, social media platforms, and more. The utilization of big data is pivotal, offering the chance to leverage vast information for substantial advantages across diverse fields, thereby enhancing comprehension, decision-making, efficiency, and fostering innovation in various domains. Big data, distinguished by its remarkable attributes of enormous volume, high velocity, diverse variety, and significant value, represent a transformative force reshaping the industry worldwide. Their pervasive impact continues to unlock new possibilities, driving innovation and advancements in technology, decision-making processes, and societal progress in an increasingly data-centric world. The use of these technologies is becoming more widespread, facilitating and accelerating operations that were once much more complicated. In particular, big data impacts across multiple sectors such as business and commerce, healthcare and science, finance, education, geography, agriculture, media and entertainment and also mobility and logistics. Within the transportation sector, which is the focus of this study, big data applications encompass a wide variety, spanning across optimization in vehicle routing, real-time traffic management and monitoring, logistics efficiency, reduction of travel times and congestion, enhancement of the overall transportation systems, but also mitigation of pollutant emissions contributing to environmental sustainability. Meanwhile, in public administration and the development of smart cities, big data aids in improving public services, urban planning, and decision-making processes, leading to more efficient and sustainable urban environments. Access to vast data reservoirs enables deeper insights, revealing hidden patterns and facilitating more precise and timely decision-making. Additionally, advancements in cloud computing and artificial intelligence (AI) have further amplified the potential of big data, enabling more sophisticated and comprehensive analyses. Certainly, utilizing big data presents various advantages but also entails several challenges regarding data privacy and security, ensuring data quality, managing and storing large volumes of data effectively, integrating data from diverse sources, the need for specialized skills to interpret analysis results, ethical considerations in data use, and evaluating costs against benefits. Addressing these difficulties requires well-structured strategies and policies to balance the benefits of big data with privacy, security, and efficient data management concerns. Building upon these premises, the current research investigates the efficacy and influence of big data by conducting an overview of the primary and recent implementations of big data in transportation systems. Overall, this research allows us to conclude that big data better provide to enhance rational decision-making for mobility choices and is imperative for adeptly planning and allocating investments in transportation infrastructures and services.

Keywords: big data, public transport, sustainable mobility, transport demand, transportation planning

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Authors: Nuno Biga

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Artificial Intelligence (AI) allows machines to interpret information and learn from context analysis, giving them the ability to make predictions adjusted to each specific situation. In addition to learning by performing deterministic and probabilistic calculations, the 'artificial brain' also learns through information and data provided by those who train it, namely its users. The "Assisted-BIGAMES" version of the Accident & Emergency (A&E) simulator introduces the concept of a "Virtual Assistant" (VA) that provides users with useful suggestions, namely to pursue the following operations: a) to relocate workstations in order to shorten travelled distances and minimize the stress of those involved; b) to identify in real time the bottleneck(s) in the operations system so that it is possible to quickly act upon them; c) to identify resources that should be polyvalent so that the system can be more efficient; d) to identify in which specific processes it may be advantageous to establish partnership with other teams; and e) to assess possible solutions based on the suggested KPIs allowing action monitoring to guide the (re)definition of future strategies. This paper is built on the BIGAMES© simulator and presents the conceptual AI model developed in a pilot project. Each Virtual Assisted BIGAME is a management simulator developed by the author that guides operational and strategic decision making, providing users with useful information in the form of management recommendations that make it possible to predict the actual outcome of different alternative management strategic actions. The pilot project developed incorporates results from 12 editions of the BIGAME A&E that took place between 2017 and 2022 at AESE Business School, based on the compilation of data that allows establishing causal relationships between decisions taken and results obtained. The systemic analysis and interpretation of this information is materialised in the Assisted-BIGAMES through a computer application called "BIGAMES Virtual Assistant" that players can use during the Game. Each participant in the Virtual Assisted-BIGAMES permanently asks himself about the decisions he should make during the game in order to win the competition. To this end, the role of the VA of each team consists in guiding the players to be more effective in their decision making through presenting recommendations based on AI methods. It is important to note that the VA's suggestions for action can be accepted or rejected by the managers of each team, and as the participants gain a better understanding of the game, they will more easily dispense with the VA's recommendations and rely more on their own experience, capability, and knowledge to support their own decisions. Preliminary results show that the introduction of the VA provides a faster learning of the decision-making process. The facilitator (Serious Game Controller) is responsible for supporting the players with further analysis and the recommended action may be (or not) aligned with the previous recommendations of the VA. All the information should be jointly analysed and assessed by each player, who are expected to add “Emotional Intelligence”, a component absent from the machine learning process.

Keywords: artificial intelligence (AI), gamification, key performance indicators (KPI), machine learning, management simulators, serious games, virtual assistant

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Authors: D. Garg, S. Luthra, A. Haleem

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Due to growing concern about environmental and social consequences throughout the world, a need has been felt to incorporate sustainability concepts in conventional manufacturing. This paper is an attempt to identify and evaluate drivers in implementing sustainable manufacturing in Indian context. Nine possible drivers for successful implementation of sustainable manufacturing have been identified from extensive review. Further, Decision Making Trial and Evaluation Laboratory (DEMATEL) approach has been utilized to evaluate and categorize these identified drivers for implementing sustainable manufacturing in to the cause and effect groups. Five drivers (Societal Pressure and Public Concerns; Regulations and Government Policies; Top Management Involvement, Commitment and Support; Effective Strategies and Activities towards Socially Responsible Manufacturing and Market Trends) have been categorized into the cause group and four drivers (Holistic View in Manufacturing Systems; Supplier Participation; Building Sustainable culture in Organization; and Corporate Image and Benefits) have been categorized into the effect group. “Societal Pressure and Public Concerns” has been found the most critical driver and “Corporate Image and Benefits” as least critical or the most easily influenced driver to implementing sustainable manufacturing in Indian context. This paper may surely help practitioners in better understanding of these drivers and their priorities towards effective implementation of sustainable manufacturing.

Keywords: drivers, decision making trial and evaluation laboratory (DEMATEL), India, sustainable manufacturing

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Authors: Katejarinporn Chaiya, Thawit Janbanklong

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The purposes of this study were to design and find users’ satisfaction after using the decision support system for tourism in the Northern part of Thailand, which can provide tourists with touristic information and plan their personal voyage. Such information can be retrieved systematically based on personal budget and provinces. The samples of this study were five experts and users: 30 "white collars" in Bangkok. This decision support system was designed via ASP.NET. Its database was developed by using MySQL, for administrators to effectively manage the database. The application outcome revealed that the innovation works properly as sought in objectives. Specialists and white collars in Bangkok have evaluated the decision support system; the result was satisfactorily positive.

Keywords: decision Support System, ASP.NET, MySQL, white collars

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Authors: Utkrash Sarkar, Vineet Tiwari, Shailendra Singh

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The development of social media has brought about a tremendous change in the marketing scenario for every industry. It has become a new hybrid element of the promotional mix in the marketing segment. This paper tries to show some light on the fact that in today’s scenario social media is a platform that everyone should take in consideration for any type of marketing campaign. In this paper, we have formulated a questionnaire, and through it, we have tried to gather information from the respondents that how social media is influencing their decision when they choose their travel destinations for tourism purpose, does it help in creating any awareness about places which they don’t have an idea? As a result, guiding the state government and providing them with a marketing strategy that how they can use social media in a better manner so that they could help increase their revenue and can make people aware about the places of the state which the target audience can plan to go for their next vacation.

Keywords: social media, marketing, information, decision making

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Authors: Elahe Sarfi, Esmat Noroozi, Farhad Hosseinzadeh Lotfi

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One of the important issues in Data Envelopment Analysis is the ranking of Decision Making Units. In this paper, a method for ranking DMUs is presented through which the weights related to efficient units should be chosen in a way that the other units preserve a certain percentage of their efficiency with the mentioned weights. To this end, a model is presented for ranking DMUs on the base of their superefficiency by considering the mentioned restrictions related to weights. This percentage can be determined by decision Maker. If the specific percentage is unsuitable, we can find a suitable and feasible one for ranking DMUs accordingly. Furthermore, the presented model is capable of ranking all of the efficient units including nonextreme efficient ones. Finally, the presented models are utilized for two sets of data and related results are reported.

Keywords: data envelopment analysis, efficiency, ranking, weight

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Authors: Tessa Heeren

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The following proposal pertains to the complex process of successfully implementing health policies that are based on public health research. A systematic review was conducted by myself and faculty at the Cluj School of Public Health in Romania. The reviewed articles covered a wide range of topics, such as barriers and facilitators to multi-sector collaboration, differences in professional cultures, and systemic obstacles. The reviewed literature identified communication, collaboration, user-friendly dissemination, and documentation of processes in the execution of applied research as important themes for the promotion of evidence in the public health decision-making process. This proposal fits into the Academy Health National Health Policy conference because it identifies and examines differences between the worlds of research and politics. Implications and new insights for federal and/or state health policy: Recommendations made based on the findings of this research include using politically relevant levers to promote research (e.g. campaign donors, lobbies, established parties, etc.), modernizing dissemination practices, and reforms in which the involvement of external stakeholders is facilitated without relying on invitations from individual policy makers. Description of how evidence and/or data was or could be used: The reviewed articles illustrated shortcomings and areas for improvement in policy research processes and collaborative development. In general, the evidence base in the field of integrating research into policy lacks critical details of the actual process of developing evidence based policy. This shortcoming in logistical details creates a barrier for potential replication of collaborative efforts described in studies. Potential impact of the presentation for health policy: The reviewed articles focused on identifying barriers and facilitators that arise in cross sector collaboration, rather than the process and impact of integrating evidence into policy. In addition, the type of evidence used in policy was rarely specified, and widely varying interpretations of the definition of evidence complicated overall conclusions. Background: Using evidence to inform public health decision making processes has been proven effective; however, it is not clear how research is applied in practice. Aims: The objectives of the current study were to assess the extent to which evidence is used in public health decision-making process. Methods: To identify eligible studies, seven bibliographic databases, specifically, PubMed, Scopus, Cochrane Library, Science Direct, Web of Science, ClinicalKey, Health and Safety Science Abstract were screened (search dates: 1990 – September 2015); a general internet search was also conducted. Primary research and systematic reviews about the use of evidence in public health policy in Europe were included. The studies considered for inclusion were assessed by two reviewers, along with extracted data on objective, methods, population, and results. Data were synthetized as a narrative review. Results: Of 2564 articles initially identified, 2525 titles and abstracts were screened. Ultimately, 30 articles fit the research criteria by describing how or why evidence is used/not used in public health policy. The majority of included studies involved interviews and surveys (N=17). Study participants were policy makers, health care professionals, researchers, community members, service users, experts in public health.

Keywords: cross-sector, dissemination, health policy, policy implementation

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Authors: Sarah O. Alhumoud, Mawaheb I. Altuwaijri, Tarfa M. Albuhairi, Wejdan M. Alohaideb

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Large-scale data stream analysis has become one of the important business and research priorities lately. Social networks like Twitter and other micro-blogging platforms hold an enormous amount of data that is large in volume, velocity and variety. Extracting valuable information and trends out of these data would aid in a better understanding and decision-making. Multiple analysis techniques are deployed for English content. Moreover, one of the languages that produce a large amount of data over social networks and is least analyzed is the Arabic language. The proposed paper is a survey on the research efforts to analyze the Arabic content in Twitter focusing on the tools and methods used to extract the sentiments for the Arabic content on Twitter.

Keywords: big data, social networks, sentiment analysis, twitter

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Authors: G. M. B. P. Abeysekara, W. A. D. C. Wijerathna

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Terminal choice from the multiple terminals region is not a simple decision and it is very complex, because shipping lines should consider on influential factors for the terminal choice at once according to their requirement. Therefore, terminal choice is a multiple criterion decision making (MCDM) situation under a specially designed decision hierarchy. Identification of perspective of shipping lines regarding terminal choice is vital important for the decision makers regarding container terminals. Thus this study is evaluated perception on main and feeder shipping lines’ regarding port of Colombo container terminals, and ranked terminals according to shipping lines preference. Analytic Hierarchy Process (AHP) model is adapted to this study, since it has features similar to the MCDM, it is weighted every influential factor by using pair wise comparisons, and consistency of the decision makers’ judgments are checked to evaluate trustworthiness of gathered data. And rating method is used to rank the terminals within Port of Colombo by assigning particular preference values with respect to the criteria and sub criteria. According to the findings of this study, main lines’ mainly concern on water depth of approach channel, depth of berth, handling charges and handling equipment facilities. And feeder lines’ main concerns were handling equipment facilities, loading and discharging efficiency, depth of berth and handling charges. Findings of the study suggested concentrating regarding the emphasized areas in order to enhance the competitiveness of terminals, and to increase number of vessel callings at the Port of Colombo. Application of above finding of the terminals within Port of Colombo lead to a far better competition among terminals and would uplift the overall level of services.

Keywords: AHP, Main and feeder shipping lines, criteria, sub criteria

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Authors: Roberta Martino, Viviana Ventre

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Empirical evidence has, over time, confirmed that the behavior of individuals is inconsistent with the descriptions provided by the Discounted Utility Model, an essential reference for calculating the utility of intertemporal prospects. The model assumes that individuals calculate the utility of intertemporal prospectuses by adding up the values of all outcomes obtained by multiplying the cardinal utility of the outcome by the discount function estimated at the time the outcome is received. The trend of the discount function is crucial for the preferences of the decision maker because it represents the perception of the future, and its trend causes temporally consistent or temporally inconsistent preferences. In particular, because different formulations of the discount function lead to various conclusions in predicting choice, the descriptive ability of models with a hyperbolic trend is greater than linear or exponential models. Suboptimal choices from any time point of view are the consequence of this mechanism, the psychological factors of which are encapsulated in the discount rate trend. In addition, analyzing the decision-making process from a psychological perspective, there is an equivalence between the selection of dominated prospects and a degree of impatience that decreases over time. The first part of the paper describes and investigates the anomalies of the discounted utility model by relating the cognitive distortions of the decision-maker to the emotional factors that are generated during the evaluation and selection of alternatives. Specifically, by studying the degree to which impatience decreases, it’s possible to quantify how the psychological and emotional mechanisms of the decision-maker result in a lack of decision persistence. In addition, this description presents inconsistency as the consequence of an inconsistent attitude towards time-delayed choices. The second part of the paper presents an experimental phase in which we show the relationship between inconsistency and impatience in different contexts. Analysis of the degree to which impatience decreases confirms the influence of the decision maker's emotional impulses for each anomaly in the utility model discussed in the first part of the paper. This work provides an application in the field of personalized behavioral finance. Indeed, the numerous behavioral diversities, evident even in the degrees of decrease in impatience in the experimental phase, support the idea that optimal strategies may not satisfy individuals in the same way. With the aim of homogenizing the categories of investors and to provide a personalized approach to advice, the results proven in the experimental phase are used in a complementary way with the information in the field of behavioral finance to implement the Analytical Hierarchy Process model in intertemporal choices, useful for strategic personalization. In the construction of the Analytic Hierarchy Process, the degree of decrease in impatience is understood as reflecting irrationality in decision-making and is therefore used for the construction of weights between anomalies and behavioral traits.

Keywords: analytic hierarchy process, behavioral finance, financial anomalies, impatience, time inconsistency

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Authors: Bishakha Majumdar, Ranjeet Nambudiri

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Considerable dichotomy exists in research regarding the role of optimism and self-efficacy in work and career outcomes. Optimism and self-efficacy are related to performance, commitment and engagement, but also are implicated in seeing opportunities outside the firm and switching jobs. There is absence of research capturing these opposing strands of findings in the same model and providing a holistic understanding of how the expectancy beliefs operate in case of the working professional. We attempt to bridge this gap by proposing that career-decision self-efficacy and career outcome expectations affect intention to quit through the competitive mediation pathways of internal and external marketability. This model provides a holistic picture of the role of career expectancy beliefs on career outcomes, by considering perceived career opportunities both inside and outside one’s present organization. The understanding extends the application of career expectancy beliefs in the context of career decision-making by the employed individual. Further, it is valuable for reconsidering the effectiveness of hiring and retention techniques used by a firm, as selection, rewards and training programs need to be supplemented by interventions that specifically strengthen the stability pathway.

Keywords: career decision self-efficacy, career outcome expectations, marketability, intention to quit, job mobility

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Authors: S. Vaibhav Kant Sahu, Surabhi Bipin Seth

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Human well-being has multiple constituents including the basic material for a good life, freedom and choice, health, good social relations, and security. Poverty is also multidimensional and has been defined as the pronounced deprivation of well-being. Dhurwa tribe of Bastar (India) have symbiotic relation with nature, it provisions ecosystem service such as food, fuel and fiber; regulating services such as climate regulation and non-material benefits such as spiritual or aesthetic benefits and they are managing their forest from ages. The demand for ecosystem services is now so great that trade-off among services become rule. Aim of study to explore evidences for linkages between ecosystem services and well-being of indigenous community, how much it helps them in poverty reduction and interaction between them. Objective of study was to find drivers of change and evidence concerning link between ecosystem, human development and sustainability, evidence in decision making does it opt for multi sectoral objectives. Which means human well-being as the central focus for assessment, while recognizing that biodiversity and ecosystems also have intrinsic value. Ecosystem changes that may have little impact on human well-being over days or weeks may have pronounced impacts over years or decades; so assessments needed to be conducted at spatial and temporal scales under social, political, economic scales to have high-resolution data. Researcher used framework developed by Millennium ecosystem assessment; since human action now directly or unknowingly virtually alter ecosystem. Researcher used ethnography study to get primary qualitative data, secondary data collected from panchayat office. The responses were transcribed and translated into English, as interview held in Hindi and local indigenous language. Focus group discussion were held with group of 10 women at Tiriya village. Researcher concluded with well-being is not just gap between ecosystem service supply but also increases vulnerability. Decision can have consequences external to the decision framework these consequences are called externalities because they are not part of the decision-making calculus.

Keywords: Bastar, Dhurwa tribe, ecosystem services, millennium ecosystem assessment, sustainability

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Authors: Ayat-Allah Bouramdane

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

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

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Authors: Marzouk Benali, Jawad Jeaidi, Behrang Mansoornejad, Olumoye Ajao, Banafsheh Gilani, Nima Ghavidel Mehr

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Canadian forest industry is seeking to identify and implement transformational strategies for enhanced financial performance through the emerging bioeconomy or more specifically through the concept of the biorefinery. For example, processing forest residues or surplus of biomass available on the mill sites for the production of biofuels, biochemicals and/or biomaterials is one of the attractive strategies along with traditional wood and paper products and cogenerated energy. There are many possible process-product biorefinery pathways, each associated with specific product portfolios with different levels of risk. Thus, it is not obvious which unique strategy forest industry should select and implement. Therefore, there is a need for analytical and design tools that enable evaluating biorefinery strategies based on a set of criteria considering a perspective of sustainability over the short and long terms, while selecting the existing core products as well as selecting the new product portfolio. In addition, it is critical to assess the manufacturing flexibility to internalize the risk from market price volatility of each targeted bio-based product in the product portfolio, prior to invest heavily in any biorefinery strategy. The proposed paper will focus on introducing a systematic methodology for designing integrated biorefineries using process systems engineering tools as well as a multi-criteria decision making framework to put forward the most effective biorefinery strategies that fulfill the needs of the forest industry. Topics to be covered will include market analysis, techno-economic assessment, cost accounting, energy integration analysis, life cycle assessment and supply chain analysis. This will be followed by describing the vision as well as the key features and functionalities of the I-BIOREF software platform, developed by CanmetENERGY of Natural Resources Canada. Two industrial case studies will be presented to support the robustness and flexibility of I-BIOREF software platform: i) An integrated Canadian Kraft pulp mill with lignin recovery process (namely, LignoBoost™); ii) A standalone biorefinery based on ethanol-organosolv process.

Keywords: biorefinery strategies, bioproducts, co-production, multi-criteria decision making, tool

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Authors: Albert T. Akume, P. D. Dahida

Abstract:

This paper examines the effect of various epochs of governments on policy making in Nigeria. The character of governance and public policy making of both epochs was exclusive, non-participatory and self-centric. As a consequence the interests of citizenry were not represented, neither protected nor sought to meet fairly the needs of all groups. The introduction of the post-1999 democratic government demand that the hitherto skewed pattern of policy making cease to be a character of governance. Hence, the need for citizen participation in the policy making process. The question then is what mode is most appropriate to engender public participation so as to make the policy making process functional? Given the prevailing social, economic and political dilemmas the utilization of the direct mode of citizen participation to affect policy outcome is doubtful if not unattainable. It is due to these predicament that this paper uses the documentary research design argues for the utilization of the indirect mode of citizen participation in the policy making process so as to affect public policy outcome appropriately and with less cost, acrimony and delays.

Keywords: governance, public policy, participation, representation, civil society

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Authors: Mijoh A. Gbededo, Kapila Liyanage, Sabuj Mallik

Abstract:

The emerging approaches to sustainable manufacturing are considered to be solution-oriented with the aim of addressing the environmental, economic and social issues holistically. However, the analysis of the interdependencies amongst the three sustainability dimensions has not been fully captured in the literature. In a recent review of approaches to sustainable manufacturing, two categories of techniques are identified: 1) Sustainable Product Development (SPD), and 2) Sustainability Performance Assessment (SPA) techniques. The challenges of the approaches are not only related to the arguments and misconceptions of the relationships between the techniques and sustainable development but also to the inability to capture and integrate the three sustainability dimensions. This requires a clear definition of some of the approaches and a road-map to the development of a holistic approach that supports sustainability decision-making. In this context, eco-innovation, social impact assessment, and life cycle sustainability analysis play an important role. This paper deployed an integrative approach that enabled amalgamation of sustainable manufacturing approaches and the theories of reciprocity and motivation into a holistic simulation-based impact analysis framework. The findings in this research have the potential to guide sustainability analysts to capture the aspects of the three sustainability dimensions into an analytical model. Additionally, the research findings presented can aid the construction of a holistic simulation model of a sustainable manufacturing and support effective decision-making.

Keywords: life cycle sustainability analysis, sustainable manufacturing, sustainability performance assessment, sustainable product development

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Authors: Vishnu Pratap Singh Kirar

Abstract:

The main aim of the communication system is to achieve maximum performance. In cognitive radio, any user or transceiver have the ability to sense best suitable channel, while the channel is not in use. It means an unlicensed user can share the spectrum of licensed user without any interference. Though the spectrum sensing consumes a large amount of energy and it can reduce by applying various artificial intelligent methods for determining proper spectrum holes. It also increases the efficiency of Cognitive Radio Network (CRN). In this survey paper, we discuss the use of different learning models and implementation of Artificial Neural Network (ANN) to increase the learning and decision-making capacity of CRN without affecting bandwidth, cost and signal rate.

Keywords: artificial neural network, cognitive radio, cognitive radio networks, back propagation, spectrum sensing

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Authors: Cheng Zeng, Xia Luo

Abstract:

Passenger organization has always been an essential part of China's metro operation and management. Facing the massive passenger flow, stations need to improve their intelligence and automation degree by an appropriate integrated system. Based on the existing integrated supervisory control system (ISCS) and simulation software (Anylogic), this paper designs an intelligent passenger organization system (IPOS) for metro stations. Its primary function includes passenger information acquisition, data processing and computing, visualization management, decision recommendations, and decision response based on interlocking equipment. For this purpose, the logical structure and intelligent algorithms employed are particularly devised. Besides, the structure diagram of information acquisition and application module, the application of Anylogic, the case library's function process are all given by this research. Based on the secondary development of Anylogic and existing technologies like video recognition, the IPOS is supposed to improve the response speed and address capacity in the face of emergent passenger flow of metro stations.

Keywords: anylogic software, decision-making support system, intellectualization, ISCS, passenger organization

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Authors: Ezeabasili Chibuike Patrick

Abstract:

The complex situation of construction industries in Nigeria and the risk of failures involved includes cost overrun, time overrun, Corruption, Government influence, Subcontractor challenges, Political influence and Instability, Cultural differences, Human resources deficiencies, cash flow Challenges, foreign exchange issues, inadequate design, Safety, low productivity, late payment, Quality control issues, project management issues, Environmental issues, Force majeure Competition amongst others has made the industry prone to risk and failures. Good project management remains effective in improving decision-making, which minimizes these risk events. This study was done to address these project risks and good decision-making to avert them. A mixed-method approach to research was used to do this study. Data collected by questionnaires and interviews on thirty-two (32) construction professionals was used in analyses to aid the knowledge and management of risks that were identified. The study revealed that there is no good risk management expertise in Nigeria. Also, that the economic/political situation and the recent COVID-19 pandemic has added to the risk and poor management strategies. The contingency theory and cost has therefore surfaced to be the most strategic management method used to reduce these risk issues and they seem to be very effective.

Keywords: strategies, risk management, contingency theory, Nigeria

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Authors: Yosra Mefteh Rekik, Younes Boujelbene

Abstract:

We introduce in this paper a new conceptual model representing the stock market dynamics. This model is essentially based on cognitive behavior of the intelligence investors. In order to validate our model, we build an artificial stock market simulation based on agent-oriented methodologies. The proposed simulator is composed of market supervisor agent essentially responsible for executing transactions via an order book and various kinds of investor agents depending to their profile. The purpose of this simulation is to understand the influence of psychological character of an investor and its neighborhood on its decision-making and their impact on the market in terms of price fluctuations. Therefore, the difficulty of the prediction is due to several features: the complexity, the non-linearity and the dynamism of the financial market system, as well as the investor psychology. The Artificial Neural Networks learning mechanism take on the role of traders, who from their futures return expectations and place orders based on their expectations. The results of intensive analysis indicate that the existence of agents having heterogeneous beliefs and preferences has provided a better understanding of price dynamics in the financial market.

Keywords: artificial intelligence methods, artificial stock market, behavioral modeling, multi-agent based simulation

Procedia PDF Downloads 423