Search results for: affective-analytical decision framework

Authors: Rimac Smiljanic Ana, Pepur Sandra, Bulog Ivana

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Financial decision-making in the household is not simple, and it demands that the decision-maker has proper knowledge and skills. Usually, high uncertainty, risk, and stress surround household financial decision-making since it is extremely important and critical for household wealth accumulation and for the well-being of all household members. Generally, skilful people tend to have higher confidence in certain tasks they perform, and they achieve better results. Therefore, in the household context, the possession of certain skills by the ones who make financial decisions for the household is of particular importance. This paper addresses financial literacy as an important skill for household decision-making. Apart from financial literacy, the paper also considers other factors, such as employment, education, and age, as significant for household financial decision-making. The analysis is based on quantitative individual-level survey data. The data collection was conducted during January and February 2021 in Croatia through an online survey. To reach a wide variety of participants, the snowball sampling method was used. The result revealed interesting and somewhat puzzling results. Our results point to the importance of financial literacy skills for household decision-making.

Keywords: skill, financial literacy, decision-making, household financijal decision making

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Authors: James M. Wakiru, Liliane Pintelon, Peter Muchiri, Stanley Mburu

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Maintenance performance measurement (MPM) represents an integrated aspect that considers both operational and maintenance related aspects while evaluating the effectiveness and efficiency of maintenance to ensure assets are working as they should. Three salient issues require to be addressed for an asset-intensive organization to employ an MPM-based framework to optimize maintenance. Firstly, the organization should establish important perfomance metric(s), in this case the maintenance objective(s), which they will be focuss on. The second issue entails aligning the maintenance objective(s) with maintenance optimization. This is achieved by deriving maintenance performance indicators that subsequently form an objective function for the optimization program. Lastly, the objective function is employed in an optimization program to derive maintenance decision support. In this study, we develop a framework that initially identifies the crucial maintenance performance measures, and employs them to derive maintenance decision support. The proposed framework is demonstrated in a case study of a geothermal drilling rig, where the objective function is evaluated utilizing a simulation-based model whose parameters are derived from empirical maintenance data. Availability, reliability and maintenance inventory are depicted as essential objectives requiring further attention. A simulation model is developed mimicking a drilling rig operations and maintenance where the sub-systems are modelled undergoing imperfect maintenance, corrective (CM) and preventive (PM), with the total cost as the primary performance measurement. Moreover, three maintenance spare inventory policies are considered; classical (retaining stocks for a contractual period), vendor-managed inventory with consignment stock and periodic monitoring order-to-stock (s, S) policy. Optimization results infer that the adoption of (s, S) inventory policy, increased PM interval and reduced reliance of CM actions offers improved availability and total costs reduction.

Keywords: maintenance, vendor-managed, decision support, performance, optimization

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Authors: Nurunnaher Nurunnaher

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This paper examines the impact of women’s participation in microcredit on women’s decision making in the slum areas of Dhaka city, Bangladesh. There is confusion in the literature about whether women’s empowerment is or is not a trickle down impact of poverty alleviation or household well-being, and the studies use more or less similar indicators to measure the status of household and the status of women. Studies very rarely conceptualize and operationalize the term ‘empowerment’ as the word is often used without proper care by policy makers and development practitioners instead of household wellbeing. Currently, decision making in many studies has been used as an indicator of women’s empowerment when assessing the impact of microcredit programs on women. Based on a qualitative and feminist study this paper operationalizes women’s empowerment through the development of a conceptual framework, the identification of assessment criteria and the development of proper indicators that guided the whole study. The testimonies of participants, both men and women, were the basis of exploration of women’s lived experiences, which is the most appropriate method to explore the impact of such programs on women’s empowerment. The study considers empowerment as a process that affects various levels of life and gender relationships. The study found that there is a positive change in women’s position in decision making when women have developed an independent economic base with credit money. However, predominantly, women’s decision making is shared with men with the final decision still in the men’s hands. It can be said that women’s microcredit participation has not significantly challenged the social norms, therefore it is not surprising that women who hand over credit to their husband rarely have any power in intra-household bargaining process. Nevertheless, overall it is evident that women are continuously struggling toward the freedom to have the authority over household, economic and personal matters. It is concluded that while making strategic choices or gaining empowerment requires several steps, women’s participation in decision-making has several implications on their lives and potentially challenges patriarchy.

Keywords: women, gender inequality/equality, decision making, empowerment, microcredit, slums, Dhaka, Bangladesh

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Authors: Danielle Preziuso, Kamila Kazimierczuk, Annalise Stein, Bethel Tarekegne

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Coastal communities experience a variety of distinct socioeconomic, technical, and environmental vulnerabilities, all of which accrue heightened risk with increasingly frequent and severe climate change impacts. Marine renewable energy (MRE) offers a potential solution for mitigating coastal community vulnerabilities, especially water-energy dependencies while delivering promising co-benefits such as increased resilience and more sustainable energy outcomes. This paper explores coastal community vulnerabilities and service dependencies based on the local drivers that create them, with attention to climate change impacts and how they catalyze water-energy unmet needs in these communities. We examine the vulnerabilities through the lens of coastal Tribal communities (i.e., the Makah Tribe, the Kenaitze Tribe, Quinault Nation), as indigenous communities often face compounded impacts of technical, economic, and environmental vulnerabilities due to their underlying socio-demographic inequalities. We offer an environmental and energy justice indicators framework to understand how these vulnerabilities disproportionately manifest and impact the most vulnerable community members, and we subsequently utilize the framework to inform a weighted decision matrix tool that compares the viability of MRE-based alternative energy futures in addressing these vulnerabilities. The framework and complementary tool highlight opportunities for future MRE research and pilot demonstrations that directly respond to the vulnerabilities of coastal communities.

Keywords: coastal communities, decision matrix, energy equity, energy vulnerability, marine energy, service dependency

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Authors: Ali Farzan

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Classification of data objects or patterns is a major part in most of Decision making systems. One of the popular and commonly used classification methods is Decision Tree (DT). It is a hierarchical decision making system by which a binary tree is constructed and starting from root, at each node some of the classes is rejected until reaching the leaf nods. Each leaf node is a representative of one specific class. Finding the splitting criteria in each node for constructing or training the tree is a major problem. Particle Swarm Optimization (PSO) has been adopted as a metaheuristic searching method for finding the best splitting criteria. Result of evaluating the proposed method over benchmark datasets indicates the higher accuracy of the new PSO based decision tree.

Keywords: decision tree, particle swarm optimization, splitting criteria, metaheuristic

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Authors: Purnomo Yustianto, Robin Doss

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As a process of developing a service system, the term ‘service engineering’ evolves in scope and definition. To achieve an integrated understanding of the process, a general framework and an ontology are required. This paper extends a previously built service engineering framework by exploring metamodels for the framework artefacts based on a foundational ontology and a metamodel landscape. The first part of this paper presents a correlation map between the proposed framework with the ontology as a form of evaluation for the conceptual coverage of the framework. The mapping also serves to characterize the artefacts to be produced for each activity in the framework. The second part describes potential metamodels to be used, from the metamodel landscape, as alternative formats of the framework artefacts. The results suggest that the framework sufficiently covers the ontological concepts, both from general service context and software service context. The metamodel exploration enriches the suggested artefact format from the original eighteen formats to thirty metamodel alternatives.

Keywords: artefact, framework, service, metamodel

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Authors: Ilaria Barletta, Mahesh Mani, Björn Johansson

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The concept of sustainability encompasses economic, environmental, social and institutional considerations. Sustainable manufacturing (SM) is, therefore, a multi-faceted concept. It broadly implies the development and implementation of technologies, projects and initiatives that are concerned with the life cycle of products and services, and are able to bring positive impacts to the environment, company stakeholders and profitability. Because of this, achieving SM-related goals requires a holistic, life-cycle-thinking approach from manufacturing companies. Further, such an approach must rely on a logic of continuous improvement and ease of implementation in order to be effective. Currently, there exists in the academic literature no comprehensively structured frameworks that support manufacturing companies in the identification of the issues and the capabilities that can either hinder or foster sustainability. This scarcity of support extends to difficulties in obtaining quantifiable measurements in order to objectively evaluate solutions and programs and identify improvement areas within SM for standards conformance. To bridge this gap, this paper proposes the concept of a framework for assessing and continuously improving the sustainability of manufacturing companies. The framework addresses strategies and projects for SM and operates in three sequential phases: analysis of the issues, design of solutions and continuous improvement. A set of interviews, observations and questionnaires are the research methods to be used for the implementation of the framework. Different decision-support methods - either already-existing or novel ones - can be 'plugged into' each of the phases. These methods can assess anything from business capabilities to process maturity. In particular, the authors are working on the development of a sustainable manufacturing maturity model (SMMM) as decision support within the phase of 'continuous improvement'. The SMMM, inspired by previous maturity models, is made up of four maturity levels stemming from 'non-existing' to 'thriving'. Aggregate findings from the use of the framework should ultimately reveal to managers and CEOs the roadmap for achieving SM goals and identify the maturity of their companies’ processes and capabilities. Two cases from two manufacturing companies in Australia are currently being employed to develop and test the framework. The use of this framework will bring two main benefits: enable visual, intuitive internal sustainability benchmarking and raise awareness of improvement areas that lead companies towards an increasingly developed SM.

Keywords: life cycle management, continuous improvement, maturity model, sustainable manufacturing

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Authors: Kimberley K. Whyte-Jones

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Public participation may improve the quality of environmental management decisions. However, the quality of such a decision is strongly dependent on the quality of the process that leads to it. In order to ensure an effective and efficient process, key features of best practice in participation should be carefully observed; this would also combat disillusionment of citizens, decision-makers and practitioners. The overarching aim of this study is to determine what constitutes an effective public participation process relevant to the Newfoundland and Labrador, Canada context, and to discover whether the public participation process that led to the 2014-2024 Provincial Sustainable Forest Management Strategy (PSFMS) met best practices criteria. The research design uses an exploratory case study strategy to consider a specific participatory process in environmental decision-making in Newfoundland and Labrador. Data collection methods include formal semi-structured interviews and the review of secondary data sources. The results of this study will determine the validity of a specific public participation best practice framework. The findings will be useful for informing citizen participation processes in general and will deduce best practices in public participation in environmental management in the province. The study is, therefore, meaningful for guiding future policies and practices in the management of forest resources in the province of Newfoundland and Labrador, and will help in filling a noticeable gap in research compiling best practices for environmentally related public participation processes.

Keywords: best practices, environmental decision-making, forest management, public participation

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Authors: Sabina Akter, Osiris Valdez Banda, Pentti Kujala, Jani Romanoff

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This paper examines the relationship between on-board environmental factors and customer overall satisfaction in the context of the cruise on-board experience. The on-board environmental factors considered are ambient, layout/design, social, product/service and on-board enjoyment factors. The study presents a data-driven framework and model for the on-board cruise experience. The data are collected from 893 respondents in an application of a self-administered online questionnaire of their cruise experience. This study reveals the cruise passengers’ on-board experience through the customer decision journey based on the publicly available data. Pearson correlation and regression analysis have been applied, and the results show a positive and a significant relationship between the environmental factors and on-board experience. These data help understand the cruise passengers’ on-board experience, which will be used for the ultimate decision-making process in cruise ship design.

Keywords: cruise behavior, customer activities, on-board environmental factors, on-board experience, user or customer satisfaction

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Authors: Mayuri Roy Choudhury, Deepti Paul

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Many states in the United States are aiming for high renewable energy targets by the year 2045. In order to achieve this goal, they must do transition to Electrical Vehicles (EVS). We first applied the Multi-Level perspective framework to describe the inter-disciplinary complexities associated with the transition to EVs. Thereafter we addressed these complexities by creating an inter-disciplinary policy framework that uses data science algorithms to create evidence-based policies in favor of EVs. Our policy framework uses a systems level approach as it addresses transitions to EVs from a technology, economic, business and social perspective. By Systems-Level we mean approaching a problem from a multi-disciplinary perspective. Our systems-level approach could be a beneficial decision-making tool to a diverse number of stakeholders such as engineers, entrepreneurs, researchers, and policymakers. In addition, it will add value to the literature of electrical vehicles, sustainable energy, energy economics, and management as well as efficient policymaking.

Keywords: transition, electrical vehicles, systems-level, algorithms

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Authors: Musarrat Jabeen

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Thoughtful intelligence offers a sustainable position to enhance the influence of decision-makers. Thoughtful Intelligence implies the understanding to realize the impact of one’s thoughts, words and actions on the survival, dignity and development of the individuals, groups and nations. Thoughtful intelligence has received minimal consideration in the area of Decision Support Systems, with an end goal to evaluate the quantity of knowledge and its viability. This pattern degraded the imbibed contribution of thoughtful intelligence required for sustainable decision making. Given the concern, this paper concentrates on the question: How to present a model of Thoughtful Decision Support System (TDSS)? The aim of this paper is to appreciate the concepts of thoughtful intelligence and insinuate a Decision Support System based on thoughtful intelligence. Thoughtful intelligence includes three dynamic competencies: i) Realization about long term impacts of decisions that are made in a specific time and space, ii) A great sense of taking actions, iii) Intense interconnectivity with people and nature and; seven associate competencies, of Righteousness, Purposefulness, Understanding, Contemplation, Sincerity, Mindfulness, and Nurturing. The study utilizes two methods: Focused group discussion to count prevailing Decision Support Systems; 70% results of focus group discussions found six decision support systems and the positive inexistence of thoughtful intelligence among decision support systems regarding sustainable decision making. Delphi focused on defining thoughtful intelligence to model (TDSS). 65% results helped to conceptualize (definition and description) of thoughtful intelligence. TDSS is offered here as an addition in the decision making literature. The clients are top leaders.

Keywords: thoughtful intelligence, sustainable decision making, thoughtful decision support system

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Authors: M. Taheri Tehrani, H. Ajorloo

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In this paper, an intelligent multi-agent framework is developed for each router in which agents have two vital functionalities, traffic shaping and buffer allocation and are positioned in the ports of the routers. With traffic shaping functionality agents shape the traffic forward by dynamic and real time allocation of the rate of generation of tokens in a Token Bucket algorithm and with buffer allocation functionality agents share their buffer capacity between each other based on their need and the conditions of the network. This dynamic and intelligent framework gives this opportunity to some ports to work better under burst and more busy conditions. These agents work intelligently based on Reinforcement Learning (RL) algorithm and will consider effective parameters in their decision process. As RL have limitation considering much parameter in its decision process due to the volume of calculations, we utilize our novel method which invokes Principle Component Analysis (PCA) on the RL and gives a high dimensional ability to this algorithm to consider as much as needed parameters in its decision process. This implementation when is compared to our previous work where traffic shaping was done without any sharing and dynamic allocation of buffer size for each port, the lower packet drop in the whole network specifically in the source routers can be seen. These methods are implemented in our previous proposed intelligent simulation environment to be able to compare better the performance metrics. The results obtained from this simulation environment show an efficient and dynamic utilization of resources in terms of bandwidth and buffer capacities pre allocated to each port.

Keywords: principal component analysis, reinforcement learning, buffer allocation, multi- agent systems

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Authors: H. D. Arora, Anjali Dhiman

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Uncertainty is found everywhere and its understanding is central to decision making. Uncertainty emerges as one has less information than the total information required describing a system and its environment. Uncertainty and information are so closely associated that the information provided by an experiment for example, is equal to the amount of uncertainty removed. It may be pertinent to point out that uncertainty manifests itself in several forms and various kinds of uncertainties may arise from random fluctuations, incomplete information, imprecise perception, vagueness etc. For instance, one encounters uncertainty due to vagueness in communication through natural language. Uncertainty in this sense is represented by fuzziness resulting from imprecision of meaning of a concept expressed by linguistic terms. Fuzzy set concept provides an appropriate mathematical framework for dealing with the vagueness. Both information theory, proposed by Shannon (1948) and fuzzy set theory given by Zadeh (1965) plays an important role in human intelligence and various practical problems such as image segmentation, medical diagnosis etc. Numerous approaches and theories dealing with inaccuracy and uncertainty have been proposed by different researcher. In the present communication, we generalize fuzzy entropy proposed by De Luca and Termini (1972) corresponding to Shannon entropy(1948). Further, some of the basic properties of the proposed measure were examined. We also applied the proposed measure to the real life decision making problem.

Keywords: entropy, fuzzy sets, fuzzy entropy, generalized fuzzy entropy, decision making

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Authors: Babek Erdebilli

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The aim of this study is to develop and describe a new methodology for the Multi-Criteria Decision-Making (MCDM) problem using IFE (Elimination Et Choix Traduisant La Realite (ELECTRE) model. The proposed models enable Decision-Makers (DMs) on the assessment and use Intuitionistic Fuzzy Numbers (IFN). A numerical example is provided to demonstrate and clarify the proposed analysis procedure. Also, an empirical experiment is conducted to validation the effectiveness.

Keywords: multi-criteria decision-making, IFE, DM’s, fuzzy electre model

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Authors: Elke Meex, Elke Knapen, Griet Verbeeck

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The focus of sustainable building is gradually shifting from energy efficiency towards the more global environmental impact of building design during all life-cycle stages. In this context, many tools have been developed that use a LCA-approach to assess the environmental impact on a whole building level. Since the building design strongly influences the final environmental performance and the architect plays a key role in the design process, it is important that these tools are adapted to his work method and support the decision making from the early design phase on. Therefore, a comparative evaluation of the degree of architect-friendliness of some LCA tools on building level is made, based on an evaluation framework specifically developed for the architect’s viewpoint. In order to allow comparison of the results, a reference building has been designed, documented for different design phases and entered in all software tools. The evaluation according to the framework shows that the existing tools are not very architect-friendly. Suggestions for improvement are formulated.

Keywords: architect-friendliness, design supportive value, evaluation framework, tool comparison

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Authors: Alaa Tag-Eldin Mohamed

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The environmental, cultural, social, and technological changes have led higher education institutes to question their traditional roles. Many declarations and frameworks highlight the importance of fulfilling social responsibility of higher education institutes. The study aims at developing a framework of university social responsibility and sustainability (USR&S) with focus on South Valley University (SVU) as a case study of Egyptian Universities. The study used meetings with 12 vice deans of community services and environmental affairs on social responsibility and environmental issues. The proposed framework integrates social responsibility with strategic management through the establishment and maintenance of the vision, mission, values, goals and management systems; elaboration of policies; provision of actions; evaluation of services and development of social collaboration with stakeholders to meet current and future needs of the community and environment. The framework links between different stakeholders internally and externally using communication and reporting tools. The results show that SVU integrates social responsibility and sustainability in its strategic plans. It has policies and actions however fragmented and lack of appropriate structure and budgeting. The proposed framework could be valuable for researchers and decision makers of the Egyptian Universities. The study proposed recommendations and highlighted building on the results and conducting future research.

Keywords: corporate social responsibility (CSR), south valley university, sustainable university, university social responsibility and sustainability (USR&S)

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Authors: Seun Mayowa Sunday

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Loan prediction is one of the most significant and recognised fields of research in the banking, insurance, and the financial security industries. Some prediction systems on the market include the construction of static software. However, due to the fact that static software only operates with strictly regulated rules, they cannot aid customers beyond these limitations. Application of many machine learning (ML) techniques are required for loan prediction. Four separate machine learning models, random forest (RF), decision tree (DT), k-nearest neighbour (KNN), and logistic regression, are used to create the loan prediction model. Using the anaconda navigator and the required machine learning (ML) libraries, models are created and evaluated using the appropriate measuring metrics. From the finding, the random forest performs with the highest accuracy of 80.17% which was later implemented into the Django framework. For real-time testing, the web application is deployed on the Alibabacloud which is among the top 4 biggest cloud computing provider. Hence, to the best of our knowledge, this research will serve as the first academic paper which combines the model development and the Django framework, with the deployment into the Alibaba cloud computing application.

Keywords: k-nearest neighbor, random forest, logistic regression, decision tree, django, cloud computing, alibaba cloud

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Authors: Rolla Monib, Chris I. Goodier, Alistair Gibbs

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The aim of this paper is to investigate the key drivers in planning the construction phase for infrastructure projects to reduce project delays. To achieve this aim, the research conducted three case studies using semi-structured and unstructured interviews (n=36). The results conclude that a lack of modularisation awareness is among the key factors attributed to project delays. The current emotive and ill-informed approach to decision-making, coupled with the lack of knowledge regarding appropriate construction method selection, prevents the potential benefits of modularisation being fully realised. To assist with decision-making for the best construction method, the research presents project management tools to help decision makers to choose the most appropriate construction approach through optimising the use of modularisation in EC. A decision-making checklist and diagram are presented in this paper. These checklist tools and diagrams assist the project team in determining the best construction method, taking into consideration the module type.

Keywords: infrastructure, modularization, decision support, decision-making

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Authors: Warda Ajaz

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This study uses the ‘Community Capitals Framework’ (CCF) to develop a community resilience index that can serve as a useful tool for measuring resilience of communities in diverse contexts and backgrounds. CCF is an important analytical tool to assess holistic community change. This framework identifies seven major types of community capitals: natural, cultural, human, social, political, financial and built, and claims that the communities that have been successful in supporting healthy sustainable community and economic development have paid attention to all these capitals. The framework, therefore, proposes to study the community development through identification of assets in these major capitals (stock), investment in these capitals (flow), and the interaction between these capitals. Capital based approaches have been extensively used to assess community resilience, especially in the context of natural disasters and extreme events. Therefore, this study identifies key indicators for estimating each of the seven capitals through an extensive literature review and then develops an index to calculate a community resilience score. The CCF-based community resilience index presents an innovative way of operationalizing the concept of community resilience and will contribute toward decision-relevant research regarding adaptation and mitigation of community vulnerabilities to climate change-induced, as well as other adverse events.

Keywords: adverse events, community capitals, community resilience, climate change, economic development, sustainability

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Authors: Indre Brazauskaite, Vilte Auruskeviciene

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The paper explores the Stage-Gate framework application for innovation maturity among small and medium-sized enterprises (SMEs). Innovation management becomes an essential business survival process for all sizes of organizations that can be evaluated and audited systemically. This research systemically defines and assesses the innovation process from the perspective of the company’s top management. Empirical research explores attitudes and existing practices of innovation management in SMEs in Baltic countries. It structurally investigates the current innovation management practices, level of standardization, and potential challenges in the area. Findings allow to structure of existing practices based on an institutionalized model and contribute to a more advanced understanding of the innovation process among SMEs. Practically, findings contribute to advanced decision-making and business planning in the process.

Keywords: innovation measure, innovation process, SMEs, stage-gate framework

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Authors: Barbora Chmelíková

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Making sound financial decisions is an essential skill which can have an impact on life of each consumer of financial products. The aim of this paper is to examine decision-making concerning financial matters and personal finance. The selected target group was university students majoring in finance related fields. The study was conducted in the Czech Republic at Masaryk University in 2015. In order to analyze financial decision-making questions related to basic finance decisions were developed to address the research objective. The results of the study suggest gaps in detecting best solutions to given financial decision-making questions among finance students. The analysis results indicate relation between financial decision-making and own experience with holding and using concrete financial products.

Keywords: financial decision-making, financial literacy, personal finance, university students

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Authors: Y. Kourd, D. Lefebvre, N. Guersi

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This paper presents a new idea for fault detection and isolation (FDI) technique which is applied to industrial system. This technique is based on Neural Networks fault-free and Faulty behaviors Models (NNFM's). NNFM's are used for residual generation, while decision tree architecture is used for residual evaluation. The decision tree is realized with data collected from the NNFM’s outputs and is used to isolate detectable faults depending on computed threshold. Each part of the tree corresponds to specific residual. With the decision tree, it becomes possible to take the appropriate decision regarding the actual process behavior by evaluating few numbers of residuals. In comparison to usual systematic evaluation of all residuals, the proposed technique requires less computational effort and can be used for on line diagnosis. An application example is presented to illustrate and confirm the effectiveness and the accuracy of the proposed approach.

Keywords: neural networks, decision trees, diagnosis, behaviors

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Authors: Meshari Aljohani, Stephan Olariu, Ravi Mukkamala

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Data is essential for enhancing the quality of life. Its value creates chances for users to profit from data sales and purchases. Users in data marketplaces, however, must share and trade data in a secure and trusted environment while maintaining their privacy. The first main contribution of this paper is to identify enabling technologies and challenges facing the development of decentralized data marketplaces. The second main contribution is to propose a decentralized data marketplace framework based on blockchain technology. The proposed framework enables sellers and buyers to transact with more confidence. Using a security deposit, the system implements a unique approach for enforcing honesty in data exchange among anonymous individuals. Before the transaction is considered complete, the system has a time frame. As a result, users can submit disputes to the arbitrators which will review them and respond with their decision. Use cases are presented to demonstrate how these technologies help data marketplaces handle issues and challenges.

Keywords: blockchain, data, data marketplace, smart contract, reputation system

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Authors: Bundit Pungnirund

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This research aimed to study the relationship between marketing mix attitudes, motivation of buying decision and tendency of consumer decision making in buying the condominiums in Thailand. This study employed by survey and quantitative research. The questionnaire was used to collect the data from 400 sampled of customers who interested in buying condominium in Bangkok. The descriptive statistics and Pearson’s correlation coefficient analysis were used to analyze data. The research found that marketing mixed factors in terms of product and price were related to buying decision making tendency in terms of price and room size. Marketing mixed factors in terms of price, place and promotion were related to buying decision making tendency in term of word of mouth. Consumers’ buying motivation in terms of social acceptance, self-esteemed and self-actualization were related to buying decision making tendency in term of room size. In addition, motivation in self-esteemed was related to buying decision making tendency within a year.

Keywords: condominium, marketing mix, motivation, tendency of consumer decision making

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Authors: Shahram Payandeh

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This paper presents an overview of a model which can be used as a part of a decision support system when fusing information from multiple sensing environment. Data fusion has been widely studied in the past few decades and numerous frameworks have been proposed to facilitate decision making process under uncertainties. Multi-sensor data fusion technology plays an increasingly significant role during people tracking and activity recognition. This paper presents an overview of a quantum model as a part of a decision-making process in the context of multi-sensor data fusion. The paper presents basic definitions and relationships associating the decision-making process and quantum model formulation in the presence of uncertainties.

Keywords: quantum model, sensor space, sensor network, decision support

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Authors: Tulio Sulbaran, Sandeep Langar

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Architects are an integral part of the construction industry and are continuously incorporating decisions that influence projects during their life cycle. These decisions aim at selecting best alternative from the ones available. Unfortunately, this decision making process is mainly unexplored in the construction industry. No instrument to measure construction decision, based on knowledgebase of decision-makers, has existed. Additionally, limited literature is available on the topic. Recently, an instrument to gain an understanding of the construction decision-making process was developed by Dr. Tulio Sulbaran from the University of Texas, San Antonio. The instrument’s name is 'Construction Decision Making Inventory (CDMI)'. The CDMI is an innovative idea to measure the 'What? When? How? Moreover, Who?' of the construction decision-making process. As an innovative idea, its statistical validity (accuracy of the assessment) is yet to be assessed. Thus, the purpose of this paper is to describe the results of a case study with architects in the south-east of the United States aimed to determine the CDMI validity. The results of the case study are important because they assess the validity of the tool. Furthermore, as the architects evaluated each question within the measurements, this study is also guiding the enhancement of the CDMI.

Keywords: decision, support, inventory, architect

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Authors: K. Marciniak, M. Owoc

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Managers as decision-makers present in different sectors should be supported in efficient and more and more sophisticated way. There are huge number of software tools developed for such users starting from simple registering data from business area – typical for operational level of management – up to intelligent techniques with delivering knowledge - for tactical and strategic levels of management. There is a big challenge for software developers to create intelligent management dashboards allowing to support different decisions. In more advanced solutions there is even an option for selection of intelligent techniques useful for managers in particular decision-making phase in order to deliver valid knowledge-base. Such a tool (called Intelligent Dashboard for SME Managers–InKOM) is prepared in the Business Intelligent framework of Teta products. The aim of the paper is to present solutions assumed for InKOM concerning on management of stored knowledge bases offering for business managers. The paper is managed as follows. After short introduction concerning research context the discussed supporting managers via information systems the InKOM platform is presented. In the crucial part of paper a process of knowledge transformation and validation is demonstrated. We will focus on potential and real ways of knowledge-bases acquiring, storing and validation. It allows for formulation conclusions interesting from knowledge engineering point of view.

Keywords: business intelligence, decision support systems, knowledge management, knowledge transformation, knowledge validation, managerial systems

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Authors: Fusun Akdag

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Today, as business becomes increasingly global, managers/leaders of multinational companies or local companies work with employees or customers from a variety of cultural backgrounds. To do this effectively, they need to develop cultural competence. Therefore, cultural intelligence (CQ) becomes a vitally important aptitude and skill, especially for leaders. The organizational success or failure depends upon the way, the kind of leadership which has been provided to its members. The culture we are born into deeply effects our values, beliefs, and behavior. Cultural intelligence (CQ) focuses on how well individuals can relate and work across cultures. CQ helps minimize conflict and maximize performance of a diverse workforce. The term 'decision,' refers to a commitment to a course of action that is intended to serve the interests and values of particular people. One dimension of culture that has received attention is individualism-collectivism or, independence-interdependence. These dimensions are associated with different conceptualizations of the 'self.' Individualistic cultures tend to value personal goal pursuit as opposed to pursuit of others’ goals. Collectivistic cultures, by contrast, view the 'self' as part of a whole. Each person is expected to work with his or her in-group toward goals, generally pursue group harmony. These differences underlie cross-cultural variation in decision-making, such as the decision modes people use, their preferences, negotiation styles, creativity, and more. The aim of this study is determining the effect of CQ on decision making styles of male and female managers in Turkey, an emergent economy framework. The survey is distributed to gather data from managers at various companies. The questionnaire consists of three parts: demographics, The Cultural Intelligence Scale (CQS) to measure the four dimensions of cultural intelligence and General Decision Making Style (GMDS) Inventory to measure the five subscales of decision making. The results will indicate the Turkish managers’ score at metacognitive, cognitive, motivational and behavioral aspects of cultural intelligence and to what extent these scores affect their rational, avoidant, dependent, intuitive and spontaneous decision making styles since business leaders make dozens of decisions every day that influence the success of the company and also having an impact on employees, customers, shareholders and the market.

Keywords: cultural intelligence, decision making, gender differences, management styles,

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Authors: Leah Wright, Trevor Townsend

Abstract:

Mode choice models are crucial instruments in the analysis of travel behaviour. These models show the relationship between an individual’s choice of transportation mode for a given O-D pair and the individual’s socioeconomic characteristics such as household size and income level, age and/or gender, and the features of the transportation system. The most popular functional forms of these models are based on Utility-Based Choice Theory, which addresses the uncertainty in the decision-making process with the use of an error term. However, with the development of artificial intelligence, many researchers have started to take a different approach to travel demand modelling. In recent times, researchers have looked at using neural networks, fuzzy logic and rough set theory to develop improved mode choice formulas. The concept of cloud theory has recently been introduced to model decision-making under uncertainty. Unlike the previously mentioned theories, cloud theory recognises a relationship between randomness and fuzziness, two of the most common types of uncertainty. This research aims to investigate the use of cloud theory in mode choice models. This paper highlights the conceptual framework of the mode choice model using cloud theory. Merging decision-making under uncertainty and mode choice models is state of the art. The cloud theory model is expected to address the issues and concerns with the nested logit and improve the design of mode choice models and their use in travel demand.

Keywords: Cloud theory, decision-making, mode choice models, travel behaviour, uncertainty

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Authors: Karrar Raoof Kareem Kamoona, Enas Fathi Taher AlHares, Zeynep Isik

Abstract:

The various disciplines in the construction industry and the co-existence of the people in the various disciplines are what builds well-developed, closely-knit interpersonal skills at various hierarchical levels thus leading to a varied way of leadership. The varied decision making aspects during the lifecycle of a project include: autocratic, participatory and last but not least, free-rein. We can classify some of the decision makers in the construction industry in a hierarchical manner as follows: project executive, project manager, superintendent, office engineer and finally the field engineer. This survey looked at how decisions are made during the construction period by the key stakeholders in the project. From the paper it is evident that the three decision making aspects can be used at different times or at times together in order to bring out the best leadership decision. A blend of different leadership styles should be used to enhance the success rate during the project lifecycle.

Keywords: leadership style, construction, decision-making, built environment

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