Search results for: model for making decisions in emergencies

Authors: Freddy Munzhelele

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Setting: the empirical research has shown that the life cycle theory has an impact on the firms’ financing decisions, particularly the dividend pay-outs. Accordingly, the life cycle theory posits that as a firm matures, it gets to a level and capacity where it distributes more cash as dividends. On the other hand, the young firms prioritise investment opportunities sets and their financing; thus, they pay little or no dividends. The research on firms’ financing decisions also demonstrated, among others, the adoption of trade-off and pecking order theories on the dynamics of firms capital structure. The trade-off theory talks to firms holding a favourable position regarding debt structures particularly as to the cost and benefits thereof; and pecking order is concerned with firms preferring a hierarchical order as to choosing financing sources. The case of life cycle hypothesis explaining the financial managers’ decisions as regards the firms’ capital structure dynamics appears to be an interesting link, yet this link has been neglected in corporate finance research. If this link is to be explored as an empirical research, the financial decision-making alternatives will be enhanced immensely, since no conclusive evidence has been found yet as to the dynamics of capital structure. Aim: the aim of this study is to examine the impact of life cycle theory on the capital structure dynamics trade-off and pecking order theories of firms listed in retail, industrial and mining sectors of the JSE. These sectors are among the key contributors to the GDP in the South African economy. Design and methodology: following the postpositivist research paradigm, the study is quantitative in nature and utilises secondary data obtainable from the financial statements of sampled firm for the period 2010 – 2022. The firms’ financial statements will be extracted from the IRESS database. Since the data will be in panel form, a combination of the static and dynamic panel data estimators will used to analyse data. The overall data analyses will be done using STATA program. Value add: this study directly investigates the link between the life cycle theory and the dynamics of capital structure decisions, particularly the trade-off and pecking order theories.

Keywords: life cycle theory, trade-off theory, pecking order theory, capital structure, JSE listed firms

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Authors: Zhen Wu, David Lupien St-Pierre, Georges Abdul-Nour

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In decision making under strict uncertainty, decision makers have to choose a decision without any information about the states of nature. The classic criteria of Laplace, Wald, Savage, Hurwicz and Starr are introduced and compared in a case study of sewer network planning. Furthermore, results from different criteria are discussed and analyzed. Moreover, this paper discusses the idea that decision making under strict uncertainty (DMUSU) can be viewed as a two-player game and thus be solved by a solution concept in game theory: Nash equilibrium.

Keywords: decision criteria, decision making, sewer network planning, decision making, strict uncertainty

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Authors: Gamze Safak, Umut Arslanoglu

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Cultural and tourism conservation and development zones and tourism centers are the boundaries declared for the purpose of protecting, using, and evaluating the sectoral development and planned development in areas where historical and cultural values are heavily involved and/or where tourism potential is high. The most rapidly changing regions in Turkey are tourism areas, especially the coastal areas. Planning these regions is not about only an economic gain but also a natural and physical environment and refers to a complex process. If the tourism sector is not well controlled, excessive use of natural resources and wrong location choices may cause damage to natural areas, historical values, and socio-cultural structure. Since the strategic decisions taken in the environmental order and zoning plans, which are the means of guiding the physical environment of the Ministry of Culture and Tourism, which have the authority to make plans in tourism centers, are transformed into plan decisions that find the spatial expression, comprehensive evaluation of all kinds of data, following the historical development and based on the correct and current data is required. In addition, the authority has a number of competences in tourism promotion as well as the authority to plan, leading to the necessity of taking part in the applications requiring complex analysis such as the management and integration of the country's economic, political, social and cultural resources. For this purpose, Tourism Inventory System (TES) project, which consists of a series of subsystems, has been developed in order to solve complex planning and method problems in the management of site-related information. The scope of the project is based on the integration of numerical and verbal data in the regions within the jurisdiction of the authority, and the monitoring of the historical development of urban planning studies, making the spatial data of the institution easily accessible, shared, questionable and traceable in international standards. A dynamic and continuous system design has been put into practice by utilizing the advantage of the use of Geographical Information Systems in the planning process to play a role in making the right decisions, revealing the tools of social, economic, cultural development, and preservation of natural and cultural values. This paper, which is prepared by the project team members in TES (Tourism Inventory System), will present a study regarding the applicability of GIS in cultural and natural heritage conservation.

Keywords: cultural conservation, GIS, geographic information system, tourism inventory system, urban planning

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Authors: Jolly Puri, Shiv Prasad Yadav

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Multi-component data envelopment analysis (MC-DEA) is a popular technique for measuring aggregate performance of the decision making units (DMUs) along with their components. However, the conventional MC-DEA is limited to crisp input and output data which may not always be available in exact form. In real life problems, data may be imprecise or fuzzy. Therefore, in this paper, we propose (i) a fuzzy MC-DEA (FMC-DEA) model in which shared and undesirable fuzzy resources are incorporated, (ii) the proposed FMC-DEA model is transformed into a pair of crisp models using cut approach, (iii) fuzzy aggregate performance of a DMU and fuzzy efficiencies of components are defined to be fuzzy numbers, and (iv) a numerical example is illustrated to validate the proposed approach.

Keywords: multi-component DEA, fuzzy multi-component DEA, fuzzy resources, decision making units (DMUs)

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Authors: Adel Pasztor

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International doctoral mobility is a largely under-researched component of academic mobility and migration. This is in stark contrast to the case of student mobility where much research has been undertaken on Erasmus students; or the growing research on academic staff mobility which can be viewed as a key part of highly skilled migration. The aim of this paper is to remedy the situation by specifically focusing on international doctoral students studying at elite higher education institutions in the United Kingdom. In doing so, in-depth qualitative interviews with doctoral students and recent graduates were carried out in order to identify the signifiers of an internationally mobile doctoral student and unpack the decision-making processes leading onto the choice of higher education institution abroad. Overall, a diverse range of degree subjects from within the humanities and the social sciences were covered with a relatively large spread of nationalities which include the following countries: Italy, Germany, Hungary, Latvia, Bulgaria, Turkey, Lebanon, Israel, Australia, USA, China, and Chile. The interview questions were designed to probe the motivations, choices, educational trajectories and career plans of international doctoral students relative to their social class background, gender, nationality or funding. It was clear from the interviews that there were two main types of international doctoral students: those who ‘did not think anything else was ever a serious possibility’, contrasted with the other, more opportune type, to whom ‘it happened to be a PhD’. There were marked differences between the two types since initial access to university, mainly because educational decisions such as the doctorate do not happen in a vacuum, rather are built on the individual’s higher education aspirations and previous educational choices. The results were in line with existing literature suggesting that those with higher educated parents and from schools strongly supporting the choice process fared better as they were able to make well informed, well thought through as well as strategic decisions for their future involving the very best universities within the national boundaries. Being ‘at the right place’ often meant access to prestigious doctoral scholarships thus, the route of the PhD has been chosen even if it did not necessarily enhance career opportunities. At the same time, the initial higher education choices of those with limited capital were played out locally, although they did aim for the best universities within their geographically constrained landscape of choice. Here, the majority of students referred to some ‘turning points’ in their lives which lead them towards considering international doctoral opportunities but essentially their proactive, do-it-yourself attitude was behind the life-changing educational opportunities.

Keywords: choice, doctoral students, international mobility, PhD, UK

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Authors: Buket Metin

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Buildings cause a variety of loads on the environment due to activities performed at each stage of the building life cycle. Construction is the first stage that affects both the natural and built environments at different steps of the process, which can be defined as transportation of materials within the construction site, formation and preparation of materials on-site and the application of materials to realize the building subsystems. All of these steps require the use of technology, which varies based on the facilities that contractors and subcontractors have. Hence, environmental consequences of the construction process should be tackled by focusing on construction technology options used in every step of the process. This paper presents an environmental decision-making model for assessing on-site performances of subcontractors based on the construction technology options which they can supply. First, construction technologies, which constitute information, tools and methods, are classified. Then, environmental performance criteria are set forth related to resource consumption, ecosystem quality, and human health issues. Finally, the model is developed based on the relationships between the construction technology components and the environmental performance criteria. The Fuzzy Analytical Hierarchy Process (FAHP) method is used for weighting the environmental performance criteria according to environmental priorities of decision-maker(s), while the Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method is used for ranking on-site environmental performances of subcontractors using quantitative data related to the construction technology components. Thus, the model aims to provide an insight to decision-maker(s) about the environmental consequences of the construction process and to provide an opportunity to improve the overall environmental performance of construction sites.

Keywords: construction process, construction technology, decision making, environmental performance, subcontractor

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Authors: K. M. Anusha, R. Krishnaveni

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Crossing a decade of the 21st century, the paradigm of human resources can be seen evolving with the strategic gene induced into it. There seems to be a radical shift descending as the corporate sector calls on its HR team to become strategic rather than administrative. This transferal eventually requires the metrics employed by these HR teams not to be just operationally reactive but to be aligned to an evidence-based strategic thinking. Realizing the growing need for a prescriptive metric model for effective HR analytics, this study has designed a conceptual framework for a basic metric model that can assist IT-HRM professionals to transition to a practice of evidence-based decision-making to enhance organizational performance.

Keywords: metric model, evidence based HR, HR analytics, strategic HR practices, IT sector

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Authors: Saniye Çeşmecioğlu

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The importance of project sustainability and success has become increasingly significant due to the proliferation of external environmental factors that have decreased project resistance in contemporary times. The primary approach to forestall the failure of projects is to ensure their long-term viability through the strategic selection of projects as creating judicious project selection framework within the organization. Decision-makers require precise decision contexts (models) that conform to the company's business objectives and sustainability expectations during the project selection process. The establishment of a rational model for project selection enables organizations to create a distinctive and objective framework for the selection process. Additionally, for the optimal implementation of this decision-making model, it is crucial to establish a Project Management Office (PMO) team and Project Steering Committee within the organizational structure to oversee the framework. These teams enable updating project selection criteria and weights in response to changing conditions, ensuring alignment with the company's business goals, and facilitating the selection of potentially viable projects. This paper presents a multi-criteria decision model for selecting project sustainability and project success criteria that ensures timely project completion and retention. The model was developed using MACBETH (Measuring Attractiveness by a Categorical Based Evaluation Technique) and was based on broadcaster companies’ expectations. The ultimate results of this study provide a model that endorses the process of selecting the appropriate project objectively by utilizing project selection and sustainability criteria along with their respective weights for organizations. Additionally, the study offers suggestions that may ascertain helpful in future endeavors.

Keywords: project portfolio management, project selection, multi-criteria decision making, project sustainability and success criteria, MACBETH

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Authors: Oscar Vega Camacho, Andrea Vargas, Ellery Ariza

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This paper presents the application of finite dynamic programming, specifically the "Markov Chain" model, as part of the decision making process of a company in the cosmetics sector located in the vicinity of Bogota DC. The objective of this process was to decide whether the company should completely reconstruct its waste water treatment plant or instead optimize the plant through the addition of equipment. The goal of both of these options was to make the required improvements in order to comply with parameters established by national legislation regarding the treatment of waste before it is released into the environment. This technique will allow the company to select the best option and implement a solution for the processing of waste to minimize environmental damage and the acquisition and implementation costs.

Keywords: decision making, markov chain, optimization, waste water

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Authors: Radmila Hajkova, Jiri Palecek, Hana Malachova, Alena Oulehlova

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Ensuring of continuity of business is the basic strategy of every company. Continuity of organization activities includes comprehensive procedures that help in solving unexpected situations of natural and anthropogenic character (for example flood, blaze, economic situations). Planning of continuity operations is a process that helps identify critical processes and implement plans for the security and recovery of key processes. The aim of this article demonstrates application of system approach to managing business continuity called business continuity management systems in military issues. This article describes the life cycle of business continuity management which is based on the established cycle PDCA (plan-do-check-act). After this is carried out by activities which are making by the University of Defence during activation of forces and means of the Integrated rescue system in case of emergencies - accidents at a nuclear power plant in Czech republic. Activities of various stages of deployment earmarked forces and resources are managed and evaluated by using MCMS application (military continuity management system).

Keywords: business continuity management system, emergency management, military, nuclear safety

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Authors: Anita Lazurko, Laszlo Pinter, Jeremy Richardson

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Uncertain climate projections, multiple possible development futures, and a financing gap create challenges for water infrastructure decision making. In contrast to conventional predict-plan-act methods, an emerging decision paradigm that enables social-ecological resilience supports decisions that are appropriate for uncertainty and leverage social, ecological, and economic multifunctionality. Concurrently, water infrastructure project finance plays a powerful role in sustainable infrastructure development but remains disconnected from discourse in socio-ecological resilience. At the time of research, a project to transfer water from Lesotho to Botswana through South Africa in the Orange-Senqu River Basin was at the pre-feasibility stage. This case was analysed through documents and interviews to investigate how uncertainty and multifunctionality are conceptualised and considered in decisions for the resilience of water infrastructure and to explore bridging concepts that might allow project finance to better enable socio-ecological resilience. Interviewees conceptualised uncertainty as risk, ambiguity and ignorance, and multifunctionality as politically-motivated shared benefits. Numerous efforts to adopt emerging decision methods that consider these terms were in use but required compromises to accommodate the persistent, conventional decision paradigm, though a range of future opportunities was identified. Bridging these findings to finance revealed opportunities to consider a more comprehensive scope of risk, to leverage risk mitigation measures, to diffuse risks and benefits over space, time and to diverse actor groups, and to clarify roles to achieve multiple objectives for resilience. In addition to insights into how multiple decision paradigms interact in real-world decision contexts, the research highlights untapped potential at the juncture between socio-ecological resilience and project finance.

Keywords: socio-ecological resilience, finance, multifunctionality, uncertainty

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Authors: Sabrina S. W. Chan, Emily Schwartzman, Nicholas O. Rule

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Past literature showed mixed findings on how smiling affects a person’s chance of getting hired. On one hand, smiling suggests enthusiasm, cooperativeness, and enthusiasm, which can elicit positive impressions. On the other hand, smiling can suggest weaker professionalism or a filler to hide nervousness, which can lower a candidate’s perceived competence. Emotion expressions can also be perceived differently depending on the person’s gender and can activate certain gender stereotypes. Women especially face a double bind with respect to hiring decisions and smiling. Because women are socially expected to smile more, those who do not smile will be considered stereotype incongruent. This becomes a noisy signal to employers and may lower their chance of being hired. However, women’s smiling as a formality may also be an obstacle. They are more likely to put on fake smiles; but if they do, they are also likely to be perceived as inauthentic and over-expressive. This paper sought to investigate how smiling affects hiring decisions, and whether this relationship is moderated by gender. In Study 1, participants were shown a series of smiling and emotionally neutral face images, incorporated into fabricated LinkedIn profiles. Participants were asked to rate how hireable they thought that candidate was. Results showed that participants rated smiling candidates as more hireable than nonsmiling candidates, and that there was no difference in gender. Moreover, individuals who did not study business were more biased in their perceptions than those who did. Since results showed a trending favoritism over female targets, in suspect of desirability bias, a second study was conducted to collect implicit measures behind the decision-making process. In Study 2, a mouse-tracking design was adopted to explore whether participants’ implicit attitudes were different from their explicit responses on hiring. Participants asked to respond whether they would offer an interview to a candidate. Findings from Study 1 was replicated in that smiling candidates received more offers than neutral-faced candidates. Results also showed that female candidates received significantly more offers than male candidates but was associated with higher attractiveness ratings. There were no significant findings in reaction time or change of decisions. However, stronger hesitation was detected for responses made towards neutral targets when participants perceived the given position as masculine, implying a conscious attempt of making situational judgments (e.g., considering candidate’s personality and job fit) to override automatic processing (evaluations based on attractiveness). Future studies would look at how these findings differ for positions which are stereotypically masculine (e.g., surgeons) and stereotypically feminine (e.g., kindergarten teachers). Current findings have strong implications for developing bias-free hiring policies in workplace, especially for organizations who maintain online/hybrid working arrangements in the post-pandemic era. This also bridges the literature gap between face perception and gender discrimination, highlighting how engendered facial cues can affect individual’s career development and organization’s success in diversity and inclusion.

Keywords: engendered facial cues, face perception, gender stereotypes, hiring decisions, smiling, workplace discrimination

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Authors: Ivana Bulog, Ana Rimac Smiljanić, Sandra Pepur

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The financial fragility of households has received increased attention following the recent health crisis, which has created uncertainty and caused increased levels of stress and consequently impaired individual and family well-being. Job losses and/or reduced wages and insecurity increased the number of people that were unable to meet unexpected expenses, which, in many cases, led to increased household debt levels. This presents a threat to the stability of the financial system and the whole economy; therefore, reducing financial fragility and improving financial literacy present challenges for academicians, practitioners, and policymakers. Concerning financial fragility, significant research attention has been devoted to financial knowledge and financial literacy. However, apart from specific knowledge, personal characteristics are of great importance in making financial decisions in the household. Self-efficacy is one of the personal non-cognitive attributes that is a valuable framework for understanding how household financial decisions are made. Thus, this research proposes that individual levels of financial literacy and self-efficacy are related to the indebtedness and financial instability of the household. The primary data were collected using a structured, self-administered online questionnaire, and a snowball sampling method was applied to reach the participants. Preliminary results confirm our assumptions on the influence of financial literacy and self-efficacy on household financial stability.

Keywords: financial literacy, self-efficacy, household financial fragility, well-being

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Authors: A. M. John-Otumu, M. M. Rahman, M. C. Onuoha, E. P. Ojonugwa

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A Convolutional Neural Network (CNN) model for predicting Lassa fever was built using Python 3.8.0 programming language, alongside Keras 2.2.4 and TensorFlow 2.6.1 libraries as the development environment in order to reduce the current high risk of Lassa fever in West Africa, particularly in Nigeria. The study was prompted by some major flaws in existing conventional laboratory equipment for diagnosing Lassa fever (RT-PCR), as well as flaws in AI-based techniques that have been used for probing and prognosis of Lassa fever based on literature. There were 15,679 blood smear microscopic image datasets collected in total. The proposed model was trained on 70% of the dataset and tested on 30% of the microscopic images in avoid overfitting. A 3x3x3 convolution filter was also used in the proposed system to extract features from microscopic images. The proposed CNN-based model had a recall value of 96%, a precision value of 93%, an F1 score of 95%, and an accuracy of 94% in predicting and accurately classifying the images into clean or infected samples. Based on empirical evidence from the results of the literature consulted, the proposed model outperformed other existing AI-based techniques evaluated. If properly deployed, the model will assist physicians, medical laboratory scientists, and patients in making accurate diagnoses for Lassa fever cases, allowing the mortality rate due to the Lassa fever virus to be reduced through sound decision-making.

Keywords: artificial intelligence, ANN, blood smear, CNN, deep learning, Lassa fever

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Authors: Krishna Kisi, Tulio Sulbaran

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This literature review offers valuable insights into integrating cognitive science and neuroimaging with project management practices, presenting a crucial resource for leadership within the construction industry. This paper highlights the significant benefits of applying interdisciplinary approaches to enhance project management effectiveness and project outcomes by exploring the intricate connections between cognitive processes, decision-making, and project management. Key findings emphasize the critical role of cognitive status in determining the performance and project outcomes of construction workers, underlining the necessity for leadership to prioritize cognitive well-being and mental health as central components of project management strategies. The review identifies a gap in current practices, particularly the need for more objective tools for assessing cognitive status within the construction sector, and proposes the adoption of neuroimaging technologies to bridge this gap. The study highlights how integrating cognitive psychology and neuroscience clarifies decision-making processes, aiding leaders in comprehending the mental constraints and biases that influence project decisions. By integrating neuroscientific insights with traditional management practices, leaders can enhance their strategies for training, team dynamics, and risk assessment, ultimately leading to more informed, efficient, and productive construction project management. This comprehensive literature review underscores the importance of adopting an interdisciplinary approach to leadership and management within high-risk industries. It provides a foundation for construction project managers to leverage cognitive science and neuroimaging advancements to improve efficiency, productivity, and decision-making in construction projects' complex and dynamic environments.

Keywords: decision making, literature review, neuroimaging, project management

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Authors: Zichun Chu

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The issue of tribal poverty has always attracted attentions. Due to social and economic difficulties, the indigenous people's personal development and tribal development have been greatly restricted. Past studies have pointed out that poverty may come from a lack of education. The United Nations Sustainable Development Goals (SDGs) also stated that if we are to solve the poverty problem, providing education widely is an important key. According to the theory of intellectual capital adaptation, “being capable” and “willing to do” are the keys of development. Therefore, we can say that the "ability" and "will" of tribal residents for their tribal development is the core concern of the tribal development. This research was designed to investigate the career choice development model of indigenous tribe people by investigating the current status of human capital, social capital, and cultural capital of tribal residents. This study collected 327 questionnaires (70% of total households) from Truku tribe to answer the research question: Did education help them for job choosing decisions from the aspects of human capital, social capital, and cultural capital in tribal status. This project highlighted the ‘single tribal research approach’ to gain an in-depth understanding of the human capital formed under the unique culture of the tribe (Truku tribe). The results show that the education level of most research participants was high school, very few high school graduates chose to further their education to college level; due to the lack of education of their parents, the social capital was limited to support them for jobs choice, most of them work for labor and service industries; however, their culture capital was comparably rich for works, the sharing culture of Taiwanese indigenous people made their work status stable. The results suggested that we should emphasize more on the development of vocational education based on the tribe’s location and resources. The self-advocacy of indigenous people should be developed so that they would gain more power on making career decisions. This research project is part of a pilot project called “INDIGENOUS PEOPLES, POVERTY, AND DEVELOPMENT,” sponsored by the National Science and Technology Council of Taiwan. If this paper were accepted to present in the 2023 ICIP, it would be lovely if a panel is formed for me and other co-researchers (Chuanju Cheng, Chih-Yuan Weng, and YiXuan Chen), for the audience will be able to get a full picture of this pilot project.

Keywords: career choices, career model, indegenous career development, indigenous education, tribe

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Authors: Yidnekachew Daget, Hong Zhang

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The decision-making process in order to select the suitable housing system for application in housing construction has been a challenge for many developing countries. This study evaluates the decision process to identify the suitable housing systems for adoption in Addis Ababa. Ten industrialized housing systems were considered as alternatives for comparison. These systems have been used in a housing development in different parts of the world. A relevant literature review and contextual analysis were conducted. An analytical hierarchy process and an Expert Choice Comparion platform were employed as a research technique and tool to evaluate the professionals’ level of preferences with regard to the housing systems. The findings revealed the priority rank and characteristics of the suitable housing systems to be adapted for application in housing development. The decision criteria and the analytical process used in this study can help the decision-makers and the housing developers in developing countries make effective evaluations and decisions.

Keywords: analytical hierarchy process, decision-making, expert choice comparion, industrialized housing systems

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Authors: Supunmali Ahangama, Danny Chiang Choon Poo

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Health analytics (HA) is used in healthcare systems for effective decision-making, management, and planning of healthcare and related activities. However, user resistance, the unique position of medical data content, and structure (including heterogeneous and unstructured data) and impromptu HA projects have held up the progress in HA applications. Notably, the accuracy of outcomes depends on the skills and the domain knowledge of the data analyst working on the healthcare data. The success of HA depends on having a sound process model, effective project management and availability of supporting tools. Thus, to overcome these challenges through an effective process model, we propose an HA process model with features from the rational unified process (RUP) model and agile methodology.

Keywords: agile methodology, health analytics, unified process model, UML

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Authors: H. Zidoum, A. AlShareedah, S. Al Sawafi, A. Al-Ansari, B. Al Lawati

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Systemic lupus erythematosus (SLE) is an autoimmune disease with genetic and environmental components. SLE is characterized by a wide variability of clinical manifestations and a course frequently subject to unpredictable flares. Despite recent progress in classification tools, the early diagnosis of SLE is still an unmet need for many patients. This study proposes an interpretable disease classification model that combines the high and efficient predictive performance of CatBoost and the model-agnostic interpretation tools of Shapley Additive exPlanations (SHAP). The CatBoost model was trained on a local cohort of 219 Omani patients with SLE as well as other control diseases. Furthermore, the SHAP library was used to generate individual explanations of the model's decisions as well as rank clinical features by contribution. Overall, we achieved an AUC score of 0.945, F1-score of 0.92 and identified four clinical features (alopecia, renal disorders, cutaneous lupus, and hemolytic anemia) along with the patient's age that was shown to have the greatest contribution on the prediction.

Keywords: feature selection, classification, systemic lupus erythematosus, model interpretation, SHAP, Catboost

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Authors: Grace Omowunmi Soyebi

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Data Mining is the extraction of information from a large database which helps in predicting a trend or behavior, thereby helping management make knowledge-driven decisions. One principal problem of most hospitals in rural areas is making use of the file management system for keeping records. A lot of time is wasted when a patient visits the hospital, probably in an emergency, and the nurse or attendant has to search through voluminous files before the patient's file can be retrieved; this may cause an unexpected to happen to the patient. This Data Mining application is to be designed using a Structured System Analysis and design method, which will help in a well-articulated analysis of the existing file management system, feasibility study, and proper documentation of the Design and Implementation of a Computerized medical record system. This Computerized system will replace the file management system and help to easily retrieve a patient's record with increased data security, access clinical records for decision-making, and reduce the time range at which a patient gets attended to.

Keywords: data mining, medical record system, systems programming, computing

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Authors: Oscar Vega Camacho, Andrea Vargas Guevara, Ellery Rowina Ariza

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This paper presents the application of finite dynamic programming, specifically the "Markov Chain" model, as part of the decision making process of a company in the cosmetics sector located in the vicinity of Bogota DC. The objective of this process was to decide whether the company should completely reconstruct its wastewater treatment plant or instead optimize the plant through the addition of equipment. The goal of both of these options was to make the required improvements in order to comply with parameters established by national legislation regarding the treatment of waste before it is released into the environment. This technique will allow the company to select the best option and implement a solution for the processing of waste to minimize environmental damage and the acquisition and implementation costs.

Keywords: decision making, Markov chain, optimization, wastewater

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Authors: Ali Abbas

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Industrial Engineering is a broad multidisciplinary field with intersections and applications in numerous areas. In out current environment, the path from a phenomenon to value involves numerous people with expertise in various areas including domain knowledge of a field and the ability to make decisions within an operating environment that lead to value creation. We propose some skills that industrial engineering programs should focus on, and argue that an industrial engineer is a decision maker instead of a problem solver.

Keywords: decision analysis, problem-solving, value creation, industrial engineering

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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: Estela Díaz

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This article aims to make three contributions. First, build on the literature on ethical decision-making literature by exploring factors that influence the intention of adopting veganism. Second, study the superiority of extended models of the Theory of Planned Behavior (TPB) for understanding the process involved in forming the intention of adopting veganism. Third, analyze the moderating effect of gender on TPB given that attitudes and behavior towards animals are gender-sensitive. No study, to our knowledge, has examined these questions. Veganism is not a diet but a political and moral stand that exclude, for moral reasons, the use of animals. Although there is a growing interest in studying veganism, it continues being overlooked in empirical research, especially within the domain of social psychology. TPB has been widely used to study a broad range of human behaviors, including moral issues. Nonetheless, TPB has rarely been applied to examine ethical decisions about animals and, even less, to veganism. Hence, the validity of TPB in predicting the intention of adopting veganism remains unanswered. A total of 476 non-vegan Spanish university students (55.6% female; the mean age was 23.26 years, SD= 6.1) responded to online and pencil-and-paper self-reported questionnaire based on previous studies. TPB extended models incorporated two background factors: ‘general attitudes towards humanlike-attributes ascribed to animals’ (AHA) (capacity for reason/emotions/suffer, moral consideration, and affect-towards-animals); and ‘general attitudes towards 11 uses of animals’ (AUA). SPSS 22 and SmartPLS 3.0 were used for statistical analyses. This study constructed a second-order reflective-formative model and took the multi-group analysis (MGA) approach to study gender effects. Six models of TPB (the standard and five competing) were tested. No a priori hypotheses were formulated. The results gave partial support to TPB. Attitudes (ATTV) (β = .207, p < .001), subjective norms (SNV) (β = .323, p < .001), and perceived control behavior (PCB) (β = .149, p < .001) had a significant direct effect on intentions (INTV). This model accounted for 27,9% of the variance in intention (R2Adj = .275) and had a small predictive relevance (Q2 = .261). However, findings from this study reveal that contrary to what TPB generally proposes, the effect of the background factors on intentions was not fully mediated by the proximal constructs of intentions. For instance, in the final model (Model#6), both factors had significant multiple indirect effect on INTV (β = .074, 95% C = .030, .126 [AHA:INTV]; β = .101, 95% C = .055, .155 [AUA:INTV]) and significant direct effect on INTV (β = .175, p < .001 [AHA:INTV]; β = .100, p = .003 [AUA:INTV]). Furthermore, the addition of direct paths from background factors to intentions improved the explained variance in intention (R2 = .324; R2Adj = .317) and the predictive relevance (Q2 = .300) over the base-model. This supports existing literature on the superiority of enhanced TPB models to predict ethical issues; which suggests that moral behavior may add additional complexity to decision-making. Regarding gender effect, MGA showed that gender only moderated the influence of AHA on ATTV (e.g., βWomen−βMen = .296, p < .001 [Model #6]). However, other observed gender differences (e.g. the explained variance of the model for intentions were always higher for men that for women, for instance, R2Women = .298; R2Men = .394 [Model #6]) deserve further considerations, especially for developing more effective communication strategies.

Keywords: veganism, Theory of Planned Behavior, background factors, gender moderation

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Authors: Manirath Wongsim

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Information Quality (IQ) has become a critical, strategic issue in Accounting Information Systems (AIS) adoption. In order to implement AIS adoption successfully, it is important to consider the quality of information use throughout the adoption process, which seriously impacts the effectiveness of AIS adoption practice and the optimization of AIS adoption decisions. There is a growing need for research to provide insights into issues and solutions related to IQ in AIS adoption. The need for an integrated approach to improve IQ in AIS adoption, as well as the unique characteristics of accounting data, demands an AIS adoption specific IQ framework. This research aims to explore ways of managing information quality and AIS adoption to investigate the relationship between the IQ issues and AIS adoption process. This study has led to the development of a framework for understanding IQ management in AIS adoption. This research was done on 44 respondents as ten organisations from manufacturing firms in Thailand. The findings of the research’s empirical evidence suggest that IQ dimensions in AIS adoption to provide assistance in all process of decision making. This research provides empirical evidence that information quality of AIS adoption affect decision making and suggests that these variables should be considered in adopting AIS in order to improve the effectiveness of AIS.

Keywords: information quality, information quality dimensions, accounting information systems, accounting information system adoption

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Authors: Mariam Shah

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Stereotypes are not generally considered to be an acceptable influence upon any decision making process, particularly those involving judicial decision making outcomes. Yet, we are confronted with an uncomfortable truth that stereotypes may be operating to influence judicial outcomes. Variances in sentencing outcomes are not easily explained away by criminological, psychological, or sociological theorem, but may be answered via qualitative research produced within the field of phenomenology. This paper will examine the current literature pertaining to the effect of stereotypes on the criminal justice system within the UK, and will also discuss what the implications are for stereotypical influences upon decision making in the criminal justice system. This paper will give particular focus to shoplifting offences dealt with in UK criminal courts, but this research has long reaching implications for the criminal process more generally.

Keywords: decision making, judicial decision making, phenomenology, shoplifting, stereotypes

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Authors: K. Hardy, A. Maurushat

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Policy makers are increasingly looking to make evidence-based decisions. Evidence-based decisions have historically used rigorous methodologies of empirical studies by research institutes, as well as less reliable immediate survey/polls often with limited sample sizes. As we move into the era of Big Data analytics, policy makers are looking to different methodologies to deliver reliable empirics in real-time. The question is not why did these people do this for the last 10 years, but why are these people doing this now, and if the this is undesirable, and how can we have an impact to promote change immediately. Big data analytics rely heavily on government data that has been released in to the public domain. The open data movement promises greater productivity and more efficient delivery of services; however, Australian government agencies remain reluctant to release their data to the general public. This paper considers the barriers to releasing government data as open data, and how these barriers might be overcome.

Keywords: big data, open data, productivity, data governance

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Authors: Harold Vásquez, Cesar Hernández, Ingrid Páez

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This paper approach cognitive radio technic and applied pure proactive handoff Model to decrease interference between PU and SU and comparing it with reactive handoff model. Through the study and analysis of multivariate models SAW and TOPSIS join to 3 dynamic prediction techniques AR, MA ,and ARMA. To evaluate the best model is taken four metrics: number failed handoff, number handoff, number predictions, and number interference. The result presented the advantages using this type of pure proactive models to predict changes in the PU according to the selected channel and reduce interference. The model showed better performance was TOPSIS-MA, although TOPSIS-AR had a higher predictive ability this was not reflected in the interference reduction.

Keywords: cognitive radio, spectrum handoff, decision making, time series, wireless networks

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Authors: Mohammadreza Nematollahi, Bahareh Mosadegh Sedghy, Alireza Tajbakhsh

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The last two decades have witnessed substantial attention to organic and sustainable agricultural supply chains. Motivated by real-world practices, this paper aims to address two main challenges observed in organic product supply chains: decentralized decision-making process between farmers and their retailers, and competition between organic products and their conventional counterparts. To this aim, an agricultural supply chain consisting of two farmers, a conventional farmer and an organic farmer who offers an organic version of the same product, is considered. Both farmers distribute their products through a single retailer, where there exists competition between the organic and the conventional product. The retailer, as the market leader, sets the wholesale price, and afterward, the farmers set their production quantity decisions. This paper first models the demand functions of the conventional and organic products by incorporating the effect of asymmetric brand equity, which captures the fact that consumers usually pay a premium for organic due to positive perceptions regarding their health and environmental benefits. Then, profit functions with consideration of some characteristics of organic farming, including crop yield gap and organic cost factor, are modeled. Our research also considers both economies and diseconomies of scale in farming production as well as the effects of organic subsidy paid by the government to support organic farming. This paper explores the investigated supply chain in three scenarios: decentralized, centralized, and coordinated decision-making structures. In the decentralized scenario, the conventional and organic farmers and the retailer maximize their own profits individually. In this case, the interaction between the farmers is modeled under the Bertrand competition, while analyzing the interaction between the retailer and farmers under the Stackelberg game structure. In the centralized model, the optimal production strategies are obtained from the entire supply chain perspective. Analytical models are developed to derive closed-form optimal solutions. Moreover, analytical sensitivity analyses are conducted to explore the effects of main parameters like the crop yield gap, organic cost factor, organic subsidy, and percent price premium of the organic product on the farmers’ and retailer’s optimal strategies. Afterward, a coordination scenario is proposed to convince the three supply chain members to shift from the decentralized to centralized decision-making structure. The results indicate that the proposed coordination scenario provides a win-win-win situation for all three members compared to the decentralized model. Moreover, our paper demonstrates that the coordinated model respectively increases and decreases the production and price of organic produce, which in turn motivates the consumption of organic products in the market. Moreover, the proposed coordination model helps the organic farmer better handle the challenges of organic farming, including the additional cost and crop yield gap. Last but not least, our results highlight the active role of the organic subsidy paid by the government as a means of promoting sustainable organic product supply chains. Our paper shows that although the amount of organic subsidy plays a significant role in the production and sales price of organic products, the allocation method of subsidy between the organic farmer and retailer is not of that importance.

Keywords: analytical game-theoretic model, product competition, supply chain coordination, sustainable organic supply chain

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Authors: J. A. López, J. E. Olguín, C. W. Camargo, G. A. Quijano, R. Martínez

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This paper presents an anthropometric study conducted to 300 employees in a maquiladora industry that belongs to the cluster of medical products as part of a research project to pretend simulate workplace conditions under which operators conduct their activities. This project is relevant because traditionally performed a study to design ergonomic workspaces according to anthropometric profile of users, however, this paper demonstrates the importance of making decisions when the infrastructure cannot be adapted for economic whichever put emphasis on user activity.

Keywords: anthropometry, biomechanics, design, ergonomics, productivity

Procedia PDF Downloads 436