Search results for: uncertainty and decision making

Authors: Kishor Bhagwat, Gayatri Vyas

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Construction industry is earmarked with complex processes depending on the nature and scope of the project. In recent years, developments in this sector are remarkable and have resulted in both positive and negative impacts on the environment and human being. Sustainable construction can be looked upon as one of the solution to overcome the negative impacts since sustainable construction is a vast concept, which includes many parameters, and sometimes the use of multi-criteria decision making [MCDM] tools becomes necessary. The main objective of this study is to determine the weightage of sustainable building parameters with the help of MCDM tools. Questionnaire survey was conducted to examine the perspective of respondents on the importance of weights of the criterion, and the respondents were architects, green building consultants, and civil engineers. This paper presents an overview of research related to Indian and international green building rating systems and MCDM. The results depict that economy, environmental health, and safety, site selection, climatic condition, etc., are important parameters in sustainable construction.

Keywords: green building, sustainability, multi-criteria decision making method [MCDM], analytical hierarchy process [AHP], technique for order preference by similarity to an ideal solution [TOPSIS], entropy

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Authors: R. H. Fattepur, Sameer R. Fattepur, D. K. Sreekantha

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Dairy Farming is one of the key industries in India. India is the leading producer and also the consumer of milk, milk-based products in the world. In this paper, we have attempted to the replace the human expert system and to develop an artificial expert system prototype to increase the speed and accuracy of decision making dairy farming credit risk evaluation. Fuzzy logic is used for dealing with uncertainty, vague and acquired knowledge, fuzzy rule base method is used for representing this knowledge for building an effective expert system.

Keywords: expert system, fuzzy logic, knowledge base, dairy farming, credit risk

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Authors: Endri Rama, Genci Capi, Shigenori Kawahara

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The mobile robot ability to navigate autonomously in its environment is very important. Even though the advances in technology, robot self-localization and goal directed navigation in complex environments are still challenging tasks. In this article, we propose a novel method for robot navigation based on rat’s brain signals (Local Field Potentials). It has been well known that rats accurately and rapidly navigate in a complex space by localizing themselves in reference to the surrounding environmental cues. As the first step to incorporate the rat’s navigation strategy into the robot control, we analyzed the rats’ strategies while it navigates in a multiple Y-maze, and recorded Local Field Potentials (LFPs) simultaneously from three brain regions. Next, we processed the LFPs, and the extracted features were used as an input in the artificial neural network to predict the rat’s next location, especially in the decision-making moment, in Y-junctions. We developed an algorithm by which the robot learned to imitate the rat’s decision-making by mapping the rat’s brain signals into its own actions. Finally, the robot learned to integrate the internal states as well as external sensors in order to localize and navigate in the complex environment.

Keywords: brain-machine interface, decision-making, mobile robot, neural network

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Authors: Khalid Kaddoura, Tarek Zayed

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Sewer networks are constructed to protect the communities and the environment from any contact with the sewer mediums. Pipelines, being laterals or sewer mains, and manholes form the huge underground infrastructure in every urban city. Due to the sewer networks importance, the infrastructure asset management field has extensive advancement in condition assessment and rehabilitation decision models. However, most of the focus was devoted to pipelines giving little attention toward manholes condition assessment. In fact, recent studies started to emerge in this area to preserve manholes from any malfunction. Therefore, the main objective of this study is to propose a condition assessment model for sewer manholes. The model divides the manhole into several components and determines the relative importance weight of each component using the Analytic Network Process (ANP) decision-making method. Later, the condition of the manhole is computed by aggregating the condition of each component with its corresponding weight. Accordingly, the proposed assessment model will enable decision-makers to have a final index suggesting the overall condition of the manhole and a backward analysis to check the condition of each component. Consequently, better decisions are made pertinent to maintenance, rehabilitation, and replacement actions.

Keywords: Analytic Network Process (ANP), condition assessment, decision-making, manholes

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Authors: Sae-Yeon Seong, EunSun Chung, Dongjoo Chin

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Conflict of interest (COI) is one of the dominant circumstantial factors of moral corruption across various fields. Several management strategies have been proposed to prevent self-interested decision making in COIs. Among these strategies, message persuasion has been considered as a practical and effective approach. Framing and repetition are two of the major factors in the persuasion effect of message. Therefore, their effect on moral decision making in COI should be explored systematically. The purpose of this study was to compare the differential effects of positively framed message and negatively framed message, and secondly, to investigate how the effectiveness of persuasive message changes through repetitive exposures. A total of 63 participants were randomly assigned to one of 3 framing conditions: positive framing, negative framing, and no-message condition. Prior to the online experiment involving a consultation task, the differently framed persuasive message was presented to the participants. This process was repeated four times in a row. The results showed that participants with positive-framing message were less likely to provide self-interested consultation than participants in the no-message condition. Also, a U-shaped quadric relation between repetition and self-interest consultation was found. Implications and limitations are further discussed.

Keywords: conflicts of interest, persuasive message, framing effect, repetition effect, self-interested behavior

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Authors: Leila Mohammadi

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This paper presents the impact of persuasive communication implemented by fertility clinics websites, and how this information influences women at their decision-making for undertaking this procedure. The influential factors for women decisions to do social egg freezing (SEF) are analyzed from a framing theory perspective, with a specific focus on the impact of persuasive information on women’s decision making. This study follows a quantitative approach. A two-phase survey has been conducted to examine the interest rate to undertake SEF. In the first phase, a questionnaire was available during a month (May 2015) to women to answer whether or not they knew enough information of this process, with a total of 230 answers. The second phase took place in the two last weeks of July 2015. All the respondents were invited to a seminars called ‘All about egg freezing’ and afretwards they were requested to answer the second questionnaire. After the seminar, in which they were given an extensive amount of information about egg freezing, a total of 115 women replied the questionnaire. The collected data during this process were analyzed using descriptive statistics. Most of the respondents changed their opinion in the second questionaire which was after receiving information. Although in the first questionnaire their self-evaluation of having knowledge about this process and the implemented technologies was very high, they realized that they still need to access more information from different sources in order to be able to make a decision. The study reached the conclusion that persuasive and framed information by clinics would affect the decisions of these women. Despite the reasons women have to do egg freezing and their motivations behind it, providing people necessary information and unprejudiced data about this process (such as its positive and negative aspects, requirements, suppositions, possibilities and consequences) would help them to make a more precise and reasonable decision about what they are buying.

Keywords: decision making, fertility clinics, framing theory, persuasive information, social egg freezing

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Authors: Arianne Van Der Wal, Femke Van Horen, Amir Grinstein

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Consumers in today’s world are confronted with the alarming consequences of unsustainable behavior such as pollution and resource degradation. In addition, they are facing an increase in uncertainty due to, for instance, economic instability and terror attacks. Although these two problems are central to consumers’ lives, occur on a global scale, and have significant impact on the world’s political, economic, environmental, and social landscapes, they have not been systematically studied in tandem before. Contributing to research on persuasion and pro-social behavior, this paper shows in five studies (three experimental studies and one field study) that the two problems are intertwined. We demonstrate that uncertainty leads to lower sustainable behavior in comparison to certainty (Studies 1 and 2) and that this is due to consumers displaying higher levels of temporal discounting (i.e., adopting a more immediate orientation; Study 2). Finally, providing valuable implications for policy makers and responsible marketers, we show that emphasizing the immediate benefits of sustainable behavior during uncertainty buffers the negative effect (Studies 3 and 4).

Keywords: sustainable behavior, uncertainty, temporal discounting, framing

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Authors: Aliaksei Patsekha, Michael Hohenberger, Harald Raupenstrauch

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An effective emergency response to accidents with chemical, biological, radiological, nuclear, or explosive materials (CBRNE) that represent highly dynamic situations needs immediate actions within limited time, information and resources. The aim of the study is to provide the foundation for division of unsafe area into risk zones according to the impact of hazardous parameters (heat radiation, thermal dose, overpressure, chemical concentrations). A decision on the boundary values for three risk zones is based on the vulnerability analysis that covered a variety of accident scenarios containing the release of a toxic or flammable substance which either evaporates, ignites and/or explodes. Critical values are selected for the boundary definition of the Red, Orange and Yellow risk zones upon the examination of harmful effects that are likely to cause injuries of varying severity to people and different levels of damage to structures. The obtained results provide the basis for creating a comprehensive real-time risk map for a decision support at CBRNE operations.

Keywords: boundary values, CBRNE threats, decision making process, hazardous effects, vulnerability analysis, risk zones

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Authors: Afia Naheed, Manmohan Singh, David Lucy

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This work is based on a mathematical as well as statistical study of an SEIJTR deterministic model for the interpretation of transmission of severe acute respiratory syndrome (SARS). Based on the SARS epidemic in 2003, the parameters are estimated using Runge-Kutta (Dormand-Prince pairs) and least squares methods. Possible graphical and numerical techniques are used to validate the estimates. Then effect of the model parameters on the dynamics of the disease is examined using sensitivity and uncertainty analysis. Sensitivity and uncertainty analytical techniques are used in order to analyze the affect of the uncertainty in the obtained parameter estimates and to determine which parameters have the largest impact on controlling the disease dynamics.

Keywords: infectious disease, severe acute respiratory syndrome (SARS), parameter estimation, sensitivity analysis, uncertainty analysis, Runge-Kutta methods, Levenberg-Marquardt method

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Authors: Sade Ogundipe

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The private healthcare sector in the United Kingdom has experienced unprecedented challenges during times of crisis, necessitating effective leadership adaptability. This qualitative study delves into the dynamic landscape of leadership within the sector, particularly during crises, employing the lenses of complexity theory and institutional theory to unravel the intricate mechanisms at play. Through in-depth interviews with 25 various levels of leaders in the UK private healthcare sector, this research explores how leaders in UK private healthcare organizations navigate complex and often chaotic environments, shedding light on their adaptive strategies and decision-making processes during crises. Complexity theory is used to analyze the complicated, volatile nature of healthcare crises, emphasizing the need for adaptive leadership in such contexts. Institutional theory, on the other hand, provides insights into how external and internal institutional pressures influence leadership behavior. Findings from this study highlight the multifaceted nature of leadership adaptability, emphasizing the significance of leaders' abilities to embrace uncertainty, engage in sensemaking, and leverage the institutional environment to enact meaningful changes. Furthermore, this research sheds light on the challenges and opportunities that leaders face when adapting to crises within the UK private healthcare sector. The study's insights contribute to the growing body of literature on leadership in healthcare, offering practical implications for leaders, policymakers, and stakeholders within the UK private healthcare sector. By employing the dual perspectives of complexity theory and institutional theory, this research provides a holistic understanding of leadership adaptability in the face of crises, offering valuable guidance for enhancing the resilience and effectiveness of healthcare leadership within this vital sector.

Keywords: leadership, adaptability, decision-making, complexity, complexity theory, institutional theory, organizational complexity, complex adaptive system (CAS), crises, healthcare

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Authors: Elias Udeaja, Elijah Udoh

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Exploring an extended SVAR model (SVAR-X), we use the case of Nigeria to hypothesize for the role of uncertainty as the underlying source of asymmetries in the response of monetary policy to output and inflation. Deciphered the empirical finding is the potential of monetary policy exhibiting greater sensitive to shocks due to output growth than they do to shocks due to inflation in recession periods, while the reverse appears to be the case for a contractionary monetary policy. We also find the asymmetric preference in the response of monetary policy to changes in output and inflation as relatively more pronounced when we control for uncertainty as the underlying source of asymmetries.

Keywords: asymmetry response, developing economies, monetary policy shocks, uncertainty

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Authors: Mekdelawit Teferi Alamirew

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As a practical tool, the Geographical information system (GIS) was used for data integration, collection, management, analysis, and output presentation in pavement mangement systems . There are many GIS techniques to improve the maintenance activities like Dynamic segmentation and weighted overlay analysis which considers Multi Criteria Decision Making process. The results indicated that the developed MPI model works sufficiently and yields adequate output for providing accurate decisions. Hence considering multi criteria to prioritize the pavement sections for maintenance, as a result of the fact that GIS maps can express position, extent, and severity of pavement distress features more effectively than manual approaches, lastly the paper also offers digitized distress maps that can help agencies in their decision-making processes.

Keywords: pavement, flexible, maintenance, index

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Authors: Arif Sikander, Imran Saeed

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The behavioral pattern and performance of airline pilots are influenced by the level of stress, their ethical decision-making ability and above all their leadership style as part of the Crew Management process. Cultural differences of pilots, especially while working in ex-country airlines, could influence the stress perception. Culture also influences ethical decision making. Leadership style is also a variable dimension, and pilots need to adapt to the cultural settings while flying with the local pilots as part of their team. Studies have found that age, education, gender, and management experience are statistically significant factors in ethical maturity. However, in the decades to come, more studies are required to validate the results over and over again; thereby, providing support for the validity of the Moral Development Theory. Leadership style plays a vital role in ethical decision making. This study is grounded in the Moral Development theory and seeks to analyze the styles of leadership of airline pilots related to ethical decision making and also the influence of the culture on their stress perception. The sample for the study included commercial pilots from a National Airline. It is expected that these results should provide useful input to the literature in the context of developing appropriate Talent Management strategies. The authors intend to extend this study (carried out in one country) to major national carriers (many countries) to be able to develop a ultimate framework on Talent Management which should serve as a benchmark for any international airline as most of them (e.g., Emirates, Etihad, Cathay Pacific, China Southern, etc.) are dependent on the supply of this scarce resource from outside countries.

Keywords: ethics, leadership, pilot, stress

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Authors: Ahmad Sarfaraz, Raiyad Herwies

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In this paper, a multi-criteria decision making analysis is used to help any organization selects the best KM tool that fits and serves its needs. The AHP model is used based on a previous study to highlight and identify the main criteria and sub-criteria that are incorporated in the selection process. Different KM tools alternatives with different criteria are compared and weighted accurately to be incorporated in the GP model. The main goal is to combine the GP model with the AHP model to ensure that selecting the KM tool considers the resource constraints. Two important issues are discussed in this paper: how different factors could be taken into consideration in forming the AHP model, and how to incorporate the AHP results into the GP model for better results.

Keywords: knowledge management, analytical hierarchy process, goal programming, multi-criteria decision making

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Authors: Mokrane Selma

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The shift towards decision making (DM) based on artificial intelligence (AI) techniques will change the way in which consumer markets and our societies function. Through AI, predictive analytics is being used by businesses to identify these patterns and major trends with the objective to improve the DM and influence future business outcomes. This paper proposes an Artificial Neural Network (ANN) approach to predict the success of telemarketing calls for selling bank long-term deposits. To validate the proposed model, we uses the bank marketing data of 41188 phone calls. The ANN attains 98.93% of accuracy which outperforms other conventional classifiers and confirms that it is credible and valuable approach for telemarketing campaign managers.

Keywords: bank telemarketing, prediction, decision making, artificial intelligence, artificial neural network

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Authors: Abdulrahman M. Qahtani, Gary. B. Wills, Andy. M. Gravell

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Communicating and managing customers’ requirements in software development projects play a vital role in the software development process. While it is difficult to do so locally, it is even more difficult to communicate these requirements over distributed boundaries and to convey them to multiple distribution customers. This paper discusses the communication of multiple distribution customers’ requirements in the context of customised software products. The main purpose is to understand the challenges of communicating and managing customisation requirements across distributed boundaries. We propose a model for Communicating Customisation Requirements of Multi-Clients in a Distributed Domain (CCRD). Thereafter, we evaluate that model by presenting the findings of a case study conducted with a company with customisation projects for 18 distributed customers. Then, we compare the outputs of the real case process and the outputs of the CCRD model using simulation methods. Our conjecture is that the CCRD model can reduce the challenge of communication requirements over distributed organisational boundaries, and the delay in decision making and in the entire customisation process time.

Keywords: customisation software products, global software engineering, local decision making, requirement engineering, simulation model

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Authors: Ebru Turgal, Beyza Doganay Erdogan

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Machine learning aims to model the relationship between the response and features. Medical decision-making researchers would like to make decisions about patients’ course and treatment, by examining the repeated measurements over time. Boosting approach is now being used in machine learning area for these aims as an influential tool. The aim of this study is to show the usage of multivariate tree boosting in this field. The main reason for utilizing this approach in the field of decision-making is the ease solutions of complex relationships. To show how multivariate tree boosting method can be used to identify important features and feature-time interaction, we used the data, which was collected retrospectively from Ankara University Chest Diseases Department records. Dataset includes repeated PF ratio measurements. The follow-up time is planned for 120 hours. A set of different models is tested. In conclusion, main idea of classification with weighed combination of classifiers is a reliable method which was shown with simulations several times. Furthermore, time varying variables will be taken into consideration within this concept and it could be possible to make accurate decisions about regression and survival problems.

Keywords: boosted multivariate trees, longitudinal data, multivariate regression tree, panel data

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Authors: Smail Tigani, Mohamed Ouzzif

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This work presents a discrete quantitative state prediction algorithm with intelligent behavior making it able to self-improve some performance aspects. The specificity of this algorithm is the capacity of self-rectification of the prediction strategy before the final decision. The auto-rectification mechanism is based on two parallel mathematical models. In one hand, the algorithm predicts the next state based on event transition matrix updated after each observation. In the other hand, the algorithm extracts its residues trend with a linear regression representing historical residues data-points in order to rectify the first decision if needs. For a normal distribution, the interactivity between the two models allows the algorithm to self-optimize its performance and then make better prediction. Designed key performance indicator, computed during a Monte Carlo simulation, shows the advantages of the proposed approach compared with traditional one.

Keywords: discrete state, Markov Chains, linear regression, auto-adaptive systems, decision making, Monte Carlo Simulation

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Authors: Lee Waters, Itay Basevitch, Matthew Timmis

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Objectives: Eye tracking technology is a valuable method of assessing individuals gaze behaviour, but it does not unveil why they are engaging in certain practices. To address limitations in sport eye tracking research the present paper aims to investigate the gaze behaviours soccer officials engage in during successful and unsuccessful offside decisions, but also why. Methods: 20 male active amateur qualified (Level 4-7) soccer officials (Mage 22.5 SD 4.61 yrs) with an average experience of 41-50 games wore eye tracking technology during an applied attack versus defence drill. While reviewing the eye tracking footage, retrospective semi-structured interviews were conducted (M=20.4 min; SD=6.2; Range 11.7 – 26.8 min) and once transcribed inductive thematic analysis was performed. Findings and Discussion: To improve the understanding of gaze behaviours and how officials make sense of the environment, during the interview’s key constructs of offside, decision making, obstacles and emotions were summarised as the higher order themes while making offside decisions. Gaze anchoring was highlighted to be a successful technique to allow officials to see all relevant information, whereas the type of offside was emphasised to be a key factor in correct interpretation. Furthermore, specific decision-making training was outlined to be inconsistent and not always applicable. Conclusions: Key constructs have been identified and explained, which can be shared with soccer officials through training regimes. Eye tracking technology has also been shown to be a useful and innovative reflective tool to assist in the understanding of individuals gaze behaviours.

Keywords: eye tracking, gaze behvaiour, decision making, reflection

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Authors: Lien-Fa Lin, Yung-Ming Li, Fu-Shun Hsieh

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With the advancement of information technology and development of group commerce, people have obviously changed in their lifestyle. However, group commerce faces some challenging problems. The products or services provided by vendors do not satisfactorily reflect customers’ opinions, so that the sale and revenue of group commerce gradually become lower. On the other hand, the process for a formed customer group to reach group-purchasing consensus is time-consuming and the final decision is not the best choice for each group members. In this paper, we design a social decision support mechanism, by using group discussion message to recommend suitable options for group members and we consider social influence and personal preference to generate option ranking list. The proposed mechanism can enhance the group purchasing decision making efficiently and effectively and venders can provide group products or services according to the group option ranking list.

Keywords: social network, group decision, text mining, group commerce

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Authors: Antonios Paraskevas, Michael Madas

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For a university to maintain its international competitiveness in education, it is essential to recruit qualitative academic staff as it constitutes its most valuable asset. This selection demonstrates a significant role in achieving strategic objectives, particularly by emphasizing a firm commitment to the exceptional student experience and innovative teaching and learning practices of high quality. In this vein, the appropriate selection of academic staff establishes a very important factor of competitiveness, efficiency and reputation of an academic institute. Within this framework, our work demonstrates a comprehensive methodological concept that emphasizes the multi-criteria nature of the problem and how decision-makers could utilize our approach in order to proceed to the appropriate judgment. The conceptual framework introduced in this paper is built upon a hybrid neutrosophic method based on the Neutrosophic Analytical Hierarchy Process (N-AHP), which uses the theory of neutrosophy sets and is considered suitable in terms of a significant degree of ambiguity and indeterminacy observed in the decision-making process. To this end, our framework extends the N-AHP by incorporating the Neutrosophic Delphi Method (N-DM). By applying the N-DM, we can take into consideration the importance of each decision-maker and their preferences per evaluation criterion. To the best of our knowledge, the proposed model is the first which applies the Neutrosophic Delphi Method in the selection of academic staff. As a case study, it was decided to use our method for a real problem of academic personnel selection, having as the main goal to enhance the algorithm proposed in previous scholars’ work, and thus taking care of the inherent ineffectiveness which becomes apparent in traditional multi-criteria decision-making methods when dealing with situations alike. As a further result, we prove that our method demonstrates greater applicability and reliability when compared to other decision models.

Keywords: multi-criteria decision making methods, analytical hierarchy process, delphi method, personnel recruitment, neutrosophic set theory

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Authors: Gunnar Oskarsson, Gudjon Helgi Egilsson

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Due to globalization, small and medium-sized enterprises (SME) increasingly offer their products and services in foreign markets. The main reasons are either to compensate for a decreased market share in their home market or to exploit opportunities in foreign markets, which are becoming less distant and better accessible than before. International markets are particularly important for companies located in a small economy and offering specialized products. Although more accessible, entering international markets is both expensive and difficult. In order to select the most appropriate markets, it is, therefore, important to gain an insight into the factors that have an impact on success, or potential failure. Although there has been a reasonable volume of research into the theory of internationalization, there is still a need to gain further understanding of the decision-making process of SMEs in small economies and the most important characteristics that distinguish between success and failure. The main objective of this research is to enhance knowledge on the internationalization of SMEs, including the drivers for the decision to internationalize, and the most important factors contributing to success in their internationalization activities. A qualitative approach was found to be most appropriate for this kind of research, with the objective of gaining a deeper understanding and discovering factors which impact a company’s decision-making and potential success. In-depth interviews were conducted with 14 companies in different industries located in Iceland, a country extensively dependent on export revenues. The interviews revealed several factors as drivers of internationalization and, not surprisingly, the most frequently mentioned source of motivation was that the local market is inadequate to maintain a sustainable operation. Good networking relationships were seen as a particular priority for potential success, searching for new markets was mainly carried out through the internet, although sales exhibitions and sales trips were also considered important. When it comes to the final decision as to whether a market should be considered for further analysis, economy, labor cost, legal environment, and cultural barriers were the most common factors to be weighted. The ultimate answer to successful internationalization, however, is largely dependent on a coordinated and experienced management team. The main contribution of this research is offering an insight into factors affecting decision-making in the internationalization process of SMEs, based on the opinion and experience of managers of SMEs in a small economy.

Keywords: internationalization, success factors, small and medium-sized enterprises (SMEs), drivers, decision making

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Authors: Mojtaba Sadeghi, Farshid Baniassadi, Hamed Kashani

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One of the challenging issues faced by seismic retrofitting consultants and employers is quick decision-making on the demolition or retrofitting of a structure at the current time or in the future. For this reason, the existing models proposed by researchers have only covered one of the aspects of cost, execution method, and structural vulnerability. Given the effect of each factor on the final decision, it is crucial to devise a new comprehensive model capable of simultaneously covering all the factors. This study attempted to provide an integrated framework that can be utilized to select the most appropriate earthquake risk mitigation solution for buildings. This framework can overcome the limitations of current models by taking into account several factors such as cost, execution method, risk-taking and structural failure. In the newly proposed model, the database and essential information about retrofitting projects are developed based on the historical data on a retrofit project. In the next phase, an analysis is conducted in order to assess the vulnerability of the building under study. Then, artificial neural networks technique is employed to calculate the cost of retrofitting. While calculating the current price of the structure, an economic analysis is conducted to compare demolition versus retrofitting costs. At the next stage, the optimal method is identified. Finally, the implementation of the framework was demonstrated by collecting data concerning 155 previous projects.

Keywords: decision making, demolition, construction management, seismic retrofit

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Authors: Katerina Nerantzaki, Panayiota Metallidou, Anastasia Efklides

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The aim of the study was to investigate: (a) changes in the intensity of various epistemic emotions during cognitive processing in a decision-making task and (b) their associations with metacognitive feelings of difficulty and confidence. One hundred and fifty-two undergraduate university students were asked individually to read in the e-prime environment decision-making scenarios about moral dilemmas concerning self-driving cars, which differed in the level of conflict they produced, and then to make a choice between two options. Further, the participants were asked to rate on a four-point scale four epistemic emotions (surprise, curiosity, confusion, and wonder) and two metacognitive feelings (feeling of difficulty and feeling of confidence) after making their choice in each scenario. Changes in cognitive processing due to the level of conflict affected differently the intensity of the specific epistemic emotions. Further, there were interrelations of epistemic emotions with metacognitive feelings.

Keywords: confusion, curiosity, epistemic emotions, metacognitive experiences, surprise

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Authors: Dinamarie Fonzone

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Employer-sponsored health insurance (ESI) strategic decision-making processes rely on financial analysis to guide leadership in choosing plans that will produce optimal organizational spending outcomes. These financial decision-making methods have not abated ESI costs. Previously unrecognized external social determinants, the impact on ESI plan spending, and other organizational strategies are emerging and are important considerations for organizational decision-makers and change management practitioners. The purpose of thisstudy is to examine the relationship between the social determinants of health (SDoH), employer-sponsored health insurance (ESI) plans, andthe unintended consequence of health inequity. A quantitative research design using selectemployee records from an existing employer human capital management database will be analyzed. Statistical regressionmethods will be used to study the relationships between certainSDoH (employee income, neighborhood geographic living area, and health care access) and health plan utilization, cost, and chronic disease prevalence. The discussion will include an application of the social gradient of health theory to the study findings, organizational transformation through changes in ESI decision-making mental models, and the connection of ESI health inequity to organizational development and changediversity, equity, and inclusion strategies.

Keywords: employer-sponsored health insurance, social determinants of health, health inequity, mental models, organizational development, organizational change, social gradient of health theory

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Authors: Ezgi Nevruz, Kasirga Yildirak, Ashis SenGupta

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Comparing or ranking risks is the main motivating factor behind the human trait of making choices. Cumulative prospect theory (CPT) is a preference theory approach that evaluates perception and bias in decision making under risk and uncertainty. We aim to investigate the aggregate claims of different risk classes in terms of their comparability and amenability to ordering when the impact of risk perception is considered. For this aim, we prioritize the aggregate claims taken as actuarial risks by using various stochastic ordering relations. In order to prioritize actuarial risks, we use stochastic relations such as stochastic dominance and stop-loss dominance that are proposed in the frame of partial order theory. We take into account the dependency of the individual claims exposed to similar environmental risks. At first, we modify the zero-utility premium principle in order to obtain a solution for the stop-loss premium under CPT. Then, we propose a stochastic stop-loss dominance of the aggregate claims and find a relation between the stop-loss dominance and the first-order stochastic dominance under the dependence assumption by using properties of the familiar as well as some emerging multivariate claim distributions.

Keywords: cumulative prospect theory, partial order theory, risk perception, stochastic dominance, stop-loss dominance

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Authors: Sonia Anand Knowlton

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There are some cases where we as a society feel deeply uncomfortable with the use of Artificial Intelligence (AI) tools in the judicial decision-making process, and justifiably so. A perfect example is COMPAS, an algorithmic model that predicts recidivism rates of offenders to assist in the determination of their bail conditions. COMPAS turned out to be extremely racist: it massively overpredicted recidivism rates of Black offenders and underpredicted recidivism rates of white offenders. At the same time, there are certain uses of AI in the judicial decision-making process that many would feel more comfortable with and even support. Take, for example, a “super-breathalyzer,” an (albeit imaginary) tool that uses AI to deliver highly detailed information about the subject of the breathalyzer test to the legal decision-makers analyzing their drunk-driving case. This article evaluates the point at which a judge’s use of AI tools begins to undermine the public’s trust in the administration of justice. It argues that the answer to this question depends on whether the AI tool is in a role in which it must perform a moral evaluation of a human being.

Keywords: artificial intelligence, judicial reasoning, morality, technology, algorithm

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Authors: Priyanka Verma, Vijaya Dixit, Rishabh Bajpai

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This research paper is aimed at selecting appropriate material handling equipment among the given choices so that the automation level in material handling can be enhanced. This work is a practical case scenario of material handling systems in consumer electronic appliances manufacturing organization. The choices of material handling equipment among which the decision has to be made are Automated Guided Vehicle’s (AGV), Autonomous Mobile Robots (AMR), Overhead Conveyer’s (OC) and Battery Operated Trucks/Vehicle’s (BOT). There is a need of attaining a certain level of automation in order to reduce human interventions in the organization. This requirement of achieving certain degree of automation can be attained by material handling equipment’s mentioned above. The main motive for selecting above equipment’s for study was solely based on corporate financial strategy of investment and return obtained through that investment made in stipulated time framework. Since the low cost automation with respect to material handling devices has to be achieved hence these equipment’s were selected. Investment to be done on each unit of this equipment is less than 20 lakh rupees (INR) and the recovery period is less than that of five years. Fuzzy analytic hierarchic process (FAHP) is applied here for selecting equipment where the four choices are evaluated on basis of four major criteria’s and 13 sub criteria’s, and are prioritized on the basis of weight obtained. The FAHP used here make use of triangular fuzzy numbers (TFN). The inability of the traditional AHP in order to deal with the subjectiveness and impreciseness in the pair-wise comparison process has been improved in the FAHP. The range of values for general rating purposes for all decision making parameters is kept between 0 and 1 on the basis of expert opinions captured on shop floor. These experts were familiar with operating environment and shop floor activity control. Instead of generating exact value the FAHP generates the ranges of values to accommodate the uncertainty in decision-making process. The four major criteria’s selected for the evaluation of choices of material handling equipment’s available are materials, technical capabilities, cost and other features. The thirteen sub criteria’s listed under these following four major criteria’s are weighing capacity, load per hour, material compatibility, capital cost, operating cost and maintenance cost, speed, distance moved, space required, frequency of trips, control required, safety and reliability issues. The key finding shows that among the four major criteria selected, cost is emerged as the most important criteria and is one of the key decision making aspect on the basis of which material equipment selection is based on. While further evaluating the choices of equipment available for each sub criteria it is found that AGV scores the highest weight in most of the sub-criteria’s. On carrying out complete analysis the research shows that AGV is the best material handling equipment suiting all decision criteria’s selected in FAHP and therefore it is beneficial for the organization to carry out automated material handling in the facility using AGV’s.

Keywords: fuzzy analytic hierarchy process (FAHP), material handling equipment, subjectiveness, triangular fuzzy number (TFN)

Procedia PDF Downloads 434

Authors: Ulrike Dowie, Ralph Grothmann

Abstract:

Rational planning decisions are based upon forecasts. Precise forecasting has, therefore, a central role in business. The prediction of customer demand is a prime example. This paper introduces recurrent neural networks to model customer demand and combines the forecast with uncertainty measures to derive decision support of the demand planning department. It identifies and describes the keys to the successful implementation of an AI-based solution: bringing together data with business knowledge, AI methods, and user experience, and applying agile software development practices.

Keywords: agile software development, AI project success factors, deep learning, demand forecasting, forecast uncertainty, neural networks, supply chain management

Procedia PDF Downloads 189

Authors: Sylvie Michel, Emmanuelle Gagnou, Joanne Hamet

Abstract:

Researchers in the fields of AI and Robotics frequently encounter ethical dilemmas throughout their research endeavors. Various ethical challenges have been pinpointed in the existing literature, including biases and discriminatory outcomes, diffusion of responsibility, and a deficit in transparency within AI operations. This research aims to pinpoint these ethical quandaries faced by researchers and shed light on the mechanisms behind ethical decision-making in the research process. By synthesizing insights from existing literature and acknowledging prevalent shortcomings, such as overlooking the heterogeneous nature of decision-making, non-accumulative results, and a lack of consensus on numerous factors due to limited empirical research, the objective is to conceptualize and validate a model. This model will incorporate influences from individual perspectives and situational contexts, considering potential moderating factors in the ethical decision-making process. Qualitative analyses were conducted based on direct observation of an AI/Robotics research team focusing on collaborative robotics for several months. Subsequently, semi-structured interviews with 16 team members were conducted. The entire process took place during the first semester of 2023. Observations were analyzed using an analysis grid, and the interviews underwent thematic analysis using Nvivo software. An initial finding involves identifying the ethical challenges that AI/robotics researchers confront, underlining a disparity between practical applications and theoretical considerations regarding ethical dilemmas in the realm of AI. Notably, researchers in AI prioritize the publication and recognition of their work, sparking the genesis of these ethical inquiries. Furthermore, this article illustrated that researchers tend to embrace a consequentialist ethical framework concerning safety (for humans engaging with robots/AI), worker autonomy in relation to robots, and the societal implications of labor (can robots displace jobs?). A second significant contribution entails proposing a model for ethical decision-making within the AI/Robotics research sphere. The model proposed adopts a process-oriented approach, delineating various research stages (topic proposal, hypothesis formulation, experimentation, conclusion, and valorization). Across these stages and the ethical queries, they entail, a comprehensive four-point comprehension of ethical decision-making is presented: recognition of the moral quandary; moral judgment, signifying the decision-maker's aptitude to discern the morally righteous course of action; moral intention, reflecting the ability to prioritize moral values above others; and moral behavior, denoting the application of moral intention to the situation. Variables such as political inclinations ((anti)-capitalism, environmentalism, veganism) seem to wield significant influence. Moreover, age emerges as a noteworthy moderating factor. AI and robotics researchers are continually confronted with ethical dilemmas during their research endeavors, necessitating thoughtful decision-making. The contribution involves introducing a contextually tailored model, derived from meticulous observations and insightful interviews, enabling the identification of factors that shape ethical decision-making at different stages of the research process.

Keywords: ethical decision making, artificial intelligence, robotics, research

Procedia PDF Downloads 79