Multi-attribute Utility Model Research Articles

Three Layered Architecture for Driver Behavior Analysis and Personalized Assistance with Alert Message Dissemination in 5G Envisioned Fog-IoCV

The Internet of connected vehicles (IoCV) has made people more comfortable and safer while driving vehicles. This technology has made it possible to reduce road casualties; however, increased traffic and uncertainties in environments seem to be limitations to improving the safety of environments. In this paper, driver behavior is analyzed to provide personalized assistance and to alert surrounding vehicles in case of emergencies. The processes involved in this research are as follows. (i) Initially, the vehicles in an environment are clustered to reduce the complexity in analyzing a large number of vehicles. Multi-criterion-based hierarchical correlation clustering (MCB-HCC) is performed to dynamically cluster vehicles. Vehicular motion is detected by edge-assisted road side units (E-RSUs) by using an attention-based residual neural network (AttResNet). (ii) Driver behavior is analyzed based on the physiological parameters of drivers, vehicle on-board parameters, and environmental parameters, and driver behavior is classified into different classes by implementing a refined asynchronous advantage actor critic (RA3C) algorithm for assistance generation. (iii) If the driver’s current state is found to be an emergency state, an alert message is disseminated to the surrounding vehicles in that area and to the neighboring areas based on traffic flow by using jelly fish search optimization (JSO). If a neighboring area does not have a fog node, a virtual fog node is deployed by executing a constraint-based quantum entropy function to disseminate alert messages at ultra-low latency. (iv) Personalized assistance is provided to the driver based on behavior analysis to assist the driver by using a multi-attribute utility model, thereby preventing road accidents. The proposed driver behavior analysis and personalized assistance model are experimented on with the Network Simulator 3.26 tool, and performance was evaluated in terms of prediction error, number of alerts, number of risk maneuvers, accuracy, latency, energy consumption, false alarm rate, safety score, and alert-message dissemination efficiency.

Exploring Cruise Tourists’ Preferences and Satisfaction: The Case of Taiwan

In this study, the product attributes of cruise tours are distinguished into on-board activities, leisure space, cabin comfort, Michelin restaurant, and refund mechanism, and the multi-attribute utility model of cruise tours is constructed using the choice experiment (CE) method. Of the 575 questionnaires distributed, 439 were valid, with an effective recovery rate of 76.3%. The results revealed the following: (1) when cruisers travel, what they value the most is the quality of service on board, followed by the facilities on board; (2) passengers’ preferences for comfortable pool space and more activities on board are negatively significant, indicating that they do not prefer to add these amenities and experiences to the cruise ship; (3) passengers are willing to pay extra to upgrade the interior cabin to one with a view and to experience the Michelin restaurant; and (4) influenced by the COVID-19 pandemic, cruisers are more willing to manage their own health. Moreover, the pandemic does not reduce their willingness to travel by cruise.

Target-Oriented User Equilibrium Considering Travel Time, Late Arrival Penalty, and Travel Cost on the Stochastic Tolled Traffic Network

In this paper, we employ a target-oriented approach to analyze the multi-attribute route choice decision of travelers in the stochastic tolled traffic network, considering the influence of three attributes, which are (stochastic) travel time, (stochastic) late arrival penalty, and (deterministic) travel cost. We introduce a target-oriented multi-attribute travel utility model for this analysis, where each attribute is assigned a target by travelers, and travelers’ objective is to maximize their travel utility that is determined by the achieved targets. Moreover, the interaction between targets is interpreted as complementarity relationship between them, which can further affect their travel utility. In addition, based on this travel utility model, a target-oriented multi-attribute user equilibrium model is proposed, which is formulated as a variational inequality problem and solved with the method of successive average. Target for travel time is determined via travelers’ on-time arrival probability, while targets for late arrival penalty and travel cost are given exogenously. Lastly, we apply the proposed model on the Braess and Nguyen–Dupuis traffic networks, and conduct sensitivity analysis of the parameters, including these three targets and the target interaction between them. The study in this paper can provide a new perspective for travelers’ multi-attribute route choice decision, which can further show some implications for the policy design.

Top Down or Bottom Up? Disentangling the Channels of Attention in Risky Choice

Economists have become increasingly interested in using attention to explain behavioral patterns both on the micro and macro level. This has resulted in several disparate theoretical approaches. Some, like rational inattention, assume a “top-down” model of executive optimization. Others, like salience theory, assume a “bottom-up” influence where attention is driven by contextual factors. This distinction is fundamental for the economic implications of attention, but so far there is little understanding of their relative importance. We propose a multi-attribute random utility model that unifies prior theoretical approaches by distinguishing between the impact of top-down and bottom-up attention. We accomplish this by separating agent-specific and decision-specific variation in attention and verify our framework in an eye-tracking experiment on risky choice. We find that both top-down and bottom-up attention are connected to important choice variables: both are associated with the weighting of the attributes of choice options, while top-down attention is additionally associated with measures of loss aversion. We discuss the insights regarding the nature of attention and its role in economic theory.

User values and the development of a cybersecurity public policy for the IoT

Public administrators, entrusted to develop public policy to manage the growing complexities of the IoT, face significant challenges. The challenges exist because of three reasons; First, there is a lack of policy direction. Second, user values related to cybersecurity are not well understood. Third, there is a lack of clarity as to how IoT public policy should be developed. In this paper we argue that new IoT policy should be guided by key stakeholder values (i.e. what users think to be important). We utilize the Public Value Forum to elicit public values to inform decision-making surrounding IoT policy by public administrators, conceptually informed by Rational choice theory. We use a five-phase process to introduce the decision context (i.e. the policy problem), define fundamental objectives, rank these objectives, identify value-based trade-offs between them and construct a multi-attribute utility model. The findings indicate several key themes for IoT security from the citizens themselves and decision-making administrators in diverse public agencies developing IoT cybersecurity public policy.

A multi-attribute utility model for environmental decision-making: an application to casting

It is a well-known fact among environmental researchers that the casting process presents challenges to those entrusted with protecting the environment. Prior studies suggested models for health risk assessment that offered alternatives to help lower toxic emissions. Limitations were encountered when those alternatives were discussed for their acceptability in the pouring, cooling and shakeout stages of the casting process. The current study proposes to enrich the relevancy of these previous models to decision-makers by incorporating technical and economic attributes of interest to the manufacturer. The enhanced model uses a multi-attribute utility function to minimize toxic emission while controlling for technical and economic constraints. Under policy limitations, the model was complemented with a human factor as an uncertain belief encompassing partiality of the expert’s judgment or the stakeholder’s preference. The results of a simulation used for illustration purpose were encouraging to the usefulness of the proposed model. The sensitivity to variable scenarios accounting for environmental pollutants proved to build a consensus around potential alternatives.

A multi-attribute utility theory approach to ordering policy for perishable items

Most retailers aim at operating with low cost and low stock-out probability. In this paper, we consider a retailer who manages the inventory of a perishable product using a continuous review (Q,r) policy with these two performance measures. We rely on the multi-attribute utility theory to combine these two measures into a single weighted utility function. We incorporate the decision maker’s risk-aversion/risk-seeking attitude. We obtain the optimal policy parameters by maximizing the weighted utility function. We conduct a numerical study to demonstrate the sensitivity of the optimal policy parameters to the risk-aversion/risk-seeking attitude of the decision maker and weights of evaluation measures. Our results reveal that the risk behavior does not have a significant effect on policy parameters while the weights of evaluation measures are influential. We compare our multi-attribute utility model with three well-known alternative (Q,r) policies. In the first one, we study the expected cost as a single performance measure. In the second one, we consider a service level constraint and in the third one, we use CVaR measure. We conclude that our multi-attribute approach has multiple favorable attributes compared to its widely used alternatives.

STOCHASTIC MULTI-ATTRIBUTE UTILITY MODEL

In real situations, the attribute value (mostly variable)can be best represented by introducing the finite numberof attribute values level, to which the correspondingprobabilities should also be attached. Stochastic Multi-Attribute Utility Model has the ability to analyze suchstochastic multi-attribute problems. The choice of one,from the set of available options, is made by choosingthe best option based on the maximum expected utilitystructure. In this paper, we will mention some argumentsfor the development of the Stochastic Multi-AttributeUtility Model, its advantages (they are closer to reality),disadvantages (analytically difficult technique, subjectiveassessments of the values of variable attributes), aswell as the process of solving the problem.

Robustness of the Multi-Attribute Utility Model for Bridge Maintenance Planning

Optimisation of maintenance planning is an essential part of bridge management. With the purpose to support maintenance planning, a multi- objective decision-making model is introduced in this paper. The model is based on multi-attribute utility theory, which is used for the optimisation process when multiple performance goals have to be taken into account. In the model, there are several parameters, which are freely chosen by the decision maker. The model is applied to the inventory of 22 bridges, where four Key Performance Indicators were determined for four performance aspects: reliability, availability, costs and environment. A sensitivity analysis is performed by changing risk tolerance parameter and attribute weights to determine the robustness of the model. The Multi-Attribute Utility model and sensitivity analysis presented in this paper will help decision-makers to examine the robustness of the optimal solution by dynamically changing the critical parameters.

Sustainability assessment of ecological intensification practices in coconut production

Environmental impact and economic performance assessments are important subjects for the definition of strategies for sustainable management in agriculture. The objective of the present study was to assess such impacts in a set of reference farms dedicated to coconut production, conforming a gradient with respect to the adoption of technologies and ecological intensification practices. Ranging in scale from smaller family farms to larger corporate enterprises, and from coconut monocultures to diversified crops and integrated coconut-livestock systems, the six cases were studied through a multi-attribute utility model comprising 62 indicators related to five sustainability dimensions: (i) Landscape ecology, (ii) Environmental quality, (iii) Sociocultural values, (iv) Economic values and (v) Management and administration. Detailed cash flow analyses permitted a critical view regarding the influence of technology adoption, ecological intensification, and management for sustainability as criteria for economic viability. The results attest to the value of produce diversification as opportunity toward technology integration, which correlated positively with higher sustainability indices in all dimensions. Tradeoff analysis showed a negative correlation between socio-environmental performance indices and profitability, whereas none of the cases studied showed constrained economic viability, indicating that ecological intensification in coconut production can also entail social improvements, by promoting fairer share of revenues and benefits among stakeholders. Recommendations issued to farmers and management teams, related with agronomic factors and practices adopted in production intensification, favor the communication of appropriate mechanisms for technology adoption, translating farm-level sustainability assessments into action for sustainability.

A simulation study for residential electricity user behavior under dynamic variable pricing with demand charge

ABSTRACTAttempting to increase energy efficiency and improve system load factors in an electricity distribution system, Demand Response (DR) has long been proposed and implemented as a form of load management. Various pricing structures incentivizing consumers to shift energy consumption from on-peak to off-peak periods are evident in this field. Most DR methods currently used in practice belong to static variable pricing (e.g., Time of Use, Critical Peak Pricing) and the impact of such tariffs has been well established. However, dynamic variable pricing in general is less studied and much less practiced in the field, due to the lack of understanding of consumer behavior in response to price uncertainty. In this article, we study a novel dynamic variable pricing scheme that uses the coincident demand charge to reduce load consumption during peak events. We employ a multi-attribute utility function and model predictive control to simulate consumer behavior of utility maximization in home energy consumption. We use a conditional Markov chain to model and predict the system peak. Effects of the proposed residential electricity rate based on coincident demand charge are compared with other pricing schemes through simulation validated with real-world residential load profiles. Finally, we extend the simulations to study the impact of integrating renewable solar production in a DR program.

Model-based space planning for temporary structures using simulation-based multi-objective programming

Construction trades need to share temporary structures to increase the output of direct work while controlling the labor input of indirect work. The purpose of this research is to develop a framework to determine the optimal location of temporary structures in a computerized practical manner for piping construction projects. Based on the spatial relationship between work envelope and scaffolding placement requirements, this paper presents the optimization model in two phases: the simulation-based optimization model and a multi-attribute utility (MAU) based alternative selection model. A multi-objective optimization model is established to improve scaffolding availability among multiple activities while maximizing piping crew productivity. The multi-attribute utility model is employed to handle the uncertainty of the assessment weights on the attributes to illustrate the preference of decision makers among different scaffolding placement alternatives obtained from the first phase. The approach was validated in a piping module, which provided superintendents and space planners with an effective decision-making tool among possible scaffolding alternatives in piping construction. The proposed optimization technique is an alternative methodology for solving the productivity-tasks-scaffolding trade-off problem, which further revolutionizes the spatial coordination process of workspace management and temporary structure planning.

Restoring a Radionuclide Contaminated Aquatic Ecosystem: A Group Decision Making Problem with Incomplete Information within MAUT Accounting for Veto

In this paper we consider the evaluation of intervention countermeasures for the restoration of a radionuclide contaminated aquatic ecosystem, simultaneously taking into account several conflicting objectives, like environmental, social and economic impacts. We propose an extension of the additive multi-attribute utility model to incorporate the concept of veto to deal with this group decision-making problem. Moreover, we consider what is known as decision-making with partial, imprecise or incomplete information, which accounts for uncertainty about the alternative performances and imprecision concerning DM preferences by means of intervals or ordinal information. Veto values for the most important DMs are used to define veto ranges, whereas veto values corresponding to the other less important DMs are partially taken into account, leading to the construction of adjust ranges. We then build the veto and adjust functions into the additive model, and a dominance matrix accounting for incomplete information is computed. A dominance measuring method is then used to derive a ranking of alternatives for each DM, which are then aggregated taking into account their relative importance.

Decision making for Pap testing among Pacific Islander women.

This study employed a Multi-Attribute Utility (MAU) model to examine the Pap test decision-making process among Pacific Islanders (PI) residing in Southern California. A total of 585 PI women were recruited through social networks from Samoan and Tongan churches, and Chamorro family clans. A questionnaire assessed Pap test knowledge, beliefs and past behaviour. The three MAU parameters of subjective value, subjective probability and momentary salience were measured for eight anticipated consequences of having a Pap test (e.g., feeling embarrassed, spending money). Logistic regression indicated that women who had a Pap test (Pap women) had higher total MAU utility scores compared to women who had not had a Pap test within the past three years (No Pap women) (adjusted Odds Ratio = 1.10). In particular, Pap women had higher utilities for the positive consequences 'Detecting cervical cancer early, Peace of mind, and Protecting my family', compared to No Pap women. It is concluded that the connection between utility and behaviour offers a promising pathway toward a better understanding of the decision to undergo Pap testing.

A game theoretic model for resource allocation among countermeasures with multiple attributes

We study a strategic, two-player, sequential game between an attacker and defender. The defender must allocate resources amongst possible countermeasures and across possible targets. The attacker then chooses a type of threat and a target to attack. This paper proposes a model for determining optimal resource allocation by combining game theory with a simple multi-attribute utility model. Given a set of possible attributes representing goals or preferences, we allow each player to choose a weight for each attribute, where the subset of attributes with nonzero weights represents that player’s preferences. Every countermeasure is given a score for its effectiveness at both mitigating the effects of an attack in terms of each attribute and reducing the probability of the success of an attack. Furthermore, the consequences of each possible attack are scored in terms of each attribute. The multi-attribute utility aspect of this model uses these scores, along with the players’ weights, to form the basis of the utility (or disutility) for each player. We find that (i) the zero-sum game where the attacker’s and defender’s weights are identical results in the worst losses for the defender, (ii) in general cases the defender’s equilibrium strategy has the result of making the attacker indifferent between multiple attacks and (iii) the use of target-independent countermeasures (i.e. countermeasures which operate at national levels as opposed to operating at differing levels for each target) can increase the cost-effectiveness of countermeasures.

A multi-attribute utility model for generating a sustainability index in the banking sector

The study develops a performance evaluation model for banking while integrating sustainability. This model is based on a multi-attribute utility approach. It accounts for the interests of the various banks' stakeholders in a win–win paradigm. In addition, it yields a global measure of performance as an indication of a bank's sustainability degree, referred to as banking sustainability performance index. This index may constitute a basis for ranking banks. Further, the model may constitute a bridge between the assessment types of financial and extra-financial rating agencies. It can also be seen as a measuring tool that complements the emerging trend of integrated reporting. A real application is performed on three French banks.

Entropy-optimal weight constraint elicitation with additive multi-attribute utility models

We consider the elicitation of incomplete preference information for the additive utility model in terms of linear constraints on the weights. Eliciting incomplete preferences using holistic pair-wise judgments is convenient for the decision maker, but selecting the best pair-wise comparison is difficult. We propose a framework for comparing holistic preference elicitation questions based on their expected information gain, and introduce a procedure for approximating the optimal question. We extend the basic approach to generate reference alternatives that differ on only a few attributes, and to determine when further preference information is unlikely to reduce decision uncertainty. We present results from computational experiments that assess the performance of the procedure and assess the impact of limiting the number of attributes on which the reference alternatives differ. The tests show that the proposed method performs well, and when implemented in a decision support system it may substantially improve on-line elicitation using pair-wise comparisons.

Abstract A03: Designing culturally appropriate health interventions for Pacific Islanders: The “Support Our Women” Pap test study

Abstract Objective: The purpose of this study is to test the efficacy of a social support intervention involving women and their male partners to increase Pap testing behaviors in the Chamorro, Samoan, and Tongan communities of Southern California. Methods: Study participants were Samoan, Tongan, and Chamorro women, ages 21-65, mainly from Southern California; and their male partners. Health educators from three community based organizations spearheaded an organizational sampling approach to recruit eligible women and their male partners from Samoan and Tongan churches and Chamorro clans. Intervention participants received a two-hour culturally tailored workshop that include the following: group activity, information on Pap testing, video, and corresponding materials. Comparison participants received a brochure about Pap testing. Three waves of data are collected from all participants: pretest (before workshop or brochure), posttest1 (immediately after workshop or brochure), and posttest2 (6 months follow-up). Data collected included demographics, acculturation, cervical cancer and Pap testing knowledge, attitudes, beliefs and behaviors; decision making utility (based upon the Multi-Attribute Utility model), and social support (based upon the Medical Outcomes Study - Social Support Survey and Provided Support subscale from Berlin Social Support Scale). Results: A total of 561 women and 488 men who completed pretest and posttest 1, recruited from 75 different churches and clans. Women who had received a Pap test in the past three years report greater social support from their male partners, compared to women who had not had a Pap test within the past three years. The male partners of women who had a Pap test in the past three years believed that they provided more social support to their partner, compared to the male partners of women who had not had a Pap test within the past three years. There were also nearly significant increases (1.41 points for intervention vs. .87 points for control; p < .07) in all decision making scores from pretest to posttest1. Specifically, two MAU consequences (“feeling embarrassed about Pap tests” and “protecting my family by receiving a Pap test”) showed significant increases (.16 vs. .04, p < .05; and .20 vs. .08, p < .05; respectively). Conclusion: Our findings suggest that the intervention, which facilitated increased social support from women's male partners, resulted in higher Pap testing behaviors among women themselves. Application: The relationship between social support and Pap testing may be especially relevant for populations beyond Pacific Islanders, since there are many collectivistic cultures that place a greater importance on the well-being of others within their social network compared to themselves. Citation Format: Sora Park Tanjasiri, Lola Santos, Michele Mouttapa, Jie Weiss, Jasmine DeGuzman Lacsamana, Lou Quitugua, Isileli Vunileva, Elenoa Vaikona, Vanessa Tui'one May, Peter Flores, Perci Flores, Dorothy Vaivao, Marina Tupua, Genesis Lutu. Designing culturally appropriate health interventions for Pacific Islanders: The “Support Our Women” Pap test study. [abstract]. In: Proceedings of the Seventh AACR Conference on The Science of Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; Nov 9-12, 2014; San Antonio, TX. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2015;24(10 Suppl):Abstract nr A03.

Unchained melody: revisiting the estimation of SF-6D values

In the original SF-6D valuation study, the analytical design inherited conventions that detrimentally affected its ability to predict values on a quality-adjusted life year (QALY) scale. Our objective is to estimate UK values for SF-6D states using the original data and multi-attribute utility (MAU) regression after addressing its limitations and to compare the revised SF-6D and EQ-5D value predictions. Using the unaltered data (611 respondents, 3503 SG responses), the parameters of the original MAU model were re-estimated under three alternative error specifications, known as the instant, episodic, and angular random utility models. Value predictions on a QALY scale were compared to EQ-5D3L predictions using the 1996 Health Survey for England. Contrary to the original results, the revised SF-6D value predictions range below 0 QALYs (i.e., worse than death) and agree largely with EQ-5D predictions after adjusting for scale. Although a QALY is defined as a year in optimal health, the SF-6D sets a higher standard for optimal health than the EQ-5D-3L; therefore, it has larger units on a QALY scale by construction (20.9% more). Much of the debate in health valuation has focused on differences between preference elicitation tasks, sampling, and instruments. After correcting errant econometric practices and adjusting for differences in QALY scale between the EQ-5D and SF-6D values, the revised predictions demonstrate convergent validity, making them more suitable for UK economic evaluations compared to original estimates.

Strategic priority setting for vaccines policy and global health education

Abstract Background Priority setting for new and existing vaccines is a complex but important task. Health outcomes or cost-effectiveness are not the only criteria for priority ranking of vaccine candidates. Real life prioritisation and development of new vaccines invariably involves balancing many programmatic features, including dosage requirements and cost (and their consequences on coverage and efficacy), developmental risk, interface with existing programmes (for example, vaccination schedules and capabilities), focus on special populations, and even the strengthening of homeland security or public health aid. We aimed to develop a software tool to assist in the process of ranking candidate vaccines. Methods SMART Vaccines (Strategic Multi-Attribute Ranking Tool for Vaccines) combines population-specific data about demographics, health burdens, costs of disease treatment, and design attributes of potential new vaccines to support a multi-attribute utility model. The software offers 28 total attributes (plus up to seven user-defined attributes) from which users can select and weight a subset (maximum of 10) to create SMART Scores to rank candidate vaccines. Sensitivity-analysis tools built into SMART Vaccines allow users to specify the most desirable target product profiles for a single disease, or the ranking of candidate vaccines across different diseases. The programme also allows users to add attributes to the model, and to specify the weights given to the seleted set of attributes used in evaluation of vaccine candidates. Findings Preliminary testing with a range of public health organisations and vaccine developers has demonstrated that the concept underlying SMART Vaccines can be expanded for comparisons between public health interventions (treatment versus prevention of disease options), and even to quite different uses such as vaccines for animal health. Interpretation Early uses of SMART Vaccines have demonstrated that the multi-criteria approach not only enhances transparency in public health decision making, but also allows incorporation of many influential factors that remain hidden or unrecognized in more traditional cost-effectiveness analysis. Furthermore, use of SMART Vaccines facilitates decision convergence when stakeholder interests have conflicting priorities. To bolster the further development of SMART Vaccines, we envision a user community with research universities, especially those with strengths in global public health, to act as the software host. Funding US Department of Health and Human Services, National Vaccine Program Office and Fogarty International Center, National Institutes of Health.