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Multiplicative Utility Function
Abstract
This paper presents sufficient conditions for a multiattribute utility function to be either multiplicative or additive. The number of requisite assumptions to imply the main result is equal to the number of attributes. Because the assumptions involve only trade-offs between two attributes at a time or lotteries over one attribute, it is reasonable to expect that decision makers can ascertain whether these assumptions are appropriate for their specific problems. Procedures are given for verifying the assumptions and assessing the resulting utility functions. The paper concludes with a sketch of a recent application of the results to a six-attribute problem relating to the development of Mexico City's airport facilities.
... Because of the simplicity of the required operations, our algorithm is shown to have computational times comparable to those of standard numerical evaluation software for graphical models (Section 4.4). In contrast to standard software, which assumes an additive factorization between utility nodes, we also explicitly analyze cases when the more general class of multiplicative utility functions might be necessary [29,30,44]. We concentrate our study on the class of multiplicative factorizations because this provides some computational advantages over, for example, the more general class of multilinear utilities [30], whilst allowing for enough flexibility to model the DM's preferences in many real cases [22,29]. ...
... In contrast to standard software, which assumes an additive factorization between utility nodes, we also explicitly analyze cases when the more general class of multiplicative utility functions might be necessary [29,30,44]. We concentrate our study on the class of multiplicative factorizations because this provides some computational advantages over, for example, the more general class of multilinear utilities [30], whilst allowing for enough flexibility to model the DM's preferences in many real cases [22,29]. This factorization turns out to be particularly efficient since it leads to a distributed propagation of EUs as shown in Proposition 1. ...
... and P 0 (·) denotes the power set without the empty set, n I is the number of elements in the set I. For h = 0, the multiplicative factorisation of an MID, U (y [n] ), is a weighted sum of the terms U (y P i ): thus coinciding with the class of commonly used additive factorizations [29]. Therefore the methodology we develop here applies to utility factorizations of additive form, or additive IDs, as well. ...
Influence diagrams provide a compact graphical representation of decision problems. Several algorithms for the quick computation of their associated expected utilities are available in the literature. However, often they rely on a full quantification of both probabilistic uncertainties and utility values. For problems where all random variables and decision spaces are finite and discrete, here we develop a symbolic way to calculate the expected utilities of influence diagrams that does not require a full numerical representation. Within this approach expected utilities correspond to families of polynomials. After characterizing their polynomial structure, we develop an efficient symbolic algorithm for the propagation of expected utilities through the diagram and provide an implementation of this algorithm using a computer algebra system. We then characterize many of the standard manipulations of influence diagrams as transformations of polynomials. We also generalize the decision analytic framework of these diagrams by defining asymmetries as operations over the expected utility polynomials.
... Based on the attributes and the decision strategy, the "best" option from the decision maker's perspective has to be identified and selected. We apply the two decision strategies EBA [10] and MAU [33]. ...
... whereby the base b > 1 and the factor β have to be suitably chosen. For the additive utility function we have to set β = 1 to ensure n ∑ k=1 α k = 1 (Keeney, 1974). For the multiplicative utility function, we know based on [33] that if n ∑ k=1 α k > 1, then a multiplicative utility function has to be employed, and for λ, ...
... For the additive utility function we have to set β = 1 to ensure n ∑ k=1 α k = 1 (Keeney, 1974). For the multiplicative utility function, we know based on [33] that if n ∑ k=1 α k > 1, then a multiplicative utility function has to be employed, and for λ, ...
This paper explores consumer decision making, particularly focusing on the increasing prevalence of choices on the Internet such as online shopping. Examining the fundamental question of how individuals decide how to decide, our paper draws upon the effort–accuracy framework. This framework indicates that people typically consider both the cognitive effort associated with employing a specific decision strategy and the decision quality (i.e., accuracy) implied by using a particular strategy. However, decision strategies with high accuracy imply high effort. Empirical evidence shows that people often use decision strategies that require little effort. As a result, accuracy is often not high. Against this backdrop, this paper introduces a quantitative approach leveraging principal component analysis (PCA) as a decision support tool. Based on a simulation study, the approach demonstrates that it is possible to maintain high accuracy with significantly reduced effort in multi-attribute decision situations where attribute information is available in a quantitative format. This demonstration is based on the example of two decision strategies, which are both theoretically and practically highly relevant: the multi-attribute utility model (MAU) and the elimination-by-aspects strategy (EBA). By employing PCA for dimensionality reduction, the approach becomes particularly advantageous for online shops and online comparison portals, presenting users with concise yet accurate information. It is important to emphasize that our PCA approach is designed for data with a natural ordering, primarily focusing on quantitative variables. Consequently, decision situations where qualitative variables (e.g., product design or color) play a role in the decision-making process will need further exploration in future studies. However, we present a first solution to this problem so that our approach, based on this solution, can be implemented by online shops and online comparison portals in the near future.
... In our model, all Aoriented users are identical in the sense that they all prefer Platform-A to Platform-B (Keeney 1974;Al-Najjar 2004). Likewise, all Boriented users prefer Platform-B to Platform-A. ...
... com/ marke ting-solut ions/ audience 3 For example, advertisers understand that Instagram has more interestbased targeting options and Facebook has more advanced behavioral targeting options but may not know precisely how their targeting algorithms work.4 This modeling specification is applicable in cases where individuals have similar characteristics, goals, and preferences and the decisions being made affect them in similar ways(Keeney 1974;Al-Najjar 2004).5 A similar specification has been used in the literature on network markets(Katz and Shapiro 1992;Church and Gandal 1993;Economides 1996).6 ...
When two social media platform businesses merge, a critical decision for the merged entity is whether to keep both platforms operational. We investigate the role of user‐homing and the platforms' user bases and advertiser bases in the decision. The only source of revenue for the platforms is the fees charged to the advertisers for advertising on the platforms. Different groups of advertisers have different platform preferences. The main results show that when all users single‐home (multihome), the gain from the merger is more from keeping one (both) platform operational. A merger is welfare increasing if the users single‐home.
... Such quantitative tools and methods include, but are not limited to, correlation of force calculators (Hogg, 1993), Lancaster equations (Taylor, 1974), and Markov chains (Chung, 1967) to model attrition and forecast combat power for both combat and noncombat forces. Additionally, we do not provide a definitive decision-making methodology, such as multi-objective decision analysis (Keeney, 1974), though the use of axiomatic decision analysis methods would improve overall decision quality and eliminate the potential arbitrary ranking of different COAs. None of these limitations prevent the use of our methodology in support of tactical assessments, as they are only means of improving a staff's analytical capacity. ...
... None of these limitations prevent the use of our methodology in support of tactical assessments, as they are only means of improving a staff's analytical capacity. Ultimately, an effective tactical assessment requires quantitative and qualitative inputs to address the commander's values and preferences (Keeney, 1974). ...
A formal methodology for the development and execution of a tactical assessment process in support of large-scale combat operations does not exist in current U.S. Army doctrine. Current doctrine describes the assessment process for the operational and strategic levels of war and provides general guidelines for integration into the Joint Planning Process. However, existing doctrinal gaps result in inconsistent assessment processes and products for enabling tactical decision making. As a result, division and corps assessments cells do not possess a fully articulated doctrinal methodology for developing and integrating assessments into the organization's planning process. Building off current doctrine and best practices, we provide a methodology for developing and integrating tactical assessment frameworks with doctrinal planning processes. Our methodology outlines the inputs and outputs for production and execution of a tactical assessment plan enabling risk-informed decision making in large-scale combat operations. This tactical assessment methodology is up to date with current doctrine, and is adaptable to the full spectrum of tactical military operations. This methodology also enables robust and repeatable operational assessments that effectively inform commander decisions. By deliberately building an assessment framework concurrent with an operations plan, we enable robust and relevant assessments that provide improved decision making, and enhanced interoperability among U.S. Army division and corps-level headquarters.
... This summary is extended to discuss the applicability of MCDA techniques for use in decision making within a sample of commonly utilized modeling paradigms. Research and practical application have shown that additive models are the most extensively used model in multi-criteria decision analysis [56]. However, a review of these techniques uses and applications within M&S has not been conducted. ...
... The interpretation of an attribute weight within a particular modeling framework should be the same regardless of the method used to obtain weights [65]; however, the same consistency in attribute weighting cannot be said to be present across all multi-criteria decision analysis frameworks [66]; • Consider the ranges of attributes. People tend to neglect accounting for attribute ranges when assigning weights using weighting methods that do not stress them [56,67]; rather, these individuals seem to apply some intuitive interpretation of weights as a very generic degree of importance of attributes, as opposed to explicitly stating ranges, which is preferred [68][69][70]. This problem could occur when evaluating job opportunities. ...
Computational models and simulations often involve representations of decision-making processes. Numerous methods exist for representing decision-making at varied resolution levels based on the objectives of the simulation and the desired level of fidelity for validation. Decision making relies on the type of decision and the criteria that is appropriate for making the decision; therefore, decision makers can reach unique decisions that meet their own needs given the same information. Accounting for personalized weighting scales can help to reflect a more realistic state for a modeled system. To this end, this article reviews and summarizes eight multi-criteria decision analysis (MCDA) techniques that serve as options for reaching unique decisions based on personally and individually ranked criteria. These techniques are organized into a taxonomy of ratio assignment and approximate techniques, and the strengths and limitations of each are explored. We compare these techniques potential uses across the Agent-Based Modeling (ABM), System Dynamics (SD), and Discrete Event Simulation (DES) modeling paradigms to inform current researchers, students, and practitioners on the state-of-the-art and to enable new researchers to utilize methods for modeling multi-criteria decisions.
... The overall satisfaction of some participants may depend on a small number of benefits, for example they may be willing to adopt a lower bag limit or even a catch-and-release policy in exchange for a longer fishing season (Sutton, 2003;Abbott et al., 2018). Other participants may value a balance across a wider variety of benefits, and derive a higher overall utility if no single benefit is completely sacrificed to gain others (Keeney, 1974). ...
... closer to asymptotic utility values) under steeper curvatures, so there is less potential gain in total utility by increasing size limits to lengthen seasons. Alternative approaches to aggregating utility components, such as using products instead of sums, could make these trade-offs less extreme because no utility components would be fully sacrificed, otherwise the total utility would also be low (Keeney, 1974). Likewise, more fully incorporating heterogeneity in preferences between different segments of the population could make these trade-offs less extreme. ...
Recreational fishing benefits associated with angling opportunity, such as fishing season duration and certainty of season duration, may outweigh trip-based benefits, such as retained catch, in measures of angler utility. We developed an age-structured population dynamics model to predict how these three beneficial attributes are affected by four recreational management parameters: minimum size limit; bag limit; inter-season quota transfer limits; and in-season adjustment of season duration. We incorporated results of stated-preference angler surveys to produce a bioeconomic model for two case studies: Atlantic Florida red snapper, and central Oregon Pacific halibut. In maximizing long-term total utility, a strong trade-off between season length and retained daily catch was observed in both fisheries, arising from increased minimum size limits which lengthened fishing seasons but reduced daily retained catch. The optimal management policy across the combination of beneficial attributes was sensitive to assumptions of the curvature of utility functions, i.e. to the degree to which anglers value those attributes with diminishing marginal returns, but generally involved satisfying the strong stated preferences for increased angling opportunity.
... , x n ) is u(x 1 , x 2 , . . . , x n ) [21]. Here, we will utilize the concept of the utility independence of attributes (see, e.g. ...
... is the so-called multi-attribute additive utility function [21]. We can get Eq. ...
In many situations, the application of traditional additive measures is not sufficient to describe the uncertainty appropriately. Therefore, new demands have arisen for not necessarily additive, but monotone (fuzzy) measures. Since these measures play an important role in describing various phenomena, there is an increasing interest in them.
... (Attributes are also known as evaluation measures or performance scores.) To compare the alternatives and identify the best one, the decision-maker may model his preferences to develop a value function and select the alternative that has the greatest value (Keeney, 1974;Keeney and Raiffa, 1993). If the magnitudes of the attributes are known (that is, there is no uncertainty about them), then this is straightforward. ...
... Generally, this work builds on the foundations of multi-attribute decision analysis (Keeney andRaiffa, 1976, 1993), statistical decision theory (Raiffa and Schlaifer, 1961;Pratt et al., 1995), optimization under uncertainty (Powell, 2016), and the economic value of information (Lawrence, 1999). Howard (1970) illustrated the key concepts related to analyzing experimentation decisions with a coin-flipping example. ...
Attributes provide critical information about the alternatives that a decision-maker is considering. When their magnitudes are uncertain, the decision-maker may be unsure about which alternative is truly the best, so measuring the attributes may help the decision-maker make a better decision. This paper considers settings in which each measurement yields one sample of one attribute for one alternative. When given a fixed number of samples to collect, the decision-maker must determine which samples to obtain, make the measurements, update prior beliefs about the attribute magnitudes, and then select an alternative. This paper presents the sample allocation problem for multiple attribute selection decisions and proposes two sequential, lookahead procedures for the case in which discrete distributions are used to model the uncertain attribute magnitudes. The two procedures are similar but reflect different quality measures (and loss functions), which motivate different decision rules: (1) select the alternative with the greatest expected utility and (2) select the alternative that is most likely to be the truly best alternative. We conducted a simulation study to evaluate the performance of the sequential procedures and hybrid procedures that first allocate some samples using a uniform allocation procedure and then use the sequential, lookahead procedure. The results indicate that the hybrid procedures are effective; allocating many (but not all) of the initial samples with the uniform allocation procedure not only reduces overall computational effort but also selects alternatives that have lower average opportunity cost and are more often truly best.
... However, these are almost exclusively designed to work when the utility can be assumed to factorize additively, i.e. assuming that the utility can be written as a linear combination of smaller dimensional functions over disjoint subsets of the decision problem's attributes. An exception is the multiplicative influence diagram (Leonelli, Riccomagno and Smith, 2015), whose evaluation algorithm works not only for additive factorizations but also for more general multiplicative ones (Keeney, 1974). ...
A variety of statistical graphical models have been defined to represent the conditional independences underlying a random vector of interest. Similarly, many different graphs embedding various types of preferential independences, as for example conditional utility independence and generalized additive independence, have more recently started to appear. In this paper we define a new graphical model, called a directed expected utility network, whose edges depict both probabilistic and utility conditional independences. These embed a very flexible class of utility models, much larger than those usually conceived in standard influence diagrams. Our graphical representation, and various transformations of the original graph into a tree structure, are then used to guide fast routines for the computation of a decision problem's expected utilities. We show that our routines generalize those usually utilized in standard influence diagrams' evaluations under much more restrictive conditions. We then proceed with the construction of a directed expected utility network to support decision makers in the domain of household food security.
... Some examples can be given as follows. Keeney (1972Keeney ( , 1974Keeney ( , 1977 tried to systematically reveal the approaches that will reveal the highest expected utility in the evaluation of multiple utility functions, in election situations involving uncertainty. Shapiro (1976) dealt with multi-criteria public investment decision making with mixed integer programming. ...
Multi-criteria decision-making techniques have been developed for solving complex problems with more than one alternative, and many types have emerged over time due to their importance/benefit. These models help the process of making the most accurate decision by evaluating many quantitative and qualitative criteria in a wide variety of sectors/fields. The COPRAS model is one of these methods and has been used to solve many problems and make decisions since its introduction in 1994. The COPRAS method also contains a problem that overshadows its importance. In the COPRAS method, a weighted normalised decision matrix is constructed to obtain dimensionless weighted values from comparative indices. At this stage, if the denominator is negative, this process not only fails to produce the desired result, but also reverses the ranking and prepares the ground for the selection of the wrong alternative. This study proposes a solution that eliminates this negative sum problem in the COPRAS method and ensures the smooth operation of the COPRAS method.
... It can be both quantitative and qualitative. Many researchers have worked in this area starting with Fishburn [6] followed by Keenley [7,8]. Chen [9] proposed MADM under fuzzy environment. ...
In our daily lives, individuals face countless choices across different aspects. Many a times these decisions are made based on a number of factors, some of which are obvious, whereas some of them are vague and not precise. These can result in facing certain challenges while making decisions. To handle such situations Multi-Criteria Decision Making (MCDM) techniques have been developed. The aim of this article is to suggest a method to rank and hence choose a university for students’ admission using the method Fuzzy Technique for Order of Preference by Similarity to Ideal Solution (FTOPSIS). To achieve the goal a novel distance measure has been proposed, and some axiomatic properties have also been proved for the same. The proposed approach aids in the process of university selection by ranking the universities based on certain criteria in fuzzy environment. The results obtained suggest that the proposed model provides a accurate way to select the best university among the large number of choices available for the considered universities. The paper settles with a discussion of a case study and experimental findings.
... Multi-criteria decision-making (MCDM) methods are methodologies developed in the general context of decision science to structure and formalize complex decision-making processes. The context of decision-making methods can be broadly subdivided into two categories, the Multi-Attribute Utility Theory (MAUT) methods [26,27], and the methods based on the outranking concept [28]. The application of either multi-criteria decision approaches in ranking or selecting the most suitable vehicle among a set of different technological alternatives is a topic frequently discussed in the literature [29][30][31][32][33]. ...
In the last decade, with the increased concerns about the global environment, attempts have been made to promote the replacement of fossil fuels with sustainable sources. For transport, which accounts for around a quarter of total greenhouse gas emissions, meeting climate neutrality goals will require replacing existing fleets with electric or hydrogen-propelled vehicles. However, the lack of adequate decision support approach makes the introduction of new propulsion technologies in the transportation sector a complex strategic decision problem where distorted non-optimal decisions may easily result in long-term negative effects on the performance of logistic operators. This research addresses the problem of transport fleet renewal by proposing a multi-criteria decision-making approach and takes into account the multiple propulsion technologies currently available and the objectives of the EU Green Deal, as well as the inherent scenario uncertainty. The proposed approach, based on the TOPSIS model, involves a novel decision framework referred to as a generalized life cycle evaluation of the environmental and cost objectives, which is necessary when comparing green and traditional propulsion systems in a long-term perspective to avoid distorted decisions. Since the objective of the study is to provide a practical methodology to support strategic decisions, the framework proposed has been validated against a practical case referred to the strategic fleet renewal decision process. The results obtained demonstrate how the decision maker’s perception of the technological evolution of the propulsion technologies influences the decision process, thus leading to different optimal choices.
... During the assessment of multi-attribute utility functions, each transformation function must satisfy additive, utility, or preferential independence (Fishburn and Keeney, 1974;Keeney, 1974;Keeney and Raiffa, 1993). If the addition is selected, the transformation/utility functions must satisfy De Morgan's laws (Dombi and Csiszár, 2021). ...
The utility function-based sum of ranking differences (uSRD) method is proposed as a utility function-based multi-criteria decision analysis tool. Our idea is that the transformation functions can be represented by a utility function that can be aggregated with multi-attribute utility functions. We present a framework incorporating utility values as the basis for three different but interconnected analyses. The exemplary application focuses on greenhouse gas emissions and economic indicators of 147 countries. First, the uSRD is applied to the utility values to uncover the hidden relationships of the 40 indicators. A ranking of countries is established to see which sample performs the best and the worst in both emissions and economy. Lastly, mitigation actions are delegated to countries through a three-stage assignment that connects emissions to utilities, sectors, and mitigation actions. The results show that the uSRD excels as a support tool for decision-making.
... Multi-criteria decision making (MCDM) methods are methodologies developed in the general context of decision science to structure and formalize complex decision-making processes. The context of decision-making methods can be broadly subdivided into two categories, the Multi-Attribute Utility Theory (MAUT) methods [26,27], the methods based on the outranking concept [28]. The application of either multi criteria decision approaches in ranking or selecting the most suitable vehicle among a set of different technological alternatives is a topic frequently discussed in the literature [29,30]. ...
In the last decade, with the increased concerns about the global environmental situation, attempts have been made to promote the replacement of fossil fuels with sustainable sources. For transport, which accounts for around a quarter of total greenhouse gas emissions, meeting climate neutrality goals will require replacing existing fleets with electric or hydrogen propelled vehicles. This research addresses the problem of transport fleet renewal by proposing a multi-criteria decision-making approach, taking into account the multiple propulsion technologies currently available and the objectives of the EU Green Deal, as well as the uncertainty related to the technological scenario, in a generalized Life Cycle framework. The proposed approach, based on the TOPSIS model, demonstrates how the optimality of the choice is related to the different technological scenarios and to the risky attitude of the decision maker. The proposed methodology is finally validated against a practical case referred the strategic fleet renewal decision process, and the results obtained demonstrate how the decision maker’s perception about the technological evolution of the propulsion technologies influences the decision process, thus leading to different optimal choices.
... where m : 2 G → R is a set function such that m(T ) = 0 for all T ⊆ G with |T | > 2. In fact, the model we are proposing can be applied also when constraints in (1) are non-linear, for example, when the preference of the DM can be represented by a multiplicative utility function (Keeney, 1974;Keeney and Raiffa, 1976). In these cases, one can apply an acceptance/rejection method (see e.g. ...
In multiple criteria decision aiding, very often the alternatives are compared by means of a value function compatible with the preferences expressed by the Decision Maker. The problem is that, in general, there is a plurality of compatible value functions, and providing a final recommendation on the problem at hand considering only one of them could be considered arbitrary to some extent. For such a reason, Stochastic Multicriteria Acceptability Analysis gives information in statistical terms by taking into account a sample of models compatible with the provided preferences. These statistics are given assuming the existence of a probability distribution in the space of value functions being defined a priori. In this paper, we propose some methods aiming to build a probability distribution on the space of value functions considering the preference information given by the Decision Maker. To prove the goodness of our proposal we performed an extensive set of simulations. Moreover, a sensitivity analysis on the variables of our procedure has been done as well.
... Notice also that ENDGU social orderings also satisfy another interesting property: evaluations of risks on population size n are independent of the individuals' utility level, provided that all existing individuals have the same utility level in all states of the world and in the two lotteries being compared. This property is known as weak additivity in Pollak (1967) and as preferential independence in Keeney (1974). However, this property is also satisfied by ENWGU social orderings with F constant and G non-constant, so it does not characterize ENDGU. ...
Utilitarianism is the most prominent social welfare function in economics. We present three new axiomatic characterizations of utilitarian (that is, additively-separable) social welfare functions in a setting where there is risk over both population size and individuals’ welfares. We first show that, given uncontroversial basic axioms, Blackorby et al.’s (J Popul Econ 11:1–20, 1998) Expected Critical-Level Generalized Utilitarianism is equivalent to a new axiom holding that it is better to allocate higher utility-conditional-on-existence to possible people who have a higher probability of existence. The other two characterizations extend and clarify classic axiomatizations of utilitarianism from settings with either social risk or variable-population, considered alone.
... It is one of the fastest growing fields of Operation Research (OR) and can be carved into two categories: MODM (Multi Objective Decision Making) and MADM (Multi Attribute Decision Making). Multi-Attribute Utility Theory [1][2] was the commonly utilized MCDM method. Many researchers have contributed to this branch of study and its applications have been employed in many areas like quality control [3], risk management [4], production management etc. [5]. ...
... Prior research ([5]) has used multiattribute utility functions that are either multiplicative or additive. We add a new multiplicative term vqx in the utility function used in the base model. ...
The number and impact of open source projects is increasing. We examine the impact of competition from open source software (OSS) on proprietary software providers by analyzing three cases: (i) proprietary software as a monopoly, (ii) mixed duopoly competition between proprietary software provider and OSS, and (i) duopoly competition between two proprietary software providers. We use an analytical model to capture two important features of OSS: (i) its zero licensing price and (ii) its lower usability in comparison with proprietary software. Prior studies have shown that competition from OSS causes the proprietary software provider to produce software that is both lower quality and lower priced than software offered by a monopolist. In contrast, our paper shows that these results hold under certain conditions but are not always true. We find that competition from OSS can induce the proprietary software provider to increase its software quality and price relative to those of the monopolist when the proprietary software provider’s cost of enhancing software quality is moderate. Surprisingly, we also find that competition from OSS can lead to a reduction in social welfare. Whereas prior research has shown this result in the context of network effects, we show that this can occur in the absence of network effects and offer a novel explanation.
... To develop our proposed formulations (Equations 4.1,4.3,4.5), we used the concept of additive and multiplicative effects in decision making (Anderson, 1965;Keeney, 1974). The additive effect implies that an effect of an extreme variable moderately decreases by another more neutral variable; however, through the multiplicative effect, an extreme variable can produce an exaggerated effect (Hensley & Levin, 1976). ...
For decades, the interaction between water and people has attracted hydrologists’ attention. However, the coevolution of social and natural processes, which occurs across a range of time scales, has not yet been adequately characterized. This research gap has motivated more research in recent years under the umbrella of “socio-hydrology”. The purpose of socio-hydrology is to posit the endogeneity of humans in a hydrological system and then to investigate feedback mechanisms between hydrological and human systems that might lead to emergent phenomena.
The current state-of-the-art in socio-hydrology faces several challenges that include (1) a tenuous connection of socio-hydrology to broader research on social, economic, and policy aspects of water resources, (2) the (in)capability of socio-hydrological models to capture human behavior by generic feedback mechanisms that can be extrapolated to other places, and (3) unsatisfying calibration or validation processes in modeling. To address the first gap, a socio-hydrology study needs to connect proper social theories on water-related human decision making with a water resource model based on a given context and scale. Addressing the second gap calls for socio-hydrology research with case studies in different and contrasting regions and at different scales. In fact, such study can shed light on the similarities and differences in socio-hydrological systems in different contexts and scales as initial steps for future research. The third research gap calls for a socio-hydrology study that improves calibration and validation processes. Thus, to address all these gaps in one thesis, two case studies with completely different environments are chosen to investigate various phenomena at different scales.
The research presented here contributes to socio-hydrological understanding at two spatial scales. To account for the heterogeneity of human decision making and its interactions with the hydrologic system, an agent-based modeling (ABM) approach is used in this research. The first objective is to explore human adaptation to drought as well as the subsequent expected or unexpected effects on the agricultural sector and to develop a socio-hydrological model to predict agricultural water demand. To do so, an agent-based agricultural water demand model (ABAD) is developed. This model is applied to the Bow River Basin in Alberta, Canada, as a study region, which has recently experienced drought periods. The second objective is to explore conflict-and-cooperation processes in transboundary rivers as socio-hydrological phenomena at a large scale. The Eastern Nile Basin Socio-hydrological (ENSH) model is developed and applied to the Eastern Nile Basin (ENB) in Africa in which conflict-and-cooperation dynamics can be seen among Egypt, Sudan, and Ethiopia. The ENSH model aims to quantify and simulate these countries’ willingness to cooperate in the ENB.
ABAD demonstrates (1) how farmers’ attitudes toward profits, risk aversion, environmental protection, social interaction, and irrigation expansion explain the dynamics of the water demand and (2) how the conservation program may paradoxically lead to the rebound phenomenon whereby the water demand may increase after decreasing through modernized irrigation systems. Through the ABAD model analysis, economic factors are found to dominantly control possible rebounds. Based on the insights gained via the model analysis, it is discussed that several strategies, including community participation and water restrictions, can be adopted to avoid the rebound phenomenon in irrigation systems. Fostering farmers’ awareness about the average water use in their community could be a means to avoid the rebound phenomenon through community participation. Also, another strategy to avoid the rebound phenomenon could be to reassign water allocations to reduce farmers’ water rights.
The ENSH model showed that (1) socio-political factors (i.e., relative political stability and foreign direct investment) can explain two historical trends (i.e., (a) fluctuations in Ethiopia’s willingness to cooperate between 1983 and 2009 and (b) a decreasing Ethiopia’s willingness to cooperate between 2009 and 2016); (2) the 2008 food crisis (i.e., Sudan’s food gap) may account for Sudan recovering its willingness to cooperate; and (3) Egypt’s political (in)stability plays a role in its willingness to cooperate.
The outcomes of this research can provide valuable insights to support policymakers for the long-term sustainability of water planning. This research investigates two main socio-hydrological phenomena at different spatial scales: the agricultural rebound phenomenon at a small geographical scale and the conflict and cooperation phenomena at a large geographical scale. The emergence of these phenomena can be a complex resultant of interaction and feedback mechanisms between the social system at the individual, institutional, and society levels and the hydrological system. Through developing quantitative socio-hydrological models, this research investigates the feedback mechanisms that may lead to the rebound phenomenon at a small scale and the conflict and cooperation phenomenon at a large scale. Finally, the research shows how these socio-hydrological models can be used for sustainable water management to avoid negative long-term consequences.
... tarafından portföy seçim problemine uygulanmak amaçlı oluşturulan SAW (Simple Additive Weighting) yöntemi, Ağırlıklı Toplam Model (Weighted Sum Model) olarak da bilinmektedir (Çakır ve Perçin, 2013: 452).Fayda teorisi olarak karşılık bulan MAUT yöntemi, Fisburn (1967) veKeeney (1974) tarafından uygulanmaya başlanmıştır (Ömürbek, Karaatlı ve Balcı, 2016: 239). Çok nitelikli fayda teorisi karar yöntemlerinin çeşitli ihtiyaçları hesaplaması nedenli uygun bir karar verme yöntemi olarak belirlenmiştir. ...
İnsani kalkınmayı belirleyebilmek için insan ile alakalı birçok konuya hâkim olmak gerekmektedir. Bu durum coğrafyadan coğrafyaya, ülkeden ülkeye farklılıklar göstermektedir. İnsan yaşamında sağlık, eğitim, gelir-iş gibi faktörler önemli olduğu kadar özgürlük faktörleri de önemlidir. Bu çalışmanın amacı, her ülkenin kalkınma potansiyelini gösteren 2018 insani kalkınma raporlarında yer alan boyutlara ek olarak; özgürlük boyutları eklendiğinde, ülkelerin yeni potansiyel durumlarını ortaya koymaktır. Çalışmada, Çok Kriterli Karar Verme (ÇKKV) yöntemleri kullanılmıştır. İlk aşamada yaşam beklentisi, sağlık ve gelir endeksi; sonrasında kişisel özgürlük, ekonomik özgürlük ve bireysel özgürlük endeksi belirlenerek toplamda altı boyut alınmıştır. Yaşam beklentisi, gelir ve sağlık ÇÇKV yöntemlerinden ARAS, MAUT, SAW ve Borda Sayım yöntemleri ile analiz edilmiş ardından kalkınma boyutlarına özgürlük boyutları da eklenerek ülkelerin analizleri ortaya konulmuştur. Özgürlük boyutları eklendiğinde sıralamada en çok farklılık gösteren ülkeler Katar, Brunei, Kuveyt, Umman, Suudi Arabistan olmuştur.
... • Analytical Hierarchy Process (AHP) (Saaty et al, 2007) • Preference Ranking Organisation Method for Enrichment Evaluation (PROMETHEE) (Opricovic, 1998) • ELimination Et Choix Traduisant la REalité (ELECTRE) (Benayoun et al, 1966) • Multi-Attribute utility Theory (MAUT) (Keeney, 1974) Belton and Stewart (2002) describe the 'three core elements' of MCDA, which are dominant in all of the methodologies above (including MCDM) which are as follows: ...
Existing research spanning academic and industrial literature shows that due to the ever-increasing number of descriptions of BIM on top of a saturation of standards methods and procedures, with little evidence on how to achieve goals for truly collaborative BIM, a gap is forming between theoretical and applied BIM, and thusly reducing the potential advantages and benefits of implemented BIM. Objectives set as part of this research, post systematic review of both academic and industrial literature were to firstly define a common meaning of what collaborative BIM is through the development of a syntax to support a hypothetical infrastructure project utilising academic and industry BIM experts. This was then followed by bringing to the front the inefficiencies in their current form and define how the fundamental parts of BIM are assigned and then prioritised both qualitatively and quantitively, in order to enhance information clarity (goals and objective achievement) and inconsistency reduction towards better ways of implementation. Conclusive findings derived from this research states that information management was determined by the focus group in being the key and top-level component in achieving collaborative BIM, which was determined via the contribution and development of an objective focused implementation framework adapted from the Analytical Hierarchy Process (AHP). This methodology increases the certainty of goal attainment for project team members, by presenting them with a dynamic qualitative and quantitative methodology that guides, determines and agrees the objective focus in an adaptable method through focal clarity of the intended use and what is required to be achieved through the adoption of collaborative BIM for a range of stakeholders. In summary, the research findings herein assert the need and benefit of objectifying collectively agreed focus on the desire of collaborative BIM including a range of stakeholders. Furthermore, inconsistencies towards agreements of standardisation and quality assurance are revealed, which is countered and supported by the developed novel methodology, in order to reduce the impact of such lack of consensus going forwards towards seeking better understanding and thus implementation of collaborative BIM.
... EO system tradespaceA two objective multiplicative value function[41] computes monthly revenue with a maximum revenue of $200M ...
Motivated by the growth of the commercial space economy and renewed focus on the disaggregation of military space systems, this work develops a method for conceptual design of federated satellite systems as a collaborative system-of-systems (SoS). Objectives seek to improve the likelihood of successful SoS formation and pursue constituent system utility robustness. The proposed metaheuristic optimization tradespace exploration method accounts for technical and economic design variables and multi-decision maker strategy dynamics. Constituent system designs are ranked on their simulated net present value. A game-theoretic measure of risk dominance is used in concert with net present value to assess robustness and utility of candidate SoS designs. The method is validated with a notional application case that assesses potential collaboration between Earth observing and telecommunications systems. Results demonstrate a fundamental trade between system efficiency and robustness and highlight the importance of accounting for strategy dynamics when designing systems for collaboration.
... These implications follow from the specific quasi-separable form of the utility function U. For more details and background including the derivation of K from the k i values in the multiplicative case, see Keeney (1974) or Anderson et al. (1977, p. 86). The essence is that, instead of trying to assess the n-dimensional utility function U(x 1 , x 2 , . . ...
The purpose of the first edition of the book, published in 1997, was to contribute to improved agricultural decision making by explaining what can be done in risk analysis and management. Since 1997 progress has been made in risk analysis in agriculture. The material covered in this second edition has been restructured and most of the 1997 text has been revised. Topics that are more thoroughly dealt with in this edition include: assessing and quantifying the degree of risk aversion of a decision maker; judging how important risk aversion is likely to be in particular circumstances; an improved approach for partially ordering risky stochastic distributions when the decision maker's attitude to risk is not fully known; stochastic simulation and its combination with optimization for the analysis of risky choice; and risk considerations in agricultural policy making. The book is written for advanced undergraduate and postgraduate students of agricultural economics and farm management, as well as advisers to farmers and agricultural research workers. It has 13 chapters and a subject index.
... These implications follow from the specific quasi-separable form of the utility function U. For more details and background including the derivation of K from the k i values in the multiplicative case, see Keeney (1974) or Anderson et al. (1977, p. 86). The essence is that, instead of trying to assess the n-dimensional utility function U(x 1 , x 2 , . . ...
As with earlier editions, the aim of this book is to support better agricultural decision making by explaining what can be done nowadays in risk analysis and risk management. As before, the intended readership includes senior undergraduate or graduate students of agricultural and rural resource management, agricultural research workers, people involved in advising farmers, such as extension workers, financial advisers and veterinarians, some farmers themselves, and policy makers. Methods of risk analysis and management are evolving rapidly. This third edition includes some recent advances in both theory and methods of analysis. New material includes sections on state-contingent versus stochastic production functions and an introduction to the use of copulas for modelling stochastic dependency. Improvements in available software continue to expand the scope to better represent and model real-world risky choices, and this edition has updated its advice concerning use of contemporary software. The book has 13 chapters.
... These implications follow from the specific quasi-separable form of the utility function U. For more details and background including the derivation of K from the k i values in the multiplicative case, see Keeney (1974) or Anderson et al. (1977, p. 86). The essence is that, instead of trying to assess the n-dimensional utility function U(x 1 , x 2 , . . ...
As with earlier editions, the aim of this book is to support better agricultural decision making by explaining what can be done nowadays in risk analysis and risk management. As before, the intended readership includes senior undergraduate or graduate students of agricultural and rural resource management, agricultural research workers, people involved in advising farmers, such as extension workers, financial advisers and veterinarians, some farmers themselves, and policy makers. Methods of risk analysis and management are evolving rapidly. This third edition includes some recent advances in both theory and methods of analysis. New material includes sections on state-contingent versus stochastic production functions and an introduction to the use of copulas for modelling stochastic dependency. Improvements in available software continue to expand the scope to better represent and model real-world risky choices, and this edition has updated its advice concerning use of contemporary software. The book has 13 chapters.
... Applications of additive and multiplicative modes and their comparison have been studied in various problems, for instance, in index analysis in economics, in mixed probability distributions, in SVD techniques Conklin, 2005, 2006;Lipovetsky, 2009Lipovetsky, , 2013. Transforming to logarithmic scales corresponds to using a multiplicative utility function known by many works (for example, Keeney, 1974;Mehrez et al., 1988). ...
Two Envelopes paradox presents a fascinating problem in probability and decision making. The player is presented with two envelopes and informed that one of them contains twice as much money as the other one. The player takes one of them without looking inside, and is then given the opportunity to change their mind and take the second envelope instead of the first one. Assuming that the 1 st envelope contains a value A, then the 2 nd one can have 2A or A/2 with equal probability, and its expected value is the mean 1.25A, or 25% profit from switching envelopes. It is a great result, but we could denote the amount in the 2 nd envelope as A and repeat the derivation outcome 1.25A already in 1 st envelope, so each of them is worth more than the other one. So, to switch or not to switch?-That is the question. As shown in this article, the ideas borrowed from the Analytic Hierarchy Process can help in resolving this paradox by transforming the ratio scale into the additive or logarithmic scales which correspond to application of the multiplicative utility function.
... La Formule C.1 présente la formule générique de la fonction d'utilité avec quatre attributs, définie par [Kee74]. ...
L'industrie est à la recherche d'un nouveau type de moyens de production, flexibles et reconfigurables, permettant un investissement incrémental suivant la demande du marché.Les lignes de production actuelles de moteurs dans l'industrie automobile sont dédiées à une famille de produits, pour une cadence donnée. L'introduction d'un nouveau produit nécessite de lourds investissements et un arrêt prolongé des lignes.Les installations futures doivent permettre des variations en volume et en type de produits, en utilisant les ressources à leur capacité maximale dans un souci de rentabilité.L'objectif est l'élaboration d'une démarche de conception du système reconfigurable. Des solutions, faisant appel à la robotique collaborative et mobile et à des principes de modularité de l'équipement, sont proposées et évaluées via simulation. La configuration présentant le meilleur compromis performance-reconfigurabilité-investissements est retenue.L'attitude du décideur face au risque est également prise en compte, afin de le guider au mieux lors la conception.
... The development of multiattribute utility theory from a utility framework is also well illustrated elsewhere. 31 The process of MCDA in the context of HTA could be summarized in the phases of problem structuring, model building, model assessment, model appraisal, and the development of action plans. 32 In turn, these phases include the steps of selecting and structuring criteria, measuring the performance of alternative options, scoring the options, weighting the criteria, calculating weighted aggregate scores, dealing with uncertainty, and examining the findings. ...
The Institute for Clinical and Economic Review (ICER) in the United States recently published a 2020 update to its value assessment framework. We are commenting on the method by which the benefits of health interventions are integrated, relating to contextual considerations and other factors relevant to an intervention’s value. We start by discussing the theoretical foundations of decision analysis and its extension to multiple criteria decision analysis (MCDA). Then we provide a detailed, evidence-based response to some of the claims made by ICER with regard to the use of MCDA methods and stakeholder engagement. Finally, we provide a number of recommendations on the use of quantitative decision analysis and decision conferencing that could be of relevance to the ICER methodology. Overall, we agree that some of the proposed changes by ICER are moving in the right direction toward improving transparency in the value assessment process, but these changes are probably inadequate. We advocate that more serious attention should be paid to the use of quantitative decision analysis together with decision conferencing for the construction of value preferences via group processes for the integration of an intervention’s various benefit components.
... However, it is difficult to obtain data on the travel purpose and passenger types. 5 See Keeney (1974). In addition, intuitively, if the connection is super-fast and has no stops, there would still be no connectivity when there is no seat available. ...
This study proposes a series of statistical and regression approaches to investigate city-cluster transport connectivity patterns. Three major city clusters in China are selected for this study, namely, the Beijing-Tianjin-Hebei (BTH), the Yangtze River Delta (YRD), and the Pearl River Delta (PRD) economic zones. Our analyses examine three aspects of city-cluster connectivity patterns: (i) connectivity distribution among cities within the city cluster; (ii) dependence of the non-center city on the center city; and (iii) the impact of improved intra-city-cluster rail connectivity on air-connectivity distribution. First, it is found that the BTH has the most concentrated connectivity among the three city clusters, with Beijing clearly dominating the other cities in every kind of connectivity. The connectivity distributions are more balanced in the YRD and PRD. Second, the calculated “survival connectivity” and regression analyses suggest that non-center cities heavily rely on the center city as the hub to develop their network connectivity. Such a “hub-and-spoke system” helps a non-center city improve total connectivity but reduces its direct connectivity to other cities outside the city cluster. Finally, our regression analysis shows that improved intra-city-cluster rail connectivity further deteriorates the air-connectivity disparity within the city cluster, which occurs because the center city benefits more from the upgraded air-HSR (high speed rail) intermodal connectivity because it can attract air passengers from neighboring non-center cities. Relevant policy implications and suggestions are also discussed in the paper. We believe the proposed statistical and regression approaches can be easily applied to examine city-cluster connectivity in other contexts and countries.
... The utility functions for individual attributes may be linear or non-linear, as elicited from the decision maker, and the way the weights on attribute ranges are assessed means that the derived weights may or may not sum to 1.0. If the sum of the weights is not 1.0, the aggregation of the attribute utilities is multiplicative, otherwise it is additive (Keeney, 1974;Keeney and Raiffa, 1976;Hardaker et al., 2015, ch. 10). 3 Despite the theoretical merits of MAUT, full implementation of the method confronts difficulties in eliciting the required judgements from decision makers. ...
This study provides a multi-attribute approach to support decisions by Norwegian crop farmers considering adopting innovative crop protection measures. In modelling choice among pest management strategies, we have accounted for both economic risks, risks to human health and risks to the environment. We used the Simple Multi-Attribute Rating Technique (SMART) to evaluate the results of a field trial comparing four different pest management strategies. In the trial, various pre-crops in year one were followed by two consecutive years of winter wheat. Two treatments had different levels of integrated pest management (IPM). IPM1 was the most innovative treatment and used less pesticides (i.e. herbicides, insecticides and fungicides) than IPM2. The third treatment ('Worst Case', WC) used pesticides routinely. The fourth treatment ('No Plant Protection', NPP) used no plant protection measures except one reduced dose of herbicide per year on winter wheat. Two main attributes were included in the SMART analysis, an economic indicator and a pesticide load indicator, each of which comprised a number of attributes at a subsidiary level. The results showed that the IPM1 and NPP strategies performed better than IPM2 and the WC strategies. However, the ranking of the pest management practices depended on the weighting of the two main attributes. Although the SMART analysis gave ordinal utility values, permitting only ranking of the alternatives, we were able to transform the results to measure financial differences between the alternatives.
Benefit-risk assessment is commonly conducted by drug and medical device developers and regulators, to evaluate and communicate issues around benefit-risk balance of medical products. Quantitative benefit-risk assessment (qBRA) is a set of techniques that incorporate explicit outcome weighting within a formal analysis to evaluate the benefit-risk balance. This report describes emerging good practices for the 5 main steps of developing qBRAs based on the multicriteria decision analysis process. First, research question formulation needs to identify the needs of decision makers and requirements for preference data and specify the role of external experts. Second, the formal analysis model should be developed by selecting benefit and safety endpoints while eliminating double counting and considering attribute value dependence. Third, preference elicitation method needs to be chosen, attributes framed appropriately within the elicitation instrument, and quality of the data should be evaluated. Fourth, analysis may need to normalize the preference weights, base-case and sensitivity analyses should be conducted, and the effect of preference heterogeneity analyzed. Finally, results should be communicated efficiently to decision makers and other stakeholders. In addition to detailed recommendations, we provide a checklist for reporting qBRAs developed through a Delphi process conducted with 34 experts.
The textile industry is one of the most complex sectors, in terms of the materials and chemical processes used from petroleum and the environmental degradation during its production and disposal. It is therefore a sector looking for new possibilities and for more sustainable materials and applications. One option is to use natural dyes, as they are considered biodegradable, do not pollute the environment, and have potential use for many sectors, including the fashion industry. In this study, Alanya silk was dyed by a natural dyeing method with crocus sativus, Helichrysum arenarium, and Glycyrrhiza glabra L., plants that grow in and around the Alanya region. Quercus aegilops L. grown in the region was preferred as mordant, a natural binder, and is one of the plants with the highest tannin content, and it was used with a more environmentally friendly and sustainable approach to increase the binding in natural dyeing instead of chemical mordants. The aim is to provide an environmental and scientific contribution to the dyeing producers in this region. According to the MAUT (Multi-Attribute Utility Theory) method, the best dyes in terms of fastness and color efficiency were determined as the dyes made with the Glycyrrhiza glabra L. plant.
We provide a unifying framework for the evaluation of population health. We formalize several axioms for social preferences over distributions of health. We show that a specific combination of those axioms characterizes a large class of population health evaluation functions combining concerns for quality of life, quantity of life and health shortfalls. We refer to the class as (unweighted) aggregations of health-adjusted life years (HALYs). Two focal (and somewhat polar) members of this family are the (unweighted) aggregations of quality-adjusted life years (QALYs), and of disability-adjusted life years (DALYs). We also provide new characterization results for these focal members that enable us to scrutinize their normative foundations and shed new light on their similarities and differences.
Businesses promote their products and services to consumers through advertising in order to create a desire to buy. Today, the development of technology offers businesses a wide range of advertising channel options. Choosing the most suitable advertising channel for businesses is a decision problem that requires the consideration of a large number of contradictory criteria. In this study, advertising behavior of SMEs in Sivas was examined with AHP, DEMATEL and maut methods, one of the multi-criteria decision making methods. In the study, the importance weights of the criteria affecting advertising behavior were determined by AHP and DEMATEL methods. Advertising channel selection was made for a company using MAUT method using criterion importance weights determined by AHP and DEMATEL methods. In the study, AHP and DEMATEL methods were found to be applicable methods in the choice of advertising channels along with the Maut method.
While conflict-and-cooperation phenomena in transboundary basins have been widely studied, much less work has been devoted to representing the process interactions in a quantitative way. This paper identifies the main factors in the riparian countries’ willingness to cooperate in the Eastern Nile River Basin, involving Ethiopia, Sudan, and Egypt, from 1983 to 2016. We propose a quantitative model of the willingness to cooperate at the national and river basin scales. Our results suggest that relative political stability and foreign direct investment can explain Ethiopia’s decreasing willingness to cooperate between 2009 and 2016. Further, we show that the 2008 food crisis may account for Sudan recovering its willingness to cooperate with Ethiopia. Long-term lack of trust among the riparian countries may have reduced basin-wide cooperation. While the proposed model has some limitations regarding model assumptions and parameters, it does provide a quantitative representation of the evolution of cooperation pathways among the riparian countries, which can be used to explore the effects of changes in future dam operation and other management decisions on the emergence of conflict and cooperation in the basin.
Motivated by the growth of the commercial space economy and renewed focus on the disaggregation of military space systems, this work develops a method for conceptual design of federated satellite systems as a collaborative system of systems (SOS). Objectives seek to improve the likelihood of successful SOS formation and pursue constituent system utility robustness. The proposed metaheuristic optimization trade-space exploration method accounts for technical and economic design variables and multi-decision-maker strategy dynamics. Constituent system designs are ranked on their simulated net present value. A game-theoretic measure of risk dominance is used in concert with the net present value to assess the robustness and utility of candidate SOS designs. The method is validated with a notional application case that assesses potential collaboration between Earth-observing and telecommunications systems. The proposed methodology reduces the threshold probability of partner collaboration for which SOS participation is economically rational by up to 18% for the most efficient designs as compared to a typical conceptual design method, thereby increasing the likelihood of successful SOS formation. The results highlight the importance of accounting for strategy dynamics when designing systems for collaboration.
It is a historic fact that the railway as mono-transport had been so long time the major subject of the national transportation project since the Meiji era. This has been continued till the early 1960s when the Japanese economy had taken off and the motorization was about to start. A paradigm shift had been made and the movement had begun to well place the right shares to right transportation modes including road transport in the market of transportation services based on the general-market-equilibrium-oriented analysis. This is the philosophy and concept of the comprehensive transport system. It is the modern topic in transportation economics in the sense that it must give the right answer with the shares as well as reply to the practical concerns by all related stakeholders in the private sectors and the government ministries or departments under the vertically segmented administrative system.
After a risk assessment has been completed and feasible risk reduction measures have been reviewed, decisions must be made to select the most appropriate safeguards and/or a decision taken to determine as to what residual risk would be conditionally accepted. The straightforward way is to set up a binary decision tree and compare for each event scenario, the risk reduction gain versus cost of two or more acceptable alternatives. However, often many contributing factors must be considered, such as: the nature, importance, and context of the risk, availability of the measures, procurement and maintenance costs, the impact to personnel and particularly to the public near the hazardous area, vulnerability of the environment, determination and weighting of important contributing safety factors, and uncertainties inherent to the available information.
In such more complex cases, the decision problem takes the form of building argumentation for a preferred solution with a team of experts, or making a choice from a number of options and selection criteria using the independent opinions of experts/stakeholders. The former is known as the Toulmin model of argumentation, the latter are Multi-Criteria Decision Making (MCDM) methods or Multi-Criteria Decision Analysis. In the latter case, one criterion is weighted as more important than another by experts of which in turn opinion can be weighted based on, e.g., education and experience, together resulting in a ranking of the alternatives. Where the Toulmin model will squeeze out explicit rational arguments sharpened by rebuttal ones, in MCDM/MCDA methods due to the weighting and mathematical processing, the best compromise ranking of the options will result, despite experts’ opinions are intuitive. Well-known is the simple linear model of the Analytic Hierarchical Process (AHP), but a number of more sophisticated methods will be briefly described in this document. In Multi- Attribute Utility Theory (MAUT) utility is a guiding principle, hence economics dominate. A number of methods will be selected for working out an example and comparing results.
Purpose
The purpose of this paper is to test the impact of the soybean rejuvenation plan and the subsidy on farmers' land allocation decisions, which may reference policy adjustment from a micro perspective.
Design/methodology/approach
The paper develops a multi-objective optimized programming model on farm-level, which simulated the land-use changes, as well as the resulting changes in benefits of the rational “typical farm”. The simulation scenarios include changes in subsidy policy and production efficiency, and the baseline scenario was the production status in 2018.
Findings
The results show that an increase in soybean producer subsidy will encourage farmers to allocate more land for soybean planting, which can be considered as a policy tool in promoting soybean production in China. Besides, the effect of subsidy in adjusting soybean acreage for farms is further affected by external conditions such as production technology (such as breeding technology, pesticide and fertilizer application efficiency). Meanwhile, large-scale farms show more significant land adjustments when facing changes in policies and external conditions.
Originality/value
The value of this paper is to simulate the effects of soybean policy and subsidy change on farmers' land-allocation decisions through a multi-objective farmer decision-making model, which provides a micro perspective to understand the implementation effect of the soybean revitalization plan.
div class="section abstract"> This paper proposes a method to evaluate the sensitivity of the perceived quality of a panel interface design to variation in the measurements of fit and finish. The novelty of this approach is in the application of the concept of utility to fit and finish. The significance is in the ability to evaluate alternative designs with regard to perceived quality long before time and money are spent on their realization. In the automotive industry “fit and finish” is the term applied to the precision of the alignment of one part to another. Fit and finish gives the buyer a sense of the overall quality of the vehicle purely from an aesthetic perspective. Fit and finish is usually evaluated by the manufacturer through dimensional measurements of the gap and flushness conditions between panels. Since variation in gap and flushness increases the probability that a vehicle will result in poorly perceived fit and finish, limits are put on the variation to reduce the potential detriment to perceived quality. It is suspected that the customer’s perception of quality is highly influenced by the design of the geometrical interface between panels but there is currently inadequate means of evaluating that influence.
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While our society began to recognize the importance to capture the uncertain preference of people, the existing literature has confined its research work only under a static preference framework in crowdfunding. This paper represents the attempt to incorporate people uncertain preference on product quality and attributes into crowdfunding for production and pricing. More specifically, with describe the uncertain preference of supporters on product quality with robust optimization method, the distribution of the uncertain preference in the worst cases is solved firstly and the corresponding optimal product quality is investigated. Then, according to the different preference of supporters for product attributes, the differentiated pricing strategy is considered in the second stage. Finally, the model is extended to the situation that the third-party platform is participation to illustrate the effectiveness of platform on sharing economy. The research provides the sponsor with the quality level of product production and the corresponding optimal prices for different product quality and attributes. And the results show that: (i) It is optimal for sponsor to increase the unit price of the taste product and not to decide the product quality at the early stage when the risk of investors uncertain preference on product quality is greater than a certain value; (ii) Compare with the low effort level of the platform, the price of the taste product is lower when the platform effort level is high.
par Catherine Le Galès, Catherine Buron, Nathalie Costet, Sophia Rosman et Gérard Slama Le Health Utilities Index (HUI) est constitué d’une classification d’états de santé et d’une fonction de pondération de ces états. La classification permet de décrire la santé d’un individu ou d’une population à un moment donné et au cours du temps. Les états de santé étant multidimensionnels, la théorie de l’utilité multiattribut de Keeney et Raiffa, prolongement de la théorie de l’utilité espérée, permet de construire la fonction de pondération supposant que chaque dimension du HUI est un attribut de la fonction d’utilité. Après avoir rappelé les fondements théoriques retenus pour modéliser la fonction d’utilité multiattribut associée au HUI3, l’enquête de révélation des préférences effectuée en population française et la construction des fonctions d’utilité moyenne et médiane sont présentées et discutées.
Utility theory is interested in people's preferences or values and with assumptions about a person's preferences that enable them to be represented in numerically useful ways. The first two sections of this paper say more about what utility is, why people are interested in it, and how it is interpreted and used in the management and behavioral sciences. The third section summarizes a number of utility theories: it may be used either as a concluding overview of the range and variety of utility theories or as a bridge to the final sections. The final eight sections comprise a semi-technical survey of particular theories for readers interested in greater depth.
Suppose f is a real-valued function on A and A is a subset of X1 × X2 × … × Xn. Then there are real-valued functions f1,…,fn on X1,…,Xn such that f(x) = f1(x1) + … + fn(xn) for all x in A if and only if f(x1) + … + f(xm) = f(y1) + … + f(ym), whenever each xj and yj is in A and is a permutation of ,…, for each i from 1 to n. The relevance of this theorem for measurement theory and especially for expected-utility theory is noted.
This paper introduces and defines the concept of utility independence, and derives general expressions for simplifying the assessment of multiattribute utility functions, given that certain utility independence assumptions hold. These results are more general than the commonly used additive utility function, which is shown to be a special case. Finally, the paper discusses the relevance of this work as an approximation technique when requisite assumptions are not satisfied.
One of the most important concepts in value theory or utility theory is the notion of independence among variables or additivity of values. Its importance stems from numerous multiple-criteria procedures used for rating people, products, and other things. Most of these rating procedures rely on the notion of independence (often implicitly) for their validity. However, a satisfactory definition of independence (additivity), based on multi-dimensional consequences and hypothetical gambles composed of such consequences, has not appeared. This paper therefore presents a definition of independence for cases where the set of consequences X is a product set X1 × X2 × ⋯ × Xn, each element in X being an ordered n-tuple (x1, x2, …, xn). The definition is stated in terms of indifference between special pairs of gambles formed from X. It is then shown that if the condition of the definition holds, the utility of each (x1, x2, …, xn) in X can be written in the additive form φ(x1, x2, …, xn) = φ1(x1) + φ2(x2) + ⋯ + φn(xn), where φi is a real-valued function defined on the set Xi, i = 1, 2, …, n. The development is free of any specific assumptions about φ (e.g., continuity, differentiability) except that it be a von Neumann-Morgenstern utility function, and places no restrictions on the natures of the Xi.
One of the important methodological problems concerning the application of decision analysis to complex problems is the restrictiveness of existing techniques for systematically assessing multiattributed utility functions valid for decision making under uncertainty. This is the problem addressed in this paper. Operational assumptions are postulated about the decision maker's preferences for multiattributed consequences, and functional forms of utility functions satisfying these assumptions are derived. The results are a number of representation theorems which simplify the assessment of the utility function provided the requisite assumptions hold. A special case of these results is the well-known additive utility function. A procedure to verify the appropriateness of the necessary assumptions is included.
The essential character of what is classically considered, e.g., by N. R. Campbell, the fundamental measurement of extensive quantities is described by an axiomatization for the comparision of effects of (or responses to) arbitrary combinations of “quantities” of a single specified kind. For example, the effect of placing one arbitrary combination of masses on a pan of a beam balance is compared with another arbitrary combination on the other pan. Measurement on a ratio scale follows from such axioms. In this paper, the essential character of simultaneous conjoint measurement is described by an axiomatization for the comparision of effects of (or responses to) pairs formed from two specified kinds of “quantities”. The axioms apply when, for example, the effect of a pair consisting of one mass and one difference in gravitational potential on a device that responds to momentum is compared with the effect of another such pair. Measurement on interval scales which have a common unit follows from these axioms; usually these scales can be converted in a natural way into ratio scales.A close relation exists between conjoint measurement and the establishment of response measures in a two-way table, or other analysis-of-variance situations, for which the “effects of columns” and the “effects of rows” are additive. Indeed, the discovery of such measures, which are well known to have important practical advantages, may be viewed as the discovery, via conjoint measurement, of fundamental measures of the row and column variables. From this point of view it is natural to regard conjoint measurement as factorial measurement.
This paper reports an analysis done for the Secretaria de Obras Publicas (Ministry of Public Works) of Mexico to help select the most "effective" strategy for developing the airport facilities of the Mexico City metropolitan area to insure quality air service for the remainder of the century. Effectiveness is a complex function including attributes of cost, safety, capacity of the airport facilities, noise levels, social disruption, and access times. A decision analytic model was used for evaluating strategies. The attributes were adapted to account for impacts over time, and probability density functions and a utility function were assessed over the six attributes. Details of these assessments are given. The results and implications of the analyses are discussed. A unique aspect of the study involved the assessment of a multiattribute utility function and its use to aid an important policy decision.