Number Of Available Alternatives Research Articles

IMPACT OF THE OBJECTIVE ATTRIBUTE WEIGHTING ON FIVE POPULAR MULTI-CRITERIA DECISION-MAKING METHODS: AN EMPIRICAL STUDY

In a Multi Criteria Decision Making (MCDM) problem, it is rarely possible to optimize all objectives simultaneously, since they can be contradictory, ambiguous or may involve other types of inconsistencies or uncertainties. Therefore, when trying to choose from a number of available alternatives, a decision maker is expected to assign weights to attributes whose values are utilized to evaluate the alternative under consideration for ranking. Attributes can be qualitative or quantitative, and their weights can be assigned by the decision maker in a somewhat subjective manner or algorithmically. In this paper, the impact of attribute weighting approaches on the ranking results across a number of widely used MCDM methods are discussed. That is, it examines how different weighting methods affect the results on the same multi-criteria decision-making methods when making a rating. In doing so, consider five MCDM methods, namely, Evamix, Aras, Topsis, Vikor, Waspas, under three different objective attribute weight assignment procedures, namely, Critic, Entropy, and Standart Deviation (SD). Results indicate that, in some cases, the employed attribute weight-assignment mechanism influences the rating results more heavily than the MCDM method itself. In other words, different MCDM methods tend to yield similar results under the same weight assignment method whereas, the same method produces more distinguishable results under different weighting schemes.

Mixed Multinomial Probit Model Accommodating Flexible Covariance Structure and Random Taste Variation: An Application to Commute Mode Choice Behavior

This paper developed a mixed multinomial probit (MMNP) model with alternative error specification and random coefficients (for both generic variables and personal attributes) to accommodate flexible covariance structure and taste variation. The MMNP model can be efficiently estimated with analytic approximations of multivariate normal cumulative distribution functions, which avoid defects of simulation-based integration in the mixed multinomial logit (MMNL) model. The integral dimension of the MMNL model increases as random coefficients increase, but it only depends on the number of available alternatives in the MMNP model. Simulation experiments and empirical analysis of Shanghai commuters’ mode choice behavior were undertaken to examine the performance of MMNP models. Both simulation results and empirical results show that MMNP models can well accommodate flexible covariance structures and taste variation reflected through random coefficients being associated with both generic and personal variables. Empirical results indicate that the MMNP model performs better than traditional discrete choice models, such as the multinomial logit, the cross-nested logit, MMNL, and multinomial probit models. Random coefficients of “in-vehicle time of car” and “number of companions” indicate taste heterogeneity and the identifiability of random coefficients associated with both generic and personal attributes. Pairwise positive correlations between car/taxi, bus/metro, and bus/bus and metro are to be expected. However, the positive correlation between the car and metro modes may be unique to the Chinese city, Shanghai, because of the developed metro system. Unequal error variances reflect heterogeneities in unspecified factors in commute modes’ utilities. The MMNP model will offer an alternative efficient way to accommodate taste heterogeneity and flexible error covariance structure in discrete choice models. Compared with the MMNL model, the MMNP model can accommodate more random coefficients without increasing computational complexity.

TOOLKIT FOR SELECTING TECHNOLOGY AS A TRANSFER OBJECT UNDER MULTI-CRITERIA CONDITIONS

The article analyzes the features of the development of small and medium-sized enterprises (SMEs) in the context of the COVID-19 pandemic. There revealed the negative trends associated with the disproportionality of the sectoral structure of the business and the low enterprises’ innovative activity. The key measures of state support for entrepreneurship taken by the Government of the Russian Federation in the period 2020–2021 are considered. The expediency of stimulating small and medium-sized businesses to participate in the process of technology transfer is determined, based on which the main purpose of the study is formulated, associated with the formation of economic and mathematical tools for choosing a technology for further implementation in the practice of SMEs. The research substantiates the expediency of using the fuzzy-multiple simplified method of analysis of hierarchies by Saaty for choosing technological solutions from a finite number of available alternatives, taking into account the interests of small and medium-sized businesses. The proposed approach makes it possible to increase the degree of validity of management decisions by reducing the volume of metamathematical operations and reducing the impact of subjectivism.

SELECTION OF OUTBOUND LOCATIONS IN GUNUNGKIDUL USING A MULTI-OBJECT OPTIMIZATION METHOD BASED ON REPORTING ANALYSIS

Decision support system (DSS) is a computer-based system that can help users make decisions. One of the DSS applications is to select outbound locations in Gunungkidul by using the Multi-Object Optimization method on the Base Ratio of Analysis (MOORA). Outbound is an open-air learning method based on direct experience presented in the form of games, discussions and adventures. So that participants will get feedback about the impact of the activities carried out which is useful for self-development in the future. The application of the MOORA method is a method that can determine the weight of each criterion, then proceed with a ranking process that will select the best alternative from a number of available alternatives. In this study an application for outbound location selection in Gunungkidul was made using the MOORA method, an application designed based on a website, this test was carried out using black box testing. The results of this study show that the best location based on the criteria weight and ranking with several alternatives is the location of the Nglanggeran Ancient Volcano with a value of 0.1507, Sri Getuk Waterfall with a result of 0.0909, Kampung Jelok with a result of 0.01497, Goa Pindul with a result of 0.00182, Sundak Beach with a result The result is -0.07192, Wulenpari with the result -0.08854, and the last one is Indrayanti beach with the result -0.13179.

Shortlisting procedure with a limited capacity

A decision maker, who is overwhelmed by the number of available alternatives, limits her consideration. We investigate a model where a decision maker’s capacity determines whether she is overwhelmed: She considers all the available alternatives if their number does not exceed her capacity; otherwise, she applies a shortlisting procedure to reduce the number of alternatives to within her capacity. We show how to deduce the decision maker’s capacity, her preference and the alternatives that she considers from the observed behavior. Furthermore, we provide the necessary and sufficient conditions for a consideration function to be derived by the shortlisting procedure with a limited capacity.

Why Do States Intervene in the Elections of Others? The Role of Incumbent–Opposition Divisions

AbstractWhy do states intervene in elections abroad? This article argues that outsiders intervene when the main domestic contenders for office adopt policy positions that differ from the point of view of the outside power. It refers to the split between the government's and opposition's positions as policy polarization. Polarization between domestic political forces, rather than the degree of unfriendliness of the government in office, attracts two types of interventions: process (for or against democracy) and candidate (for or against the government) interventions. The study uses a novel, original data set to track local contenders’ policy positions. It shows that the new policy polarization measurement outperforms a number of available alternatives when it comes to explaining process and candidate interventions. The authors use this measurement to explain the behavior of the United States as an intervener in elections from 1945 to 2012. The United States is more likely to support the opposition, and the democratic process abroad, if a pro-US opposition is facing an anti-US government. It is more likely to support the government, and undermine the democratic process abroad, if a pro-US government is facing an anti-US opposition. The article also presents the results for all interveners, confirming the results from the US case.

Product availability in discrete choice experiments with private goods

The proneness of stated preference methods to different biases has increased the popularity of incentivized choice experiments (ICE). ICEs, however, are not free from challenges. One such challenge when using ICEs in market valuation is that some product alternatives may not be available to incentivize experiments. In this context, withholding information about product availability could be considered deception while disclosing information raises questions regarding influences on participants’ choice behavior. The present study explores this issue by changing the number of available product alternatives in an induced value choice experiment. Participant engagement is captured using an eye-tracking and measurement scales. The results suggest, while incentives matter, engagement matters more. A random-effects logit estimation reveals that engagement is positively correlated with profit-maximizing behavior, while the number of available alternatives is not. A similar result of engagement holds after accounting for differences in payouts between alternatives. In contrast, the same thing cannot be said for number of available alternatives. When the difference between potential payouts is small, no number of available alternatives has a significant effect on profit-maximizing behavior. When the difference between payouts is larger, any number of available alternatives increases the likelihood of choosing the profit-maximizing choice. The findings suggest that researchers could successfully conduct ICE with trustworthy results without having all the product alternatives being available as long as participants are engaged in the choice task.

The decision to check in multialternative choices and limited sensitivity to default

AbstractGiven the rapid proliferation of smartphone applications and data aggregation websites, in many situations people can use decision aids to guide their choices. For example, they may consider whether to use a navigation device to check the fastest route or whether to use a price comparison website to find the cheapest deal. In what circumstances will subjects use a costly comparison decision aid (which I refer to as “checking”) to choose for them? In six studies, I investigate the impact of the number of available alternatives and checking's attractiveness on the decision to check. While at first increasing the attractiveness of checking led to higher checking rates, a further increase in the number of available alternatives (and thus checking's attractiveness) did not increase the checking rate. Surprisingly, even when checking had a 40% higher expected value compared with not checking, the observed checking rate was below 45%, contrary to risk and ambiguity aversion predictions. Furthermore, labeling the checking alternative as the default had no impact on its choice rate. I find large individual differences in decisions to check. Surprisingly, subjects' initial decisions had high predictive power over their subsequent checking rates, even after 100 trials with full feedback. I propose two simple learning models that capture well the aggregated results.

Why Do States Intervene in the Elections of Others?

Why do states intervene in elections abroad? We argue that outsiders intervene when the main domestic contenders for office adopt policy positions that differ from the point of view of the outside power. We refer to the split between the government’s and opposition’s positions as policy polarization. Polarization between domestic political forces, rather than the degree of unfriendliness of the government in office, is what attracts interventions of two types: process (for or against democracy) and candidate (for or against the government) interventions. We provide a novel, original data set to track the policy positions of local contenders. We show that the new policy polarization measurement outperforms a number of available alternatives when it comes to explaining process and candidate interventions. We use it to explain the behavior of the United States as an intervener in elections over the period 1945 to 2012. The United States is more likely to support the opposition, and the democratic process abroad, if a pro-US opposition is facing an anti-US government. It is is more likely to support the government, and undermine the democratic process abroad, if a pro-US government is facing an anti-US opposition. We also present results for all interveners, confirming the results from the US case.

A group decision making support system for the Web: How to work in environments with a high number of participants and alternatives

One of the main challenges that the appearance of Web 2.0 and the overall spreading of the Internet have generated is how to tackle with the high number of users and information available. This problem is also inherited by the group decision making problems that can be carried out over the Web. In this article, to solve this issue, a group decision making support system that allows the use of a high number of participants and alternatives is presented. This method allows any number of participants to join the decision making process at any time. Furthermore, they let them provide information only about a certain subset of alternatives. The high participation rate can provide enough information for the decision process to be carried out even if the participants do not provide information about all the high number of available alternatives.

Choice among two and three alternatives.

Although choice between two alternatives has been widely researched, fewer studies have examined choice across multiple (more than two) alternatives. Past models of choice behavior predict that the number of alternatives should not affect relative response allocation, but more recent research has found violations of this principle. Five pigeons were presented with three concurrently scheduled alternatives. Relative reinforcement rates across these alternatives were assigned 9:3:1. In some conditions three keys were available; in others, only two keys were available. The number of available alternatives did not affect relative response rates for pairs of alternatives; there were no significant differences in behavior between the two and three key conditions. For two birds in the three-alternative conditions and three birds in the two-alternative conditions, preference was more extreme for the pair of alternatives with the lower overall pairwise reinforcer rate (3:1) than the pair with higher overall reinforcer rate (9:3). However, when responding during the changeover was removed three birds showed the opposite pattern in the three-alternative conditions; preference was more extreme for the pair of alternatives with the higher overall reinforcer rate. These findings differ from past research and do not support established theories of choice behavior.

What factors affect cross-modal substitutioň – Evidences from the oslo area

The vast majority of studies on urban travel demand focus on the effect on the demand of one travel mode given a change in the characteristics of that same transport mode, for example, own-elasticities. comparatively little is known about cross-elasticities of demand. In particular, there is a need for a better understanding of the underlying mechanisms of modal substitution, that is a better understanding of cross-modal diversion factors (Dfs) defined as the proportion of people who leave mode a and switch to mode b. The purpose of this article is to investigate what factors explain variations in Dfs across transport modes, submarkets and policy measures. using a recently developed empirical travel mode choice model for the Oslo area, we simulate over 10,000 different Dfs by systematically changing the underlying transport modes, submarkets and policies (size, direction and type of change). With descriptive statistics, we show how the Dfs vary on a general level. most results are immediately intuitive, for example that car drivers mostly substitute to walk for short-distance trips but that those Dfs diminish rapidly with increasing distance. Interestingly, we find rather high Dfs across different forms of public transportation. With successive regression analyses we show that the number of available alternatives and relative market shares significantly affect Dfs.

Inference of Consumer Consideration Sets

When consumers face a large number of alternatives, they tend to simplify the decision problem by reducing the number of available alternatives to a subset of relevant alternatives, i.e. a consideration set. Since consideration sets are typically unobserved, most studies in the demand literature have to assume a consideration model. If these consideration models are misspecified, the demand estimates can be biased. In this paper, we develop an approach to formally test any two competing models of consideration against one another in order to determine which model fits the data best. Our test follows the intuition of a menu approach and uses supplemental data on marginal cost-shifters to construct overidentifying restrictions. We show an application to German retailing of coffee and milk. We find that consideration sets are fundamentally different for coffee and milk, and relate our findings to differences in demand and supply conditions of the two product categories.

A multi-criteria decision model for the selection of professional service innovative organisation

The purpose of this paper is to demonstrate an application of a multi-criteria decision model (MCDM) for the selection of best professional service organisation (PSO) from a number of available alternatives based on service innovation elements. For that purpose, a conceptual model for MCDM has been adopted. Different service innovation elements are classified into critical, objective and subjective factors in the evaluation process and the selection procedure is demonstrated with a hypothetical case. The decision to select a particular professional service organisation is very important when multiple professional service organisations are available. A quantitative basis for comparison and selection of the professional service organisation among a host of alternative professional service organisation could greatly impact on the eventual organisations brand image. Thus, an algorithm - performance value analysis (PVA), for the selection of PSO has been developed from literature. The study expands the scope for managers in selecting the best professional service organisation.

A multi-criteria decision model for the selection of professional service innovative organisation

The purpose of this paper is to demonstrate an application of a multi-criteria decision model (MCDM) for the selection of best professional service organisation (PSO) from a number of available alternatives based on service innovation elements. For that purpose, a conceptual model for MCDM has been adopted. Different service innovation elements are classified into critical, objective and subjective factors in the evaluation process and the selection procedure is demonstrated with a hypothetical case. The decision to select a particular professional service organisation is very important when multiple professional service organisations are available. A quantitative basis for comparison and selection of the professional service organisation among a host of alternative professional service organisation could greatly impact on the eventual organisations brand image. Thus, an algorithm - performance value analysis (PVA), for the selection of PSO has been developed from literature. The study expands the scope for managers in selecting the best professional service organisation.

Introduction to Optimization Models

We refer to a model that uses mathematical programming to find an optimal quantity as an optimization model. Thus, an optimization model differs from an evaluation model in that it goes beyond simply evaluating the consequences of proposed alternatives: It actually identifies the “optimal” alternative. How does an optimization model accomplish this impressive task? In this age of readily available computing power and ever more user-friendly software, it is possible to build and use optimization models without a detailed understanding of the mathematics that underlie the answer to this question. To truly take advantage of this capability, however, it is necessary to have a basic understanding of some core concepts. The primary objective of this note is to introduce these concepts. This note is highly pragmatic; the companion note “The Mathematics of Optimization” (UVA-QA-0683) explores more deeply the mathematical foundations of the concepts and is designed for the user with the motivation and mathematical background to further explore the topic. Excerpt UVA-QA-0682 March 29, 2010 INTRODUCTION TO OPTIMIZATION MODELS The primary source of difficulty in some decisions is the sheer number of available alternatives from which to choose. This is most frequently the case when the decision to be made is the specification of a quantity, such as how large to make a production batch size, what percentage of a portfolio to put into each available investment alternative, or how to allocate an advertising budget among possible vehicles. For those types of decisions, a model that simply evaluates the performance of a given alternative can be useful in facilitating a search over the possible alternatives. Such a model is limited in its value, however. The search it requires can be time-consuming, with no guarantee of ever finding the exact optimal quantity. Frequently, in situations like this, it is possible to identify the optimal quantitywithout resorting to such a search, using a technique known as mathematical programming. We refer to a model that uses mathematical programming to find an optimal quantity as an optimization model. Thus, an optimization model differs from an evaluation model in that it goes beyond simply evaluating the consequences of proposed alternatives: It actually identifies the “optimal” alternative. How does an optimization model accomplish this impressive task? In this age of readily available computing power and ever more user-friendly software, it is possible to build and use optimization models without a detailed understanding of the mathematics that underlie the answer to this question. To truly take advantage of this capability, however, it is necessary to have a basic understanding of some core concepts. The primary objective of this note is to introduce these concepts. This note is highly pragmatic; the companion note “The Mathematics of Optimization” (UVA-QA-0683) explores more deeply the mathematical foundations of the concepts and is designed for the user with the motivation and mathematical background to further explore the topic. . . .

A Basic Study on the Effect of the Transportation Environment on the Individual Life Satisfaction

This study focused on modeling the indexes of individual built environment and their effects on the subjective evaluation of the life. The life satisfaction is regarded as the stable index for measuring happiness in the past researches in this decade. Thus the authors adopted it as the main subjective index in this study. The indexes of built environment of individual were measured as the number of available alternatives and the experience of activity abandoning, based on the idea of capability theory. The empirical study used the data collected in the mountain area. The authors found that the life satisfaction is not directly related with the number of alternatives but the experience of activity abandoning trip which means the margin of the capability is related.本研究は、個人の生活環境の指標構築と生活の主観的な評価に対するその指標の影響についての基礎的な研究です．過去の研究において，主観的な生活満足度が主観的生活評価を安定的に測定できる指標とされてきたため，この研究では，生活評価の指標として主観的な生活満足度を使用します．また，個人の生活環境の指標としては，プリズム制約に基づいた利用可能な選択肢の数と，これまでの活動断念の経験を指標としました．この考え方はケイパビリティ理論の考えに基づいたものです．実証研究では，山間地において集められた個人の評価とアクティビティデータを使用しました．その結果，主観的生活満足度が選択肢の数とは直接関連づけられませんでしたが，その余裕を意味する活動を断念した経験が生活満足度と関連していることが明らかになりました．

Re-examining the requirements for verification of patient identifiers during medication administration: No wonder it is error-prone

Patient identification errors are one of the major causes of medication errors. Most medication error studies to date have focused on reporting patient misidentification statistics from case studies, on classifying types of patient identification errors, or on evaluating the impact of technology on the patient identification process, but few have proposed specific strategies or guidelines to decrease patient identification errors. Our study makes three key contributions to the patient identification literature. To better understand the verification of patient identifiers (VPI) process, we first formalize the requirements for this process based on the Joint Commission's national patient safety guidelines. Second, we show the implications of these requirements by applying them to artifacts typically used in medication administration (e.g., patient's statements about their identity, patient's identification band, medication label, and medication order). Third, we evaluate whether nurses comply with these requirements when administering medications using data from clinical simulations. We found that nurses must choose from a considerable number of alternatives to fulfill the Joint Commission guidelines. Despite the number of available alternatives, a small percentage of nurses complied with the requirements for VPI, whether doing so manually or using barcode verification technology. Our findings suggest further study is needed to determine what strategies might improve compliance.

Do ultra-orphan medicinal products warrant ultra-high prices? A review

Do ultra-orphan medicinal products warrant ultra-high prices? A review Eline Picavet,1 David Cassiman,2 Steven Simoens1 1Department of Pharmaceutical and Pharmacological Sciences, KU Leuven, Leuven, Belgium; 2Department of Hepatology, University Hospital Leuven, Leuven, Belgium Abstract: Ultra-orphan medicinal products (ultra-OMPs) are intended for the treatment, prevention, or diagnosis of ultra-rare diseases, ie, life-threatening or chronically debilitating diseases that affect less than one per 50,000 individuals. Recently, high prices for ultra-OMPs have given rise to debate on the sustainability and justification of these prices. The aim of this article is to review the international scientific literature on the pricing of ultra-OMPs and to provide an overview of the current knowledge on the drivers of ultra-OMP pricing. The pricing process of ultra-OMPs is a complex and nontransparent issue. Evidence in the literature seems to indicate that ultra-OMPs are priced according to rarity and what the manufacturer believes the market will bear. Additionally, there appears to be a trend between the price of an ultra-OMP and the number of available alternatives. Patients, third-party payers, and pharmaceutical companies could benefit from more transparent pricing strategies. With a view to containing health care costs, it is likely that cost-sharing strategies, such as performance-based risk sharing arrangements, will become increasingly more important. However, it is vital that any measures for price control are consistent with the intended goals of the incentives to promote the development of new OMPs. Ideally, a balance must be struck between attaining affordable prices for ultra-OMPs and securing a realistic return on investment for the pharmaceutical industry. Keywords: ultra-orphan medicinal product, ultra-rare disease, pricing

A Fuzzy Mathematical Model for Multi Criteria Group Decision making-An Application in Supply Chain Management

paper presents a Fuzzy Multi-Criteria Group Decision analysis approach for selecting supplier in a supply chain management. Supplier selection has attained supreme importance for companies in the current scenario because of increasing global competition. Proper selection of suppliers plays a crucial role on the overall performance of the company. The number of available alternatives in the current market is on a rise and hence it becomes difficult to select a supplier from a large lot. An attempt has been made to develop a new composite model using the Fuzzy method based on Schwartz Sequential Dropping method. Finally, an example based on a case study is given to demonstrate the procedure of the proposed methodology.