Ideal Point Model Research Articles

One money, one voice? Evaluating ideological positions of euro area central banks

We provide new insights into the effectiveness of central bank communication in the euro area relying on a novel methodology. The time-varying text based ideal point model (TV-TBIP) is used focusing on two crucial topics communicated by central bankers, namely price stability and financial stability. The methodology permits identification of the ideological position of the speaker. We find that the ECB transitions between a high ideal point state reminiscent of interventionist monetary policy and their effects on financial markets and a low ideal point state with emphasis on risks to fragmentation from monetary policy and financial stability policies. The individual euro area central banks tend to mirror the ECB’s position which suggests that some specialization/coordination of responsibilities from the communications activities of euro area national central banks takes place. National central banks’ positions change gradually and usually during crisis periods. In contrast, the ECB’s ideological position is very stable. We also conduct several econometric tests that point to national inflation rates influencing ideological positions. Additionally, we find that professional forecasts are responsive to the position taken of central bankers in their speeches.

Expectation Disconfirmation, Ideal Point and Kano Models of Customer Satisfaction: A Comparison

This article compares three customer satisfaction models: expectation disconfirmation, ideal point, and Kano. It depicts the details of the three types of satisfaction stochastic models. A beauty shop's e-commerce database is used as empirical data for parameter estimates and model comparisons. The model calibration uses both root-mean-square deviation (RMSD) and the Chi-square test. The results demonstrate that the expectation disconfirmation model has the maximum fitness in the RMSD index, but the lowest goodness of fit in the Chi-square test. In contrast, the ideal point model produces opposite findings on the RMSD index and the Chi-square test. The expectation model, which has a larger number of parameters than the other two models, can be used for elastic changes to explain varied situational elements of pleasure, but it also requires more data to be stable. However, the ideal point model has a simpler structure than the other two models. There is only one parameter to estimate, which makes it easy to apply. However, it is less accurate than the other two models when measuring dynamic satisfaction.

The customer preferences on product quality of Abian Tubuh Tofu

This study aims to determine the quality of food sector SME products that are widely spread in Mataram City. The focus of research is on tofu products which are one of the superior products in this city. This study used the survey sample method, by choosing the Abian Tubuh tofu industry center as the research location. The study population was all customers knew who came to make purchases at some predetermined traditional market. In determining respondents as data sources in this study, researchers used purposive sampling techniques. Because the number of members of the study population is not known with certainty, the number of research samples was determined at 100 respondents. To answer the problem posed, the analytical tool used is the Ideal-Point Model, which is a consumer evaluation of what is perceived with what is desired. This model measures the difference between what is perceived and what consumers want. The results showed that the quality of SME products tofu Abian Tubuh, Mataram City was very good. This is indicated by the quality value being in the upper interval class which means that the quality of the tempeh product is in accordance with consumer wishes.

Product Quality of SMEs Food Production in The Perspective of Islamic Economics

This study aims to determine the quality of SMEs product in the food industry which are widely spread in Mataram City. The focus of the research is on tempeh product which are one of the leading products in the city. In addition to analyzing the quality of tempeh products, this study also analyzes aspect of quality of this product from an Islamic economic perspective. In determining respondents as data sources in this study, researchers used purposive sampling techniques. To answer the problem posed, the analysis tool used is the Ideal-Point Model, which is a consumer evaluation of what is perceived with what is desired. This model measures the difference between what is perceived and what consumers want. The result shows that the product quality of SME tempeh is very good. This is indicated by the quality value being at the upper interval class which means that the quality of the tempeh product is in accordance with the wishes of consumers. Based on the Islamic view, respondents have the perception of tempeh products as products with halal ingredients, a good process, and are a valuable offer and useful.

The Effects of Aberrant Responding on Model-Fit Assuming Different Underlying Response Processes.

Aberrant responding on tests and surveys has been shown to affect the psychometric properties of scales and the statistical analyses from the use of those scales in cumulative model contexts. This study extends prior research by comparing the effects of four types of aberrant responding on model fit in both cumulative and ideal point model contexts using graded partial credit (GPCM) and generalized graded unfolding (GGUM) models. When fitting models to data, model misfit can be both a function of misspecification and aberrant responding. Results demonstrate how varying levels of aberrant data can severely impact model fit for both cumulative and ideal point data. Specifically, longstring responses have a stronger impact on dimensionality for both ideal point and cumulative data, while random responding tends to have the most negative impact on data model fit according to information criteria (AIC, BIC). The results also indicate that ideal point data models such as GGUM may be able to fit cumulative data as well as the cumulative model itself (GPCM), whereas cumulative data models may not provide sufficient model fit for data simulated using an ideal point model.

Vulnerability assessment of the eco-geo-environment of mining cities in arid and semi-arid areas: A case study from Zhungeer, China

Assessing the ecological and geological environment vulnerability (EGEV) of cities arid and semi-arid regions is important for urban planning, development, and ecological protection. This study investigated the ecological and geological environmental problems and possible potential risk factors in Zhungeer City and constructed an EGEV assessment index system covering the geological environment, human activities, coal mining, and hydrological conditions. We proposed a linear weighted model to calculate the comprehensive weight of each indicator using the Analytical Hierarchy Process (AHP) and Entropy method based on distance function optimization (AELW), and frequency ratio accuracy is then introduced to compare the remarkable classification performance between AELW and other models. The frequency ratio accuracy results show that AELW model has the highest accuracy for EGEV assessment (62.77 %), followed by Multiplicative Integrated Normalization Model (MINM, 61.46 %), AHP (60.98 %), Ideal Point Model (IPM, 60.30 %) and Entropy (53.55 %). The EGEV of Zhungeer was classified as I-V from lowest into highest, among which the EGEV of I-II-III accounted for 78.15 %, EGEV of IV accounted for 16.42 %, and the EGEV of V risk area accounted for 5.43 %, with a good overall ecological and geological environment quality. These results can provide tangible management suggestions for reducing EGEV in Zhungeer city, and the AELW model provides direction for EGEV assessment in other similar areas.

A Study of Land Ecological Environment Evaluation Based on an Ideal Point Model

The paper took Guang’an City in Sichuan Province of China as a research region, and it built an evaluation index system based on 14 evaluation indices according to four criteria, namely, ecological background, ecological structure, ecological benefits, and ecological stress. The Delphi algorithm and entropy weight (a combination of subjective and objective methods) were used to calculate the weight value of each evaluation index, and an ideal point model was used to calculate the ideal point value. The ideal point ecological grade was classified, and the principal component analysis method was used to obtain the main control factors of each year, which revealed the relationship between the ecological distribution of ideal points and the environmental impact factor, with the changing characteristics of the ecology in the research region according to the hotspot model of the spatial differentiation of land ecological quality as the main control factor. Lastly, the paper also analyzed the land ecological quality of Guangan City in 2000, 2005, 2010, and 2015. The study results show that the overall land ecological quality in Guang’an City generally increased from 2005 to 2015. The proportion of forest land area and the temperature were the most important main control factors. The air temperature and the land ecological quality were positively correlated.

Py-irt: A Scalable Item Response Theory Library for Python

py-irt is a Python library for fitting Bayesian item response theory (IRT) models. At present, there is no Python package for fitting large-scale IRT models. py-irt estimates latent traits of subjects and items, making it appropriate for use in IRT tasks as well as in ideal point models. py-irt is built on top of the Pyro and PyTorch frameworks and uses GPU-accelerated training to scale to large data sets. It is the first Python package for large-scale IRT model fitting. py-irt is easy to use for practitioners and also allows for researchers to build and fit custom IRT models. py-irt is available as open-source software and can be installed from GitHub or the Python Package Index. History: Accepted by Ted Ralphs, Area Editor for software tools. Supplemental Material: The software that supports the findings of this study is available within the paper and its Supplementary Information [ https://pubsonline.informs.org/doi/suppl/10.1287/ijoc.2022.1250 ] or is available from the IJOC GitHub software repository ( https://github.com/INFORMSJoC ) at [ http://dx.doi.org/10.5281/zenodo.6818509 ].

Optimization Analysis of Full Life Cycle Energy Efficiency Multi-Objective Parallel Pump Sets

Aiming at the problem that the current single-objective control model of parallel pumping groups only focuses on the optimization of energy efficiency of operating conditions and operating costs, and cannot adjust the real-time working conditions of the pump group according to the comprehensive energy efficiency state of the pump group in the whole life cycle and adjust the pump group operation strategy accordingly, A multi-objective optimal control model for energy efficiency of a pump set is proposed, which can adjust the weight coefficients of three objective functions autonomously according to the current energy efficiency state of the pump set in the whole life cycle. In this way, the high energy efficiency of the parallel pump group in the low wear stage, that is, the low target deviation and specific energy consumption, and the high reliability in the high wear stage, that is, the lower impeller load improves the efficiency of the pump group in the whole life cycle and extend the service life of the pump group. Determine the multi-objective energy efficiency optimization control model of the pump group, use the main function linear and geometric weighting method, the ideal point value, and the distance deviation method to determine the objective function, and solve the multi-objective ideal point model with the help of LINGO, and obtain the optimal solution of the highest system total efficiency, the lowest pump group specific energy consumption and the highest system reliability. Pareto Frontier Comparison is used to study the transversality of the ideal point model solution set. Experimental results show that through the distribution of the model solution in the indicator space, the model can adjust the control strategy according to the real-time state of the pump group by adjusting the target weight combination.

Bmggum: An R Package for Bayesian Estimation of the Multidimensional Generalized Graded Unfolding Model With Covariates.

Over the past couple of decades, there has been an increasing interest in adopting ideal point models to represent noncognitive constructs, as they have been demonstrated to better measure typical behaviors than traditional dominance models do. The generalized graded unfolding model (GGUM) has consistently been the most popular ideal point model among researchers and practitioners. However, the GGUM2004 software and the later developed GGUM package in R can only handle unidimensional models despite the fact that many noncognitive constructs are multidimensional in nature. In addition, GGUM2004 and the GGUM package often yield unreasonable estimates of item parameters and standard errors. To address these issues, we developed the new open-source bmggum R package that is capable of estimating both unidimensional and multidimensional GGUM using a fully Bayesian approach, with supporting capabilities of stabilizing parameterization, incorporating person covariates, estimating constrained models, providing fit diagnostics, producing convergence metrics, and effectively handling missing data.

Debate Reaction Ideal Points: Political Ideology Measurement Using Real-Time Reaction Data

AbstractIdeal point models have become a powerful tool for defining and measuring the ideology of many kinds of political actors, including legislators, judges, campaign donors, and members of the general public. We extend the application of ideal point models to the public using a novel data source: real-time reactions to statements by candidates in the 2012 presidential debates. Using these reactions as inputs to an ideal point model, we estimate individual-level ideology and evaluate the quality of the measure. Debate reaction ideal points provide a method for estimating a continuous, individual-level measure of ideology that avoids survey response biases, provides better estimates for moderates and the politically unengaged, and reflects the content of salient political discourse relevant to viewers’ attitudes and vote choices. As expected, we find that debate reaction ideal points are more extreme among respondents who strongly identify with a political party, but retain substantial within-party variation. Ideal points are also more extreme among respondents who are more politically interested. Using topical subsets of the debate statements, we find that ideal points in the sample are more moderate for foreign policy than for economic or domestic policy.

The Structure of Political Choices: Distinguishing Between Constraint and Multidimensionality

AbstractIn the literatures on public opinion and legislative behavior, there are debates over (1) how constrained preferences are and (2) whether they are captured by a single left–right spectrum or require multiple dimensions. But insufficient formalization has led scholars to equate a lack of constraint with multidimensional preferences. In this paper, we refine the concepts of constraint and dimensionality in a formal framework and describe how they translate into separate observable implications for political preferences. We use this discussion to motivate a cross-validation estimator that measures constraint and dimensionality in the context of canonical ideal point models. Using data from the public and politicians, we find that American political preferences are one-dimensional, but there is more constraint among politicians than among the mass public. Furthermore, we show that differences between politicians and the public are not explained by differences in agendas or the incentives faced by the actors.

THE CONSUMER PERCEPTION ON QUALITY OF THE PEARL JEWELRY CRAFTS PRODUCTS MATARAM

The research aims to determine consumer perception on the quality of pearl jewelry products in Mataram. The population is consumers of pearl jewelry products, and the respondent determination technique is purposive sampling. The number of sample taken is 100 people. To answer the problem posed, the Ideal-Point Model is used. The model measures the gap (difference) between what is perceived and what consumers need. The result shows that the interest of consumers in purchasing pearl jewelry is mainly due to pearl quality, followed by other quality attributes. The quality value gap is quite large in the attributes of conformity to specifications, frame material, aesthetic value, price, and pearl jewelry design. Even though there is a value gap in some quality attributes, overall quality of Sekarbela pearl jewelry products is very good according to consumer perception.Keywords:Perception, Consumer, Quality, Crafts, Pearls

The Science and Practice of Item Response Theory in Organizations

Item response theory (IRT) is a modeling approach that links responses to test items with underlying latent constructs through formalized statistical models. This article focuses on how IRT can be used to advance science and practice in organizations. We describe established applications of IRT as a scale development tool and new applications of IRT as a research and theory testing tool that enables organizational researchers to improve their understanding of workers and organizations. We focus on IRT models and their application in four key research and practice areas: testing, questionnaire responding, construct validation, and measurement equivalence of scores. In so doing, we highlight how novel developments in IRT such as explanatory IRT, multidimensional IRT, random item models, and more complex models of response processes such as ideal point models and tree models can potentially advance existing science and practice in these areas. As a starting point for readers interested in learning IRT and applying recent developments in IRT in their research, we provide concrete examples with data and R code.

Rock Mass Structural Plane Classification Method Based on Improved Ideal Point Model

Rock Mass Structural Plane Classification Method Based on Improved Ideal Point Model

Evaluation on Ground Surface Accuracies of Large-Depth and Steeply Micro-Structured SiC Surfaces

Microstructures can be used to enhance technical surfaces with additional functionalities, which are driving advances in many fields of industrial applications. However, it is difficult to obtain 3D valid information about large-depth and steeply micro-structured surfaces owing to the limitation of the white light interferometric measurements. Therefore, the registration of bisection-measured micro-topographies is proposed using the interactive closest point (ICP) method combined with the genetic algorithm, with the objective of evaluating the micro-form and micro-profile accuracies of a micro-structured surface. First, a diamond grinding-wheel V-tip was employed to fabricate micro-pyramid-structured SiC; subsequently, 3 ideal point models were constructed to match the measured point clouds using the ICP method; finally, the non-dominated sorting genetic algorithm-II (NSGA-II) was used to micro-alignment the bisection-measured point clouds with regard to micro-form and micro-profile errors. It is shown that the registration accuracy is dominated by the ideal profile point number, but the registration efficiency depends on the ideal point number. The the NSGA-II could improve the registration accuracy of micro-profile by 42.6% compared with traditional ICP matching. It is confirmed that the micro-grinding is able to control the micro-form and the micro-profile accuracies within 4%.

Matches Made With Information: Fitting Measurement Models to Adult Attachment Data.

Many self-report inventories in social/personality psychology are developed and scored using dominance-based assumptions. Specifically, they assume that the relationship between item endorsement and the latent trait is monotonically increasing; thus, individuals with high standings on the trait would be likely to endorse all items. It is possible, however, that the item response process for these inventories follows an ideal point process in which respondents only endorse items that best describe them, leading to nonmonotonic relations between item responses and latent traits. This research examined whether the item response process underlying the Experiences in Close Relationships-Revised-a commonly used self-report measure of adult attachment styles-is best understood as a dominance or ideal point process. Study 1 showed that the ideal point model provided a good account of the response process and provided better interpretability for the full trait continuum than a dominance model. Importantly, people who were the most insecure were the most likely to be scored differently under these two item response models. In Study 2, the association between attachment anxiety and subjective well-being scores was higher using ideal point than dominance-based scoring, and this was especially the case among subsets of people who were highly insecure. Study 3 demonstrated a similar pattern using simulation data. In summary, when dominance-based methods are used to measure adult attachment, people who are extremely insecure may be assessed in suboptimal ways.

PREFERENSI WISATAWAN MILENIAL MANCANEGARA KE BADUNG, BALI

In this era of tourism activities become a trend for the millennial generation. In tourism activities, of course, there are considerations in choosing an object as a destination for a tour or referred to as a reference. Tourist preferences need to be known to measure how much tourist interest in a tourist attraction. Badung, Bali is one of the biggest destinations for foreign tourists. The purpose of this study was to determine the characteristics, preferences, and attitudes of milenial tourists in choosing a tourist attraction in Badung. Data analysis techniqes used in this study is observation, questionnaire. Quantitative descriptive data analysis technique with the calculation of cross-tabulation and chi-square analysis and ideal point models. A total of 120 respondents were selected purposively, namely milenial foreign tourists aged 18 - - 37 years. The characteristics of milenial tourists in this study the majority are aged 25 - - 30 years, Country of origin Australia, last high school education, unmarried status, aiming for a vacation, staying 4 - - 7 days, first visit, traveling with friends. The preferences of milenial tourists there are 9 preferences, among others, tourist activities where tourists choose to look around, on milenial tourists choose villas, where to eat millennial tourists choose restaurants, and on transportation, millennial tourists choose family cars. On Sosial Media used by tourists choosing Instagram, when using Sosial Media tourists choose 4 - - 6 hours, when uploading photos of millennial tourists choose a few hours after editing photos, on information sites used by millennial tourists choose Google, and on photo capture tools that are used by millennial travelers to choose mobile phones. The attitude of millennial tourists in this study is that Badung has a tourist attraction that can be interpreted as good millennial tourist attitudes.

The Influence of the President and Government Coalition on Roll-Call Voting in Brazil, 2003–2006

In Brazil’s legislative process, political exchanges between the government and legislature is an essential feature. This article focuses on the role of the president and political parties in Brazil’s national legislative process. Because nonideological factors influence voting, roll calls do not suffice for estimation of legislators’ policy preferences. In this article, we derive a spatial model of voting in which voting behavior is induced by both ideological motivations and coalition dynamics and develop a multilevel ideal-point model implied by the spatial voting model. After the proposed model is applied to the analysis of roll-call votes in the Brazilian Chamber of Deputies between 2003 and 2006, coalition dynamics is found to influence the voting behavior of legislators. We also confirm the finding in previous studies that the ideological alignment of political parties in the legislature contrasts with the perceived positions.

An Item-Level Analysis for Detecting Faking on Personality Tests: Appropriateness of Ideal Point Item Response Theory Models.

How to detect faking on personality measures has been investigated using various methods and procedures. As previous findings are mixed and rarely based on ideal point item response theory models, additional research is needed for further exploration. This study modeled the responses of personality tests using ideal point method across instructed faking and honest responding conditions. A sample of undergraduate students participated the within-subjects measures to examine how the item location parameter derived from the generalized graded unfolding model changed, and how individuals’ perception about items changed when faked. The mean test scores of faking group was positively correlated to the magnitude of within-subjects score change. The item-level analysis revealed both conscientiousness items (18.8%) and neuroticism items (50.0%) appeared significant shifts on item parameters, suggesting that response pattern changed from honest to faking conditions. The direction of the change appeared both in positive and negative way, demonstrating that faking could increase or decrease personality factor scores. The results indicated that the changes of perceptions on items could be operated by faking, offering some support for the ideal point model to be an adequate measure for detecting faking. However, the findings of diagnostic accuracy analysis also implied that the appropriateness of ideal point models for detecting faking should be under consideration, also be used with caution. Implications, further research directions, and limitations are discussed.