Part-worth Functions Research Articles

선택 기반 컨조인트 분석을 통한 감귤 선호도 조사

Conjoint analysis is a method that predicts the consumer choice by estimating the utility of product's attributes. This study aims to investigate how citrus products can be optimized based on consumer preferences through a choice-based conjoint analysis method. Citrus is one of Jeju's main fruit and play an important part in the Jeju agricultural market. This study seeks to identify the atrribute of citrus that influence consumer choice. In this study, we conduct a choice-based conjoint analysis on four attributes of citrus, including weight, size, price, and packaging. The analysis model is the part-worth function model and the vector model. The part-worth function model estimated the utility of attribute level and the relative importance of the attributes. The vector model estimated the willingness-to-pay price, and then estimated latent class analysis. As a result, weight, size, and price had a great influence on consumer choice among the four attributes, while packaging had a relatively small influence. This study provides valuable insight to explores the optimal combination of citrus attributes preferred by consumers. The optimal combination increase the competitiveness of citrus in the market. And it provide guide to build effective product development strategies and market segmentation strategies for Jeju farmers and agricultural entrepreneurs.

An Analysis of Preference for Potted Houseplant Products Using a Conjoint Analysis Method for the Development of Pet Plant Products

Background and objective: Recently, social interest in indoor plants (houseplants) has been increasing. This study was conducted to determine consumer preferences for houseplants by surveying their perception of houseplants, also referred to as “pet plants” using a conjoint analysis method.Methods: For the conjoint analysis, Attribute 1 was defined as the type of houseplants, which was divided into four levels: orchids, oriental orchids, general foliage plants, and variegated foliage plants. Attribute 2 was set as the shape of pots and was classified into two levels: square and round. Attribute 3 was set as the material of pots, and was divided into four levels: earthenware, ceramic, plastic and onggi (Korean style earthenware). Sixteen profiles were extracted through the orthogonal design using the SPSS Statistics. The survey was conducted online in December 2021, and the responses of 320 out of 332 respondents were analyzed, after unclear responses were excluded.Results: A conjoint analysis of the preference for houseplant products was conducted using part-worth function models. When purchasing houseplants, it was found that the material of pots (53.0%) was considered as the most important attribute, followed by the type of plants (34.0%), and the shape of the pots (13.0%) (Pearson's R = .991, <i>p</i> = .000). Foliage plants (part-worth utility = .143) for the type of plants, round shape (part-worth utility = .056) for the shape of pots, and ceramic (part-worth utility = .284) for the material of pots were preferred as a priority. Clusters with similar part-worths were established using the coefficients representing the estimated part-worths for each attribute derived from a conjoint analysis, as a variable. Cluster 1 was a group of 153 people that had 109 females (36.6%), 68 people in their 50s (22.8 %), 59 bachelor's degree holders (19.8 %), and 42 workers in flower business (14.1 %) as the majority for each demographic item. They preferred variegated foliage plants in round-shaped ceramic pots. Cluster 2 was a group of 104 people with 71 females (23.8%), 44 people in their 50s (14.8%), 47 bachelor's degree holders (15.8%), and 30 flower-related industrial workers (10.1%) for the largest share. They preferred foliage plants in round-shaped earthen pots. Cluster 3 was a group of 41 people with 32 females (10.7%), 17 people in their 50s (5.7%), 25 bachelor's degree holders (8.4%), and 9 office workers (3.0%) and 9 workers in flower businesses (3.0%) for the largest share. They preferred general foliage plants planted in round-shaped ceramic pots.Conclusion: In this study, consumers' perceptions of pet plants were confirmed. The findings can be used as basic data for the development of pet plant products, which is likely to aid houseplant producers in creating new income sources, giving positive effects to differentiated plant producers and flower shops.

Consumer Acceptance of Gene-Edited versus Genetically Modified Foods in Korea.

Food made with gene-editing has received considerable attention in recent years because it is claimed to be a little different from traditional genetically modified breeding methods concerning safety. However, consumer acceptance of these novel foods and their potential market uptake remains to be answered. This study aims to assess differences in the acceptance of gene-edited and genetically modified foods in Korea. The choice-based conjoint analysis is adopted to estimate part-worth functions for the soybean oil attributes with 200 surveyed samples. The estimated part-worth values reveal how much each attribute affects consumers’ decision-making. Estimated results suggest that consumers tend to accept gene-editing more than genetically modified foods. The acceptance of novel technology is shown to correspond closely to the degree of consumers’ scientific knowledge, highlighting the importance of revealing relevant information regarding the technology. Results also show that country of origin is a significant food-specific attitudinal factor in shaping consumer preferences.

06/02481 Effectiveness of an energy-consumption information system on energy savings in residential houses based on monitored data: Ueno, T. et al. Applied Energy, 2006, 83, (2), 166–183.

Studies on household energy use generally focus on social and psychological factors influencing the acceptability of energy-saving measures. However, the influence of physical characteristics of energy-saving measures on their acceptability is largely ignored. In this study, preferences for different types of energy-saving measures were examined, by using an additive part-worth function conjoint analysis. Energy-saving measures differed in the domain of energy savings (measures aimed at home energy savings versus measures aimed at transport energy savings), energy-saving strategy (technical improvements, different use of products, and shifts in consumption), and the amount of energy savings (small versus large energy savings). Energy-saving strategy appeared to be the most important characteristic influencing the acceptability of energy-saving measures. In general, technical improvements were preferred over behavioral measures and especially shifts in consumption. Further, home energy-saving measures were more acceptable than transport energy-saving measures. The amount of energy savings was the least important characteristic: there was hardly any difference in the acceptability of measures with small and large energy savings. Except for respondents differing in environmental concern, there were no differences in average acceptability of the energy-saving measures between respondent groups. However, some interesting differences in relative preferences for different types of energy-saving measures were found between respondent groups.

Household preferences for energy-saving measures: A conjoint analysis

Studies on household energy use generally focus on social and psychological factors influencing the acceptability of energy-saving measures. However, the influence of physical characteristics of energy-saving measures on their acceptability is largely ignored. In this study, preferences for different types of energy-saving measures were examined, by using an additive part-worth function conjoint analysis. Energy-saving measures differed in the domain of energy savings (measures aimed at home energy savings versus measures aimed at transport energy savings), energy-saving strategy (technical improvements, different use of products, and shifts in consumption), and the amount of energy savings (small versus large energy savings). Energy-saving strategy appeared to be the most important characteristic influencing the acceptability of energy-saving measures. In general, technical improvements were preferred over behavioral measures and especially shifts in consumption. Further, home energy-saving measures were more acceptable than transport energy-saving measures. The amount of energy savings was the least important characteristic: there was hardly any difference in the acceptability of measures with small and large energy savings. Except for respondents differing in environmental concern, there were no differences in average acceptability of the energy-saving measures between respondent groups. However, some interesting differences in relative preferences for different types of energy-saving measures were found between respondent groups.

Conjoint Analysis of Consumer Preferences and Evaluations of a Processed Meat

A conjoint experiment was designed to survey and analyze a sample of Taiwanese housewives for their evaluations of various Chinese sausage attributes. Individual part-worth functions based on respondents' preference ranking data were estimated. Subsequently, the Ward's method of cluster analysis was employed to form three distinct market segments. A multinomial logit model was then estimated to identify important socioeconomic variables that differentiate the market segments. The study assesses the relative importance of the selected product attributes and draws implications concerning what attributes are most desirable and what potential trade-offs among attributes are acceptable to the consumers.

スキーリゾート計画への部分効用関数の適用 : スキーリゾート施設に対する利用者の評価に関する研究 その2

This study aimed to develop a method to compare alternatives of ski-resort planning. This paper reports the part worth function of ski-resort, and a case study that compared two ski-resort plan alternatives. To adapt conjoint analysis, the authors chose 6 attributes of ski-resort plan and generated 18 concept cards. These cards were ranked by 18 skiers. The level of importance of each attributes and the part-worth functions were calculated from the ranked order. Utility values that were sum of part worth functions and the use intention ratio of each concept card were mutually correlated. By regression analysis, two formulas that estimate the use intention ratio from utility value were made. Using the formulas two plan alternatives of ski resort in Hokkaido area were compared.

Technical Note—Factors Influencing the Selection of Preference Model Form for Continuous Utility Functions in Conjoint Analysis

In conjoint analysis, a consumer's utility function for a continuous attribute is usually estimated using a part worth function. However, one may also use continuous functions. The purpose of the paper is to investigate through simulation the combined influence of the number of degrees of freedom, the nature of the “true” utility function and the amount of error in the data on the selection of a utility function. The focus is on functions that are known or expected to be monotone within the range of attribute levels of interest. One can then choose among linear, quadratic and part worth functions. The results show (a) that estimation procedures with monotonicity constraints should be used, and (b) that it is best to use quadratic or part worth functions rather than linear functions to minimize potential losses in predictive validity.

Conjoint Analysis of Price Premiums for Hotel Amenities

Over the past decade or so, conjoint analysis (Green and Rao 1971; Johnson 1974) appears to have become one of industry's most widely applied marketing research techniques for estimating consumer's multi-attribute utility functions (Cattin and Wittink 1982). However, a continuing problem in application of conjoint analysis is how to handle the price attribute in the construction of stimulus profiles for presentation to respondents. In many cases of practical interest, the price level will be highly correlated with other product attribute levels. If the researcher ignores this correlation by allowing the price levels to vary independently of other attributes, the resulting profiles may appear sufficiently unrealistic to result in respondents' discounting each profile's attractiveness, thus reducing the validity of the results. A related problem which adds to the complexity of new product pricing research is the bundling issue. In the context of conjoint analysis, the question is whether one can predict a respondent's evaluation of a bundle of product attributes and price as a simple linear function of the summed part worths of the entities making up the bundle when each entity is presented with its actual price. Metric hybrid conjoint models have received a fair amount of industry application to date. The purpose of these models is to reduce data collection time while still retaining individual differences in part-worth functions. The present paper extends this class of models to include categorical conjoint analysis in which the criterion variable is classificatory. This model is applied to an extremely large conjoint problem involving over 40 attributes and over 100 attribute levels. The study results support the viability of the model for dealing with extremely large conjoint problems. The study also shows evidence of the inability of simple functions of self-explicated utilities for components of a bundle of hotel amenities to predict respondents' preferences for the total bundle. (Journal of Business, 1984, vol. 57, no. 1, pt. 2) ? 1984 by The University of Chicago. All rights reserved. 0021-9398/84/5712-0019$0 1.50

Structural Reliability and Stability of Nonmetric Conjoint Analysis

Structural reliability and stability of nonmetric conjoint analysis are examined under conditions of severe structural perturbation and substantial variation in the number of stimulus profiles. The individual-level part worth functions are jackknifed. The jackknifed parameters, derived relative importance weights, and standard errors of estimated parameters are examined across the different treatment conditions. The results indicate that conjoint analysis is a fairly robust procedure for assessing an individual's preferences.

Conjoint Measurement and the Analysis of Noisy Data: A Comment

In a previous study reported here Moriarity and Barron [1976] used conjoint measurement to model the materiality judgment process of audit partners. They did so following the approach suggested by Krantz and Tversky [1971] in which axiomatic conjoint measurement (ACM) is used to identify the functional form of the decision maker's judgment model, and then numerical conjoint measurement (NCM) is applied to find the best-fitting scale values (part-worth functions).' Shortly thereafter, the American Accounting Association's Committee on Human Information Processing (AAA [1978]) suggested that conjoint measurement would be useful in the study of certain aspects of human information processing in accounting research, particularly for testing alternative composition rules which uses only ordinal properties of the data [1978, p. 32]. Composition rules refer to the functional forms (e.g., additive, multiplicative, etc.) of decision makers' judgment models.2 In a later paper, Moriarity and Barron [1979] examined the preaudit materiality judgments of audit partners, in which they assumed an additive model and used a holistic orthogonal parameter estimation procedure (Barron and Person, [1979]). Swieringa [1979] criticized this

Discussion of a Judgment-Based Definition of Materiality

Moriarity and Barron illustrate the use of conjoint analysis to describe the extent to which each of five financial variables was considered important by five auditors in making materiality judgments. Additive models were fitted to subjects' responses to derive the values of the partworth function over four levels of each variable for each auditor. These values were then analyzed to assess the importance of each variable for each auditor in making the materiality judgments. The authors conclude that the analysis produced interpretable values for the part-worth function for each auditor, provided acceptable predictions of judgments not used to fit the particular model, but revealed a lack of consensus across auditors for both the values for the part-worth functions and the predictions. In discussing their illustration, I focus on three major issues. The first is the process of identifying or selecting the attributes or variables which are likely to be relevant to auditors in making materiality judgments. The second is the process of implementing conjoint analysis to estimate the structure of these judgments. The third is the extent to which the approach illustrated provides insights about how various factors or variables affect materiality judgments and why highly trained professionals with extensive experience often reach different conclusions in similar situations.

Subjective evaluation models and conjoint measurement

Several types of measurement and scaling models are applied to empirical data involving a sample of housewives' preferences for profile descriptions of retail discount cards. Additive conjoint measurement is used to obtain part-worth functions for the various component descriptors. In addition, subjects' self-explicated models are compared with actual rankings of the discount cards. The results of the study indicate that additive conjoint models provide good descriptions of the data and that self-explicated models also show reasonable accuracy in predicting actual rankings. However, no significant association was found between differences in evaluative behavior and a battery of attitudinal and socio-economic measurements obtained from the same subjects.