Predict Consumer Preferences Research Articles

Consumer preference prediction by using a hybrid evidential reasoning and belief rule-based methodology

Consumer preference prediction is a key factor to the success of new product development. This paper presents a hybrid evidential reasoning (ER) and belief rule-based (BRB) methodology for consumer preference prediction and a novel application to orange juices. The orange juices are distinguished by their values of sensory attributes, which are grouped for simplicity into different categories such as appearance, aroma, texture, flavour, and aftertaste. The ER approach is used to aggregate consumer preferences for category attributes into an overall preference, and the BRB methodology is used to model the casual relationships between category attributes and their sensory attributes. The casual relationships between the overall preference and the sensory attributes of orange juices are trained and tested using real data and memorized for prediction or new product design. A case study involving 16 orange juices is conducted using the proposed hybrid ER and BRB methodology to demonstrate its novel applications. The results show that the hybrid ER and BRB methodology can fit and predict consumer preferences with high accuracy.

Conjoint Analysis

Conjoint analysis is a market-based research model that has been used by businesses for more than 35 years to predict consumer preferences in product design and purchasing. Researchers in medicine, healthcare economics, and health policy have discovered the value of this methodology in determining treatment preferences, resource allocation, and willingness to pay. To describe the conjoint analysis methodology and explore value-added applications in nursing research. Conjoint analysis methodology is described, using examples from the healthcare and business literature, and personal experience with the method. Nurses are called upon to increase interdisciplinary research, provide an evidence base for nursing practice, create patient-centered treatments, and revise nursing education. Other disciplines have met challenges like these using conjoint analysis and discrete choice modeling.

The welfare effects of restricted hospital choice in the US medical care market

AbstractManaged care health insurers in the USA restrict their enrollees' choice of hospitals to within specific networks. This paper considers the implications of these restrictions. A three‐step econometric model is used to predict consumer preferences over health plans conditional on the hospitals they offer. The results indicate that consumers place a positive and significant weight on their expected utility from the hospital network when choosing plans. A welfare analysis, assuming fixed prices, implies that restricting consumers' choice of hospitals leads to a loss to society of approximately $1 billion per year across the 43 US markets considered. This figure may be outweighed by the price reductions generated by the restriction. Copyright © 2006 John Wiley & Sons, Ltd.

Linking product offering to consumer needs; inclusion of credence attributes and the influences of product features

The Quality Guidance Model was extended beyond sensory properties to include credence motivations like healthiness, environmental friendliness, naturalness, and safety. This Extended Quality Guidance Model was built and tested to explain consumer preferences from consumer perceptions, expert sensory judgments, and metabolite features of tomatoes. The different type of features (sensory, technical, and consumer perceptions) made it possible to explore the actionability of the features in predicting consumer preferences both in-store and upon consumption.

Urban consumer preferences and sensory evaluation of locally produced and imported rice in West Africa

Parboiled rice produced in Ghana is of poor quality and is being overtaken by imported rice. This study sought to investigate consumer preference and relate sensory attributes with consumer acceptability of rice. The majority of consumers preferred imported raw and parboiled rice to that produced locally. Acceptability was influenced by location and gender. Individual preferences of consumers varied and four different segments of consumers with similar liking of the rice samples were identified. The largest three segments (86% of consumers) preferred the imported rice but differed in their preferences for the local rice. A niche segment (14%) mostly preferred traditional local rice. Regression models to predict consumer preference from the sensory panel scores were based on either brown colour of the cooked rice or unshelled paddy in the uncooked form. The models were suitable for three of the consumer segments representing 86% of the consumers. This suggests that while a sensory panel could be used to rapidly monitor consumer acceptability in product development, it was not valid for all consumers. The implications of these findings are discussed.

Sound quality metric development for the Air Conditioning and Refrigeration Institute

The current method of assessing acoustic signatures from residential air conditioning units is defined in the Air Conditioning and Refrigeration Institute (ARI 270) 1995 Standard for the Sound Rating of Outdoor Unitary Equipment. This research project was designed to assess the efficacy of the metric to predict consumer preference. The original metric and modified versions of that metric were evaluated as tools for use in today’s market. The ARI 270 metric was implemented in software with additional features and the flexibility to modify the features applied. Numerous product acoustic signatures were analyzed and compared using the original metric and various modifications of that metric. As a result of that analysis a set of synthesized signatures was generated that targets problem areas for an application of the metric to typical signature configurations. A subjective jury evaluation was conducted to establish the consumer preference for those synthesized signatures. A statistical correlation of the various configurations was conducted to assess the degree of the relationship between the subjective preferences and the various metric calculations. Recommendations were made for modifications to improve the current metric’s ability to predict a subjective preference. [Programming completed by Jonathan Peters (ARL/PSU). Research supported by ARI.]

Measuring consumer response to food products

The failure of taste tests to predict the market performance of new food products (cf. Burger King's new french fries, New Coke) illustrate the inability of marketing researchers to perform such tests effectively. Food scientists, with their expertise at testing the sensory effects of foods, can make an important contribution to the ability of food producers to predict consumer preference and choice. However, for their experiments to have the needed external validity to achieve such marketing objectives, food scientists must incorporate into their experiments certain elements of consumer purchase behavior and the marketing context in which food products are considered for purchase. In this paper, we discuss those aspects of consumer choice behavior and the marketplace that are pertinent to accurately predicting consumer food purchase behavior, and how they may be incorporated into experimental studies aimed at predicting food preference and choice.

Predicting Hotel Choice Decisions and Segmenting Hotel Consumers: A Comparative Assessment of a Recent Consumer Based Approach

Given the intensified competition to attract today's increasingly discerning hotel guests, it is vital for hotel managers to understand the set or bundle of hotel attributes which are demanded by the potential traveler. Unfortunately, marketing research in hotels is still mainly confined to the analysis of guest-related data collected during registration or from guest comment cards. These data, however, have little merit as predictors of customer behaviour and cannot answer the “what if” questions. In recent and past research in hospitality and tourism, researchers have demonstrated the use of product attributes in predicting consumer preferences and segmenting markets (Bell and Morey 1997; Kim 1996). In undertaking this approach to behavioral study, many researchers in the field have been attracted to use conjoint attribute part-worths, (the judgmentally quantified attribute valuesderived from conjoint modeling. This study attempts to utilize the compositional self-explication model as a reference model to assess the comparative superiority of the conjoint model in predicting client preferences among travelers to Hong Kong. It also seeks to reveal subgroup preference variations by using two segmentation approaches. The overall finding indicated that the most important hotel attribute sought by all respondents is Room Rate, followed by Star Rating, Location, Brand and Room Type. In terms of market segments, the results revealed similar preference profiles among leisure, short-haul and infrequent travelers as one group and business, long-haul and frequent travelers as another.

Sensory Characteristics of Apple Juice Evaluated by Consumer and Trained Panels

ABSTRACT: To identify sensory characteristics of unclarified apple juice and to compare unclarified and clarified types, 140 consumers and 10 trained panelists evaluated 16 commercial apple juice samples (4 clarified and 12 unclarified). Unclarified and clarified juices were clearly separated by the first principal component (PC1), whose main factor was fresh, green, and sweet aroma. It was difficult to predict consumer preference by regression models using trained panel preference and analytical attributes. Mapping consumers' overall preferences on a sensory profile made by PC1 and PC2, the consumer panel preferred apple juice with moderately increased fresh and green aroma and thoroughly decreased sour and astringent.

Predicting Consumer Preferences for Fresh Salmon: The Influence of Safety Inspection and Production Method Attributes

A rank-ordered logit model is estimated using data collected by a mail survey of consumers in the northeastern and mid-Atlantic United States. The methodology, based on conjoint analysis, determines the average relative importance and value of three product attributes for fresh salmon (seafood inspection, production method, and price), and estimates the relative attractiveness of particular products to consumers. When used in combination with demographic data and responses to questions on perceptions, the analysis suggests market segmentations and potential marketing strategies based on the heterogeneity in preferences among consumers.

Sensory Evaluation of Fruit Quality in an Apple Breeding Program

Overcoming bias in fruit quality evaluation is a challenge to fruit breeders, who must predict consumer preferences; databases of accurate fruit descriptions would be invaluable in helping them make selections to suit market needs. In order to obtain as informative a description as possible, plant breeding staff worked with sensory science personnel to define and quantify the appearance, flavor, and texture sensations they were experiencing when evaluating apples. Ten visual properties, nine flavor attributes, and nine texture characteristics were identified by evaluators; these were then clearly defined and reference materials representing the range of values found in apples were chosen as benchmarks. After screening and a brief training, nine people are now carrying out evaluations for the breeding project. In order to streamline the procedure, after two seasons of use the attributes are being examined for the usefulness in discriminating between genotypes.

The Role of Wholesaler-Distributors as Marketing Experts

Wholesaler=distributors are important representatives of manufacturers in wine industry. Their role as experts in predicting consumer preference is tested in the context of this industry. An experiment is perofrmed using four wines and three prices. Consumers and wholesalers rate the wine quality and the wholesalers are asked to predict consumer quality perceptions. Consumers used price in making quality judgments even after tasting the wine. Wine wholesalers, as predicted, used taste and not price in making their quality judgments, but were unable to accurately predict consumer reactions. Further analysis shows that these marketing experts used different criteria in making quality judgments, which may account for their inability to predict consumer tastes.

A Classification Tree for Predicting Consumer Preferences for Risk Reduction

American Journal of Agricultural EconomicsVolume 73, Issue 5 p. 1416-1421 Invited Papers Session A Classification Tree for Predicting Consumer Preferences for Risk Reduction John K. Horowitz, John K. Horowitz assistant professor University of MarylandSearch for more papers by this authorRichard T. Carson, Richard T. Carson associate professor University of California, San DiegoSearch for more papers by this author John K. Horowitz, John K. Horowitz assistant professor University of MarylandSearch for more papers by this authorRichard T. Carson, Richard T. Carson associate professor University of California, San DiegoSearch for more papers by this author First published: 01 December 1991 https://doi.org/10.2307/1242394Citations: 4AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Citing Literature Volume73, Issue5December 1991Pages 1416-1421 RelatedInformation

Beer chemistry and canadians' beer preferences

AbstractBeer companies want to understand the relationship between the chemical characteristics of beer and the preferences for beer exhibited by consumers. Two data sets were provided to the analysts in this case study. The first set consisted of chemical measurements on 91 beers and preference measurements on the same beers collected from beer consumers in blind taste tests. The analysts were asked to use these data to develop a statistical model relating beer chemistry and consumer preferences for beer. The second data set consisted of chemical measurements on a holdout sample of 37 beers. The analysts were asked to employ their statistical model to predict consumer preferences for the beers in the holdout sample. The case study assesses the success of their modelling efforts.

Interviewing by computer for explanation and prediction in sensory analysis: a case example for fragrance

This paper describes a method of directly interviewing consumers using computers. In order to demonstrate the validity of this approach, an example is given where qualitative attributes of fragrances were rated using this system and these data used to accurately predict consumer preferences.

Consumer Preference Judgments: An Exposition with Empirical Applications

The modeling of preferences for multiattribute alternatives has received an increased attention in marketing (consumer behavior) and management science (decision analysis). The research in the two disciplines is closely related and can be applied to predicting consumer preferences for multiattribute options. The purpose of this paper is to illustrate and discuss several preference models and measurement techniques that have been used mainly by decision analysts and which are applicable in the consumer preference judgment context. A pilot application of the measurement techniques which provides some insight on their relative predictive accuracy and on the usefulness of empirically verifying the conditions necessary for the existence of the preference models is reported, too.

Relation of Preference Panel and Trained Panel Scores on Dry Whole Milk

Summary Dry whole milk samples manufactured by the EURDD Dairy Products Laboratory, Washington, D. C., were scored by an Oregon State University trained panel, EURDD Dairy Products Laboratory, Washington, D. C., trained panel, EURDD Engineering and Development Laboratory, Wyndmoor, Pennsylvania, trained panel, and by an OSU preference panel of from 100 to 160 student judges. After preliminary testing of 63 samples by the DPL and OSU panels, two series of 50 samples each for a total of 100 samples were tested by all four panels, except the Wyndmoor panel, which tested only 96 samples. Two of the three trained panels used modifications of the American Dairy Science Association score-card for dry whole milk. The Oregon trained panel used a simple six-factor ballot. The student preference panel scored the samples on the nine-point hedonic scale. All data were statistically analyzed for correlation and regression coefficients. Results indicated that total scores from the trained panels could be used as a basis for a scoring system which would predict consumer preference scores. The trained panels’ scores for individual scoring factors, i.e., cooked, oxidized, stale, astringent flavors, did not satisfactorily predict preference scores, but could be used as an indication of possible flavor defects in dry whole milk samples.

A Psychometric Approach to Predicting Consumer Preference1

A Psychometric Approach to Predicting Consumer Preference¹