The Importance of Apple attributes: A Comparison of Self-explicated and Conjoint Analysis Results

the goal of this article was to determine the importance of apple attributes using two research techniques – self-explicated procedure and conjoint analysis. Research was conducted on a sample of 426 consumers of apples in Zagreb, Croatia. The results of self-explicated and conjoint analysis procedures revealed differences in ranking of apple attributes regarding their importance. It is demonstrated that conjoint analysis gives more detailed results and that it is not influenced by respondents’ tendency to give socially acceptable answers. The results of conjoint analysis also give more information for the producers of apples who can use them to create a product that matches consumers’ wishes.apple, conjoint analysis, self-explicated method, Demand and Price Analysis,

Correspondence analysis and categorical conjoint measurement

We show the equivalence between the use of correspondence analysis (CA) of concadenated tables and the application of a particular version of conjoint analysis called categorical conjoint measurement (CCM). The connection is established using canonical correlation (CC). The second part introduces the interaction e¤ects in all three variants of the analysis and shows how to pass between the results of each analysis.Correspondence analysis, conjoint analysis, canonical correlation, categorical data

ASSESSING THE IMPORTANCE OF APPLE ATTRIBUTES: AN AGRICULTURAL APPLICATION OF CONJOINT ANALYSIS

The use of conjoint analysis in assessing consumers' preferences for attributes is demonstrated with the apple as an example. Conjoint analysis may be used to estimate the importance of attributes and attribute levels through decomposition of consumers' ranking of alternative attribute combinations. It is shown that conjoint analysis provides results that may not be obtained from a survey where respondents are asked to directly state their assessment of the importance of attributes.Food Consumption/Nutrition/Food Safety,

The Valuation of the IJmeer Nature Reserve using Conjoint Analysis

This paper describes an application of conjoint analysis. The subject of the valuation study is the IJmeer nature reserve, which will be partly destroyed when the new residential area IJburg is built. This paper addresses the following question: ‘What is the extent of the loss of green and recreational values?’. In this study, the conjoint analysis consists of three different analyses based on a three-piece valuation question. The respondents are asked to subsequently rank, mark and indicate the acceptability of a set of six cards.environmental economics, conjoint analysis

Ranking Models in Conjoint Analysis

In this paper we consider the estimation of probabilisticranking models in the context of conjoint experiments. By usingapproximate rather than exact ranking probabilities, we do notneed to compute high-dimensional integrals. We extend theapproximation technique proposed by \\citet{Henery1981} in theThurstone-Mosteller-Daniels model for any Thurstone orderstatistics model and we show that our approach allows for aunified approach. Moreover, our approach also allows for theanalysis of any partial ranking. Partial rankings are essentialin practical conjoint analysis to collect data efficiently torelieve respondents' task burden.conjoint experiments;partial rankings;thurstone order statistics model

A Dichotomic Analysis of the Surprise Examination Paradox

This paper presents a dichotomic analysis of the surprise examination paradox. In section 1, I analyse the surprise notion in detail. I introduce then in section 2, the distinction between a monist and dichotomic analysis of the paradox. I also present there a dichotomy leading to distinguish two basically and structurally different versions of the paradox, respectively based on a conjoint and a disjoint definition of the surprise. In section 3, I describe the solution to SEP corresponding to the conjoint definition. Lastly, I expose in section 4, the solution to SEP based on the disjoint definition

Optimal designs for rating-based conjoint experiments.

The scope of conjoint experiments on which we focus embraces those experiments in which each of the respondents receives a different set of profiles to rate. Carefully designing these experiments involves determining how many and which profiles each respondent has to rate and how many respondents are needed. To that end, the set of profiles offered to a respondent is viewed as a separate block in the design and a respondent effect is incorporated in the model, representing the fact that profile ratings from the same respondent are correlated. Optimal conjoint designs are then obtained by means of an adapted version of the algorithm of Goos and Vandebroek (2004). For various instances, we compute the optimal conjoint designs and provide some practical recommendations.Conjoint analysis; D-Optimality; Design; Model; Optimal; Optimal block design; Rating-based conjoint experiments; Recommendations;

Rider Preferences and Values of Equestrian Trail Characteristics in Kentucky

A conjoint analysis of equestrian trail characteristics (trail length, scenic views, open land, bathroom/shower facilities, restricted use, distance, and entrance fee) is conducted for the state of Kentucky. The conditional logit results show location is an important determiner of willingness to pay. In particular, scenic views and restricted use are highly valued (WTP above $20). However, increased distance from home to the trail results in a negative willingness to pay.Equestrian trail characteristics, Conditional logit, Conjoint analysis, Environmental Economics and Policy,

Estimating nonuse values using conjoint analysis

Conjoint analysis is a stated-preference technique for eliciting valuations of nonmarket, multi-attribute commodities. Recently it has begun to be used in environmental economics as an alternative to contingent valuation. In applications to environmental economics, though, conjoint analysis has been used to estimate use values or total values—the sum of use and nonuse values. We show a simple way to estimate the value of a resource to those who should have only nonuse values and illustrate using two surveys about national parks in Maine.