Team E Day 11

Dhiraj Doley

14073

Conjoint Analysis:

Definition:
It is a statistical technique used in market research to determine how people value different features that make up an individual product or service.Conjoint analysis became popular because it was a far less expensive and more flexible way to address these issues than Concept testing.

The objective of conjoint analysis is to determine what combination of a limited number of attributes is most influential on respondent choice or decision making.

A controlled set of potential products or services is shown to respondents and by analyzing how they make preferences between these products.

Conjoint analysis must currently be run using syntax. Unlike most procedures in SPSS for Windows, conjoint analysis requires the user to invoke two files:

1.Plan File:The plan file contains the combinations that will be presented to the participants.

2.Data File:The data file contains the participants' responses.

Types of conjoint analysis:

Adaptive Conjoint Analysis - ACA:

Adaptive Conjoint Analysis (ACA) is one of two most common methods for carrying out conjoint analysis. The benefits of ACA are that it allows for a large number of attributes (up to 30) and levels (up to 7 per attribute) to be used.

Choice Based Conjoint Analysis- CBC:

The most common alternative to ACA is Choice-based conjoint (CBC). Although this uses the same over-arching principles as ACA, in design, implementation and calculation it is completely different.

Discrete Choice Analysis

A more advanced form of choice-based conjoint is Discrete Choice Analysis (also known as "stated preference research"). DCA studies are particularly popular for transportation studies looking at modal choice - the preference between a train, car and airline for instance. 

Full profile Conjoint Analysis

An additional option that dates back a long time but that is still used is full profile conjoint analysis. Full-profile is the original form of conjoint and is still in use; though predominantly in the US it would appear. Like choice-based conjoint this uses a more limited number of attributes to describe the product or service, but sufficient cards or treatments are shown to one respondent to enable individual level utilities to be calculated.

Other forms and formats

Recent developments in conjoint include the Adaptive Choice Based Conjoint method from Saw tooth. Which combines elements of a configurator, an adaptive element and choices? In addition we have our own dobney.com conjoint designer that allows for a range of other more bespoke research areas where traditional forms of conjoint analysis are lacking or where current designs can seem too difficult from a respondent point-of-view 

Steps in generating conjoint analysis:

Step 1: Generating the Plan file:
Open SPSS ->Data > Orthogonal Design-> Generate

Define factors :
Step 2:Data -> Orthogonal Design->Display

This will give you profiles (Multiple combination of factors).Go to your subject and find out their ranking for the given profiles.

Step 3: Generate the data file
The file is generated on basis of ranking provided to different preferences.
Step 4:Run a conjoint Analysis: CONJOINT PLAN='C:\Documents and Settings\Administrator\Desktop\VXLPLAN.SAV'
/DATA=*
/SUBJECT=ID
/FACTORS=LAPTOP_CARRY INT_CONNECT_VIDEO_DEMAND
VIDEO_CONF_VOIP PRICE_PREMIUM
/RANK=PREF1 TO PREF9
/UTILITY='C:\Documents and Settings\Administrator\Desktop\OUTPUT.SAV'
/PLOT=SUMMARY
/PRINT=SUMMARYONLY.

Step 5: Analyse the output