Fixed Mobile Convergence (FMC) Services in Indonesia: A Conjoint Analysis of Customer Preference

2018 ◽  
Author(s):  
Al Bukhari Pahlevi ◽  
Muhammad Suryanegara
Keyword(s):  
Conjoint Analysis ◽  
Customer Preference ◽  
Fixed Mobile Convergence

Surprising Robustness of the Self-Explicated Approach to Customer Preference Structure Measurement

1997 ◽  
Vol 34 (2) ◽  
pp. 286-291 ◽  
Author(s):  
V. Srinivasan ◽  
Chan Su Park
Keyword(s):  
Utility Function ◽  
Conjoint Analysis ◽  
Predictive Validity ◽  
The Self ◽  
Preference Structure ◽  
Combined Approach ◽  
Customer Preference ◽  
Full Profile ◽  
Structure Measurement

The authors introduce customized conjoint analysis, which combines self-explicated preference structure measurement with full-profile conjoint analysis. The more important attributes for each respondent are identified first using the self-explicated approach. Full-profile conjoint analysis customized to the respondent's most important attributes then is administered. The conjoint utility function on the limited set of attributes then is combined with the self-explicated utility function on the full set of attributes. Surprisingly, the authors find that the self-explicated approach by itself yields a slightly (but not statistically significantly) higher predictive validity than does the combined approach.

An Approach to Modeling Customer Preference Uncertainty by Applying Bootstrap to Choice-Based Conjoint Analysis Data

2010 ◽  
Author(s):  
Swithin S. Razu ◽  
Shun Takai
Keyword(s):  
Product Development ◽  
Conjoint Analysis ◽  
New Product Development ◽  
Market Share ◽  
New Product ◽  
Analysis Data ◽  
Product Development Process ◽  
Product Concept ◽  
Customer Preference ◽  
Market Shares

Analysis of customer preferences is among the most important tasks in a new product development. How customers come to appreciate and decide to purchase a new product affects the products market share and therefore its success or failure. Unfortunately, when designers select a product concept early in the product development process, customer preference response to the new product is unknown. Conjoint analysis is a statistical marketing tool that has been used to estimate market shares of new product concepts by analyzing data on the product ratings, rankings or concept choices of customers. This paper proposes an alternative to traditional conjoint analysis methods that provide point estimates of market shares. It proposes two approaches to model market share uncertainty; bootstrap and binomial inference applied to choice-based conjoint analysis data. The proposed approaches are demonstrated and compared using an illustrative example.

scholarly journals CLUSTER AND CONJOINT ANALYSIS FOR DETERMINING ONLINE SHOP SHOPEE CUSTOMERS PREFERENCE BASED ON E-SERVICE QUALITY

2021 ◽  
Vol 15 (2) ◽  
pp. 361-372
Author(s):  
Dimas Nurwinata Rinaldi ◽  
Fahriza Nurul Azizah ◽  
Candra Galang Gemilang Putra
Keyword(s):  
Cluster Analysis ◽  
Service Quality ◽  
Conjoint Analysis ◽  
Business Strategy ◽  
Quality Attributes ◽  
Sociodemographic Characteristics ◽  
Customer Preference ◽  
Gender Education ◽  
Education Profession ◽  
Cluster 2

The use of e-commerce as a means of shopping is a trend that is very much in demand by many Indonesians. This makes e-service quality very important in a transaction. Customer preference is one of the main factors in shaping a business strategy. This research discusses the use of cluster analysis to segment Shopee's e-commerce customers based on sociodemographic characteristics with k-means algorithm and conjoint analysis to determine which e-service quality attributes are most important to each cluster. The sociodemographic characteristics to be analyzed are gender, education, profession, e-commerce visit, income, and last purchase from the e-commerce. The result from k-means algorithm is there are 2 groupings of customers based on their sociodemographic characteristics, cluster 1 with the majority of women members with frequent visits, while for cluster 2 with the majority of male members with frequent visits. With the result of cluster analysis, conjoint analysis help this research to find which e-service quality attributes are most important. The results are members in cluster 1 prioritize Full payment payment methods when shopping online, while members in cluster 2 prioritize star seller types when shopping online. The aspect that doesn't matter most when shopping online is fulfillment in cluster 1 and security in cluster 2.

scholarly journals Customer Preference of Attributes of Skema Wooden Chair Furniture

2021 ◽  
Author(s):  
Hisyam Hilmy Bahasuan ◽  
David Sukardi Kodrat
Keyword(s):  
Conjoint Analysis ◽  
Online Survey ◽  
Error Tolerance ◽  
Customer Preference ◽  
Seat Cushion ◽  
The Subject

The purpose of this research was to find the preferred combination of attributes regarding wooden chair furniture. The subject of this research was Skema Furniture, a Surabaya-based furniture developer since 2016. Variables in this research were acquired through a pre-survey with twenty of Skema Furniture’s previous customers. The attributes were form, seat cushion, customization and wood finish. The form attribute had two levels: curvilinear and rectilinear. The seat cushion attribute had two levels: using a seat cushion and not using a seat cushion. The customization attribute had two levels: the ability to customize and otherwise. The wood finish attribute had two levels: natural finish and solid color finish. Conjoint analysis was used. The sample of 134 people were past consumers of Skema Furniture from the age of 25 to 54. The sample needed for this research, using the Slovin formula, with a 0.05 error tolerance, was around 100 people. The research was conducted via an online survey, due to the COVID-19 pandemic. This research concluded that the most preferred wooden chair furniture was that with a curvilinear form, without a seat cushion, able to be customized, and with a solid color finish. The variables that were most important for the consumers were wood finish and form. This study only describes the preferences of the buyer and user of the furniture chair products. The wooden chair furniture in this research is not specified to any function of a chair. Keywords: customer preference, Skema Furniture, wooden chair furniture

PREFERENSI KONSUMEN TELUR PUYUH DI KOTA KENDARI

2017 ◽  
Vol 1 (1) ◽  
Author(s):  
Sani Wanti ◽  
Sitti Aida Adha Taridala ◽  
Takdir Saili ◽  
Budiyanto Budiyanto
Keyword(s):  
Performance Analysis ◽  
Conjoint Analysis ◽  
Consumer Choice ◽  
Customer Preference ◽  
Self Interest ◽  
And Behavior ◽  
Attributes Data

The preference of quail egg’s consumer could be determined by measuring the consumer choice.  This preference could illustrate the attribute of quail egg that could be produced by producer and accepted by consumer.  The aims of this study were to analyze the attitude and behavior of the customer in case of buying quail egg, analyze the level of self interest and satisfaction of the customer to the quail egg attribute, and analyze the customer preference on a variety of the quail egg attributes. Data collected in Kendari, South East Sulawesi and were analyzed using Fishbein Multiattribute Attitude analysis, IPA analysis (Importance Performance Analysis), and Conjoint Analysis.  The result of Fishbein Multiattribute Attitude Analysis indicated that the 61,91% consumers were fond of quail egg. In average, the acceptabiity of the customer to the quail egg was ‘quite good’ and the behavior of the customer was consistent but they to re-buy the quail egg. While the result of IPA analysis (Importance Performance Analysis) showed that the most important and the most satisfine attribute of quail egg for customer was colourful attribute. The result of Conjoint Analysis revealed that the preference of the quail egg customer in Kendari City was the quail egg with low price, seasonal availability, less than 10 gram in weight, colourful and unpacking. Keywords: quail egg; Fishbein; IPA; Conjoint analysis

Elicitation and Modeling of Customers’ Preferences in Industrial Design: A Comparative Study on Vehicle Front End

2008 ◽  
Author(s):  
Antoine Dagher ◽  
Jean-Franc¸ois Petiot ◽  
Herve´ Guyon
Keyword(s):  
Conjoint Analysis ◽  
Industrial Design ◽  
Pairwise Comparison ◽  
Preference Elicitation ◽  
Sound Design ◽  
Customer Preference ◽  
Front End ◽  
Comparison Of The Results ◽  
Design Factors

The understanding of customer preference, in relation to product attributes, is a key challenge in industrial design. It is based on preference measurement, which is a complex task, crucial for sound design decisions. In this paper, we study experimentally the influence of the preference elicitation method on the results of the test. For this, we designed a case study concerning the perception of vehicle’s front-end by a panel of subjects. Two different preference elicitation methods were used in the same session: direct rating on a scale, and pairwise comparison. Conjoint Analysis was used next to model the preference and to compute the part worth of the different design factors. Two conjoint methods were examined: rating based and choice based. The paper presents a comparison of the results of the different modeling with conjoint analysis, in order to assess the reliability and the validity of the models.

Applications of Conjoint Analysis in Industrial-Organizational Psychology

2006 ◽  
Author(s):  
Robert D. Pritchard ◽  
Melissa J. Sargent ◽  
Deborah DiazGranados ◽  
Neal W. Schmitt
Keyword(s):  
Conjoint Analysis ◽  
Organizational Psychology ◽  
Industrial Organizational Psychology

CONJOINT ANALYSIS VS PREFERENCE ANALYSIS: A COMPARISON

1987 ◽  
Vol 60 (3c) ◽  
pp. 1063-1068
Author(s):  
THOMAS R. SCHORP ◽  
H. LEE MEADOW
Keyword(s):  
Conjoint Analysis ◽  
Preference Analysis
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