The Organic Food Purchase Behaviour: Using ECT to Explore Customers’ Satisfaction
This paper bases on expectation confirmation theory (ECT) to propose a stochastic model of predicting organic food purchase behaviour. In the model, the expectation of pre-purchase and outcome performance of post-purchase are considered as relative variables. We consider these two variables as two d...
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Format: | Article |
Language: | English |
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EDP Sciences
2016-01-01
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Series: | MATEC Web of Conferences |
Online Access: | http://dx.doi.org/10.1051/matecconf/20166202011 |
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author | Huang Hui Hsin |
author_facet | Huang Hui Hsin |
author_sort | Huang Hui Hsin |
collection | DOAJ |
description | This paper bases on expectation confirmation theory (ECT) to propose a stochastic model of predicting organic food purchase behaviour. In the model, the expectation of pre-purchase and outcome performance of post-purchase are considered as relative variables. We consider these two variables as two different normal distribution and their probability density function (pdf) and cumulative distribution function(cdf) will be demonstrated to display their correlation. Then the joint density can be computed to show the results of positive or negative disconfirmation. This study also conducts an empirical data for parameter estimation and model application. We use the 0.5 as threshold level of probability to test the fitness of real overall satisfaction and the calculation results of probability. The results of chi-square testing show good fitness. Finally, the conclusion is made. |
first_indexed | 2024-12-20T03:46:06Z |
format | Article |
id | doaj.art-bbea74685da14a18b4effcda30e0f578 |
institution | Directory Open Access Journal |
issn | 2261-236X |
language | English |
last_indexed | 2024-12-20T03:46:06Z |
publishDate | 2016-01-01 |
publisher | EDP Sciences |
record_format | Article |
series | MATEC Web of Conferences |
spelling | doaj.art-bbea74685da14a18b4effcda30e0f5782022-12-21T19:54:37ZengEDP SciencesMATEC Web of Conferences2261-236X2016-01-01620201110.1051/matecconf/20166202011matecconf_iccfe2016_02011The Organic Food Purchase Behaviour: Using ECT to Explore Customers’ SatisfactionHuang Hui Hsin0Aletheia University,This paper bases on expectation confirmation theory (ECT) to propose a stochastic model of predicting organic food purchase behaviour. In the model, the expectation of pre-purchase and outcome performance of post-purchase are considered as relative variables. We consider these two variables as two different normal distribution and their probability density function (pdf) and cumulative distribution function(cdf) will be demonstrated to display their correlation. Then the joint density can be computed to show the results of positive or negative disconfirmation. This study also conducts an empirical data for parameter estimation and model application. We use the 0.5 as threshold level of probability to test the fitness of real overall satisfaction and the calculation results of probability. The results of chi-square testing show good fitness. Finally, the conclusion is made.http://dx.doi.org/10.1051/matecconf/20166202011 |
spellingShingle | Huang Hui Hsin The Organic Food Purchase Behaviour: Using ECT to Explore Customers’ Satisfaction MATEC Web of Conferences |
title | The Organic Food Purchase Behaviour: Using ECT to Explore Customers’ Satisfaction |
title_full | The Organic Food Purchase Behaviour: Using ECT to Explore Customers’ Satisfaction |
title_fullStr | The Organic Food Purchase Behaviour: Using ECT to Explore Customers’ Satisfaction |
title_full_unstemmed | The Organic Food Purchase Behaviour: Using ECT to Explore Customers’ Satisfaction |
title_short | The Organic Food Purchase Behaviour: Using ECT to Explore Customers’ Satisfaction |
title_sort | organic food purchase behaviour using ect to explore customers satisfaction |
url | http://dx.doi.org/10.1051/matecconf/20166202011 |
work_keys_str_mv | AT huanghuihsin theorganicfoodpurchasebehaviourusingecttoexplorecustomerssatisfaction AT huanghuihsin organicfoodpurchasebehaviourusingecttoexplorecustomerssatisfaction |