scholarly journals Customer Complaints Analysis Using Text Mining and Outcome-Driven Innovation Method for Market-Oriented Product Development

2018 ◽  
Vol 11 (1) ◽  
pp. 40 ◽  
Author(s):  
Junegak Joung ◽  
Kiwook Jung ◽  
Sanghyun Ko ◽  
Kwangsoo Kim
Keyword(s):  
Text Mining ◽  
Text Data ◽  
Customer Data ◽  
Air Conditioners ◽  
Customer Needs ◽  
Customer Complaints ◽  
Customer Feedback ◽  
Product Features ◽  
Stand Type

The rapid increase in the quantity of customer data has promoted the necessity to analyse these data. Recent progress in text mining has enabled analysis of unstructured text data such as customer suggestions, customer complaints and customer feedback. Much research has been attempted to use insights gained from text mining to identify customer needs to guide development of market-oriented products. However, the previous research has a drawback that identifies limited customer needs based on product features. To overcome the limitation, this paper presents application of text mining analysis of customer complaints to identify customers’ true needs by using the Outcome-Driven Innovation (ODI) method. This paper provides a method to analyse customer complaints by using the concept of job. The ODI-based analysis contributes to identification of customer latent needs during the pre-execution and post-execution steps of product use by customers that previous methods cannot discover. To explain how the proposed method can identify customer requirements, we present a case study of stand-type air conditioners. The analysis identified two needs that experts had not identified but regarded as important. This research helps to identify requirements of all the points at which customers want to obtain help from the product.

scholarly journals Dialogue Analysis Using a Text Mining Approach: Case Study of Hirono Town

2017 ◽  
Vol 3 (1) ◽  
pp. 51
Author(s):  
Madoka Chosokabe ◽  
Maiko Sakamoto ◽  
Mikiyasu Nakayama
Keyword(s):  
Text Mining ◽  
Regional Planning ◽  
Planning Process ◽  
Text Data ◽  
Information Transparency ◽  
Local Residents ◽  
The Media ◽  
Similarities And Differences ◽  
Newspaper Articles

This case study examined public participation regarding reconstruction of the disaster-affected areas in the Fukushima Prefecture of Japan following the Great East Japan Earthquake in March 2011. The study aimed at (i) identifying the topics discussed and shared by the residents, and (ii) revealing the contribution of the media to ensuring information transparency in the regional planning process. We applied text mining—in particular, correspondence analysis—to (a) the text data from dialogue sessions with local residents and (b) newspaper articles that appeared in a nation-wide newspaper in order to identify the similarities and differences between the topics discussed by session participants and those that appeared in newspaper articles. It turned out that the newspaper articles did not adequately address some important topics discussed in the dialogues. This implies that the coverage by the mass media has much room for improvement in the transparency of the information it provides and supporting the development and implementation of administrative agendas involving citizens and municipalities.

Penerapan Metode Klasifikasi Decision Tree dan Algoritma C4.5 dalam Memprediksi Kriteria Nasabah Kredit Mega Auto Finance

2020 ◽  
Vol 7 (2) ◽  
pp. 200
Author(s):  
Puji Santoso ◽  
Rudy Setiawan
Keyword(s):  
Data Mining ◽  
Decision Tree ◽  
Microsoft Excel ◽  
Customer Data ◽  
Data Mining Techniques ◽  
C4.5 Algorithm ◽  
Marketing Costs ◽  
Excel Format ◽  
Data Mining Application

One of the tasks in the field of marketing finance is to analyze customer data to find out which customers have the potential to do credit again. The method used to analyze customer data is by classifying all customers who have completed their credit installments into marketing targets, so this method causes high operational marketing costs. Therefore this research was conducted to help solve the above problems by designing a data mining application that serves to predict the criteria of credit customers with the potential to lend (credit) to Mega Auto Finance. The Mega Auto finance Fund Section located in Kotim Regency is a place chosen by researchers as a case study, assuming the Mega Auto finance Fund Section has experienced the same problems as described above. Data mining techniques that are applied to the application built is a classification while the classification method used is the Decision Tree (decision tree). While the algorithm used as a decision tree forming algorithm is the C4.5 Algorithm. The data processed in this study is the installment data of Mega Auto finance loan customers in July 2018 in Microsoft Excel format. The results of this study are an application that can facilitate the Mega Auto finance Funds Section in obtaining credit marketing targets in the future

Energy Consumption Pattern of Residential Buildings: Case Study of Residential Area in Batu Pahat, Johor

2020 ◽  
Vol 12 (9) ◽  
Author(s):  
Junaidah Jailani ◽  
◽  
Norsyalifa Mohamad ◽  
Muhammad Amirul Omar ◽  
Hauashdh Ali ◽  
...  
Keyword(s):  
Energy Consumption ◽  
Residential Buildings ◽  
Residential Area ◽  
Consumption Pattern ◽  
Air Conditioners ◽  
Residential Sector ◽  
Waste Energy ◽  
Main Factor ◽  
Energy Consumption Pattern

According to the National Energy Balance report released by the Energy Commission of Malaysia in 2016, the residential sector uses 21.6% of the total energy in Malaysia. Residents waste energy through inefficient energy consumption and a lack of awareness. Building occupants are considered the main factor that influences energy consumption in buildings, and to change energy consumption on an overall scale, it is crucial to change individual behaviour. Therefore, this study focused on analysing the energy consumption pattern and the behaviour of consumers towards energy consumption in their homes in the residential area of Batu Pahat, Johor. A self-administrated questionnaire approach was employed in this study. The findings of this study showed that the excessive use of air conditioners was a significant factor in the increasing electricity bills of homeowners as well as the inefficient use of electrical appliances. Also, this study determined the effect of awareness on consumer behaviour. This study recommends ways to help minimise energy consumption in the residential area.

Are Universities Ready to Deliver Digital Skills and Competences? A Text Mining Driven Case Study on Marketing Courses in Italy

2021 ◽  
Author(s):  
Irene Spada ◽  
Filippo Chiarello ◽  
Simone Barandoni ◽  
Gianluca Ruggi ◽  
Martini Antonella ◽  
...  
Keyword(s):  
Text Mining ◽  
Digital Skills

Text data mining: a case study

2005 ◽  
Author(s):  
C.W. Ford ◽  
Chia-Chu Chiang ◽  
Hao Wu ◽  
R.R. Chilka ◽  
J.R. Talburt
Keyword(s):  
Data Mining ◽  
Text Data ◽  
Text Data Mining
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