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Intelligent service quality management system based on analysis and forecast of VOC
This study suggests the intelligent service quality management system to analyze the causes and effects of VOC (Voice of Customer) variation and to forecast its occurrence based on the former study in the service industry, especially insurance company. In the competitive business environments, where...
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Published in: | Expert systems with applications 2010-03, Vol.37 (2), p.1056-1064 |
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container_title | Expert systems with applications |
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creator | Pyon, Chong Un Woo, Ji Young Park, Sang Chan |
description | This study suggests the intelligent service quality management system to analyze the causes and effects of VOC (Voice of Customer) variation and to forecast its occurrence based on the former study in the service industry, especially insurance company. In the competitive business environments, where customers are considered as a key success factor of the company, our research will help the company achieve the pro-activeness towards VOC and improve the quality of customer service based on scientific grounds.
The proposed system is designed with three phases: the filtering phase to detect significant variations, the pattern detection phase to generate VOC occurrence patterns, and the VOC forecasting phase. In the filtering step, VOC is calculated and normalized to get rid of apparent exaggeration. In the pattern detection step, internal factors such as product or service qualities are used as sources for generating regular patterns and external factors like sales policy and customer inflow are used as sources for generation of irregular patterns. At the last phase, we forecast VOC based on the pre-defined pattern of VOC occurrence. We evaluate the proposed methodology by applying to the real VOC in a life insurance company. |
doi_str_mv | 10.1016/j.eswa.2009.06.066 |
format | article |
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The proposed system is designed with three phases: the filtering phase to detect significant variations, the pattern detection phase to generate VOC occurrence patterns, and the VOC forecasting phase. In the filtering step, VOC is calculated and normalized to get rid of apparent exaggeration. In the pattern detection step, internal factors such as product or service qualities are used as sources for generating regular patterns and external factors like sales policy and customer inflow are used as sources for generation of irregular patterns. At the last phase, we forecast VOC based on the pre-defined pattern of VOC occurrence. We evaluate the proposed methodology by applying to the real VOC in a life insurance company.</description><identifier>ISSN: 0957-4174</identifier><identifier>EISSN: 1873-6793</identifier><identifier>DOI: 10.1016/j.eswa.2009.06.066</identifier><language>eng</language><publisher>Elsevier Ltd</publisher><subject>Analysis ; Forecasting ; Insurance ; Service quality ; Voice of Customer</subject><ispartof>Expert systems with applications, 2010-03, Vol.37 (2), p.1056-1064</ispartof><rights>2009</rights><lds50>peer_reviewed</lds50><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c331t-ce89df8aa4f5d6f537c218aa24077318e0410bdc70221d07bbd6338b07713d633</citedby><cites>FETCH-LOGICAL-c331t-ce89df8aa4f5d6f537c218aa24077318e0410bdc70221d07bbd6338b07713d633</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><link.rule.ids>314,780,784,27923,27924</link.rule.ids></links><search><creatorcontrib>Pyon, Chong Un</creatorcontrib><creatorcontrib>Woo, Ji Young</creatorcontrib><creatorcontrib>Park, Sang Chan</creatorcontrib><title>Intelligent service quality management system based on analysis and forecast of VOC</title><title>Expert systems with applications</title><description>This study suggests the intelligent service quality management system to analyze the causes and effects of VOC (Voice of Customer) variation and to forecast its occurrence based on the former study in the service industry, especially insurance company. In the competitive business environments, where customers are considered as a key success factor of the company, our research will help the company achieve the pro-activeness towards VOC and improve the quality of customer service based on scientific grounds.
The proposed system is designed with three phases: the filtering phase to detect significant variations, the pattern detection phase to generate VOC occurrence patterns, and the VOC forecasting phase. In the filtering step, VOC is calculated and normalized to get rid of apparent exaggeration. In the pattern detection step, internal factors such as product or service qualities are used as sources for generating regular patterns and external factors like sales policy and customer inflow are used as sources for generation of irregular patterns. At the last phase, we forecast VOC based on the pre-defined pattern of VOC occurrence. We evaluate the proposed methodology by applying to the real VOC in a life insurance company.</description><subject>Analysis</subject><subject>Forecasting</subject><subject>Insurance</subject><subject>Service quality</subject><subject>Voice of Customer</subject><issn>0957-4174</issn><issn>1873-6793</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2010</creationdate><recordtype>article</recordtype><recordid>eNp9UMtqwzAQFKWFpml_oCederO7smzLhl5K6CMQyKGPq5CldVDwI5GUlvx95abnwsDuMjMLM4TcMkgZsPJ-m6L_VmkGUKdQRpRnZMYqwZNS1PyczKAuRJIzkV-SK--3AEwAiBl5Ww4Bu85ucAjUo_uyGun-oDobjrRXg9pg_0sdfcCeNsqjoeNAI9MdvfVxMbQdHWrlAx1b-rleXJOLVnUeb_7mnHw8P70vXpPV-mW5eFwlmnMWEo1VbdpKqbwtTNkWXOiMxTPLQQjOKoScQWO0gCxjBkTTmJLzqoks49M6J3envzs37g_og-yt1zGNGnA8eMkLYBnLRRRmJ6F2o_cOW7lztlfuKBnIqT-5lVN_cupPQhlRRtPDyYQxwpdFJ722OGg0NqYN0oz2P_sPT115ow</recordid><startdate>20100301</startdate><enddate>20100301</enddate><creator>Pyon, Chong Un</creator><creator>Woo, Ji Young</creator><creator>Park, Sang Chan</creator><general>Elsevier Ltd</general><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>8FD</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope></search><sort><creationdate>20100301</creationdate><title>Intelligent service quality management system based on analysis and forecast of VOC</title><author>Pyon, Chong Un ; Woo, Ji Young ; Park, Sang Chan</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c331t-ce89df8aa4f5d6f537c218aa24077318e0410bdc70221d07bbd6338b07713d633</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2010</creationdate><topic>Analysis</topic><topic>Forecasting</topic><topic>Insurance</topic><topic>Service quality</topic><topic>Voice of Customer</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pyon, Chong Un</creatorcontrib><creatorcontrib>Woo, Ji Young</creatorcontrib><creatorcontrib>Park, Sang Chan</creatorcontrib><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Technology Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts – Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><jtitle>Expert systems with applications</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pyon, Chong Un</au><au>Woo, Ji Young</au><au>Park, Sang Chan</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Intelligent service quality management system based on analysis and forecast of VOC</atitle><jtitle>Expert systems with applications</jtitle><date>2010-03-01</date><risdate>2010</risdate><volume>37</volume><issue>2</issue><spage>1056</spage><epage>1064</epage><pages>1056-1064</pages><issn>0957-4174</issn><eissn>1873-6793</eissn><abstract>This study suggests the intelligent service quality management system to analyze the causes and effects of VOC (Voice of Customer) variation and to forecast its occurrence based on the former study in the service industry, especially insurance company. In the competitive business environments, where customers are considered as a key success factor of the company, our research will help the company achieve the pro-activeness towards VOC and improve the quality of customer service based on scientific grounds.
The proposed system is designed with three phases: the filtering phase to detect significant variations, the pattern detection phase to generate VOC occurrence patterns, and the VOC forecasting phase. In the filtering step, VOC is calculated and normalized to get rid of apparent exaggeration. In the pattern detection step, internal factors such as product or service qualities are used as sources for generating regular patterns and external factors like sales policy and customer inflow are used as sources for generation of irregular patterns. At the last phase, we forecast VOC based on the pre-defined pattern of VOC occurrence. We evaluate the proposed methodology by applying to the real VOC in a life insurance company.</abstract><pub>Elsevier Ltd</pub><doi>10.1016/j.eswa.2009.06.066</doi><tpages>9</tpages></addata></record> |
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language | eng |
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source | ScienceDirect Freedom Collection 2022-2024 |
subjects | Analysis Forecasting Insurance Service quality Voice of Customer |
title | Intelligent service quality management system based on analysis and forecast of VOC |
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