Antecedent of purchase intention: online seller reputation, product category and surcharge
Purpose - This paper aims to examine the antecedent of purchase intention: online seller reputation, product category and surcharge.Design methodology approach - This paper uses five experimental designs to explore the seller reputation, product category and surcharge effects in Internet shopping. T...
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| Veröffentlicht in: | Internet research 2013-01, Vol.23 (4), p.507-522 |
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| creator | Pan, Ming-Chuan Kuo, Chih-Ying Pan, Ching-Ti Tu, Wei |
| description | Purpose - This paper aims to examine the antecedent of purchase intention: online seller reputation, product category and surcharge.Design methodology approach - This paper uses five experimental designs to explore the seller reputation, product category and surcharge effects in Internet shopping. The authors chose one seller of low reputation and one seller of high reputation from Yahoo Mall. ANOVA are used to evaluate the results.Findings - Sellers of high reputation can post higher surcharges to increase the total price paid by the buyer, but sellers of low reputation cannot do so (experiment 1). Moreover, partitioned price will decrease purchase intention for sellers of low reputation more than for sellers of high reputation (experiment 2). Consumers take the longest time to make purchasing decisions when buying credence goods (experiment 3) or buying from sellers of low reputation (experiment 4). The effect of surcharge levied by sellers of low reputation is weakened for consumers with low (vs high) shipping-charge skepticism (experiment 5).Practical implications - This study is helpful to online sellers if they can identify their reputation, product category and those consumers who have shipping-charge skepticism, they can create extra profit through surcharge practice.Originality value - The authors' investigation extends the literature on consumers' price processing by identifying the important moderators (seller reputation, product category, and elaboration) and probing into the decision process (via the response time). The results suggest prescriptive strategies for online sellers. |
| doi_str_mv | 10.1108/IntR-09-2012-0175 |
| format | Article |
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The authors chose one seller of low reputation and one seller of high reputation from Yahoo Mall. ANOVA are used to evaluate the results.Findings - Sellers of high reputation can post higher surcharges to increase the total price paid by the buyer, but sellers of low reputation cannot do so (experiment 1). Moreover, partitioned price will decrease purchase intention for sellers of low reputation more than for sellers of high reputation (experiment 2). Consumers take the longest time to make purchasing decisions when buying credence goods (experiment 3) or buying from sellers of low reputation (experiment 4). The effect of surcharge levied by sellers of low reputation is weakened for consumers with low (vs high) shipping-charge skepticism (experiment 5).Practical implications - This study is helpful to online sellers if they can identify their reputation, product category and those consumers who have shipping-charge skepticism, they can create extra profit through surcharge practice.Originality value - The authors' investigation extends the literature on consumers' price processing by identifying the important moderators (seller reputation, product category, and elaboration) and probing into the decision process (via the response time). The results suggest prescriptive strategies for online sellers.</description><identifier>ISSN: 1066-2243</identifier><identifier>EISSN: 2054-5657</identifier><identifier>DOI: 10.1108/IntR-09-2012-0175</identifier><identifier>CODEN: IRESEF</identifier><language>eng</language><publisher>Bradford: Emerald Group Publishing Limited</publisher><subject>Analysis of variance ; Buying ; Categories ; College Students ; Consumer attitudes ; Consumers ; Decisions ; Electronic commerce ; Intention ; Internet ; Moderators ; Online ; Purchase intention ; Quality ; Reaction Time ; Reputation ; Reputations ; Retailing ; Skepticism ; Strategy ; Studies ; Surcharges ; Trust ; University students</subject><ispartof>Internet research, 2013-01, Vol.23 (4), p.507-522</ispartof><rights>Emerald Group Publishing Limited</rights><rights>Copyright Emerald Group Publishing Limited 2013</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c390t-300aa413bacf11f514a0f30c9ae5389edeb0102bf0d5ed58f3d7f1295fe5b68f3</citedby><cites>FETCH-LOGICAL-c390t-300aa413bacf11f514a0f30c9ae5389edeb0102bf0d5ed58f3d7f1295fe5b68f3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktopdf>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/IntR-09-2012-0175/full/pdf$$EPDF$$P50$$Gemerald$$H</linktopdf><linktohtml>$$Uhttps://www.emerald.com/insight/content/doi/10.1108/IntR-09-2012-0175/full/html$$EHTML$$P50$$Gemerald$$H</linktohtml><link.rule.ids>314,776,780,961,11615,27903,27904,52664,52667</link.rule.ids></links><search><creatorcontrib>Pan, Ming-Chuan</creatorcontrib><creatorcontrib>Kuo, Chih-Ying</creatorcontrib><creatorcontrib>Pan, Ching-Ti</creatorcontrib><creatorcontrib>Tu, Wei</creatorcontrib><title>Antecedent of purchase intention: online seller reputation, product category and surcharge</title><title>Internet research</title><description>Purpose - This paper aims to examine the antecedent of purchase intention: online seller reputation, product category and surcharge.Design methodology approach - This paper uses five experimental designs to explore the seller reputation, product category and surcharge effects in Internet shopping. The authors chose one seller of low reputation and one seller of high reputation from Yahoo Mall. ANOVA are used to evaluate the results.Findings - Sellers of high reputation can post higher surcharges to increase the total price paid by the buyer, but sellers of low reputation cannot do so (experiment 1). Moreover, partitioned price will decrease purchase intention for sellers of low reputation more than for sellers of high reputation (experiment 2). Consumers take the longest time to make purchasing decisions when buying credence goods (experiment 3) or buying from sellers of low reputation (experiment 4). The effect of surcharge levied by sellers of low reputation is weakened for consumers with low (vs high) shipping-charge skepticism (experiment 5).Practical implications - This study is helpful to online sellers if they can identify their reputation, product category and those consumers who have shipping-charge skepticism, they can create extra profit through surcharge practice.Originality value - The authors' investigation extends the literature on consumers' price processing by identifying the important moderators (seller reputation, product category, and elaboration) and probing into the decision process (via the response time). The results suggest prescriptive strategies for online sellers.</description><subject>Analysis of variance</subject><subject>Buying</subject><subject>Categories</subject><subject>College Students</subject><subject>Consumer attitudes</subject><subject>Consumers</subject><subject>Decisions</subject><subject>Electronic commerce</subject><subject>Intention</subject><subject>Internet</subject><subject>Moderators</subject><subject>Online</subject><subject>Purchase intention</subject><subject>Quality</subject><subject>Reaction Time</subject><subject>Reputation</subject><subject>Reputations</subject><subject>Retailing</subject><subject>Skepticism</subject><subject>Strategy</subject><subject>Studies</subject><subject>Surcharges</subject><subject>Trust</subject><subject>University students</subject><issn>1066-2243</issn><issn>2054-5657</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2013</creationdate><recordtype>article</recordtype><sourceid>ABUWG</sourceid><sourceid>AFKRA</sourceid><sourceid>AZQEC</sourceid><sourceid>BENPR</sourceid><sourceid>CCPQU</sourceid><sourceid>DWQXO</sourceid><sourceid>GNUQQ</sourceid><sourceid>GUQSH</sourceid><sourceid>M2O</sourceid><recordid>eNptkU1LxDAQhoMouH78AG8BLx6szqRNu_Em4hcsCKIXLyGbTrTSTdckPfjvTV0viqdhZt53eHmGsSOEM0SYn9_79FiAKgSgKAAbucVmAmRVyFo222yGUNeFEFW5y_ZifAcAVKqasZdLn8hSSz7xwfH1GOybicS7PPapG_wFH3zfeeKR-p4CD7Qek5k2p3wdhna0iVuT6HUIn9z4lsfvE-GVDtiOM32kw5-6z55vrp-u7orFw-391eWisKWCVJQAxlRYLo11iE5iZcCVYJUhWc5VjrYEBLF00Epq5dyVbeNQKOlILuvc7rOTzd0c52OkmPSqizanNZ6GMWpsQDV1raTI0uM_0vdhDD6n01gJWQmBSmYVblQ2DDEGcnodupUJnxpBT7T1RFuD0hNtPdHOHth4aEXB9O2_ll8PKr8AjAqCyw</recordid><startdate>20130101</startdate><enddate>20130101</enddate><creator>Pan, Ming-Chuan</creator><creator>Kuo, Chih-Ying</creator><creator>Pan, Ching-Ti</creator><creator>Tu, Wei</creator><general>Emerald Group Publishing Limited</general><scope>AAYXX</scope><scope>CITATION</scope><scope>0-V</scope><scope>0U~</scope><scope>1-H</scope><scope>7SC</scope><scope>7WY</scope><scope>7WZ</scope><scope>7XB</scope><scope>8FD</scope><scope>8FE</scope><scope>8FG</scope><scope>ABUWG</scope><scope>AFKRA</scope><scope>ALSLI</scope><scope>ARAPS</scope><scope>AZQEC</scope><scope>BENPR</scope><scope>BEZIV</scope><scope>BGLVJ</scope><scope>CCPQU</scope><scope>CJNVE</scope><scope>CNYFK</scope><scope>DWQXO</scope><scope>E3H</scope><scope>F2A</scope><scope>F~G</scope><scope>GNUQQ</scope><scope>GUQSH</scope><scope>HCIFZ</scope><scope>JQ2</scope><scope>K6~</scope><scope>K7-</scope><scope>L.-</scope><scope>L.0</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>M0C</scope><scope>M0N</scope><scope>M0P</scope><scope>M1O</scope><scope>M2O</scope><scope>MBDVC</scope><scope>P5Z</scope><scope>P62</scope><scope>PQBIZ</scope><scope>PQEDU</scope><scope>PQEST</scope><scope>PQQKQ</scope><scope>PQUKI</scope><scope>Q9U</scope></search><sort><creationdate>20130101</creationdate><title>Antecedent of purchase intention: online seller reputation, product category and surcharge</title><author>Pan, Ming-Chuan ; Kuo, Chih-Ying ; Pan, Ching-Ti ; Tu, Wei</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c390t-300aa413bacf11f514a0f30c9ae5389edeb0102bf0d5ed58f3d7f1295fe5b68f3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2013</creationdate><topic>Analysis of variance</topic><topic>Buying</topic><topic>Categories</topic><topic>College Students</topic><topic>Consumer attitudes</topic><topic>Consumers</topic><topic>Decisions</topic><topic>Electronic commerce</topic><topic>Intention</topic><topic>Internet</topic><topic>Moderators</topic><topic>Online</topic><topic>Purchase intention</topic><topic>Quality</topic><topic>Reaction Time</topic><topic>Reputation</topic><topic>Reputations</topic><topic>Retailing</topic><topic>Skepticism</topic><topic>Strategy</topic><topic>Studies</topic><topic>Surcharges</topic><topic>Trust</topic><topic>University students</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Pan, Ming-Chuan</creatorcontrib><creatorcontrib>Kuo, Chih-Ying</creatorcontrib><creatorcontrib>Pan, Ching-Ti</creatorcontrib><creatorcontrib>Tu, Wei</creatorcontrib><collection>CrossRef</collection><collection>ProQuest Social Sciences Premium Collection</collection><collection>Global News & ABI/Inform Professional</collection><collection>Trade PRO</collection><collection>Computer and Information Systems Abstracts</collection><collection>ABI/INFORM Collection</collection><collection>ABI/INFORM Global (PDF only)</collection><collection>ProQuest Central (purchase pre-March 2016)</collection><collection>Technology Research Database</collection><collection>ProQuest SciTech Collection</collection><collection>ProQuest Technology Collection</collection><collection>ProQuest Central (Alumni Edition)</collection><collection>ProQuest Central UK/Ireland</collection><collection>Social Science Premium Collection</collection><collection>Advanced Technologies & Aerospace Collection</collection><collection>ProQuest Central Essentials</collection><collection>ProQuest Central</collection><collection>Business Premium Collection</collection><collection>Technology Collection</collection><collection>ProQuest One Community College</collection><collection>Education Collection</collection><collection>Library & Information Science Collection</collection><collection>ProQuest Central Korea</collection><collection>Library & Information Sciences Abstracts (LISA)</collection><collection>Library & Information Science Abstracts (LISA)</collection><collection>ABI/INFORM Global (Corporate)</collection><collection>ProQuest Central Student</collection><collection>Research Library Prep</collection><collection>SciTech Premium Collection</collection><collection>ProQuest Computer Science Collection</collection><collection>ProQuest Business Collection</collection><collection>Computer Science Database</collection><collection>ABI/INFORM Professional Advanced</collection><collection>ABI/INFORM Professional Standard</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>ABI/INFORM Global</collection><collection>Computing Database</collection><collection>Education Database</collection><collection>Library Science Database</collection><collection>Research Library</collection><collection>Research Library (Corporate)</collection><collection>Advanced Technologies & Aerospace Database</collection><collection>ProQuest Advanced Technologies & Aerospace Collection</collection><collection>ProQuest One Business</collection><collection>ProQuest One Education</collection><collection>ProQuest One Academic Eastern Edition (DO NOT USE)</collection><collection>ProQuest One Academic</collection><collection>ProQuest One Academic UKI Edition</collection><collection>ProQuest Central Basic</collection><jtitle>Internet research</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Pan, Ming-Chuan</au><au>Kuo, Chih-Ying</au><au>Pan, Ching-Ti</au><au>Tu, Wei</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Antecedent of purchase intention: online seller reputation, product category and surcharge</atitle><jtitle>Internet research</jtitle><date>2013-01-01</date><risdate>2013</risdate><volume>23</volume><issue>4</issue><spage>507</spage><epage>522</epage><pages>507-522</pages><issn>1066-2243</issn><eissn>2054-5657</eissn><coden>IRESEF</coden><abstract>Purpose - This paper aims to examine the antecedent of purchase intention: online seller reputation, product category and surcharge.Design methodology approach - This paper uses five experimental designs to explore the seller reputation, product category and surcharge effects in Internet shopping. The authors chose one seller of low reputation and one seller of high reputation from Yahoo Mall. ANOVA are used to evaluate the results.Findings - Sellers of high reputation can post higher surcharges to increase the total price paid by the buyer, but sellers of low reputation cannot do so (experiment 1). Moreover, partitioned price will decrease purchase intention for sellers of low reputation more than for sellers of high reputation (experiment 2). Consumers take the longest time to make purchasing decisions when buying credence goods (experiment 3) or buying from sellers of low reputation (experiment 4). The effect of surcharge levied by sellers of low reputation is weakened for consumers with low (vs high) shipping-charge skepticism (experiment 5).Practical implications - This study is helpful to online sellers if they can identify their reputation, product category and those consumers who have shipping-charge skepticism, they can create extra profit through surcharge practice.Originality value - The authors' investigation extends the literature on consumers' price processing by identifying the important moderators (seller reputation, product category, and elaboration) and probing into the decision process (via the response time). The results suggest prescriptive strategies for online sellers.</abstract><cop>Bradford</cop><pub>Emerald Group Publishing Limited</pub><doi>10.1108/IntR-09-2012-0175</doi><tpages>16</tpages><oa>free_for_read</oa></addata></record> |
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| source | Emerald Journals |
| subjects | Analysis of variance Buying Categories College Students Consumer attitudes Consumers Decisions Electronic commerce Intention Internet Moderators Online Purchase intention Quality Reaction Time Reputation Reputations Retailing Skepticism Strategy Studies Surcharges Trust University students |
| title | Antecedent of purchase intention: online seller reputation, product category and surcharge |
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