Price Comparison and Price Dispersion: Products and Retailers at Different Internet Maturity Stages

Bock, Gee-Woo; Lee, Sang-Yong Tom; Li, Hai

doi:10.2753/jec1086-4415110404

Cited by 43 publications

(36 citation statements)

References 2 publications

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“…Besides, since many types of relationships have been proposed between perceived risk and trust, it is valuable to explore how trust influences perceived risk under different levels of price dispersion. (Walter et al, 2006) Evaluation Cost (Walter, et al, 2006) Product & Service Product cost structure (Walter, et al, 2006) Price discrimination (Pan, et al, 2002) Brand loyalty (Pan, et al, 2002) Trust and reputation (Brynjolfsson & Smith, 2000;Maxwell et al, 2011) Pricing strategy (Ghose et al, 2007) Product information quality (Chung et al, 2006) Product and service differentiation (Clemons et al, 2002) Service quality (Pan, et al, 2002) Product condition (Prieto et al, 2015) Price format (Chellappa et al, 2011) Market Number of competitors (Bock et al, 2007) Product popularity (Pan, et al, 2004) Maturity (Bock, et al, 2007) Product price level (Maxwell, et al, 2011) Effects of online price dispersion _ Transaction Risk (Biswas & Burman, 2009) Search Amount/Intention (Biswas, 2004) Internal reference price (Chen & Bei, 2005;Lai, et al, 2006) (Time Risk)…”

Section: Limitation and Future Workmentioning

confidence: 99%

How do you feel when you see a list of prices? the interplay among price dispersion, perceived risk and initial trust in Chinese C2C market

Vassileva

Noorian

et al. 2015

Journal of Retailing and Consumer Services

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The issues of trust fraud, product genuineness and price dispersion jointly make Chinese C2C buyers difficult to identify trustworthy sellers with a low price. Little is known about the generation of initial trust when buyers search products and receive lists of widely ranged prices. This study proposes a theoretical model to explain how price dispersion interacts with other factors in C2C purchase, such as initial trust, perceived risk, perceived value and purchase intention. Product type is considered as a moderator. 261 students were invited in a survey-based experiment. The results from PLS analysis show that price dispersion negatively affects perceived value, whilst, positively affects perceived risk, which further influences perceived value negatively. Price dispersion also negatively influences initial trust through perceived risk. Moreover, the negative effects of price dispersion are stronger when buyers purchase high-touch products.Keywords: consumer to consumer, trust, price dispersion, purchase intention, perceived risk The issues of trust fraud, product genuineness and price dispersion jointly make Chinese C2C buyers difficult to identify trustworthy sellers with a low price. Little is known about the generation of initial trust when buyers search products and receive lists of widely ranged prices. This study proposes a theoretical model to explain how price dispersion interacts with other factors in C2C purchase, such as initial trust, perceived risk, perceived value and purchase intention. Product type is considered as a moderator. 261 students were invited in a survey-based experiment. The results from PLS analysis show that price dispersion negatively affects perceived value, whilst, positively affects perceived risk, which further influences perceived value negatively. Price dispersion also negatively influences initial trust through perceived risk. Moreover, the negative effects of price dispersion are stronger when buyers purchase high-touch products.

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Section: Limitation and Future Workmentioning

confidence: 99%

How do you feel when you see a list of prices? the interplay among price dispersion, perceived risk and initial trust in Chinese C2C market

Vassileva

Noorian

et al. 2015

Journal of Retailing and Consumer Services

View full text Add to dashboard Cite

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“…Bock et al fi nd that the maturation of Internet markets also leads to lower prices and price dispersion [13]. 4.…”

Section: Resultsmentioning

confidence: 99%

“…Some retailers sell many different categories of products, so an average price was determined for each category-store combination. 13 The number of reviews was used as a proxy for store Popularity because the greater the number of reviews, the more products the store had sold and the more customers it had served. In the data set, the values of the number of reviews lay between 100 and 1,000,000.…”

Section: Data Aggregation and Defi Ning Variablesmentioning

confidence: 99%

Image Effects and Rational Inattention in Internet-Based Selling

Lee

Kauffman

Bergen

2009

International Journal of Electronic Commerce

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The frequency of occurrence of certain price points in Internet-based selling is investigated in order to determine what drives the observed regularities and variations. Theories based on consumer perceptions of price and quality images, and on rational inattention to price-endings are explored by specifying and testing empirical models for price-endings using more than 1.5 million daily observations on multiple product categories sold by 90 Internet-based retailers collected over a two-year period. The results show that a fi rm's on-line reputation and relative price levels affect the price-endings chosen in different product categories, and that 9-ending prices increase consumer purchases. These fi ndings support an image theory of store quality and price. The use of 9-ending prices varies across Internet selling formats in a way consistent with differences in the rational attentiveness these channels engender in consumers. This research on the role of information technology in price-setting provides insights for marketers who wish to optimize price-setting decisions in the competitive environment of Internet retailing.

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“…전자상거래의 도입이 가격경쟁에 미치는 영 향에 대해서는 이론적인 요인에 대한 탐색 [8] 에서 실증적인 가격수준의 비교 [7, 11, 13, 14, 순수온라인이 가격수준이 낮음 [1,4,9,10,11,14,18,19] 온라인업체와 오프라인 업체간의 가격차이 없음 [5,12] 온라인 업체의 가격수준이 더 높음 [2,3,7,13] 온라인 업체의 가격편차가 낮음 [10,14,19] 온라인 업체의 가격편차가 큼 …”

Section: 문헌 연구unclassified

An Empirical Study on Price Changes in e-Commerce

Lee¹

2011

The Journal of Society for e-Business Studies

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With the advancement of Internet, electronic commerce has rapidly expanded and considered as a major retail channel. In the early days of the Internet, many studies compared offline and online stores on their price level and dispersion. Since e-commerce is considered matured, we need to see price change behavior in e-commerce rather than comparing it with traditional channels. Thus, this study investigated the trend of price changes in e-commerce. The data that was gathered from a price comparison site also contained six product categories. The decrease in minimum and average price was identified and the increase in maximum price was also identified. The critical factors in the increase of maximum price are number of sellers (positive effect) and the time span after a product was released (negative effect). The differences in price changes between product categories were also investigated.

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Price Comparison and Price Dispersion: Products and Retailers at Different Internet Maturity Stages

Cited by 43 publications

References 2 publications

How do you feel when you see a list of prices? the interplay among price dispersion, perceived risk and initial trust in Chinese C2C market

How do you feel when you see a list of prices? the interplay among price dispersion, perceived risk and initial trust in Chinese C2C market

Image Effects and Rational Inattention in Internet-Based Selling

An Empirical Study on Price Changes in e-Commerce

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