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Chevalier, Judith A.; Goolsbee, Austan

doi:10.1023/a:1024634613982

Cited by 361 publications

(39 citation statements)

References 25 publications

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“…Amazon does not publish sales data for each product, but does provide sales ranking data for products in each category. Past research (e.g., Chevalier & Goolsbee, ; Sun, ) have identified a log‐linear relationship between sales rankings and actual sales, so we obtain ranking information for each product ( SalesRank ). Rankings are negatively correlated with sales, a lower ranking indicating higher sales.…”

Section: Data and Variablesmentioning

confidence: 99%

Competing with complementors: An empirical look at Amazon.com

Zhu

Liu

2018

Strategic Management Journal

353

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Research Summary: Platform owners sometimes enter complementors' product spaces and compete against them. Using data from http://Amazon.com to study Amazon's entry pattern into third‐party sellers' product spaces, we find that Amazon is more likely to target successful product spaces. We also find that Amazon is less likely to enter product spaces that require greater seller efforts to grow, suggesting that complementors' platform‐specific investments influence platform owners' entry decisions. While Amazon's entry discourages affected third‐party sellers from subsequently pursuing growth on the platform, it increases product demand and reduces shipping costs for consumers. We consider the implications of these findings for complementors in platform‐based markets. Managerial Summary: Platform owners can exert considerable influence over their complementors' welfare. Many complementors with successful products are pushed out of markets because platform owners enter their product spaces and compete directly with them. To mitigate such risks, complementors could build their businesses by aggregating nonblockbuster products or focusing on products requiring significant platform‐specific investments to grow. They should also develop capabilities in new product discovery so that they could continually bring innovative products to their platforms.

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Section: Data and Variablesmentioning

confidence: 99%

Competing with complementors: An empirical look at Amazon.com

Zhu

Liu

2018

Strategic Management Journal

353

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“…Previous research has studied the impact of online product reviews on product sales with a variety of regression models [14,15,27]. This stream of literature provides useful insights by linking online reviews with sales; most of the studies show a positive correlation between the average review score and product sales.…”

Section: Introductionmentioning

confidence: 99%

Do online reviews affect product sales? The role of reviewer characteristics and temporal effects

2008

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Online product reviews provided by consumers who previously purchased products have become a major information source for consumers and marketers regarding product quality. This study extends previous research by conducting a more compelling test of the effect of online reviews on sales. In particular, we consider both quantitative and qualitative aspects of online reviews, such as reviewer quality, reviewer exposure, product coverage, and temporal effects. Using transaction cost economics and uncertainty reduction theories, this study adopts a portfolio approach to assess the effectiveness of the online review market. We show that consumers understand the value difference between favorable news and unfavorable news and respond accordingly. Furthermore, when consumers read online reviews, they pay attention not only to review scores but to other contextual information such as a reviewer's reputation and reviewer exposure. The market responds more favorably to reviews written by reviewers with better reputation and higher exposure. Finally, we demonstrate that the impact of online reviews on sales diminishes over time. This suggests that firms need not provide incentives for customers to write reviews beyond a certain time period after products have been released.

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“…The e-retailing business model is independent of time and location constraints, and can cater to geographically widespread markets at a significantly much lower cost (Brynjolfsson et.al, 2007;Brown & Goolsbee, 2002;Chevalier & Goolsbee, 2003). All the above mentioned factors have contributed in firmly establishing the internet as a viable alternative to store-based shopping especially in the developed nations, in a relatively short span of time.…”

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confidence: 99%

Grocery Retailing in India: Online Mode versus Retail Store Purchase

Siddiqui

Tripathi

2016

IBR

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E-retailing is entering into the Indian retail scenario in a noticeable way and online grocery retailing holds a promise of acceptance by the Indian customers. This paper attempts to discover the market potential of online grocery retailing in India and consumers' perception towards its different aspects. Confirmatory factor analysis proposes that there are five underlying dimensions (convenience, value for money, variety, loyalty and ambient factors) governing the selection of mode for grocery purchase. Thereafter Binary-Logistic Regression has been employed to analyze the impact of these five broad perceptual dimensions upon the acceptance/rejection of online grocery retailing. The respondents accorded the highest importance to the factors value for money and convenience. The study suggested that issues like meeting customer expectations and preferences in terms of delivering value for money, quick and convenient purchasing, smooth delivery process, and reducing risk perceptions are critical for establishing online grocery retailing as an effective alternative to traditional brick and mortar retailing.

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Untitled

Cited by 361 publications

References 25 publications

Competing with complementors: An empirical look at Amazon.com

Competing with complementors: An empirical look at Amazon.com

Do online reviews affect product sales? The role of reviewer characteristics and temporal effects

Grocery Retailing in India: Online Mode versus Retail Store Purchase

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