کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
4972413 1451053 2016 38 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Online word of mouth: Implications for the name-your-own-price channel
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر سیستم های اطلاعاتی
پیش نمایش صفحه اول مقاله
Online word of mouth: Implications for the name-your-own-price channel
چکیده انگلیسی
We investigate the impact of increased technology-enabled consumer information sharing on the viability, optimal pricing, and profits of a name-your-own-price (NYOP) intermediary. The aim of our analysis is (a) to examine the NYOP's strategy when faced with information sharing about the threshold price above which offers are accepted; (b) to assess how consumers' access to pricing information influences NYOP's optimal pricing and profits; and (c) to examine conditions under which the NYOP pricing format may be more profitable for an intermediary compared to a posted-price format. We investigated these issues using an analytical model for an intermediary operating under two alternative business models: the merchant model and the agency model. Our analysis identifies regions in the parameter space where each sales format might be superior to the other. We find that the optimality of the NYOP format (relative to posted pricing) depends crucially on both the size of the informed consumers' market segment as well as the magnitude of bid shading, which limits the amount of surplus the NYOP intermediary is able to extract from uninformed consumers. Of particular note, we also find that (a) the NYOP does not benefit from frequently changing the threshold price in an attempt to hinder consumer learning of the bid-acceptance price level; (b) increased “word-of-mouth” transmission of information about its undisclosed threshold price does not unambiguously erode the NYOP retailer's profits; and (c) consumer valuations need not be positively correlated with haggling costs for the NYOP selling strategy to dominate posted-pricing format.
ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Decision Support Systems - Volume 91, November 2016, Pages 37-47
نویسندگان
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