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Uniform Pricing Strategy vs.Price Differentiation Strategy in the Presence of Cost Saving and Demand Increasing

机译:存在成本节约和需求增加的统一定价策略与价格差异化策略

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摘要

Price differentiation or discrimination strategy has been regarded as the best choice for firms with online and offline channels,however,recent years often witnessed the practices of the uniform pricing strategy.This paper aims to address the question whether the uniform pricing strategy may be better for the manufacturer,when the uniform pricing strategy has a positive impact on increasing the customer demand and reducing the operations cost.The research shows that the uniform pricing strategy can be better than the price differentiation strategy when the cost saving and demand increasing are large enough or the consumers' acceptance of online channel lies in a certain interval.Moreover,the manufacturers or brand owners need a tradeoff between the benefit from online channel and the negative impact from the offline channel when they implement the price differentiation strategy.Finally,the authors obtain some managerial insights and implications based on the numerical analyses,which are in line with the phenomena in practice.
机译:价格差异或歧视策略一直被认为是具有在线和离线渠道的公司的最佳选择,但是最近几年经常见证统一定价策略的实践。本文旨在解决统一定价策略是否可能更好地解决这一问题。研究表明,当成本节约和需求增长足够大或增长幅度较大时,统一定价策略可能会优于价格差异化策略,对提高客户需求和降低运营成本具有积极影响。消费者对在线渠道的接受程度处于一定的区间内。此外,制造商或品牌所有者在实施价格差异化策略时,需要在在线渠道的收益与离线渠道的负面影响之间进行权衡。基于数值分析的一些管理见解和启示, e与实践中的现象相符。

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  • 来源
    《系统科学与复杂性:英文版》 |2019年第3期|932-946|共15页
  • 作者单位

    School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;

    Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy Sciences, Beijing 100190,China;

    School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;

    School of Information Technology, Jiangxi University of Finance and Economics, Nanchang 330013, China;

    School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;

    Key Laboratory of Big Data Mining and Knowledge Management, Chinese Academy Sciences, Beijing 100190,China;

    School of Economics and Management, University of Chinese Academy of Sciences, Beijing 100190, China;

    Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, China;

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  • 入库时间 2024-01-27 03:32:46
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