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AbstractPricing is a critically important management activity with major strategic and operational implications. However, pricing is a much-neglected and ineptly administered marketing responsibility, and numerous errors are made. A prime reason for this is that firms are preoccupied with the use of convenient, often singularly cost-based, pricing methods that fail to assimilate the impact of the full range of effective pricing determinants. This article introduces the concept of the pricing wheel that is a multistage process for effective price management. It provides a systematic means for analyzing and incorporating into decision making the strategic role of price, pricing objectives, the plethora of internal and external pricing determinants, pricing strategy, the pricing technique, and the necessary implementation and control procedures. As a key element of the pricing process, the article advocates utilization of an integrative pricing technique, and it proposes a logical sequence in which it can be applied.
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CitationJobber, D. and Shipley, D. (2001). Integrative pricing via the pricing wheel. Industrial Marketing Management. Vol. 30, No. 3, pp. 301-314.
Link to publisher’s versionhttp://dx.doi.org/10.1016/S0019-8501(99)00098-X
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Online expansion: is it another kind of strategic manufacturer response to a dominant retailer?He, R.; Xiong, Y.; Cheng, Y.; Hou, Jiachen (2016)The issues of channel conflict and channel power have received widespread research attention, including Geylani et al.’s (2007) work on channel relations in an asymmetric retail setting. Specifically, these authors suggest that a manufacturer can respond to a dominant retailer’s pricing pressure by raising the wholesale price for a weak retailer over that for the dominant retailer while transferring demand to the weak retailer channel via cooperative advertising. But, is online expansion another kind of strategic manufacturer’s optimal response to a dominant retailer? In this paper, we extend this work by adding a direct online selling channel to illustrate the impact of the manufacturer’s internet entry on firms’ demands, profits, and pricing strategies and on consumer welfare. Our analysis thus includes a condition in which the manufacturer can add an online channel. If such an online channel is opened, the channel-supported network externality will always benefit the manufacturer but hurt the retailers. Consumers, however, will only benefit from the network externality when a dominant retailer is present and will be hurt when both retailers are symmetric.
Systematic Liquidity Risk and Stock Price Reaction to Large One-Day Price Changes: Evidence from London Stock Exchange.Mazouz, Khelifa; Alrabadi, Dima W.H. (University of BradfordSchool of Management, 2010-06-04)This thesis investigates systematic liquidity risk and short-term stock price reaction to large one-day price changes. We study 642 constituents of the FTSALL share index over the period from 1st July 1992 to 29th June 2007. We show that the US evidence of a priced systematic liquidity risk of Pastor and Stambaugh (2003) and Liu (2006) is not country-specific. Particularly, systematic liquidity risk is priced in the London Stock Exchange when Amihud's (2002) illiquidity ratio is used as a liquidity proxy. Given the importance of systematic liquidity risk in the asset pricing literature, we are interested in testing whether the different levels of systematic liquidity risk across stocks can explain the anomaly following large one-day price changes. Specifically, we expect that the stocks with high sensitivity to the fluctuations in aggregate market liquidity to be more affected by price shocks. We find that most liquid stocks react efficiently to price shocks, while the reactions of the least liquid stocks support the uncertain information hypothesis. However, we show that time-varying risk is more important than systematic liquidity risk in explaining the price reaction of stocks in different liquidity portfolios. Indeed, the time varying risk explains nearly all of the documented overreaction and underreaction following large one-day price changes. Our evidence suggests that the observed anomalies following large one-day price shocks are caused by the pricing errors arising from the use of static asset pricing models. In particular, the conditional asset pricing model of Harris et al. (2007), which allow both risk and return to vary systematically over time, explain most of the observed anomalies. This evidence supports the Brown et al. (1988) findings that both risk and return increase in a systematic fashion following price shocks.
Stock price reaction following large one-day price changes: UK evidenceMazouz, Khelifa; Joseph, N.L.; Joulmer, J. (2009)We examine the short-term price reaction of 424 UK stocks to large one-day price changes. Using the GJR-GARCH(1,1), we find no statistical difference amongst the cumulative abnormal returns (CARs) of the Single Index, the Fama–French and the Carhart–Fama–French models. Shocks ⩾5% are followed by a significant one-day CAR of 1% for all the models. Whilst shocks ⩽−5% are followed by a significant one-day CAR of −0.43% for the Single Index, the CARs are around −0.34% for the other two models. Positive shocks of all sizes and negative shocks ⩽−5% are followed by return continuations, whilst the market is efficient following larger negative shocks. The price reaction to shocks is unaffected when we estimate the CARs using the conditional covariances of the pricing variables.