A central question for firms releasing successive generations of a product is whether they should pursue a market-driven approach and align own product releases to existing industry-level patterns. While an alignment with industry patterns enables firms to capitalize on general market receptivity, it may also entail dilution and competitive interference effects. Using data on the consumer electronics and automotive industries, we show that the effectiveness of such alignment depends on two additional timing-related decisions: the firm’s release regularity for successive product generations and its preannouncement timing. Firms benefit from alignment to the industry only if they release successive generations in a regular manner (to create anticipation) and refrain from early preannouncements (to avoid competitive counteraction). For all other combinations of release regularity and preannouncement timing, not aligning to the industry rhythm leads to higher levels of firm performance. Taken together, our findings enable a nuanced view of the interplay of timing-related launch decisions that provides actionable guidance for managers.
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The reasoning behind our timeframe is as follows: although all firms in our dataset have existed at least since the 1990s, the initial public offering of the last firm was in August 2002. We hence chose 2002 as a starting point. Because we use rolling regressions to capture time variation in performance, the timeframe from September 2002 to August 2004 was needed as a calibration period. Thus, the final timeframe is October 2004 to September 2012.
Common to secondary data, some controls (i.e., financial leverage, market share) exhibit missing values. We imputed the missing data by linear interpolation. We also included additional dummy variables in the regression analyses, one for each variable with missing data, indicating the presence (1) or absence (0) of values. None of these dummy variables had a significant effect on firm performance (p > .10).
Be reminded that we excluded firms with strongly varying r-values across different generational products to ensure that firms consistently released successive generation products with the same regularity in release rhythm across the product portfolio. The firm-level share price made this step necessary, because to measure the performance impact of release rhythm at the firm level, the approach had to be consistent throughout the firm’s product portfolio.
For the purpose of our research, the Gaussian copula estimation procedure is not suited to conduct hierarchical analyses. As it accounts for endogeneity in the IRRA variable, this variable has to be part of the model studied and therefore a model without IRRA (i.e., “Basic model”) cannot be estimated.
Please note that endogeneity-corrected models generally do not have the best fit because they tilt the regression line away from the best-fitting OLS line and thus should not be compared with the OLS models (Ebbes et al. 2011).
We thank an anonymous reviewer for this suggestion.
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The authors thank the entire JAMS review team for their constructive and insightful recommendations throughout the whole process. Moreover, the authors thank Johannes Hattula for his helpfulcomments and suggestions for improvement.
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Bornemann, T., Hattula, C. & Hattula, S. Successive product generations: financial implications of industry release rhythm alignment. J. of the Acad. Mark. Sci. 48, 1174–1191 (2020). https://doi.org/10.1007/s11747-019-00709-y
- Successive product generations
- Launch timing strategy
- Industry release rhythm alignment
- Release regularity
- New product preannouncements