Does product bundling raise or lower consumer welfare? This and related questions have gained much attention in the theoretical literature – see, for example: Adams and Yellen (1976); Schmalensee (1984); McAfee, McMillan, and Whinston (1989); Nalebuff (2004); and Chen and Riordan (2013). However, these questions have received relatively little attention in the subsequent empirical literature – see Crawford and Yurukoglu (2012) and Gentzkow (2007).
We (Gandal, Markovich and Riordan 2013) study the importance of office suites for the evolution of market structure and the performance of the PC office-software market. In order to examine these issues, we estimate a parsimonious model of consumer demand for spreadsheets, word processors, and suites. The model allows for correlated common components of consumer tastes for spreadsheets and for word processors, plus an independent idiosyncratic taste component for each product in each category. Our focus is on how the correlation of consumer preferences for spreadsheets and word processors mattered for the profitability and competitive effects of suites.
Changes in the office-software market during the 1990s
The most important office productivity software products in the 1990s were spreadsheets, word processors, and office suites, which combined (bundled) a spreadsheet and a word processor with other value-added features and programs. During this period, the market saw:
- A shift from DOS-based to Windows-based software programs,
- A shift in market leadership from Lotus (in the spreadsheet market) and WordPerfect (in the word processor market) to Microsoft, and
- A Microsoft-led shift in strategy from selling separate products to selling office suites.
Microsoft was best positioned in the office-suite category because it already had highly rated versions of key underlying components.
Empirical analysis and counterfactual simulations
Estimation of the demand model reveals a positive correlation in consumer preferences over word processors and spreadsheets, a moderate bonus value for suites, and significant advantages for Microsoft products.
We then use the estimated demand model to simulate various hypothetical market structures in order to shed light on the welfare and competitive effects of bundling in the office productivity software market. To do so, we simulate a market setting in which Lotus sells only a spreadsheet, WordPerfect sells only a word processor, and Microsoft sells a word processor and a spreadsheet separately, as well as selling a suite.
We then compare consumer welfare in this simulated market with that in a simulated market structure in which firms only sell components: Lotus sells only a spreadsheet, WordPerfect sells only a word processor, and Microsoft sells both a word processor and a spreadsheet separately, but no suite.
Office suite had a significant effect
Our simulation results show that Microsoft’s Office suite had significant competitive effects. The introduction of Office shifts market share away from Lotus and WordPerfect, and intensifies price competition. The consequences for consumers depend on correlation.
- When the correlation in consumer preferences over word processors and spreadsheets is positive (as we find empirically) or zero, Microsoft’s introduction of an office suite benefits consumers on balance, as long as its rivals (Lotus and WordPerfect) remain active in the market.
- When correlation is negative, or if the rivals exit the market, the introduction of Microsoft's suite reduces consumer welfare.
The pro-competitive effect of bundling relies substantially on the suite bonus effect. Specifically, while in the simulations Microsoft priced its suite higher than the sum of its components, the suite bonus value is much larger than the difference between the suite price and the sum of Microsoft’s component prices when it does not offer a suite. When correlation is strong and positive, there are many consumers who purchase both components separately if suites are not available, and who are therefore inclined to buy the suite when it is available.
Our simulations also show that competing firms can be better off when a dominant firm sells components and a bundle rather than just selling a bundle. We explain the intuition with an example – suppose a consumer likes Microsoft Word, but also likes the Lotus spreadsheet.
- If Microsoft sells components, then the consumer can mix-and-match and purchase these two components.
- If Microsoft sells only suites, however, the consumer cannot purchase the mix-and-match combination and may choose the Microsoft suite instead.
Hence, pure bundling may have a foreclosure effect that reduces demand and profitability for those firms only selling components relative to the mixed bundling case. Nalebuff (2004) makes a similar point.
Since demand for mix-and-match combinations is higher under large positive correlation, we find in the simulations that the reduced foreclosure effect may dominate the standard increased competition effect of mixed bundling when the correlation in consumer preferences is positive and large. In this case, competing firms are better off under mixed bundling than under pure bundling.
References
Adams, Walter J and Janet L Yellen (1976), “Commodity Bundling and the Burden of Monopoly”, Quarterly Journal of Economics 90: 475–498.
Chen, Y and M Riordan (2013), “Profitability of Product Bundling”, International Economics Review 54: 35–57.
Crawford, G, and A Yurukoglu (2012), “The Welfare Effects of Bundling in Multichannel Television Markets”, The American Economic Review 102: 643–85.
Gandal, N, S Markovich, and M Riordan (2012), “Ain’t it ‘Suite’? Bundling in the PC Office Software Market”, CEPR Discussion Paper 9181, October.
Gentzkow, M (2007), “Valuing New Goods in a Model with Complementarity: Online Newspapers”, The American Economic Review 97: 713–744.
McAfee, Preston R, John McMillan, and Michael D Whinston (1989) “Multiproduct Monopoly, Commodity Bundling, and Correlation of Values”, Quarterly Journal of Economics 104: 371–384.
Nalebuff, Barry (2004), “Bundling as an Entry Barrier”, Quarterly Journal of Economics 119: 159–188.
Schmalensee, Richard (1984), “Gaussian Demand and Commodity Bundling”, Journal of Business 57: 58–73.
