Network Externalities in Microcomputer Software:

An Econometric Analysis of the Spreadsheet Market

Erik Brynjolfsson

MIT Sloan School of Management

E53-313

50 Memorial Drive

Cambridge, MA 02142

617-253-4319

Chris F. Kemerer

University of Pittsburgh

278a Mervis Hall

Pittsburgh, PA 15260

412/648-1572 (o)

412/648-1693 (fax)

ckemerer@katz.business.pitt.edu

First Draft: June 1993;

Revised: November 1994, July 1995

MIT Center for Information Systems Research working paper no. 265

Forthcoming in Management Science December 1996.

Network Externalities in Microcomputer Software:

An Econometric Analysis of the Spreadsheet Market

Abstract

Because of network externalities, the success of a software product may depend in part on the size of its installed base and its conformance to industry standards. This research builds a hedonic model to determine the effects of network externalities, standards, intrinsic features and a time trend on microcomputer spreadsheet software prices. When data for a sample of products during the 1987-1992 time period were analyzed using this model, four main results emerged: 1) Network externalities, as measured by the size of a product's installed base, significantly increased the price of spreadsheet products: a one percent increase in a product's installed base was associated with a 0.75% increase in its price. 2) Products which adhered to the dominant standard, the Lotus menu tree interface, commanded prices which were higher by an average of 46%. 3) Although nominal prices increased slightly during this time period, quality-adjusted prices declined by an average of 16% per year. 4) The hedonic model was found to be a good predictor of actual market prices, despite the fact that it was originally estimated using list prices. Several variations of the model were examined, and, while the qualitative findings were robust, the precise estimates of the coefficients varied somewhat depending on the sample of products examined, the weighting of the observations and the functional form used in estimation, suggesting that the use of hedonic methods in this domain is subject to a number of limitations due, inter alia, to the potential for strategic pricing by vendors.

1. Research PROBLEM AND Model

Introduction

The production of packaged computer software for microcomputers is a multi-billion dollar industry in the US alone, and it is expected to be among the fastest growing industries over the next decade. While a significant body of research examines the quality-adjusted prices of computer hardware, much less is known about software prices. The following analysis seeks to move forward in this area by building and empirically testing an econometric model identifying the factors affecting the price of an important category of microcomputer software: spreadsheets.

In microcomputer software, the purchase price reflects only a relatively small portion of the total consumer expenditure; learning and conversion costs account for much of the remainder. This, in turn, helps to create strong network externalities, with theory suggesting a consumer preference for software that is perceived as a standard (Farrell and Saloner, 1985; Saloner, 1989). We therefore focus on understanding and estimating the impact of installed base and standards on the price of software. This effort requires developing a hedonic model that uses data not only on the features and prices of products, as is traditionally done when estimating price indexes, but also on the installed base of users. Insights gained in this area are likely to have direct implications not only for the software industry, but also for a variety of other technologies that exhibit similar economic behavior.

The organization of this paper is as follows. This section gives a brief overview of previous literature in this area and presents a description of the base model. The next section describes the data used to estimate the model. Results are presented in section 3, along with additional analyses of the base model. Section 4 investigates several related research questions by examining additional specifications and subsamples. Section 5 then applies the model to an independent sample of market price data. Discussion and concluding remarks are presented in section 6.

Network Externality Theory

There is a growing body of largely theoretical literature on the economics of network externalities and standards. The classic example of a product that exhibits network externalities is the telephone: having telephone service is only valuable if there are other people with compatible telephones that a user wishes to call. A more modern example might be electronic mail systems, which are valuable to the user only to the degree that many other people also use them. One of the contributions of this literature is an explication of the possible consumer benefits of standards, such as:

• network externalities from a community of users (e.g., ability to share information in a common format),

• a larger market for complementary goods and reduced market power of sellers,

• increased price competition, since competition on other dimensions is reduced and there may be decreases in cost due to production scale economies, and

• a thicker second-hand market, leading to a reduction in uncertainty (Farrell and Saloner, 1985; Westland, 1992; Whang, 1992).

However, these benefits are offset by certain costs of standardization:

• reduced product variety or diversity,

• "excess inertia" which can slow down adoption of better standards, and

• efficiency loss if the wrong standard is imposed (David, 1985; Farrell and Saloner, 1985).

A key implication of the theory is that the existing installed base of a technology affects consumer expectations and compatibility decisions (Farrell and Saloner, 1986), although sponsorship of a technology by an industry leader can act to change expectations and/or reduce the importance of a pre-existing installed base (Cusumano et al., 1992; Fichman and Kemerer, 1993). A limitation of this literature is that there has been little empirical validation of the theory. The practical relevance of the above insights depends on whether the network externality effects are of the same order of magnitude as other effects.

One approach to documenting the existence of network externalities empirically is to look for features which are designed to maintain compatibility. For instance, the choice of file format, user interface design or other interfaces is often influenced by a desire to create compatibility with as many users and products as possible. Greenstein (1993) finds that IBM compatibility is important in the mainframe market; users of IBM mainframes are more likely to buy mainframes from IBM in the future than are users of other vendors’ products. Hartman (1989) uses a a hedonic model with dummy variables to reveal that IBM compatibility is also important for microcomputers. Gandal (1994) uses data from DataPro to construct a hedonic price index for spreadsheet software and determines that Lotus file compatibility has significant value.

In each case, the finding that compatibility with the dominant standard is valuable can be interpreted as evidence of network externalities, because the dominant standard has more users than any other standard. However, one could also interpret the coefficient on the compatibility variable in the same way as the coefficients on other feature variables -- as a reflection of its intrinsic value-- or, alternatively, as an indication of the "brand" value of being associated with a superior product.

Classic network externalities are typically defined as an increase in the value of a product as the number of users of that product increases (Farrell and Saloner, 1985; Farrell and Saloner, 1986). Therefore, direct assessment of network externalities would examine the effects of the actual installed bases of competing products, including those which were not compatible with the dominant standard, on their prices. This would provide a more direct estimate of the basic implication of network externalities: the price users will pay for a product is, in part, determined by the size of the network to which the product belongs. Software products in general, and spreadsheets in particular, make excellent test beds for this work. Learning time and compatibility are important for most types of software, giving rise to potential network externalities, and in the case of spreadsheets in the 1980s and early 1990s, there was a well-identified market standard, Lotus 1-2-3. Lotus 1-2-3 was touted as the single most successful computer application ever, and a key ingredient in the success of the highly popular IBM PC platform (Cringely, 1992, p. 147).

The Hedonic Model

In order to estimate the magnitude of the effects of standards and network externalities it is important to control for other factors that can affect the price of software. We estimate a hedonic regression model using annual data on price and features for a set of microcomputer spreadsheet packages. Hedonic models are designed to estimate the value that different product aspects contribute to a consumer’s utility or pleasure. According to Berndt (1991, p. 117), "implicit in the hedonic price framework is the assumption that ... a particular commodity can be viewed as consisting of various ... bundles ... of a smaller number of characteristics or basic attributes. In brief, the hedonic hypothesis is that heterogeneous goods are aggregations of characteristics. Moreover, implicit marginal prices of the characteristics can be calculated as derivatives of the hedonic price equation with respect to levels of the characteristics."

This hedonic regression approach, developed in the 1920s, has been used on a wide variety of products and services ranging from asparagus to automobiles to marriage dowries (Rao, 1993). A useful history and summary is provided by Berndt (1991). Perhaps the first successful application to information technology was in a study done by Chow, who estimated an annual quality-adjusted decline in mainframe computer prices of 21% from 1960-1965 (Chow, 1967). More recently, Gordon (1993) found that the annual decline in prices was at least that large for computer prices through 1987. Berndt and Griliches use hedonic regression techniques to estimate the quality-adjusted change in prices for microcomputers for the period 1982-1988 (Berndt and Griliches, 1990; Berndt, 1991); they find that the decline in real prices averaged 28% per year.

In order to estimate the optimal strategy for producers a number of researchers have focused on factors affecting hardware prices. An early paper by Michaels models the mainframe market, including such product feature attribute factors as size of main memory and the amount of secondary storage (Michaels, 1979). Most recently, Rao and Lynch (1993) construct a hedonic model to estimate the value of attributes of computer workstations. Much less work has been done in the area of computer software. One notable exception is the work of Gandal (1994). He constructs a hedonic price index for spreadsheet software and finds that Lotus file compatibility has significant value, which provides evidence of network externalities. However, as Gandal notes, two important limitations of his research are the lack of data on unit sales of products and the lack of market price data.

This paper seeks to address these two limitations and extend the research on network externalities and the hedonics of software in a number of other ways. Most importantly, in order to provide a direct assessment of the role of network externalities, our research gathers data on unit sales of spreadsheet products to calculate the implicit price of having an installed base, as well as data on several alternative measures of Lotus compatibility. Because both installed base and the method used to measure Lotus compatibility turn out to be important, including these variables addresses a missing variables bias in the other coefficient estimates. Our analysis should therefore provide more accurate estimates of the values not only of network externalities and standards, but also of other features and the time trend. Furthermore, we seek to assess the reliability of the hedonic approach in this domain by attempting to predict market prices using our model with list prices. Additional extensions, including a comparison of new products with average practice, regressions based on a market-share weighted subsample, tests of the functional form of the model, and evaluation of the role of platform changes (e.g. from MS-DOS to graphical user interfaces) are also considered.

Accordingly, we construct a hedonic model to determine the implicit price of four general types of characteristics: 1) The effect of an increase in installed base for spreadsheet products is explicitly examined, thereby providing insight into the importance of network externalities. 2) The related, but distinct, question of the effect of standards on prices is also analyzed. 3) The more traditional, intrinsic feature variables typically used in hedonic price estimation are included. 4) A time trend variable allows us to discern any change in quality-adjusted prices due to technological progress or other factors.

Thus, our general model is:

(1) Pit = f(Nit, Sit, Fit, Tt)

where: Pit = Price of software package i (in year t)

Nit = Network externalities attributes " " " "

Sit = Standards attributes " " " "

Fit = product Feature attributes " " " "

Tt = Time trend

The network externalities, standards and product feature attributes should positively influence price, whereas the expected sign on the time trend variable is negative, reflecting a decline in quality-adjusted price over time due to technical progress. We customize this general model to accommodate the appropriate hedonic variables for the microcomputer spreadsheet package market and then estimate it.

2. Data

Given the model above, four kinds of data are needed for each product by year: 1) prices, 2) network externality variables such as installed base, 3) adherence to standards, and 4) product feature attributes to help control for intrinsic "quality." Much of the data used was originally compiled and described by MIT students Donna Mayo and Daniel Young (1993).

List Price Data

Reliable information on product pricing is clearly critical for this type of hedonic model. DataQuest and International Data Corporation (IDC) both very generously provided data on the spreadsheet market. For 1992, product list prices were collected from trade press reviews. As a result, the sample may under-represent the number of different products actually sold during 1992. The list price data included up to 22 unique products in each of six years; these were pooled to create a series consisting of 93 observations.

Since these data include a time series component, the nominal prices require adjustment to account for inflation. Product prices were deflated to 1987 dollars using the GDP deflator, so the dependent variable is price in 1987 dollars.

Table 1: Dependent Variable(s)

VARIABLE NAME	DEFINITION
RLISTPRICE	Inflation-adjusted (real) list price for the product.
LOG_LIST	Natural log of the RLISTPRICE for the product.

Network Externalities

Packaged software exhibits positive network externalities in that the value of a product to an individual user increases to the degree that other people also use it (Arthur, 1988). Hence new users will prefer more popular spreadsheets to less popular ones, ceteris paribus. They will benefit from a greater abundance of third-party training opportunities and materials, complementary or compatible products, and user groups, and from an increased likelihood of vendor viability. It would thus be expected that products with a larger share of the installed base will exhibit a price premium over products with smaller shares.

The installed base of each product in each year was computed by summing its sales in all prior years, including sales of earlier, compatible versions. This definition of installed base is consistent with industry parlance and with earlier work estimating the effects of installed base on the market share of minicomputers (Hartman and Teece, 1990). The installed base share, in turn, was computed by dividing the installed base of each product by the sum of the installed bases for all products for a given year. This approach is likely to somewhat over-estimate the base share to the extent that there were other products in the market which were not in the sample, but this bias will be proportional for all products in a given year. In addition, according to DataQuest and IDC, these data represent the overwhelming majority of spreadsheet products sold.

Standards

In its pure form, a standard has no intrinsic value; rather, its value is derived by the adherence of other products to the standard. Given Lotus’s pre-eminent market position, there should be an advantage to being Lotus-compatible. Since Lotus 1-2-3 has been the dominant product in the market since its introduction in 1983, many products have attempted to capitalize on Lotus' user base by providing the option to use, for example, an exact duplicate of the Lotus 1-2-3 menu tree. This copying of the menu tree was at the heart of the lawsuit between Lotus Development Corporation and Paperback Software International, which further indicates the perceived value of this particular standard. Part of the value of the Lotus 1-2-3 menu tree stems from the greater ease of use for the installed base of users who already know the Lotus menu tree, as witnessed by this quotation from a contemporary software review:

Slash-F-R to retrieve a file. Slash-F-S to save. Slash-W-E-Y to clear the worksheet. Slash-C, mark the source range, mark the destination. Countless spreadsheet users are familiar with the command sequences popularized by Lotus 1-2-3... Because many of these users are familiar with 1-2-3, the ideal program is one that uses the same command sequence (National Software Testing Labs, 1990, p. 7)

The Lotus Menu variable also represents the source of the principal switching cost for Lotus 1-2-3 users. One can also examine the value of Lotus file compatibility, as Gandal (1994) did, or Lotus macro compatibility. However, of these measures, Lotus Menu compatibility is likely to be the most important, since a network benefit should be obtained via an opportunity to avoid the costs of incompatibility. A switch by an organization to another user interface would require an investment by every user in re-training, whereas incompatibility in reading and/or writing files could be solved through one-time construction or purchase of a converter. (Matutes and Regibeau, 1988; Farrell and Saloner, 1992). Therefore, a standards effect is represented by a Lotus Menu dummy variable, although variables for Lotus File compatibility and Lotus Macro compatibility will also be examined. The variable names are provided in Table 2.

Table 2: Network Externality and Standards Variables

VARIABLE NAME	DEFINITION
BASESHARE	Percentage of the then current installed base owned by this product
LOT_MENU	Dummy variable, one if the product supports the Lotus 1-2-3 menu tree feature, zero otherwise.

Product Feature Attribute Data

Although we focus on the network externality effects, and specifically the value installed base share and a Lotus menu interface add to a product’s price, other feature attributes are clearly part of a product’s overall attractiveness and should be controlled for. It was desirable to find a single source that contained consistent and comprehensive information on product features. A review of the comparative spreadsheet product reviews offered in major computer trade journals quickly revealed that the features reported on varied somewhat from year to year. Further, the set of products reviewed in any given year was often limited to only the most popular programs. Thus, it was not possible to rely entirely on reviews from any one journal.

One source that did meet the goals of the research was National Software Testing Lab's (NSTL) Software Digest Ratings Reports (National Software Testing Laboratories, 1985). NSTL began publishing in 1984 and produced at least one and sometimes two issues dedicated to evaluating spreadsheet products in each year. Most of the products covered were business-class spreadsheets. (National Software Testing Laboratories 1988; National Software Testing Laboratories, 1988a; National Software Testing Laboratories, 1988b). Each NSTL report also contained detailed definitions of the product features. These definitions confirmed that the feature information collected was truly comparable across years for different products, which further increased our confidence in this source. The sample set covers products sold for the years 1987 through 1992. These data were supplemented and cross-checked with spreadsheet review articles from PC Magazine, InfoWorld, Byte, Computerworld and others. For instance, all articles on spreadsheet products since PC Magazine’s inception in 1982 were examined. The data were also checked against product manuals, when available, for the more recent products.

Data were collected on the product feature attribute variables suggested as possible items that would influence purchase price decisions. The list of the variables and their definitions is presented in Table 3. A particular effort was made to collect the independent variables suggested by Gandal (1994) as significant predictors, and six of his seven ‘preferred model’ variables are included. In total, data on 28 independent variables were gathered including three alternative measures of Lotus-compatibility, four alternative operating systems, the four largest manufacturers, and 17 specific features.

Table 3: Candidate Product Feature attribute Variables

VARIABLE NAME	DEFINITION (dummy variables equal one if the product has the feature, zero otherwise)
BACKCALC	One if the spreadsheet supports background recalculation
CELLINKF	One if product can link spreadsheets by using a cell reference from an external worksheet in a formula in the current worksheet.
DB_COMPT	Equals the number of the following database file types that can be read or directly imported: dBase, Paradox, and SQL.
DDE	One if the product supports either the Microsoft Dynamic Data Exchange mechanism or the Mac Publish/Subscribe mechanism.
EMBEDCHT	One if the product has the ability to mix (embed) charts and spreadsheets on the same page.
EXT_DATA	One if the program provides links to external databases.
FONT_SUP	One if the product supports more than one font simultaneously on a worksheet or graph.
GRAPHS	One if product can create pie, bar and line graphs
LAN_COMM	One if the product has the capability of linking independent user through a local area network (LAN)
LINKING	One if product can update values in multiple (linked) spreadsheets, zero otherwise.
LOGMINRC	Log of the minimum of the maximum number of rows and columns a product supports. A power variable.
LOT_FILE	One if product is file compatible with Lotus format. Equivalent to Gandal’s "LOTCOMP".
LOT_MACR	One if the product supports Lotus macros.
MFR_BOR	One if the product is manufactured by Borland. A ‘make effect’ variable.
MFR_CA	One if the product is manufactured by Computer Associates. A ‘make effect’ variable.
MFR_LOT	One if the product is manufactured by Lotus Development Corporation. A ‘make effect’ variable. Equivalent to Gandal’s "LOTUS"
MFR_Microsoft	One if the product is manufactured by Microsoft. A ‘make effect’ variable.
MIN_CALC	One if the product supports minimal recalculation, a feature which enables the spreadsheet to recalculate only cells which need to be recalculated, rather than recalculating the entire spreadsheet when changes are made.
MOUSESUP	One if the spreadsheet supports at least three of the following mouse shortcuts: pulldown menus, drag & drop editing, speed formatting, speed filling, and icon/button bars.
OS_Macintosh	One if the product is designed to run under the Macintosh operating environment.
OS_OS2	One if the product is designed to run under the OS2 operating environment.
OS_WIN	One if the product is designed to run under the Windows operating environment.
PRNTPREV	One if the product can show an on-screen print preview.
SORT_COL	One if the product supports sorting by columns, in addition to the normal sorting by rows.
SRCH_RPL	One if the product supports global search and replace through cell contents.
WYSIWYG	One if the product supports a What You See Is What You Get interface.

Descriptive statistics

The data sample was confined to commercial spreadsheet products. Neither shareware products, aimed primarily at home or casual users, nor extremely specialized financial modeling applications (e.g., Javelin and Encore) were included in this set. To allow the assessment of the price relationships more accurately, the data set includes only stand-alone spreadsheet programs, not spreadsheets sold as part of an integrated package. Integrated software packages generally include a word processor, a spreadsheet, a communications package, and other modules all in one box for one price. It is infeasible to determine the spreadsheet module's portion of the price of an integrated software package.

This data set contains consistent information for products representing at least 75% of units sold in each year, 1987 to 1991, according to DataQuest and IDC. Thus, it offers broad coverage of the spreadsheet market for products available for different computer platforms and operating systems during this period. With multiple years of data, both longitudinal and cross-sectional differences can be observed. These two independent sources were found to be relatively consistent with each other.

In total, the data set contains 93 different product observations, where a new observation is generated for each spreadsheet revision and each year that the revision is offered. It is worth noting that, despite the fact that a new version of a product may enter the market, sales of older versions continue. Practically, this results because new products are not neatly introduced at the start of a year, nor are older products withdrawn at a year's close. Also, there are users who choose to continue purchasing a perhaps out-of-date version of a product to maintain guaranteed compatibility with current files and applications or to avoid the hardware upgrades that new software releases sometimes require. This notion proved to be especially relevant for Lotus 1-2-3 products where, for example, sales of Lotus 1-2-3 Release 2.01 continued through 1991 despite its initial release being in 1985. Taking into account repetition of prior products, there are 68 distinct versions of products (such as Lotus 1-2-3 ver. 2.01 versus Lotus 1-2-3 ver. 3.0) in the data sample. The sample size of 93 is due to the fact that product versions appear in more than one year.

Table 4 below shows the distribution of the product set by year. The data set covers spreadsheets made by 11 vendors. Table 5 details how many data observations are attributable to products from the three major spreadsheet vendors. This data set includes 58 data observations for products that operate under MS-DOS on PC-compatible computer platforms and 35 data observations that run under graphical operating systems (MS-Windows, OS/2, and Macintosh) on Apple Macintosh or PC-compatible computers. Table 6 shows the distribution of the data set over these four operating systems, and Table 7 provides summary statistics for the data set.

Table 4: Distribution of Table 5: Distribution of Table 6: Distribution o f Data Sample By Year Sample By Vendor Set By Operating System

Year	Number of Data Points	Vendor	Total Data Points	Operating System	Data Points
1987	11	Lotus	23	MS-DOS	58
1988	15	Microsoft	21	Macintosh	17
1989	17	Borland	9	Windows	12
1990	19	Others	40	OS/2	6
1991	22	TOTAL	93	TOTAL	93
1992	9
TOTAL	93

There are several product feature attributes for which information was not readily available. For instance, while a spreadsheet's speed (e.g., file loading speed, recalculation speed, etc.) may enter into a buyer's purchase decision, obtaining comparable estimates of speed for many products is infeasible for a number of reasons. From the NSTL reports, speed ratings are available for only a small fraction of the data sample. The issue of product speed is further muddied by the fact that advances in microcomputer processor speed throughout the period under consideration make speed rates from year to year incomparable. Furthermore, it may also be true that the speed of spreadsheet operations is becoming a secondary issue simply because hardware advances can be counted upon to make up for deficiencies of the software itself.

It would have been interesting to investigate product ratings for ease of use or learning, or other more subjective product qualities. However, such qualitative ratings from a consistent source are available for only a fraction of the data sample. In addition, more objective measures of product features may proxy for these more nebulous concepts. For instance, products that offer the WYSIWYG interface are often heralded for their ease of use. By quantifying the value of this interface, it may be possible to gain insight into the value created by producing a spreadsheet product that is easier to use than others in the marketplace.

Table 7: Descriptive Statistics

Variable	Mean	Standard Deviation	Maximum	Minimum
Dependent Variables
RLISTPRICE	338.36	135.46	615.73	59.85
LOG_LIST	5.70	0.57	6.42	4.09
Network Externality Variables
BASESHARE	6.45	12.27	64.65	0.00
LOT_MENU	0.49	0.50	1.00	0.00
Candidate Product Feature attribute Variables
BACKCALC	0.56	0.50	1.00	0.00
CELLINKF	0.56	0.50	1.00	0.00
DB_COMP	1.03	0.81	3.00	0.00
DDE	0.26	0.44	1.00	0.00
EMBEDCHT	0.46	0.50	1.00	0.00
EXT_DATA	0.76	0.43	1.00	0.00
FONT_SUP	0.89	0.31	1.00	0.00
GRAPHS	0.95	0.23	1.00	0.00
LAN_COMM	0.75	0.43	1.00	0.00
LINKING	0.74	0.44	1.00	0.00
LOGMINRC	6.32	1.74	10.40	5.54
LOT_FILE	0.98	0.15	1.00	0.00
LOT_MACR	0.62	0.49	1.00	0.00
MFGR_BOR	0.10	0.30	1.00	0.00
MFGR_CA	0.05	0.23	1.00	0.00
MFGR_LOT	0.25	0.43	1.00	0.00
MFGR_MS	0.20	0.41	1.00	0.00
MIN_CALC	0.69	0.47	1.00	0.00
MOUSESUP	0.27	0.45	1.00	0.00
OS_OS2	0.06	0.25	1.00	0.00
OS_Macintosh	0.18	0.39	1.00	0.00
OS_WIN	0.13	0.34	1.00	0.00
PRNTPREV	0.58	0.50	1.00	0.00
SORT_COL	0.45	0.50	1.00	0.00
SRCH_RPL	0.60	0.50	1.00	0.00
WYSIWYG	0.51	0.50	1.00	0.00

Another concern may be that competitive pressures, hardware innovations, and other market factors also have an impact on spreadsheet software prices. We believe that the time trend variable may control some of these effects, with the rest being captured by the error term.

Finally, all such estimations are limited by the fact that the data may be measured with error. This has been minimized in this study through the use of multiple contemporaneous industry sources.

3. BASE MODEL construction and estimation

We propose the following general equation:

(2) LOG_LIST = b0 + b1*Installed Base + b2*Standard + bi*Product Feature attribute i + bj*Time + e

An initial, exploratory model was created that included all available network externality and product feature attributes. From this initial model a subset of the variables that were significant at the 90% confidence level (one-tailed test) were retained, and this smaller set formed the base model. As predicted, BASESHARE and LOT_MENU were among the significant variables. The other possible measures of Lotus compatibility, LOT_FILE and LOT_MACR, were not significant. In addition, a relatively short list of five feature variables, pertaining to fairly distinct types of capabilities, also entered into the base model. The expectation is that these variables can collectively proxy for the overall "quality" of the product, including the effects of network externality features and time. The resulting base model equation is as follows:

(3) LOG_LIST = b0 + b1*BASESHARE + b2*LOT_MENU + b3*EMBEDCHT+ b4*LAN_COMM+ b5*SORT_COL + b6*SRCH_RPL+ b7*WYSIWYG + b8*TIMETREND + e

The dependent variable is the natural log of the list price of the product. The base case product, for which all the dummy variables were set equal to zero, is a commercial spreadsheet product that has no installed base of users; does not have a Lotus 1-2-3 style menu tree; cannot embed charts on the worksheet; does not support Local Area Network connections; cannot sort data by column; does not support a search and replace feature; does not have a WYSIWYG interface; and was sold in 1987.

The time trend variable is operationalized as TIMETREND = (Year - 1987), and indicates the average decline in quality-adjusted price per year. The base model results are presented in the first columns of Table 8, labeled "Base."

Table 8: Base Model and Specification tests

	Base		Linear		Indiv.	Years	Time	Periods
Variable	Coeff.	t-stat	Coeff.	t-stat	Coeff.	t-stat	Coeff.	t-stat
Intercept	4.87	32.66	132.50	4.05	4.75	23.68	4.88	31.31
Lot_Menu	0.38	2.94	102.40	3.57	0.38	3.05	0.36	3.08
Baseshare	0.0075	2.64	2.29	2.97	0.0073	2.41	0.0089	2.59
Embedcht	0.45	3.37	136.97	4.14	0.46	3.34	0.51	3.66
LAN_Comm	0.45	3.64	98.12	3.61	0.46	3.65	0.33	2.11
Sort_Col	0.33	2.50	91.35	2.79	0.32	2.48	0.51	2.76
Srch_Rpl	0.14	1.23	35.87	1.42	0.15	1.40	0.13	1.21
WYSIWYG	0.44	3.67	81.21	3.30	0.44	3.76	0.39	3.10
Timetrend	-0.16