II
RESEARCH PAPER



The National Academies | 500 Fifth St. N.W. | Washington, D.C. 20001
Copyright © National Academy of Sciences. All rights reserved.
Terms of Use and Privacy Statement



Below are the first 10 and last 10 pages of uncorrected machine-read text (when available) of this chapter, followed by the top 30 algorithmically extracted key phrases from the chapter as a whole.
Intended to provide our own search engines and external engines with highly rich, chapter-representative searchable text on the opening pages of each chapter. Because it is UNCORRECTED material, please consider the following text as a useful but insufficient proxy for the authoritative book pages.

Do not use for reproduction, copying, pasting, or reading; exclusively for search engines.

OCR for page 97
Deconstructing the Computer: Report of a Symposium II RESEARCH PAPER

OCR for page 97
Deconstructing the Computer: Report of a Symposium This page intentionally left blank.

OCR for page 97
Deconstructing the Computer: Report of a Symposium Performance Measures for Computers Jack E. Triplett The Brookings Institution I. INTRODUCTION The “Deconstructing the Computer” workshop has the purpose of gaining better understanding of computer performance, especially the contributions of computer components to computer performance. Two groups of professionals are interested in measuring the performance of computers, peripherals, and components. This paper provides a bridge between their interests. Section II explains, primarily to computer professionals, why economists want to measure computer performance and what economists do with performance measures. Subsequent sections provide background on economists’ work on measuring computers and components. As this workshop is part of the STEP Board’s “New Economy” project, one of its objectives is obtaining better performance measures for economic uses. A second audience consists of economists. It is clearly true, as Nordhaus (2002) remarked, that computer performance measures used by economists in recent years have, if anything, gone backward compared with the measures they used 15 or so years ago. We need to ask “why?” We also need to ask: “How much does it matter?” I review in section III the performance measures used by economists in the earlier computer literature, which covers primarily the mainframe years. Sections

OCR for page 97
Deconstructing the Computer: Report of a Symposium IV and V review performance measures used by economists and by statistical agencies in more recent years, where studies have turned predominantly to personal computers (PCs). II. WHAT ECONOMISTS DO WITH COMPUTER PERFORMANCE MEASURES I begin by addressing technologists. Why do economists want to measure computer performance? And what do they do with performance measures? Technologists need to understand how economists use computer performance measures in order to converse with economists on this topic. The questions do not imply that the performance measures wanted by economists are the only performance measures that matter, but fortunately it turns out that what economists want is not that different from what technologists have developed. Indeed, historically, technologists and economists have proceeded in similar directions in measuring the performance of computers. But that gets ahead of the story. Suppose, to create a simple illustrative example, one computer exists. Call it UNIVAC. Suppose three UNIVAC computers are made in 1952, and they cost $400K each.1 We are supposing that UNIVAC was the only computer produced in the economy, so total U.S. output of computers in 1952 was $1.2 million. Now suppose a new computer is developed in 1955 (I call it “new computer”), and that it has higher performance than UNIVAC. Suppose “new computer” sells for $600,000 in 1955, and suppose further that it is the only computer available in 1955, the UNIVAC having disappeared. Ten computers of this new type are produced in 1955, so the economy’s output of computers is $6 million in 1955, a fivefold expansion since 1952 in what economists call “current-price” output. This is clear enough, but other aspects of the 1952–1955 comparison are less clear (see Table 1). First, is there inflation in the computer market? “New computer” costs 50 percent more than UNIVAC, but the new computer also has higher performance. Part of its higher price is just a performance premium. Economists do not want to show an increase in computer performance as inflation. They want to measure computer inflation so that it is adjusted for changes in the performance of computers; in other words, computer inflation should be measured net of the performance premium. The example suggests that computer inflation was less than the 50 percent increase in selling price. How much less? To determine that, economists need a computer performance measure (or more precisely, the performance premium). What about computer output? “New computer” has higher performance than UNIVAC, so each “new computer” is equivalent to more than one UNIVAC. 1   These numbers correspond to UNIVAC production in 1952. See Flamm (1988), Table 3-1 for the price and page 51 for the quantity.

OCR for page 97
Deconstructing the Computer: Report of a Symposium TABLE 1 UNIVAC and “New Computer,” Hypothetical Price and Output Calculations   UNIVAC (1953) “New Computer” (1955) (Case One) “New Computer” (1955) (Case Two) Number produced 3 10 10 Price, each $400 thousand $600 thousand $600 thousand Current price output $1.2 million $6.0 million $6.0 million Performance index (M) 1.0 1.5 1.8 Computer inflation (with estimated performance premium = 1 + .7 (ΔM) 1.00 1.11 .96 Computer “constant price” output index 1.00 4.60 5.17 Computer output must have expanded by a factor greater than the threefold increase in units produced. How much greater? To answer that, economists also need a measure of computer performance. Economists also want to calculate the productivity of making computers, just as they calculate productivity in other industries. One common form of productivity is labor productivity, defined as output per worker hour. Again, if “new computer” has higher performance than UNIVAC, economists want to calculate output per labor hour in producing computers with a “quality adjustment” that incorporates the improved performance of the new computer. For estimating productivity change, “new computer’s” higher performance must be factored into the output measure. Similar statements apply to other economic measures, particularly to computer investment and capital stock. Thus, for measuring inflation, output growth, productivity growth, the volume of investment and capital stock, and for other economic measurements, economists need a measure of computer performance. It is well known that a bottom-end desktop computer today greatly outperforms anything available at the dawn of the commercial computer age, which was 50 years ago. Counting the number of computers produced will never tell us much about trends in computer output. The great expansion of computer output in the last 50 years is an expansion not only in numbers of computers but also in what might be thought of as “output per computer produced,” that is, performance per machine. We need now to discuss the properties that economists want in their measures of computer performance. To carry this forward, suppose now that we all agree on a measure of computer performance. It should not be too surprising that, as I discuss in the following section, achieving measures of computer performance is not at all a straightforward task. But set that aside, for the moment.

OCR for page 97
Deconstructing the Computer: Report of a Symposium Suppose we have an agreed-on measure of computer performance that covers the UNIVAC and the 1955 “new computer.” Suppose that we standardize our performance measure so that the UNIVAC has 1.0 performance units, and the new computer has 1.5 performance units.2 Unfortunately, even when computer performance is a scalar measure, we cannot simply divide the value of UNIVAC or “new computer” production by the performance measure in order to compare 1952 and 1955 computer output. Economists need the value of the performance indicator. There are several reasons. An old computer relationship called Grosch’s Law indicates that the cost of a computer center does not rise linearly with its computing power. Similar arguments can be made on the demand side: The incremental value of improved performance to the user does not necessarily rise proportionately with an increase in performance. Thus if “new computer” has 1.5 times the performance of UNIVAC, we need some way to value this 1.5 performance improvement ratio. We must know the performance premium, a value measure, not just the increment in performance. The valuation problem is truly daunting. Likely, UNIVAC and the replacement computer do not appear in the market at the same time. If they do, “new computer” should sell for more, and it is natural to take the ratio of the two machines’ prices as measuring the value of their relative performance. All kinds of problems exist with that, which I do not mean to minimize. For example, the high-end user might be willing to pay more than the actual price premium for “new computer” to get a high-end machine, but the low-end user might not be willing to pay the price difference; if so, the price differential only reflects the value of the performance difference to the user who is on the margin between buying the one or the other. But these are essentially aggregation problems (over users), which I set aside because they arise throughout economic statistics of this kind. A more promising situation exists empirically if there are a large number of computer models, and we have data on their prices and their performance. One can then run a regression, such as: (1) In equation (1), P is a vector of prices of computers, where models are indexed by the letter i, M is the associated performance measure for each computer, and ei is the regression error term. Using equation (1), we estimate a1 and use a1 to put a value on the performance difference among machines: If UNIVAC has M = 1.0 and “new computer” has M = 1.5, then the quantity [a1(0.5)] gives a “quality adjustment” that can be used to value the difference between the two machines. 2   And we suppose, contrary to what is true, that computer performance can be represented as a simple scalar.

OCR for page 97
Deconstructing the Computer: Report of a Symposium Suppose that we estimate a1 to be 0.7. Computer inflation between 1952 and 1955 (“quality adjusted” for “new computer’s” performance premium) is then: $600K / {$400K ((1 + 0.7(0.5))} = 1.11, or 11 percent inflation. This number is clearly less than the 1.50 (equals 50 percent inflation) that the unadjusted data would show. If “new computer” has M = 1.8, then computer prices are falling: $600K / {$400K ((1 + 0.7 (0.8))} = 0.96, or 4 percent price decline. Turning to computer output, the usual method for measuring output changes (in the national accounts, for example) is to “deflate” expenditures on a product by its price index (information on the U.S. national accounts is in Bureau of Economic Analysis, 2001). To form a deflated measure of computer output, we start from the change in “current price” output, which in our example was ($6.0 mil − $1.2 mil) / $1.2 mil, equal to a 400 percent increase. Deflating that by the price index of 1.11 gives for the “constant price” output change a 360 percent increase between 1952 and 1955. Deflated output grows less than current price output because in this example (M = 1.5) computer prices, performance adjusted, were rising. When “new computer” has a larger performance differential over UNIVAC (in the second example, M = 1.8), the price index declines, to 0.96, or a 4 percent decline. Using this declining price index as a deflator results in a “constant price” output change that is larger than the “current price” change (400 × (1/.96) = 417). In national accounts, this “constant price” output measure is sometimes (rather inappropriately) known as “real output.”3 This simple example illustrates several principles that govern estimation of computer output and investment in the U.S. national accounts. The most important one is that it shows how strongly measures of computer performance influence economic measurement of computer price change, and through the deflation procedure, how strongly computer performance affects measures of computer output, investment and productivity. Equation (1) is a relation that is known in economics as a “hedonic function,” although equation (1) is a very simple hedonic function. The “quality adjustment” outlined in the preceding paragraph is, in essence, the method applied by the Bureau of Labor Statistics (BLS) in estimating price indexes for computers, where quality adjustments for enhanced computer performance are derived from a hedonic function. This example is far too simple, however. In general, computer performance is not a scalar; it is multidimensional (the implications of this are explored in the subsequent section). Thus, computer hedonic functions look, generally, like equation (2): (2) 3   BEA also uses the somewhat cryptic term “chained dollars” to represent the same thing, and reports percentage changes in the form of index numbers, under the title “chained-type quantity index.”

OCR for page 97
Deconstructing the Computer: Report of a Symposium Each of the k variables in equation (2) is a “characteristic” of computer performance. The current BLS hedonic function for personal computers has more than a dozen characteristics. Each of the coefficients, ak in equation (2), is interpreted as the value of the corresponding computer performance characteristic. Because I have written equation (2) in a logarithmic form (the hedonic function often turns out to be logarithmic, but not always), these coefficients are not prices denominated in the usual dollars or euros, but dollar and euro prices can be extracted from the coefficients, if desired. Hedonic price indexes have become the standard economic tool for measuring price change in computers. In principle, they measure the price of computing power. Getting from the price indexes to the output investment numbers is relatively straightforward and follows the example already presented. Table 2 shows current dollar changes for computer investment in the national accounts, the computer deflator, and the resulting deflated investment numbers from the national accounts, for the years 1995–2002. In 1995 computer and peripheral “current price” investment in the United States equaled $64.6 billion. In 2000, the value of computer equipment investment equaled $93.3 billion. Thus, in current prices computer equipment investment increased by 44 percent. The computer equipment price index declined by 71 percent over the same 1995–2000 interval (from 131 to 38, using 1996 as the base). The change in current price shipments divided by the change in the price index gives the “deflated” (also called “constant price” or “real”) value of the change in computer equipment investment over that interval: As Table 2 shows, this increased four-fold (the quantity index goes from 69 in 1995 to 348 in 2000). The source of the great increase in computer investment in the national accounts numbers is not only the increase in spending on computer equipment, but also the decline in performance-corrected prices for this equipment. This same point is dramatically illustrated by the post-2000 experience. Actual spending on computer and peripheral equipment fell by 20 percent. But the TABLE 2 Private Fixed Investment in Computers and Peripheral Equipment   1995 1996 1997 1998 1999 2000 2001 2002 Billions of current dollars 64.6 70.9 79.6 84.2 90.4 93.3 74.2 74.4 Billions of chained 1996 dollarsa 49.2 70.9 102.9 147.7 207.4 246.4 239.9 284.1 Chained price index 131.29 100 77.38 56.99 43.6 37.87 30.91 26.27 Quantity index 69.4 100 145.22 208.39 292.64 347.77 338.61 400.92 a“Chained dollars” is the Bureau of Economic Analysis name for a quantity index of computer equipment output (see text). SOURCE: Bureau of Economic Analysis, NIPA Tables 5.4, 5.5, and 7.6.

OCR for page 97
Deconstructing the Computer: Report of a Symposium national accounts quantity index increased by 15 percent over the same 2000–2002 interval, because the price index fell by 30 percent (see Table 2). Tables 3 and 4 show that these trends have been going on for a long time. The price of computer equipment (computers plus peripherals) has declined 17.5 percent per year over the whole period for which national accounts investment data are available. Moreover, over the whole of the historical period, prices of computers themselves have declined faster than prices of peripherals (this is evident from Tables 3-5). The price of computing power today approaches 1/1,000 of 1 percent of what it was at the introduction of the commercial computer 50 years ago (Table 4).4 Additionally, the prices of ancillary devices have also fallen, though their performance improvements are often overshadowed by the spectacular progress in computer hardware: PC World (March, 2003, page 91) reports that the cost of storage media (disks) has fallen from $16.25 per MB of data stored in 1981 to $0.0008 (8 percent of a penny) in 2003, an annual rate of decline of 36 percent, comparable to the rate for PC computers over the same interval. Computer price indexes fall because the performance of computers is increasing very rapidly, where their actual selling prices are stable or falling. Accordingly, it is no surprise that computer output in the economy rises not so much because increasing numbers of computers are produced (though this is true) but because the capability of the computers that are produced has increased so much. The great increase in computer investment over the last 50 years as measured in the national accounts is in large part an estimate of the value of increased performance of computers over this interval. Nordhaus (2002) takes the price of computing back another 50 years, using a different approach. Though the rates of decline in the last half century are greater than in the half century before that, Nordhaus’ results indicate that high demand for improvements in computational power has existed over a long time, as well as indicating the extraordinary fruits of innovative ability set to satisfy that demand. Price indexes for computers transfer directly into economists’ measures of the output of computers, of “real” (an economist’s somewhat misleading jargon) computer investment and capital stock, and from these the rate of productivity improvement. As examples of the latter, Jorgenson, Ho, and Stiroh (2002) estimate that the contribution of ICT (information and communication technology) investment was responsible for a large proportion of the acceleration in U.S. labor productivity in years following 1995. Triplett and Bosworth (2002) reached comparable findings for the importance of ICT investment to the substantial gains 4   The mainframe index in Table 4 gives a beginning/end value of 3.91−05. But over the period for which mainframe and PC price indexes are available (1982 forward), PC prices have fallen at 21 percent per year in the government indexes, where mainframes have trailed, at 18 percent per year (Table 4). Moreover, studies suggest that the government PC price index records too little decline, certainly over the first part of this period—for example, Berndt and Rappaport (2001, Table 1) indicate that PC prices fell over 30 percent per year between 1983 and 1999. Hence, taking all this together, the round number 1/100,000 in the text.

OCR for page 97
Deconstructing the Computer: Report of a Symposium TABLE 3 Private Fixed Investment in Computers and Peripheral Equipment   Price Index (1996 = 100) Quantity Index (1996 = 100) 1959 101372.4 0.000 1960 79593.2 0.00044 1961 58800.8 0.00077 1962 41710.3 0.00143 1963 27395.1 0.00396 1964 22916.4 0.00616 1965 18936.0 0.00979 1966 13272.8 0.02354 1967 10784.1 0.03091 1968 9202.6 0.03696 1969 8332.3 0.05038 1970 7484.4 0.0605 1971 5698.7 0.07458 1972 4592.4 0.11 1973 4354.0 0.12 1974 3554.9 0.15 1975 3288.5 0.15 1976 2746.5 0.23 1977 2390.1 0.34 1978 1616.8 0.66 1979 1339.7 1.07 1980 1045.6 1.69 1981 918.9 2.63 1982 822.3 3.24 1983 685.6 4.92 1984 554.6 8.04 1985 471.5 10.10 1986 406.2 11.61 1987 346.0 14.59 1988 321.4 16.67 1989 300.1 20.27 1990 272.3 20.03 1991 244.6 21.75 1992 209.2 29.40 1993 178.4 37.31 1994 157.3 46.00 1995 131.3 69.40 1996 100.0 100.00 1997 77.4 145.22 1998 57.0 208.39 1999 43.6 292.64 2000 37.9 347.77 2001 30.9 338.61 2002 26.3 400.92 SOURCE: Bureau of Economic Analysis, NIPA Table 7.6, and unpublished BEA data in possession of the author (with more precise quantity index for earlier years). In 1959, the quantity index (1972=1) equals 0 to three decimal places in the unpublished data.

OCR for page 97
Deconstructing the Computer: Report of a Symposium TABLE 4 Price Indexes for Domestic Mainframes and PCs (1996 = 100)   Mainframes Personal Computers 1953 791125.1   1954 682645.1 1955 605330.6 1956 516628.7 1957 456095.6 1958 412943.3 1959 354208.3 1960 260717.8 1961 197440.1 1962 143811.5 1963 109881.7 1964 83549.6 1965 60060.6 1966 22761.6 1967 16110.6 1968 14560.0 1969 14513.8 1970 13967.4 1971 10847.4 1972 8871.7 1973 9453.9 1974 8041.6 1975 7771.7 1976 7106.5 1977 5582.2 1978 2812.2 1979 2306.9 1980 1591.9 1981 1311.4 1982 1106.3 1549.9 1983 1006.8 1086.5 1984 727.1 937.0 1985 537.1 877.3 1986 486.5 646.4 1987 419.1 582.9 1988 397.1 533.3 1989 346.5 496.1 1990 307.5 415.5 1991 297.6 350.4 1992 277.2 267.9 1993 234.2 207.3 1994 182.1 182.7 1995 144.0 145.3 1996 100.0 100.0 1997 68.6 67.1 1998 49.2 40.3 1999 38.6 25.7 2000 30.9 20.7   SOURCE: Triplett (1989) and unpublished Bureau of Economic Analysis data.

OCR for page 97
Deconstructing the Computer: Report of a Symposium Author Data Sources Dependent Variable Explanatory Variables Dummies for manufacturer and introduction year (gives price index, relative to earliest machines) NB: Justification for forming indexes based on technical assumptions—e.g., number of tape drive substitutes for speed in achieving same results. Cale, Gremillion, and McKenney (1979) Datapro Price at introduction for a “balanced” system (processor plus peripherals) Memory size in bytes Size (in megabytes) of online direct access storage NB: Addition time and other unspecified speed measures insignificant, partly owing to multicollinearity Fisher, McGowan and Greenwood (1983) Government lease price lists Lease prices to federal government Memory size in thou sands of bits Addition time (including access time) Transfer rate (bytes per second) Wallace (1985) GML Corp.; International Data Corp; Phister (1979) List prices of all machines Linear combination of MIPS and KOPS Memory size included or minimum memory size (units not given) Dummy variables for computer size class Dummy variables for manufacturers Cartwright, Donohoe, and Parker (1985) Auerbach Corp.; Datapro Corp.; and Computerworld List prices, all machines available Speed (memory cycle time, machine cycle time, or MIPS, depending on period) Memory size (in megabytes) Maximum number of channels Levy and Welzer (1985) Computerworld Published (list) prices, all machines from major producers MIPS Average memory size Dummy variables for manufacturer, and for newly introduced Ein-Dor (1985) Computerworld; other sources List price, selection of 106 machines MIPS (a number of other performance measures were related to MIPS and to “average computational cost”) Flamm (1987) Phister (1979) List price, all machines in source KOPS × 10−3 Memory size in megabytes

OCR for page 97
Deconstructing the Computer: Report of a Symposium Author Data Sources Dependent Variable Explanatory Variables Gordon (1989) 1954–1979 regressions Phister (1979) Prices of newly introduced machines Memory cycle time (in microseconds) Memory size (in megabytes) IBM dummy 1977–1984 regressions Computerworld Prices of all machines Machine cycle time (in nanoseconds Memory size (in megabytes) Minimum number of channels Maximum number of channels 5. Cache buffer size (units not given) Dulberger (this volume) Datamation; Computerworld; IBM List price, IBM and “plug-compatible” machines MIPS Memory size (in megabytes)—maximum and minimum “Technology class” dummy variables NB: Each machine entered twice in the data set, once with maximum memory size available, once with minimum memory size, with the appropriate price for each.

OCR for page 97
Deconstructing the Computer: Report of a Symposium ANNEX B1 Variables in Computer Hedonic Functions, Hardware Components Only   Cole et al. 1986 Berndt and Griliches 1993 Berndt et al. 1995 (desktops) Berndt and Rappaport 2002a Chwelos 2003 (laptops) Processor (CPU)   Speed MIPS MHz MHz MHz MHz * CPU or benchmark scores Memory MB (min and max) KB KB (installed and maximum) MB MB Cache no no no no no Technology variables Chip dummies 16- or 32-bit processor chip dummies 8-, 16- or 32-bit processor chip dummies Processor type; processor type*MHz Intel dummy Disk (hard) drive   Capacity MB MB MB MB MB Speed Sum of 3 no no no no Other no no Dummy for no HD no no Displays (terminals, monitors, and keyboards)   Screen size Number of characters no no no Size Resolution Dpi no no no Pixels in maximum resolution Color Number Dummy no no Dummy Other Number of function keys no no no Active or passive matrix LCD dummies Other hardware features (if yes, see Annex B2) no 7 6 2 8 Software features (if yes, see Annex B2) no no no no no

OCR for page 97
Deconstructing the Computer: Report of a Symposium Nelson et al. 1994 Pakes 2001 Moch 2001 (Germany) Rao and Lynch 1993 (workstations) Holdway 2001 (U.S.) Bourot 1997 (INSEE) MHz MHz, MHz^2 Test score MIPS MHz MHz MB MB MB KB MB MB3 no no KB no no KB Processor type Maximum memory; Apple*speed Architecture dummy no Celeron dummy Chip dummies MB GB MB MB MB MB no no no no no no no no no no no Type dummies no no Size no Size dummies Size no no no no Trinitron dummy dpi Dummy no Dummy no no no Monochrome monitor dummy no   Monochrome monitor dummy no no 5 7 6 3 9 7 2 no yes no 3 yes

OCR for page 97
Deconstructing the Computer: Report of a Symposium   Evans 2002   Barzyk 1999 (StatCan) Dalen 1989 (Sweden) Koshimaki and Vartia 2001   INSEE01 INSEE02   Processor (CPU)   Speed MHz b Test score MHz MHz Memory MB MB MB MB MB Cache no max KB no no Technology Memory type; maximum memory no no no no Disk (hard) drive   Capacity GB b MB MB no Speed no no no Access time no Other no no Type dummies no no Displays (terminals, monitors, and keyboards)   Screen size no no no no no Resolution no no no no no Color no no no no no Other no no no no no Other hardware features (if yes, see Annex B2) 7 4 6 no no Software features (if yes, see Annex B2) no no no no no aIncludes the same variables as Berndt and Rappaport (2001) plus microprocessor-type dummy variables and interactions between microprocessor type and clock speed. bReplaced by external volume measure.

OCR for page 97
Deconstructing the Computer: Report of a Symposium Statistics Finland 2000 Okamoto and Sato 2001 Lim and McKenzie 2002 van Mulligen 2002 MHz MHz CPU score MHz MB MB MB MB no no KB no Type dummy Processor type no Processor type GB MB MB GB no no no no no no no no Size Size 17″ dummy no no no no no no no no no no No monitor dummy; LCD dummy no Dummy variable for presence no 4 9 3 no no no no

OCR for page 97
Deconstructing the Computer: Report of a Symposium ANNEX B2 Computer Hedonic Functions, Other Hardware and Software Features (for other variables and sources, see Annex B1)   Berndt and Griliches Berndt et al. Berndt and Rappaport Chwelos Nelson et al. ZIP dummy no no no no no CDROM dummy no no yes no no CDROM speed no no no yes no CDRW dummy no no no no no DVD dummy no no no no no Sound card dummy no no no no no Video (MB) no no no no no Network card no no no no no Modem dummy no no no modem speed no Speakers dummy no no no no no Case type dummy no no no no no Warranty dummy no no no no no Seller dummies yes yes major brand major brand yes SCSI control no no no no no Operating system no no no no yes Other software no no no no other software utilities Other number of floppy drives slots available for expansion board mobile dummy discounted by vendor age extra hardware two or more floppy drives dummy size weight density age   battery type battery life index density discount price weight number of floppy drives extended industry standard architecture bus number of slots number of ports

OCR for page 97
Deconstructing the Computer: Report of a Symposium Pakes Moch Rao and Lynch Holdway Bourot no no no yes no no yes no no yes no no no no yes yes no no no no yes no no yes no yes no no no yes yes yes no yes yes yes no no yes no yes no no yes yes no no no yes no no yes no no yes no no no yes no Apple no yes yes no no no yes no no no yes no yes no no number of bundled applications no software office suite; MS Office no   second floppy dummy bus width number of graphics standards supported business market other cards   mouse dummy      

OCR for page 97
Deconstructing the Computer: Report of a Symposium   Evans   Barzyk   INSEE01 INSEE02   ZIP dummy no no no CDROM no no yes CDROM speed yes no no CDRW yes no no DVD dummy no no no Sound card dummy yes no no Video (MB) no yes no Network card yes no yes Modem dummy yes no yes Speakers dummy no no no Case-type dummy yes no yes Warranty dummy no yes no Seller dummies no yes yes SCSI control no no yes Operating system no no no Other software no no no Other number of slots network location  

OCR for page 97
Deconstructing the Computer: Report of a Symposium Okamoto and Sato Lim and McKenzie van Mulligen no no no no no no no no no no yes no no no no no no no no yes no no yes no yes no no no yes no no yes no no yes no Apple yes yes no yes no no no no no no no TV tuner expandability USB port vintage   workstation dummies

OCR for page 97
Deconstructing the Computer: Report of a Symposium This page intentionally left blank.