Ann Reg Sci (2010) 45:239–243DOI 10.1007/s00168-009-0318-3

COMMENTARY

The market and infrastructure perspective: reply

Brian E. Whitacre

Received: 11 May 2009 / Accepted: 6 July 2009 / Published online: 25 July 2009© Springer-Verlag 2009

Abstract A commentary on a 2008 article regarding broadband adoption inOklahoma suggests that incorporating a market and infrastructure perspective wouldhave significantly altered the arguments made. This reply argues that the distinctinfrastructure measures included in the original paper implicitly account for thisperspective. It also responds to several other critiques of the original paper.

JEL Classification R11 · O18 · C1

In a commentary included in this issue, Brown (2009) suggests that the analysis per-formed on broadband adoption in Oklahoma by Whitacre (2008) would have benefitedby incorporating the market and infrastructure perspective discussed by Brown (1981).The commentary focuses on the supply-side availability of broadband infrastructure,and implies that were such a market and infrastructure perspective taken, the argumentand possibly results would have been significantly altered. In this reply, I argue that theinclusion of distinct infrastructure measures (which implicitly account for elements ofthe market and infrastructure perspective) and the decomposition technique utilizedin the original paper make the initial results relatively robust. I also demonstrate thatincluding interaction variables in an effort to account for this type of perspective doesnot seem to be an appropriate specification. Finally, I respond to several other cri-tiques, including limiting the conclusions to the period of analysis and focusing onthe pejorative dimension of adopter categories.

B. E. Whitacre (B)Department of Agricultural Economics, 504 Ag Hall,Oklahoma State University, Stillwater, OK, 74074, USAe-mail: brian.whitacre@okstate.edu

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Brown (2009) provides a synopsis of the market and infrastructure perspectiverelevant to Oklahoma broadband by focusing on (i) propagators of the innovation,(ii) diffusion agencies through which the innovation is made available, and (iii) thediffusion strategy, including pricing and advertising. The argument is that this per-spective looks heavily at the marketing aspects of diffusion, which is seen as enablingthe resulting adoption decision. In effect, the concern is that by not considering thesesupply-side determinants, the resulting analysis is biased.

While this concern may have some theoretical validity, in practice the infrastruc-ture data used already account for the most important (and only available) elementsof this line of thought. Looking at a simple 0/1 measure for whether or not a ZIPcode has cable or DSL access does not delve into all of the lower-level components ofthe market and infrastructure perspective noted above, but it does serve as an aggre-gate measure of how this perspective ultimately played out. The yes / no availabilitymeasure accounts for the attitudes encompassed by (i) the propagators (cable TV andtelephone providers) and (ii) the diffusion agencies for distribution, since these entitieswere responsible for whether or not broadband was available at their facilities. If thereis any omission by this dataset, it is on the part of (iii) the diffusion strategy. No partof the infrastructure data looked at the prices offered by the various providers, or howaggressively they pursued marketing their product. The original paper acknowledgedthe omission of a price variable, but suggested this was not a concern due to relativelysimilar costs across the state in 2006 and the recent finding that own-price demand forbroadband is price inelastic (Flamm and Chaudhuri 2007). Obtaining data on market-ing efforts by broadband providers is simply not realistic—it would require (at best)detailed advertising budgets by each provider in the state, broken out by cost spentper ZIP code. Such information is not likely to be made public by private companiesgeared towards profit maximization. Further, with the increasing prevalence of web-site marketing during this time period (consider domain names displayed in TV ads,newspapers, billboards, magazines), the impact of distinct local broadband marketingefforts is debatable. Without such detailed data, I argue that the supply-side perspectiveis effectively captured by the infrastructure measures included in the original analysis.If the infrastructure measures were to be removed [such as the analysis performedin Mills and Whitacre (2003)], the argument that the market perspective was omittedwould bear more weight.

Another critique of the paper suggests that the observed infrastructure diffusion(whereby the number of cable systems and central offices offering broadband capa-bility doubled between 2003 and 2006) was a significantly larger contributor to theadoption process than the analysis implied. Although it is argued that I “seem to haveset aside [this evidence] in [my] conclusions,” I fully account for such diffusion in thedecomposition technique applied. In fact, the decomposition process itself basicallyreplaces the level of infrastructure (and other characteristics) in 2003 with those in2006, and vice versa. The results clearly indicate that these differing levels of charac-teristics are, indeed, only minor contributors to the increasing rates over time. Whilethe infrastructure diffusion may seem dramatic when viewed as the percentage ofcompanies with broadband capability, a more realistic perspective is given in Table 4of the original article, which shows the percentage of rural and urban residents withaccess to broadband infrastructure in 2003 and 2006. Over that 3-year period, each

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The market and infrastructure perspective: reply 241

geographic category only rose by 5% points (rural went from 48 to 53% and urbanwent from 82 to 87%), giving a bit more intuition as to why the infrastructure diffusionwas not a major contributor over this time period.

Brown (2009) also questions the limitations applied to the conclusions, suggestingthat using the market and infrastructure perspective would have allowed for conclu-sions beyond the statistical results obtained. While the importance of infrastructureundoubtedly changes over time (particularly when such infrastructure is initially intro-duced, or becomes widespread), the decomposition technique used can only accountfor the time frame under analysis. Applying a detailed, market-based approach mayprovide some additional insight into where future promotions or infrastructure mightbe set up, but provides no basis for extrapolating infrastructure’s impact on adop-tion rates beyond the period of analysis. Going beyond the statistical results offeredby the decomposition would require more than simply an altered view of the sup-ply scenario—it would entail assumptions about future characteristics and adoptionpropensities, both of which are outside the scope of the original paper.

The suggestion that the findings fit well with the idea of a supply-side divide (byincome, education, or rural/urban status) is intuitive, but was never explicitly testedin the original paper. Prieger (2003) was the first to look at such a supply-side gapat a national level, and found little evidence of unequal availability based on income.He did find that at that time, rural location decreased broadband availability. The ideaof interacting individual variables with infrastructure access is an intriguing test ofwhether incorporating a more detailed market approach (by accounting for specificcharacteristics which likely affect infrastructure availability) does in fact impact thefindings. Table 1 presents these results for 2003.

The initial column in Table 1 is exactly as shown in the original results (Table 5from Whitacre 2008). The following columns display a model with results from acomparable base category alongside cable and DSL interaction variables. As shown,only 1 of the resulting interaction variables is significant—for cable access at the$30K–$40K income level (hhinc4). Further, the only general variables that keep theirsignificance are those pertaining to income—the impact of education on the adoptiondecision has now been lost. These results suggest that the inclusion of such interac-tion terms only serves to remove significance from otherwise intuitive variables in theadoption decision, namely age and education. Generally, the lack of significance ofthe interaction terms implies that such an empirical model is not necessary.

Brown (2009) also suggests that the potentially pejorative dimension of Roger’sadoptive categories should be avoided, a point with which I agree. The statistics dis-cussed in the conclusion section of the original paper dealing with observed increasesamong low-income and low-education households are given strictly to document dif-fusion rates and are not meant to be judgmental in any way (p. 677).

I also concur with the implication that cable infrastructure’s impact was likely dueto its wide availability over a longer period of time. Figure 3 on p. 666 shows cable’sdominance in the residential broadband market in both 2003 and 2006, which is onereason for its significance in the regression results. Without data specific to promo-tional efforts, I am hesitant to assign much responsibility to the marketing componentof cable’s impact.

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Table 1 Original and interaction logit results for broadband access

Dependent variable: Original (1) Interaction (2)highspeed

2003 Base DSL Cable

Coefficient SE Coefficient SE Coefficient SE Coefficient SE

hs 0.624 0.498 0.297 0.877 −1.781 1.450 0.800 1.053

scoll 1.062 0.481** 0.571 0.899 −1.321 1.154 1.003 1.049

coll 0.972 0.488 ** 0.394 0.948 −1.667 1.275 1.160 1.115

grad 1.314 0.513 ** 0.802 0.955 −1.182 1.401 1.055 1.146

hhinc2 0.924 0.675 0.582 1.218 −0.776 1.396 0.410 1.439

hhinc3 1.679 0.647 *** 1.596 1.029 −0.004 1.516 −0.164 1.310

hhinc4 2.065 0.661 *** 0.601 1.085 −0.668 1.539 2.285 1.355 *

hhinc5 2.812 0.682 *** 1.986 1.165 * −0.802 1.555 1.296 1.414

hhinc6 2.443 0.684 *** 2.221 1.078 ** −0.379 1.625 0.422 1.383

hhinc7 3.415 0.709 *** 3.009 1.180 ** −1.549 1.525 1.103 1.464

hhinc8 3.497 0.680 *** 2.656 1.124 ** 0.388 1.768 1.394 1.387

hhinc9 3.579 0.748 *** 2.766 1.065 *** 1.275 1.693 0.840 1.455

age −0.076 0.036 ** −0.095 0.070 0.030 0.126 0.000 0.087

age2 0.000 0.000 0.000 0.001 0.000 0.001 0.000 0.001

married −0.286 0.225 0.083 0.376 0.126 0.633 −0.615 0.496

numberkids −0.108 0.104 −0.016 0.162 0.213 0.235 −0.137 0.218

retired 0.206 0.357 −0.312 0.542 −0.825 1.493 0.753 0.759

hispanic −0.855 0.595 0.380 1.716 −0.289 1.243 −0.627 1.836

black 0.782 0.425 * −1.730 0.624 0.532 1.286 0.764 1.240

indian −0.419 0.380 −0.328 0.496 1.203 0.870 −0.884 0.719

othrace −0.255 0.536 −0.206 0.728 0.336 1.231 −0.568 1.354

cable 0.652 0.254 **

dsl 0.296 0.547

both −0.107 0.627

rural −0.078 0.220 0.077 0.368 −0.566 0.562 0.009 0.470

constant −1.323 0.909 −0.198 1.463 1.188 3.189 −0.927 1.904

*, **, and *** indicate statistically significant differences from zero at the p = 0.10, 0.05, 0.01 levels, respectively

The final note of Brown (2009) deals with the complementarity of various innova-tion diffusion perspectives, particularly noting Damian Miller’s recent book (2009) onrenewable energy diffusion. Miller is quick to point out that the market and infrastruc-ture perspective is the one most closely aligned to the role of the entrepreneur, but alsorecognizes the importance of commercial firms in technology diffusion. While thispaper has focused heavily on the commercial providers of broadband access, entre-preneurs have played a significant role in providing availability—particularly to ruralareas of many states. My own extension program acknowledges the importance ofthese individuals (Whitacre 2007a,b), and I generally agree with the suggestion thattheir role needs to be considered, although the lack of formal data on the location ofsuch endeavors is limiting.

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The market and infrastructure perspective: reply 243

I appreciate the thoughtful and well-constructed comment on the original article.The argument for the marketing and infrastructure perspective in this type of analysisis relevant and deserves its own light; however, I remain convinced that the approachtaken accounts for enough of this perspective to make the analysis robust.

Acknowledgments I would like to thank the editors of Annals of Regional Science for the opportunityto write this reply.

References

Brown LA (1981) Innovation diffusion: a new perspective. Metheun, LondonBrown LA (2009) The market and infrastructure perspective: a missing link in understanding the diffusion

of broadband adoption in Oklahoma. Ann Reg Sci. doi:10.1007/s00168-009-0319-2Flamm K, Chaudhuri A (2007) An analysis of the determinants of broadband access. Telecomm Policy 31:

312–326. doi:10.1016/j.telpol.2007.05.006Miller D (2009) Selling solar: the diffusion of remewable energy in emerging markets. Earthscan, LondonMills B, Whitacre B (2003) Understanding the metropolitan—non-metropolitan digital divide. Growth

Change 34(2): 219–244. doi:10.1111/1468-2257.00215Prieger J (2003) The supply side of the digital divide: is there equal availability in the broadband internet

access market? Econ Inq 41(2): 346–363. doi:10.1093/ei/cbg013Whitacre B (2007a) “Rural broadband success story: Plainsnet.net—hometown entrepreneurs find wire-

less solution to connect their rural community.” Oklahoma State University Extension Fact SheetAGEC-1003, June 2007

Whitacre B (2007b) “Rural broadband success story: Sallisaw—a fiber optic network for the ages.”Oklahoma State University Extension Fact Sheet AGEC-1000, April 2007

Whitacre B (2008) Factors influencing the temporal diffusion of broadband adoption: evidence from Okla-homa. Ann Reg Sci 42: 661–679. doi:10.1007/s00168-007-0178-7

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