Abstract
The analysis of network effects in technology-based networks continues to be of significant managerial importance in e-commerce and traditional IS operations. Competitive strategy, economics and IS researchers share this interest, and have been exploring technology adoption, development and product launch contexts where understanding the issues is critical. This article examines settings involving countervailing and complementary network effects, which act as drivers of business value at several levels of analysis: the industry or market level, the firm or process level, the individual or product level, and the technology level. It leverages real options analysis for managerial decision-making under uncertainty across these contexts. We also identify a set of real options—compatibility, sponsorship and ownership option—which are unique to these settings, and which provide a template for managerial thinking and analysis when it is possible to delay an investment decision. We employ a hybrid jump-diffusion process to model countervailing and complementary network effects from the perspective of a user or a firm joining a network. We also do this from the perspective of a network developer. Our analysis shows that when countervailing and complementary network effects occur in the same network technology context, they give rise to real option value effects that may be used to control or modify the valuation trajectory of a network technology. The option value of waiting in these contexts jumps when the related business environment experiences shocks. Further, we find that the functional relationship between network value and the option value is not linear, and that taking into account a risk premium may not always result in a risk-neural investment. We also provide a managerial decision-making template through the different kinds of deferral options that we identify for this IT analysis context.
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Notes
A risk premium is an additional amount of payoff above the risk-free rate of interest to make a decision-maker indifferent between a higher risky payoff and a lower non-risky payoff [53]. Decision-makers who exhibit risk-neutral attitudes are indifferent to the risks involved and are only concerned about expected returns.
Two events are independent if the occurrence of one of the events gives us no information about whether the other event will occur; that is, the events have no influence on each other. When two variables co-vary, change in one is accompanied by change in other, and they are said to be correlated. Although independence implies no correlation, lack of correlation does not imply independence. In real-world settings, dx may be related to Y.
References
A. Asvanund, K. Clay, R., Krishnan, M.D. Smith, An empirical analysis of network externalities in P2P music sharing networks. Inf. Syst. Res. 15, 155–174 (2004)
Y. Au, R.J. Kauffman, What do you know? Rational expectations in IT adoption and investment. J. Manage. Inform. Syst. 20, 49–76 (2003)
Y. Bakos, B.R. Nault, Ownership and investments in electronic networks. Inform. Syst. Res. 8, 321–341 (1997)
R.D. Banker, R.J. Kauffman, R. Kumar, Managing the performance of computer-aided software engineering (CASE) development with life cycle trajectory metrics. Chapter 15, in Software Engineering Productivity Handbook, ed. by J. Keyes (McGraw Hill, New York, NY, 1993), pp. 263–284
I. Bardhan, S. Bagchi, R. Sougstad, Prioritizing a portfolio of information technology investment projects. J. Manage. Inform. Syst. 21, 33–60 (2004)
M. Benaroch, Managing IT investment risk: a real options perspective. J. Manage. Inform. Syst. 19, 43–84 (2002)
M. Benaroch, M. Jeffrey, R.J. Kauffman, S. Shah, Option-based risk management: a field study of sequential IT investment decisions. J. Manage. Inform. Syst. 24, 103–140 (2007)
M. Benaroch, R.J. Kauffman, A case for using option pricing analysis to evaluate information technology project investments. Inform. Syst. Res. 10, 70–86 (1999)
M. Benaroch, R.J. Kauffman, Justifying electronic banking network expansion using real options analysis. MIS Quart. 24, 197–225 (2000)
M. Benaroch, Y. Lichtenstein, K. Robinson, Real options in IT risk management: An empirical validation of risk options relationships. MIS Quart. 30, 827–864 (2006)
N.P.B. Bollen, Real options and product life cycles. Manage. Sci. 45, 670–684 (1999)
B. Briscoe, A. Odlyzko, B. Tilly, Metcalfe’s Law is wrong. IEEE Spectr. 43, 26–31 (2006)
M. Cantor, Estimation variance and governance, Developer Works, Rational Technical Library, IBM Corporation, March 15, 2006, www.ibm.com/developerworks/rational/library/mar06/cantor/
H. Chen, Y. Chang, Non-normality effects on the economic–statistical design of X̄ charts with Weibull in-control time. Eur. J. Oper. Res. 176, 986–998 (2007)
E. Clemons, Evaluations of strategic investments in information technology. Commun. ACM 34, 22–36 (1991)
Q. Dai, R.J. Kauffman, To be or not to B2B? an evaluative model for e-procurement channel adoption. Inform. Technol. Manage. 7, 109–130 (2006)
Q. Dai, R.J. Kauffman, S.T. March, Valuing information technology infrastructures: a growth options approach. Inform. Technol. Manage. 8, 1–17 (2007)
D.J. DeBrota, S.D. Roberts, R.S. Dittus, J.R. Wilson, Visual interactive fitting of bounded Johnson distributions. Simulation 52, 199–205 (1989)
D. Demirhan, V.S. Jacob, S. Raghunathan, IT investment strategies under declining technology cost. J. Manage. Inform. Syst. 22, 321–350 (2006)
T. Doganoglu, l. Grzybowski, Estimating network effects in mobile telephony in Germany. Inform. Econ. Policy 19, 65–79 (2007)
B. Dos Santos, Justifying investments in new information technology. J. Manage. Inform. Syst. 7, 71–90 (1991)
N. Economides, The economics of networks. Int. J. Ind. Org. 14, 673–699 (1996)
M. Evans, N. Hastings, B. Peacock, Triangular distribution, Chapter 40, in Statistical Distributions, 3rd edn (Wiley, New York, NY, 2000), pp. 187–188
R. Fichman, Real options and IT platform adoption: implications for theory and practice. Inform. Syst. Res. 15, 132–154 (2004)
R. Geske, The valuation of corporate liabilities as compound options. J. Finan. Quant. Anal. 12, 541–552 (1997)
S.R. Grenadier, A.M. Weiss, Investments in technological innovations: an option pricing approach. J. Finan. Econ. 44, 397–416 (1997)
S. Grossman, O. Hart, The costs and benefits of ownership: a theory of vertical and lateral integration. J. Polit. Economy 94, 691–719 (1986)
N. Gustafson, J. Luft, Valuing strategic flexibility in information technology investments: when do subjective valuation and real options analysis differ? 2002 Accounting, Behavior and Organizations Research Conference, American Accounting Association, Dallas, TX, 2002
K. Han, R.J. Kauffman, B.R. Nault, Information exploitation and interorganizational systems ownership. J. Manage. Inform. Syst. 21, 109–135 (2004)
K. Han, R.J. Kauffman, B.R. Nault, Relative importance, specific investment and ownership in interorganizational systems. Inform. Technol. Manage. (2008) (this issue)
O. Hart, J. Moore, Incomplete contracts and renegotiation. Econometrica 56, 755–785 (1988)
K. Huisman, Technology Investment: A Game Theoretic Real Options Approach (Kluwer, Dordrecht, Amsterdam, Netherlands, 2001)
K. Huisman, P. Kort, Strategic technology adoption taking into account future technological improvements: a real options approach. Eur. J. Oper. Res. 159, 705–728 (2004)
D. Johnson, The triangular distribution as a proxy for the beta distribution in risk analysis. The Statistician. 46, 387–398 (1997)
M.L. Katz, C. Shapiro, Network externalities, competition and compatibility. Am. Econ. Rev. 75, 425–440 (1985)
M.L. Katz, C. Shapiro, Technology adoption in the presence of network externalities. J. Polit. Economy 94, 822–841 (1986)
M.L. Katz, C. Shapiro, Product introduction with network externalities. J. Ind. Econ. 40, 55–83 (1992)
R.J. Kauffman, A. Kumar, Understanding state and national growth co-movement: a study of shared ATM networks in the United States. Electron. Com. Res. Appl. (2007), in press
R.J. Kauffman, X. Li, Technology competition and optimal investment timing: a real options perspective. IEEE Trans. Eng. Manage. 52, 15–29 (2005)
R.J. Kauffman, J.J. McAndrews, Y. Wang, Opening the ‘black box’ of network externalities in network adoption. Inform. Syst. Res. 11, 61–82 (2000)
R.J. Kauffman, Y. Wang, The network externalities hypothesis and competitive network growth. J. Org. Comput. Electron. Com. 12, 59–83 (2002)
K.W. Ko, Internet externalities and location of foreign direct investment: a comparison between developed and developing countries. Inform. Econ. Policy 19, 1–23 (2007)
S. Kotz, J.R. van Dorp, A novel method for fitting unimodal continuous distributions. IEEE Trans. 38, 421–436 (2006)
S.J. Liebowitz, S.E. Margolis, Network externality: an uncommon tragedy. J. Econ. Perspect. 8, 133–150 (1994)
S. Mathews, Business engineering: a practical approach to valuing high-risk, high-return projects using real options, 2007 INFORMS Conference, Seattle, WA (2007)
C. Matutes, P. Regibeau, Mix and match: product compatibility without network externalities. Rand. J. Econ. 19, 219–234 (1988)
R.C. Merton, Option pricing when underlying stock returns are discontinuous. J. Finan. Econ. 3, 125–144 (1976)
J.J. Moder, E.G. Rodgers, Judgment estimate of the moments of PERT type distributions. Manage. Sci. 18, 76–83 (1968)
J.P. Onnela, J. Saramäki, J. Hyvönen, G. Szabó, D. Lazer, K. Kaski, J. Kertész, A.L. Barabási, Structure and tie strengths in mobile communication networks. Proc. Natl. Acad. Sci. USA 104, 7332–7336 (2007)
S. Panayi, L. Trigeorgis, Multi-stage real options: the cases of IT infrastructure and international bank expansion. Q. Rev. Econ. Finance 38, 675–692 (1998)
O.V. Pavlov, N. Melville, R.K. Plice, Mitigating the tragedy of the digital commons: the problem of unsolicited commercial email. Commun. Assoc. Inform. Syst. 16, 73–90 (2005)
J.G. Pérez, S.C. Rambaud, L.B. García, The two-sided power distribution for the treatment of the uncertainty in PERT. Stat. Methods Appl. 14, 209–222 (2005)
J.W. Pratt, Risk aversion in the small and in the large. Econometrica 32, 122–136 (1964)
D.P. Reed, The law of the pack. Harv. Bus. Rev. 79, 23–24 (2001)
F.J. Riggins, C.H. Kriebel, T. Mukhopadhyay, The growth of interorganizational systems in the presence of network externalities. Manage. Sci. 40, 894–998 (1994)
E.M. Rogers, Diffusion of Innovation, 4th edn. (Free Press, New York, NY, 1995)
T.J. Rowley, Moving beyond dyadic ties: a network theory of stakeholder influences. Acad. Manage. Rev. 22, 887–910 (1997)
G. Saloner, A. Shepard, Adoption of technologies with network effects: an empirical examination the adoption of ATMs. Rand J. Econ. 26, 479–501 (1995)
E. Schwartz, C. Zozaya-Gorostiza, Investment under uncertainty in IT: acquisition and development projects. Manage. Sci. 49, 57–70 (2003)
M. Shurmer, An investigation into sources of network externalities in the packaged PC software market. Inform. Econ. Policy 5, 231–251 (1993)
H. Smit, Infrastructure investment as a real options game: the case of European airport expansion. Finan. Manage. 32, 27–57 (2003)
Structured Data LLC, The beta PERT distribution, New York, NY (2007), www.riskamp.com/library/pertdistribution.php
R.S. Sutton, A.G. Barto, Reinforcement Learning: An Introduction. (MIT Press, Cambridge, MA, 1998)
G.M.P. Swann, The functional form of network effects. Inform. Econ. Policy 14, 417–429 (2002)
P.P. Tallon, R.J. Kauffman, H.C. Lucas, A.B. Whinston, K. Zhu, Using real option analysis for evaluating uncertain investments in information technology. Commun. Assoc. Inform. Syst. 9, 136–167 (2002)
L. Trigeorgis, The nature of option interactions and the valuation of investments with multiple real options. J. Finan. Quant. Anal. 28, 1–20 (1993)
J.R. van Dorp, S. Kotz, A novel extension of the triangular distribution and its parameter estimation. The Statistician. 51, 63–79 (2002)
J.R. van Dorp, S.C. Rambaud, J.G. Perez, R.H. Pleguezuelo, An elicitation procedure for generalized trapezoidal distribution with a uniform central stage. Technical report TR-2007–3, Institute for Integrating Statistics in Decision Sciences, George Washington University, Washington, DC, April 4, 2007
K. Zhu, Strategic investments in information technologies. Unpublished Ph.D. dissertation, Industrial Engineering and Operations Research, Stanford University, Stanford, CA (1999)
Acknowledgments
This article was first presented at the 20th Anniversary Symposium on Competitive Strategy, Economics and Information Systems at the 2007 Hawaii International Conference on Systems Science, in January 2007. The authors benefited from feedback from Michel Benaroch, Rajiv Dewan, Eric Clemons, and other participants. We are grateful to Indranil Bardhan, for his guidance in the development of this article for Information Technology and Management, and for the helpful suggestions of three anonymous reviewers. We also appreciated the interest of the special issue guest editors, Paul Tallon and Alok Gupta, in our work. We thank Qizhi Dai, Ryan Sougstad, and the participants of our doctoral seminars at Arizona State University and the University of Minnesota for discussions on related research problems at an early stage in the development of this research. Recent discussions with Murray Cantor and Clay Williams of IBM, and Scott Matthews of Boeing have also added value to this work. Rob Kauffman acknowledges support and funding from the MIS Research Center at the University of Minnesota and the Center for Advancing Business through Information Technology at Arizona State University, as well as the W. P. Carey Chair. Finally, Ajay Kumar is grateful for doctoral fellowship funding from the Graduate School of the University of Minnesota.
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Appendix
Appendix
We now provide some additional details to further explain the modeling analysis that we conducted for the development of the results that are presented in this article.
1.1 Differential real option value
To obtain the result we have described, we analyzed the differential real option value for the network technology investment, which can be expressed as:
The superscripted notation denotes the partial differentials with respect to the variables, I U and R U, which represent investment I and the value of the revenues R that user U is able to obtain for its network technology investment. We are able to conclude that the real option value function ROV(R U, I U, t) is non-linear because the last term in Eq. A1 does not linearly relate to changes in differential real option value, dROV, with incremental changes dq in the variable q.
1.2 Application of the Bellman optimality equation
We used a risk-neutral process for the continuous part of the real option value function of the network, and substituted the equations for dR, dI U, ρ RI , dROV and dR U′ into the Bellman optimality equation, the r f ROVdt = E(dROV), the risk-free rate of interest r f . The Bellman optimality equation says that the value of a state under the optimal policy—in this case the value of the real option—must equal the expected return for the best action from that state [63]—in other words, the exercise of the real option. The Bellman equation has to satisfy two boundary conditions to be optimal. The value of the real option must be 0 at time T (the end of the horizon), because the decision to join the network cannot be deferred anymore, so that ROV(V U, I U, T) = 0. A second condition is that at any other time, 0 ≤ t < T, the value of the real option is always non-negative, and represents the value and the cost of joining the network for the user, so ROV(V U, I U, t) ≥ max[0, V U(t) − I U(t)].
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Kauffman, R.J., Kumar, A. Network effects and embedded options: decision-making under uncertainty for network technology investments. Inf Technol Manage 9, 149–168 (2008). https://doi.org/10.1007/s10799-008-0037-y
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DOI: https://doi.org/10.1007/s10799-008-0037-y