Inflating the bubble: examining dot-com investor behaviour

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Inflating the bubble: examining dot-com investor behaviourDave Valliere & Rein PetersonPublished online: 23 Feb 2007.

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Inflating the bubble: examining dot-com investor

behaviour

DAVE VALLIERE and REIN PETERSON

(Final version accepted 12 September 2003)

Findings are presented from a study of the cognitive behaviours of 57 venture capitalinvestors in the early-stage technology sector during the 1998 – 2001 Internet bubbleperiod. The inductive research methodology was based on open-ended qualitativeinterviews with investment practitioners, conducted by the lead author who was aninvestment practitioner during the bubble. The data obtained were used to develop agrounded model of how generally accepted venture capital industry decision-makingpractices were bypassed and modified by investors competing intensively in an unfamiliarsector with unknown success criteria, which contributed to the creation of the bubble.Insights from prospect theory, attribution theory and cognitive dissonance theory wereused to identify the cognitive processes that led through groupthink to the development ofa conceptual framework in the industry, similar to what organizational theorist GarethMorgan has called a Psychic Prison. The study identified four positive feedback loops inthe environment surrounding the activities of Internet investors that contributed to thebypassing of generally accepted practices by investors who believed they were behavingrationally.

Keywords: venture capitalists; investment criteria; Internet bubble; cognitive decisionmaking model; escalating commitment

Irrational exuberance?

The phenomenon of manias and speculative investment bubbles has beenextensively studied over the years (MacKay 1841, Kindleberger 2001), butthere has been limited research into the forces driving venture capital (VC)investors to participate in apparent investment bubbles. The period of1998 – 2001 (the Internet bubble) saw rapid run-ups in valuations andcapital volumes throughout the capital markets lifecycle, followed by anequally rapid collapse. During this period, the market value of publicly

Dave Valliere is sessional faculty at the Schulich School of Business, York University, Toronto,

Ontario, Canada. He is an author of several trade papers in technology management and business

strategy. His professional experience includes venture capital investing, commercial banking, and

strategic management roles in a variety of high-technology firms; e-mail: [email protected]

Rein Peterson is Professor of Policy and the Max and Anne Tannenbaum Chair in Entrepreneurship and

Family Enterprise at the Schulich School of Business, York University, Toronto, Ontario, Canada M3J

1P3. He served as the Canadian co-ordinator of the Global Entrepreneurship Monitor research project

from 1998 – 2002. He was a member of several boards of new ventures launched during the Internet

bubble; e-mail: [email protected]

Venture Capital ISSN 1369-1066 print/ISSN 1464-5343 online # 2004 Taylor & Francis Ltdhttp://www.tandf.co.uk/journals

DOI: 10.1080/1369106032000152452

VENTURE CAPITAL, JANUARY 2004, VOL. 6, NO. 1, 1 – 22

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traded Internet companies rose and fell dramatically. Pioneeringe-commerce retailer Amazon.com debuted at $18 in its 1997 IPO, rose toover $106 by December of 1999 and subsequently fell to below $15 byDecember 2001 (amounts in US$). The market for initial public offeringsin the USA exhibited similar behaviour, peaking at 446 offerings in 1999before falling to a mere 79 in 2001 (Ritter 2001). In the pre-IPO markets,venture capital investors experienced corresponding swings in businessvolumes. The US National Venture Capital Association (NVCA) reportsthat in 1998 there were 288 VC funds with $31.1 billion investment capital,and that by 2000 this had risen to 635 funds with $107.7 billion as VC firmsaggressively obtained additional funds from their respective investors—butby the end of 2001 this had fallen to only 94 funds with $5.7 billion (NVCA2002).Despite research demonstrating some net positive effects from past

speculative bubbles (Bygrave et al. 2000), these extremes in investorbehaviour have raised questions about the rationality of the participatinginvestors and the efficiency of early-stage technology-oriented capitalmarkets. Above all, the questions have centred on whether theinvestments made at that time were justifiable under normal standardsand, if not, what forces caused investors to deviate from generallyaccepted venture capital investment approaches. While much is knownabout the decision-making processes of investors during stable markets,comparatively little is known of decision-making and cognition ofinvestors during a bubble.The closest research to ours was that related to capital market myopia,

in which investors were shown to have ignored the logical implications oftheir individual investment decisions in the Winchester hard-disk-driveindustry (Sahlman and Stevenson 1986). Theirs was not a cognitiveresearch study like ours, but used economic modelling and simulation.However, their conclusions anticipated some of ours: ‘wise investorsaccept consensus conclusions at their peril. Good decision makingrequires independent judgment . . . capital market myopia is a treatabledisease’.Behavioural economics replaces strong rationality assumptions used in

economic modelling with assumptions that are consistent with evidencefrom psychology. An example of this is the prospect theory proposed byKahneman and Tversky (1979) who proposed an alternative model toexpected utility theory. In particular, they proposed that utilities aredetermined by gains and losses from some reference point rather than byoverall wealth. Of particular interest to us was the observation that peopleoften seek risk in the domain of losses when they can reach the referencepoint, while they avoid risk in the domain of gains, what they call the‘reflection effect’. Investors have the propensity to take a chance to make uptheir losses and ‘to accept gambles that would be unacceptable . . .otherwise’.A history of failure induces decision makers to frame related, future

decisions as choices between losses (Whyte 1986). Once this type ofdecision frame has been adopted, decision makers tend to behave in a risk-seeking way. A tendency towards entrapment in one’s own faulty logic can

2 DAVE VALLIERE AND REIN PETERSON

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often be observed whenever future choices can reasonably be framed aschoices between losses as after a series of failed investments. Whyte callssuch a process an escalating commitment to a losing course of action,attributable to a need on the part of decision makers to maintain an illusionthat they have not erred.In such situations, intense emotions affect thought processes so that

people tend to narrow their thinking and rely on pre-existing stereotypes,ideas and beliefs, rather than broadening their thinking and adapting theirbeliefs through learning, observation and information gathering (Clore andGasper 2000). The high degree of uncertainty inherent to VC investingexacerbates these effects; one is more likely to fall prey to rationalizationwhen the nature of the uncertainty is fuzzy and unquantified—as was thecase with investments in the early-stage technology sector during the1998 – 2001 Internet bubble period (Levin et al. 1986, Reyna and Brainerd1991).Staw has pointed out that decision makers who are personally responsible

for negative outcomes will cognitively distort negative outcomes to appearmore positive (Staw 1976). According to cognitive dissonance theory, thereis a tendency for individuals to seek consistency among their cognitions.When there is an inconsistency between attitudes and behaviours(dissonance), it is most likely that the attitude will change to accommodatethe behaviour (Festinger 1957).Attribution theory points out that people have a strong need to

understand and explain what is going on in our world (Heider 1958,Kelley 1973). They can create new attitudes, beliefs or behavioursdepending upon the explanations they decide to make. Attributions – thecauses individuals generate to make sense of their world – are evaluatedaccording to:

. consistency – the degree to which the actor performs that samebehaviour toward an object;

. distinctiveness – the degree to which an actor performs differentbehaviours with different objects;

. consensus – the degree to which other actors perform the samebehaviour with the same object.

A score of ‘high’ on all three, as is the case for most of the attributions madeby venture capitalists in our research, would indicate strong belief in acognitive model such as we develop.Human beings have a tendency to get trapped in conceptual frame-

works of their own creation (Morgan 1986). Morgan calls suchmetaphors, such socially constructed realities, Psychic Prisons (firstexplored in Plato’s Republic). Groupthink reinforces such metaphors;once a metaphor ties you in, you try to fit all your data to support thelogic you have created. These constructions are often attributed anexistence and power of their own that allow them to exercise a measure ofcontrol over their creators. We will examine the cognitive processes thatlead to the Psychic Prison entrapment of the venture capitalists caughtwithin the Internet bubble.

3INFLATING THE BUBBLE

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Studying bubble investors

A grounded research approach was used in order to extend and refinecurrent theory on the decision-making and operational processes used byinvestors (Corbin and Strauss 1990). We employed this approach to explorethe rationale used by investors to justify the investment decisions made andvaluations paid during the Internet bubble (many of which in hindsightmay appear unjustified or even irrational), and to better understand themental models these investors used at the time. Using this approach, wesought to extend current thinking on how environmental context influencesthe behaviour of early-stage venture investors.

Stalking the wild bubble investor

Data for this study were drawn from a series of informal interviews ofinvestors of various types, who were active during the 1998 – 2001 timeperiod. The interviews were conducted coincident with this time period toobtain data based on contemporaneous investor attitudes and thoughtprocesses. During this period, the lead investigator was employed as anactive practitioner in the technology investment industry, in the context ofcommercial banking for technology firms, and as a professional early-stageventure capital investor. This arrangement provided us with theperspective of an ethnographic insider working directly with many studyparticipants on investment deals and on professional analysis of trends inthe technology investment markets. Interviews were framed, therefore, asprofessional discussions of apparent trends in the market, analysis ofcompetitor behaviour, and development of resulting business strategies tobe adopted by investors. Typical interviews lasted 30 – 40 minutes.Although common questions and discussion topics were used and writtennotes prepared, the format and sequencing of each interview necessarilyvaried to reflect the immediate business context for each participant. Table1 lists some of the common questions asked.Fifty-seven technology investors in Canada and the north-eastern USA

were interviewed for this study (the data set included investors fromToronto, Ottawa, Montreal, New York, Boston, Waterloo and Vancouver).Participants were selected on the basis of their direct involvement inmaking investments in early-stage technology-based firms during theperiod under study, and their willingness to participate in interviews. Dueto the limited sample size in some locations, regional differences among theparticipants were not explored.Initial interviews were conducted with twelve participants to explore

broad themes in investor behaviours and the attitudes and concept setused by investors before the bubble. These interviews were conductedas part of normal business meetings among investors, held in theiroffices or other common meeting places for technology investors (e.g.,coffee shops). Notes and theoretical memos from these interviews wereframed as business strategy analysis for the investment firm of the leadinvestigator. Based on the data from these initial interviews, a


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preliminary set of concepts, categorizations and relationships weredeveloped.Subsequently, interviews were conducted with 57 participants, including

all 12 of the original data set. Set during the period of the Internet bubble,these interviews were directed at exploring the conceptual relationshipsemployed by the investors as they evaluated, justified and concludedspecific investment deals. These data shed light upon the mental modelsthat were employed by participants making investments during the studyperiod, and led directly to the formulation of the model extensions andrefinements presented in this paper. These interviews were conducted asadjuncts to normal business meetings, with the majority being conducted atindustry conferences (such as the 2001 Red Herring Venture Market Eastconference held in Boston, MA, and Softworld2000 held in St John’s,Newfoundland) where the context invited participants to step back fromspecific deal transaction particulars and observe the state of the market andinvestment industry from a wider perspective.Data pertaining to the environmental context for the participant

investors were obtained through ongoing review of professional journalsand periodicals targeted at technology investors, such as Red Herring andUpside magazines. In addition to providing perspectives on the views andattitudes of non-participant investors that helped shape early versions ofthe theoretical model, these sources were widely read and respected bymany of the participants, and were frequently cited as sources thatinfluenced their own views and behaviours.Independent critique of the model was sought from academic colleagues

experienced in entrepreneurial finance and cognitive social psychology,with a specific view towards guarding against bias and identifying plausiblealternative models and explanations for the data. Further validation of theexplanatory power of the model was sought by reviewing the theory with

Table 1. Typical interview questions.

How closely do you watch other investors? What are you able to learn from them?How do you find ‘hot’ new investment areas? What signals do you look for?How comfortable are you in investing in these new Internet business models?What do you think is driving the rapid run-up in prices for Internet companies?What role has the investor trade press played in this? How has the press influenced yourown thinking about Internet investing?Many recent Internet investments appear hard to justify by traditional yardsticks, yet theycontinue to be made. Why do you think that is?Do you think these new approaches to investment assessment represent a temporaryaberration? Why (not)?What do you think about the recent huge influx of capital into the VC industry, and all thenew players appearing on the scene?Have you changed the way you ‘sell’ proposed new Internet investments to your InvestmentCommittee inside your firm?[Name of a sector] seems to be a ‘hot’ area of dot-coms these days, yet you have none ofthese companies in your portfolio. Do you feel that you might be missing out on somethingbig?You’ve made an investment in the [name of sector] space, yet nobody’s figured out how tomake money there. What is giving you the confidence to make investments like these?


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six of the participants from the second data set, with the objective ofconfirming whether the mental model described was reflective of theirattitudes and behaviours during the study period. These validationinterviews were held as soon as possible after the finalization of thetheoretical model, as we believed there existed significant potential forparticipants revise or mis-remember their thoughts during the study periodin order to rationalize behaviours that, in hindsight following the collapseof the technology investment market, might later be embarrassing forparticipants.

Traditional VC investing

The fundamental investing operation of formal venture capital firms hasbeen extensively described in the literature (Huntsman and Hoban 1980,Tyebjee and Bruno 1984, Sahlman 1990, Gompers 1993, Fried and Hisrich1995, Berlin 1998). Typically, VC firms are structured as limited liabilitypartnerships in which general partners, acting as agents for the limitedpartner investors, source investment opportunities, evaluate or screen themaccording to investment criteria for the specific VC fund, structure andexecute investment contracts with the investee companies, monitor theperformance of the investees and eventually liquidate their investment,usually through initial public offering or trade sale.VC firms face the challenge of evaluating potential investee companies

in an uncertain environment where moral hazard and adverse selectionmay exist (Sahlman 1990). Some of the strategies used to mitigate theserisks include use of formal screening criteria, imposition of high hurdlerates, use of convertible securities, staging of investments into separatetranches, and close monitoring of investee companies and mentoring oftheir management (MacMillan et al. 1985, 1987, Fried and Hisrich 1994,Gompers 1995, Lerner 1995, Zacharakis and Meyer 1998, Mason andHarrison 1999, Neher 1999, Shepherd 1999, Shepherd et al. 2000, Baschaand Walz 2001).The high degree of uncertainty in the performance of VC investments

results in a wide range of performance outcomes, with some investeecompanies performing spectacularly, while others fail and die before theVC firm can exit. Indeed, an industry heuristic frequently cited by VCpractitioners is that of 10 investments, two or three will fail and result incomplete investment loss, six will survive but underperform target returnrates or provide no easy liquidity path for the VC firm (so called walkingwounded), and one or two will perform so spectacularly well as to result inacceptable overall portfolio returns (so called home runs). Some formalstudies have obtained results that confirm this practitioner viewpoint(Hunstman and Hoban 1980). This phenomenon tends to support theimposition of high hurdle rates during the investment screening stage, sinceeach new investment made must at least hold out the potential of becominga home run.VC firms do not operate in isolation. They compete with other firms

for access to attractive investment opportunities and for relationships


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with the sources of this access, such as universities, research institutions,and professionals (lawyers, accountants, etc.) serving entrepreneurs(referred to as deal flow). They also exist in an environment of mutualco-operation in sharing or syndicating individual investment opportu-nities, as a strategy for marshalling sufficient resources, for amortizingthe fixed costs of investment due diligence, or for mitigating agency risks(Lerner 1994, Lockett and Wright 2001). Furthermore, the existingmoral hazard and agency risk can result in VC firms making investmentdecisions that are designed to create a favourable impression on theirpeers, current or prospective principal sources of financing, or potentialinvestee companies—a phenomenon sometimes referred to as grand-standing (Gompers 1996, Gompers and Lerner 1998). In extreme cases,this can result in a form of herd behaviour sometimes referred to ascapital markets myopia (Sahlman and Stevenson 1985, Bygrave andTimmons 1992).Consequently, the investment decision criteria in use by VC firms are

applied within an environmental context that includes the competitive andco-operative behaviour of other VC firms and investors. VC firms arefrequently very aware of the investments being pursued and beingconcluded by each other, and of the relative success of investments beingexited by each other. Successes and failures of investments by other VCfirms can be noted and analysed for intelligence about competitiveconditions and the dynamics of the market sector in which the investeecompanies operated.Put simply, VC firms seek investments that have the potential for high-

growth and high returns and, in order to gain the opportunity to securethese high returns, the VC firms accept high risks and uncertainties in theperformance of the investments. Their perception of these growthexpectations and the attendant levels of risk is conditioned partly by thesuccess or failure of similar investments made by their peers, and partly byescalating commitment effects for individual practitioners within the firm.Figure 1 illustrates this context of competitive and environmental factorsconditioning the fundamental investing of VC firms, and the resultingsuccess or failure of the investment returns.Figure 1 is based on thought-process descriptions provided by an initial

12 study participants and demonstrates the cognitive model apparentlyused by them to establish the context for their normal investment decisionsand operations. The fundamental VC operations described above (sour-cing, screening, structuring, monitoring and exiting) all occur within thebox labelled Investment Portfolio. The other components of figure 1 showthe factors that shape the VC investors’ expectations of risk and return, andtheir corresponding approach to fundamental investment operations fornew sectors.As described to us, this cognitive model for investing in early-stage

markets works as follows:

(1) A new investment sector is recognized by investors. This sectorcomprises many companies seeking investment capital, whetherthey are start-ups or existing companies seeking growth or


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expansion. In the absence of any contrary evidence, investorsassume that success criteria for investing in this new sector are notdifferent than for other previous investment sectors—the rules ofthe investment game are still the same.

(2) First-mover investors make some initial investments. Carefulattention is paid to the performance of these investments by other,by-standing investors and, after some time, early investment resultsare achieved as some of the initial investments are exited. Theseearly results are necessarily home runs or failures, with no middleground, as the initial investors would not be seeking early exits fromcompanies that had to-date displayed middling performance;instead they would typically remain in these companies and worktowards improving their prospects.

(3) Early home run exits serve to demonstrate the upside potential ofthe sector, and thereby reinforce high return expectations ofinvestors making subsequent investments in the sector (and inaccordance with normal investment operations).

(4) Early failure exits serve to demonstrate the downside potential ofthe sector, and thereby reinforce perceptions of high risk byinvestors making subsequent investments. The cognitive model isbalanced, with both positive and negative feedback loops serving toinfluence future investment decisions.

(5) As more and more investments are made and subsequently exited,VC investor returns evolve to resemble the typical distribution ofhome runs, walking wounded and failures.

Figure 1. Cognitive model of investors in unfamiliar sectors, with known successcriteria (source: interviews with 12 investors, prior to bubble).


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Figure 1 presents a rational model for VC agents to identify and evaluatepotential investments, to evaluate the risks and prospective returns, tonegotiate and structure investment contracts and valuations of theinvestee companies, to monitor performance, and to obtain satisfactoryinvestment exits. However, it does an unsatisfactory or incomplete job inexplaining the surge in early-stage investment activity during the 1998 –2001 Internet bubble period, and the coincident run up in valuations forInternet-based start-up companies. Accordingly, we sought to investigatethe effects of the competitive environmental factors described above, andwhether they or other unidentified factors were influencing the mentalmodels used by VC investors, and thereby affecting the investmentbehaviours of VC firms.

Describing the investors

A number of concepts and coding categories emerged, either in categoriz-ing the participants or in discussions with the participants regarding theirmental models and beliefs about competitive and environmental conditionsand forces at work in their markets. These categories are described below.Of these, three were found to be most salient in aggregating the beliefs andcognitive patterns of the participants: their investment objective, the degreeof ongoing managerial involvement they maintained with investeecompanies, and the degree to which investment decisions were made ontheir individual merits.

Objective

While all investors reported desiring the achievement of economic gains,some investors also described an objective or philosophical goal to buildgrowing or enduring companies and to be associated with their inception.Other investors espoused no such goals and represented themselves asinterested solely in flipping their investments by achieving early liquidity atattractive returns so they could quickly reinvest their funds in newopportunities. We note a correlation between free-rider due diligencebehaviour (described below) and flipping as an exit objective; seven of thenine free riders reported flipping exit objectives. The relationship issuggestive, although care must be taken in light of the small sample size.Furthermore, the flipping exit objective was rarely found among profes-sional VC investors; typically, they sought exits that allowed them to buildenduring companies, in addition to achieving their economic objectives.

Involvement

This refers to the degree of active involvement they maintained with themanagement of investee companies during the monitoring phase of theinvestment. While the majority of participants were actively involved with


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the management of investee companies, passive investors still represented39% of the data set. Among investors with flipping as their objective, wefound no significant differences in the beliefs between those who wereactively involved or who were passive; involvement appeared to be salientonly for investors with company-building objectives.

Independence

This indicates whether investors considered potential investments on theirindividual merits or to achieve specific changes to the investment mixcharacteristics of the total investment portfolio of the firm (portfolio fillers).Portfolio filling was somewhat prevalent, being practiced by 28% ofparticipants. In all cases where portfolio investments were being made(being investments that fulfilled portfolio profile objectives of the investor),the practitioners were also evaluating and making investments on anindividual basis. In addition, portfolio-based investments were stillsubjected to the ordinary degree of due diligence investigations typicalfor the specific investor. We found no investors who made investmentspurely on the merits of their portfolio attributes.Table 2 provides a summary-level description of the participant data set

based on these three categories. The insights we were able to obtain forthese groups are described later in the section ‘how bubble investors think’.The first investor group, ‘sector speculators’ represent investors seeking aquick return by investing in hot markets and hyped new business models.‘Company speculators’ differ from them in that they look for hyped newindividual companies, rather than entire sectors. ‘Option creators’ seek tobuild successful companies in a sector they perceive as poised to growrapidly; they believe strongly in the sector, and so place a bet on areasonable company in that sector. ‘Company creators’ are less believers inthe prospects of an entire sector, and more in the prospects of working witha particular management team and company. ‘Diversified investors’ arehands-off, financial backers who are not operationally involved withinvestee companies, but believe in the prospects for a specific sector and arebetting on that sector. ‘Focussed investors’ are similarly hands-off backers,but have been convinced of the prospects for specific individual companiesrather than entire sectors.

Table 2. Categorization of participants (source: interviews with 57 investorsduring bubble).

Objective Involvement Independence Count Descriptive label

Flipping Portfolio filling 7 Sector speculatorsIndividual merits 6 Company speculators

Building Active Portfolio filling 7 Option creatorsIndividual merits 24 Company creators

Passive Portfolio filling 2 Diversified investorsIndividual merits 11 Focused investors


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Our analysis allowed us to further aggregate the investors into two largergroups, based on transaction independence: the portfolio proponents(comprising ‘sector speculators’, ‘option creators’ and ‘diversified inves-tors’) and the independent proponents (comprising ‘company speculators’,‘company creators’ and ‘focused investors’). These groups differedmarkedly in how they attributed their investment failures.Some of the other demographic categorizations of the participants, not

shown in table 2, are described below.

Investor role: Professional investors, informal angel investors or invest-ment intermediaries with fees at risk. Of the 57 participants, ten (17%) wereinformal angel investors and only six (11%) were financial intermediaries.The majority of 41 (72%) were formal professional investors. Of these, 34represented professional VC investment firms, and the remaining sevenrepresented commercial banks or debt-financing institutions.

Structure: Form of the investment made, whether it represented debt orequity risk. Equity-based investment structures were much more commonthan debt, representing the preferred structure for 46 (81%) of theparticipants. In particular, equity was the strongly preferred investmentstructure for those investors whose involvement was active.

Form of gain: While it was expected that investors would seek purelyeconomic gains through a high financial return, it emerged that someinvestors sought strategic gain through access to information from investeecompanies or preferred access to technology held by those companies, andsome investors sought reputational gain akin to grandstanding. Economicgain was a ubiquitous shared goal, as was expected for any group offinancial investors. Reputational gain was a minority objective, but not rare,being cited by 17% of participants. Compared to other investor roles,professional VC investors professed to be relatively uninterested inreputational gain forms. In most cases where participants had reputationalgain objectives, they freely recognized it and typically explained it as anecessary element of enhancing their ability to attract desirable investeecompanies vs. competing VC funds, suggesting perhaps that the moralhazard and agency risks attendant with this objective may not be recognizedby VC practitioners or their principal investors, or that their principalswere willing to absorb such costs as marketing expenditures.

Degree of diligence: Performed their own due diligence investigations foreach of their investment decisions, worked within an apparent communityof investors who shared due diligence efforts on an informal rotating basis,or performed no due diligence at all, acting in essence as free-riders.Regarding due diligence methods, most participants were equally splitbetween those who did their own due diligence using resources available totheir firms, and those who generally syndicated their deals and shared duediligence on an informal rotation basis with other investors. A sizeableminority of participants (16%) reported making at least some investmentswithout any significant due diligence efforts beyond a reliance on the due


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diligence or reputation of other investors, either as investors in previousfinancing rounds or as unsyndicated investors in the current round. Suchfree-rider behaviour was typically characterized by an espoused degree ofrespect for another investor, based on their previous track record.Participant 8 captured the attitude by saying, ‘[Name of investor omitted]have had a lot of success in the Internet space, and seem to know whatthey’re doing. If they like this company and are willing to put more moneyinto it, then it sounds like a good bet for us’.

Magnitude of gain: Confirming observations in the literature, we foundthat participants clearly distinguished between returns that were highlysuccessful home runs, moderately successful or unsuccessful. Furthermore,all of the participants espoused the belief that the industry heuristic forratios among these categories was reasonably accurate, and most believedtheir own investment activities would yield similar results. They perceivedthat the relative competitive success of their respective funds would bedemonstrated primarily in the magnitude of their home runs. Asparticipant 23 remarked, ‘We have our challenges like every other fund.But we’ve had such a huge win with [name of company omitted], that it’sreally helped us’. Only two of the participants (numbers 6 and 24) statedthey believed their own investment acumen would result in a higherproportion of home runs in their portfolios.

Valuation premium: Participants identified three conceptual premia thatapplied to the intrinsic valuation they assigned to specific investmentopportunities. The first was the small premium that portfolio investors werewilling to pay in order to secure investments with the profile attributes theywere currently seeking. The second was the premium that was applied tosectors that were perceived by investors to be hot or generally desirable formaking investments. Companies operating in these sectors benefited fromthis sectoral premium paid by their investors. The third premium was theamount paid by investors to place bets on sectors or target company businessmodels (by which we mean the range of revenues streams available to thecompany, and the internal economics of the company’s operations to earnthose revenues) that were suggestive of high upside gains but representingextraordinary levels of uncertainty. Referring to the valuation proposed for apotential investment in aWeb-portal technology company, participant 45putit thus, ‘Portals arehotnow.Eventhoughwedon’t yet seehowthey’regoing tomakemoney,we think they’re going tobe really huge at somepoint. Soyou’vegot to be willing to pay what it costs in order to have a finger in that pie’.

Hype awareness: Participants frequently referred to the degree ofpublicity and awareness about particular developments in the market,often using words like buzz or hype. We found three areas in which thedegree of publicity figured prominently in discussions with practitioners:surrounding the success of a particular company or entrepreneur (companyhype), surrounding a particular sector such as the portal example above(market hype) and surrounding the activity of other investors as a group(investor hype).


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Bubble-investing is different

As we analysed the early data from interviews and began to note emergentthemes in the thinking of participant investors during the Internet bubble,it became apparent that forces were operating that were not represented inthe simple cognitive model of figure 1. Participants believed that the rulesof the investment game had changed, and that the criteria for successfulinvesting were relatively unknown. This made investment decisions morechallenging. Participants were still applying fundamental VC investmentprocesses, but they were doing so within a richer environmental contextthat exhibited positive, self-reinforcing loops in the mediating forcesdriving the activities of investors. Representation of these loops hasrequired augmentation of the earlier model, as shown in figure 2.These augmentations emerged in a situation with a high degree of

consistency (e.g., VC investors have had similar impressions of attractivepre-bubble technology companies as their peers), distinctiveness (e.g., duediligence investigation, and assessment of the wins and losses of first-movers) and consensus (e.g., widespread belief that the rules for investing inInternet companies had changed), which all contribute to a strong belief inthe validity of the ‘psychic prison’ they form—a prison with vicious loopsthat ultimately drove the inflation of the Internet bubble. We will firstillustrate the operation of this augmented model by means of an example,and then follow the example with specific research findings that support thevarious model augmentations. To illustrate the thought processes under-lying these model extensions we will use the example of early investments inthe market for e-commerce portal companies. The early market for e-commerce portals was typified by high uncertainties in end-user marketacceptance (will people buy products online?), security (will they enter their

Figure 2. Cognitive model of investors in unfamiliar sectors, with unknownsuccess criteria (source: interviews with 57 investors during bubble).


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credit card numbers into a Web page, and if not, will they adopt some formof electronic cash equivalent?), profitability of the business model (will theoperating costs and customer acquisition costs for e-commerce besufficiently lower? Will online consumers demand a share of this in theform of price-based competition?), operations of the business model (howwill product be distributed, and will distribution costs erode the transactioncost advantages?), revenue streams (can we charge for advertising or foraffiliate Web site referrals?) and competitive reactions (will the bricks-and-mortar companies be able to reinvent themselves for an online world?).Despite these huge uncertainties, some early e-commerce companies, like

the nascent Amazon.com, found immediate customer acceptance andrapidly increased their business volumes, thereby already meeting the‘success’ definitions of some observers. These successes generatedsignificant market hype, where the trade press filled with stories of theimpending death of brick-and-mortar retailers and the virtually certainsuccess of portals. Investors flocked to the newly hyped sectoralopportunity, and supported new entrant e-commerce portals having adiverse range of business models and strategies—including companies thatsold products at zero or negative gross margins (e.g., buy.com) simply toacquire more visitors or eyeballs to support their advertising revenuestreams. The resulting investor hype was reflected in the anecdotal story ofa portal investment entry valuation being determined on a price-to-eyeballmultiple (e.g., audiohighway.com). Each huge entry valuation paid by aninvestor wanting a portal company further reinforced the hype in the sectorand served to attract still more investors to the space and further bid up thevalue of portal companies. In the absence of market and investor hype, onemight predict that higher entry valuations would have reduced the desire ofinvestors to get into the market sector, until a natural equilibrium price wasestablished. However, in the presence of significant hype, the high-entryvaluations actually increased the desire of investors to get into the sector,creating a positive-feedback mechanism.Eventually it became the norm among investors that an Internet

investment portfolio must include a portal play, or the investor was indanger of missing out on the opportunity completely. Some investors,therefore, made investments in portal companies, not because they feltcertain of the business model and prospects of the particular individualcompany, but more to round-out their portfolios with some (perceived)requisite exposure to the portal space. The investor hype had reached alevel at which portal investments were being made for portfolio-fillingreasons and further drove up the entry valuations for portal companies asinvestors found themselves bidding against each other.Despite these initial and rapid increases in market hype, investor hype

and valuations, the many uncertainties relating to the market for e-commerce portals remained. So, the rapid increase in investment volumewas not based on a corresponding increase in market knowledge orcorresponding decrease in investment risk. Many of the portfolio-fillinginvestments were essentially bets being placed on the eventual success ofthe portal company’s unique business model, or bets that the entire portalsector would somehow evolve to be hugely successful.


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As these investments matured, their outcomes further shaped percep-tions of bubble investors. Successful high-valuation outcomes tended toreinforce investor hype and interest in the portal sector. Unsuccessful low-valuation outcomes were perceived as evidence that, somehow, the businessmodels for successful portals were very different from traditionalbusinesses (due to the belief that normal evaluation criteria did not apply)and, therefore, placing an adequate number of bets on different portalmodels was critically important to securing a piece of the eventual portalwindfall. Moreover, this belief that portal business models were differentmeant that low-valuation outcomes did not lead to the perception ofincreased risk levels attending subsequent investments in portals. Instead,investors believed it merely confirmed that the one particular businessmodel was not going to be the winner and that there were now fewerremaining candidates. Perversely, this now led them to believe the risk ofinvesting in the remaining portal business models had actually decreased.As time passed and still more investments proved successful or failures,

the sectoral uncertainties were resolved. It was learned that selling productsat negative margins was a bad idea, even on the Internet. It was also learnedthat, while portal advertising rates could remain higher than many printmedia rates, they did not provide sufficient revenues for most portals toachieve profitability. The hype around portals began to abate. The e-commerce portal market had matured to the point where the cognitivemodel extensions of figure 2 were no longer operating; the modelrepresented in figure 1 once again sufficed and the rules of the investmentgame were again clearly adhered to.

How bubble investors think

Below we present ten propositions that emerged from, and were supportedby, the data obtained from the participants. These propositions form thebasis for the model extensions presented in figure 2.

Market hype generates investor hype: (36 participants agreed, out of 39participants opining.) Participants remarked that they were drawn to wherethe largest growth opportunities could be found, and that market hypeserved as an indicator of these areas. The larger and more frequentlyreported the early successes in a newly evolving market, the more investorswere drawn to it, keeping the sector on their radar screens. The fewparticipants who disagreed with this proposition were ‘company creators’and ‘focused investors’, two groups that believed themselves to be relativelyimmune to hype effects (similar findings were obtained for propositions 4and 5).

Investors use co-investment as a cost-reduction strategy: (28 participantsagreed, out of 28 participants opining.) Investors who participated insyndicated financings generally agreed that the sharing of due diligenceefforts was a significant benefit of this co-investment approach. There wassome suggestion that this strategy was more strongly applied among


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earlier-stage investors, where deal sizes are typically smaller and thereforeprovide a smaller base upon which to amortise the fixed costs of duediligence, but our sample data set did not afford drawing firm conclusionsabout this relationship.

Investors use co-investment as a risk mitigation strategy: (32 participantsagreed, out of 33 participants opining.) Syndicating participants noted thatthey often worked with the same partners on a series of investment deals,and that therefore a degree of trust in each other’s judgement emerged overtime. This trust formed a basis upon which investors could at times join asyndicated deal without added due diligence efforts, relying on thejudgement of existing syndicate members to mitigate deal risks.

Investor hype increases valuations through sectoral premia: (26 participantsagreed, out of 27 participants opining.) Participants concluded that thispremium was a natural result of competition among investors to get themost attractive deal opportunities. As sectoral investor hype increased,more investors were drawn into the sector and thereby increasedcompetition for deals in the sector. ‘Sector speculators’ particularlysupported this proposition. Participant 41, while assisting a portfoliocompany with a new round of financing, remarked, ‘Everyone wants whatthe other guy wants. So the best way to get a good valuation is to get a lot ofpeople interested and excited. A lot of buzz in the trade press sure helps tobuild more interest’. Approximately half of the ‘company creators’,although espousing immunity to hype effects themselves, believed therewere sufficient numbers of other investors being driven by hype effects tocause this valuation inflation to occur.

Increasing valuations increase investor hype: (17 participants agreed, out of19 participants opining.) This phenomenon created the first observedpositive-feedback loop in the model extensions we propose (labelled (a) infigure 2). Not only did increasing hype cause valuations to be bid up, butreports of rising valuations tended to reinforce the hype and created a senseof urgency for investors who were still just considering entering the hotsector, particularly among ‘sector speculators’ and ‘option creators’—twogroups that were investing primarily based on their belief that huge futuregains could be found in the sector. As participant 6 stated, ‘You don’t wantto miss out on something hot. So, if everyone agrees the sector is hot, wehave to pay the going rate to get into it. And when people hear of a big dealbeing done, it gets their attention, and makes them want to get into it.Hearing about big price tags doesn’t scare people off; instead, it makesthem wonder if they’re missing out on something good’. Participants whobelieved investor hype drove up entry valuations also believed thatincreasing valuations looped back to drive up investor hype in the self-reinforcing cycle of loop (a).

Investor hype generates portfolio investing and flipping, and increases sectoralpremia: (22 participants agreed, out of 23 participants opining.) Thisphenomenon created the second observed positive-feedback loop in the


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model (labelled (b) in figure 2). The previous feedback loop, and theresulting rapid escalation of investor hype, attracted new entrants to theearly-stage investment industry, either in the form of investors from otherindustries seeking a share of the perceived big gains to be had in theInternet or as altogether new investors. Participants believed that many ofthese new investors were speculators looking for a boost to their existingportfolios. Participant 1 commented disparagingly on this phenomenon,‘When the markets get overheated like this, it brings out everyone.Everyone has to have a search engine company and a wireless content playin their portfolio. But half these guys don’t know why they’re investing inthem. They just want to get in and get out quick’. Investors who alsoreported flipping as their investment objective, the ‘speculator’ groups,particularly reported this phenomenon.

Portfolio investing stimulates options-thinking, creating/increasing the betpremium: (13 participants agreed, out of 13 participants opining.)Participants remarked that while a minority of portfolio fillers seemed tobe adding companies simply because they were perceived as hot and couldtherefore be flipped quickly and profitably, the majority of portfolio fillingoccurred because investors believed the target companies may haverepresented significant home-run potentials—even though the ‘optioncreators’ and ‘diversified investors’ could not yet see how that would occur.Investors were purchasing the right to participate in a highly uncertain butpotentially large upside. In effect, by making an investment in the targetcompany, they were betting on any large future gains that may result fromthe sector or innovative business model that the company represented. Werefer again to the quotation of participant 45 noted above.

Successful outcomes are viewed as bet pay-offs, reinforcing investor hype: (17participants agreed, out of 17 participants opining.) This phenomenoncreated the third observed positive-feedback loop in the model (labelled (c)in figure 2). When a company with an initially highly uncertain businessmodel achieved dramatic success, and was reported in the trade press andnoted as a home run in the VC community, participants perceived theinvestment gain as a bet that had paid off big. Widespread reporting of thistended to reinforce investor hype and support the uncertainty bet premiumbeing paid by subsequent investors in the relevant sector. This propositionwas most widely supported by portfolio proponents.

Unsuccessful outcomes are viewed as indicators of increased uncertainty:(Seven participants agreed, out of seven participants opining.) Thisproposition was supported almost exclusively by investment flippers, the‘speculator’ groups. When a company with an initially highly uncertainbusiness model failed, and was reported in the trade press and noted as aloss in the VC community, participants perceived the investment loss asevidence of the magnitude of the uncertainty surrounding that businessmodel. They then made the untested (and somewhat dubious) assumptionthat this uncertainty was or remained symmetrically distributed, and thatthe increased magnitude of the downside corresponded to an overall


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increase in the variance of potential returns on investments in similarbusiness models—variance that included increased upside potential.Escalating commitment mechanisms and the resulting risk-seekingbehaviours may exacerbate this assumption, as investors facing negativeoutcomes in the Internet sector seek to make up their losses by investing yetmore. As a result, company failures involving specific unsuccessful businessmodels were taken as rationale for an increased likelihood that a successfulbusiness model remained to be discovered in the remaining population ofcompanies, rather than as evidence of increased certainty of negativeprospects. As participant 5 put it, ‘The death of [competitor name omitted]just means the win will be that much bigger for the guy with the rightbusiness model’. This viewpoint was interpreted as decreased risk (labelled(d1) in figure 2), and all the more reason to place a bet on the sector orbusiness model. This proposition was particularly supported by partici-pants who also believed that investor hype was driving up sectoral premia,due to the increase in portfolio investing. The small sample size supportingthis proposition should be noted.

Increased uncertainty leads to higher bet premia: (Five participants agreed,out of five participants opining.) This phenomenon created the fourthobserved positive-feedback loop in the model extensions we propose(labelled (d2) in figure 2). The perception of symmetrically increaseduncertainty described above as proposition 9 led some participants tosupport increased bet premia, on the expectation that the potential upsideswere correspondingly larger and that the intrinsic values of having madebets were correspondingly higher. The small sample size supporting thisproposition should be noted.

Lessons for investors

Our analysis suggests that, during the 1998 – 2001 period, Internetinvestors, unfamiliar with the new investment sector, were influencedby environmental and competitive forces that were not evident in otherperiods. These forces include a causal chain from the success of earlyInternet-based technology businesses, to increasing hype or publicityaround specific sectors and the activities of investors in those sectors, toincreases in investment levels and company valuations that were driven byperceived portfolio requirements or the placing of bets on Internetbusiness models. Moreover, the analysis of the effects of these forces oninvestor behaviour suggests the existence of four positive-feedback loopsthat acted to drive up the valuations given for potential investeecompanies. The fatal flaw in their cognition is illustrated in figure 2 byfeedback loop (d)—the perception that the business models fore-businesses were different, and did not need to follow traditional, triedand true, financial criteria for success. Portfolio proponents typicallyattributed their investment failures to poor selection of specificcompanies. They still believed in the chosen sectors, but believed theyhad simply picked the wrong company from within that sector.


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Independent proponents typically attributed their investment failures topoor execution by the investee company management or other factorstypically supporting the VC industry ‘2 out of 10’ success heuristic. Bothattributions appear to be faulty. For many of the investment transactionsobserved, the subsequent failure can be more correctly attributed to baddeals that simply should never have been funded in the first place, forwhatever reason—deals that would never have been funded had investorsbelieved the rules of the game were unchanged.In light of these findings, it is suggested that, while some investors could

be accused of reacting irrationally to the potential for quick and easyfinancial gains through investing in Internet companies, many investorsappear to have been attempting to make rationalized but logically flawedresponses to these environmental forces. This flawed perception led toescalating commitments and a failure in normal investment decisioning andgovernance practices.Figure 3 overlays onto the complex model of figure 2 a simplifying

representation of the effects of the augmented model, showing how themodel led to the initial creation and inflation of the Internet bubble. First,the environmental forces during the bubble period had the net effect ofcreating a price inflation engine that resulted in the rapid escalation of entryvaluations and attracted new investors and new capital to the sector. Thiscapital influx, and the perceived difference of unfamiliar Internet businessmodels, resulted in a dramatic increase in the volume of Internet companiesbeing funded and the amount of capital being invested – the bubble wasbeing inflated. Finally, the perceived difference of unfamiliar Internetbusiness models acted to suppress normal risk assessment controls thatmight otherwise have slowly deflated the bubble.The eventual bursting of the Internet bubble came at tremendous cost to

many companies and investors. Avoiding similar situations in the futurewill require that investors remember that having a finger in a new pie is not

Figure 3. Abstracted view of augmentation on bubble creation.


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always a good thing, particularly when the pie in only half-baked. Morespecifically, we believe several practical lessons can be drawn, and be usedby investors to avoid recurrence of bubble phenomena in other emerginginvestment sectors.First, while it may be efficient to allow developing hype among sectors

and investors to draw attention to emerging investment opportunities, it iswise to confirm whether the fundamental underpinnings in the sectorsupport the degree of hype being evidenced. Therefore, investors shouldcontinue to use the press to highlight emerging opportunities, but not relyon it as adequate due diligence. In particular, VC investors should be waryof following the leads of two groups: investor peers who have been led intopsychic prisons through escalating commitment mechanisms, and spec-ulators who are gambling according to quite different rules than theinvestment game.In addition, while rapidly escalating entry valuations in a sector may

serve as another indicator of attractive investment opportunities, investorsshould keep in mind that they also represent declining potential returns. Inthe long run, they will only rise to the point where returns arecommensurate with the risk. Hype alone cannot sustainably supportescalating sectoral entry valuations.Similarly, while paying a small bet premium to add a particular

investment to the portfolio may be justifiable on occasion, it only servesas proof of interest in the sector among competing investors. It doesnothing to prove the soundness or intrinsic value of the underlyinginvestment. Placing larger bets does not make them more likely to pay off.Finally, as a basic heuristic for investing in unfamiliar markets, investors

should remember that failures are still failures, even in sectors where therules of the game are thought to be very different. There is no market sectorso different that an investment failure is somehow good news for theinvestor. Every investment outcome acts to reduce the uncertainty aboutinvesting in the new sector. The investment failures are simply signs thatthe sector may not be as attractive as originally thought.

Future research

The results of the present research are suggestive of a number of areasdeserving of subsequent research. First, the generality of the cognitivemodel in figure 2 should be explored in other contexts. Our 57 venturecapitalists represented a relatively broad range of geographical investmentarenas. A more focused study of entrepreneurial climates in morehomogeneous regions would yield insights into any differences that mightexist. Similarly, a study of other perceived ‘hot’ investment markets, suchas the currently evolving markets for companies based on biotechnologyand nanotechnology, would yield insights into whether venture capitalistshave learned from the experience of becoming entrapped in the psychicprison of the Internet bubble logic we identified in this research.Exploration should also be undertaken into the impact of the subsequentdecline in venture capital investing that immediately followed the collapse


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of the Internet bubble on the cognitive models used by VC investors tounderstand the extent to which the collapse may have highlighted andcorrected any logical flaws in the bubble-period thinking described in thispaper, or indeed caused overcompensation. Research should be performedto verify the assumptions of symmetric uncertainty by ‘speculators’described in proposition 9, perhaps through the structure of a game orsimulation in which ‘speculator’ investors are presented with a series ofinvestment choices under winning and losing courses of action, throughwhich insights can be gained into the degree to which their risk-seekingbehaviours can be understood as escalating commitment or gambling.Finally, the current paper could be well-augmented by study into theimpact of the Internet bubble upon the ability and willingness of VCinvestors to raise money from their own funding sources, and thesubsequent need for VCs to return these funds when the bubblecollapsed.

Acknowledgements

The authors would like to recognize the valuable suggestions of WilliamBygrave, Yuval Deutsch, Thomas Keil, Robert Kleiman, Gareth Morganand Neil Wolff. Errors or shortcomings of this paper are ours alone.

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Documents

Inflating the bubble: examining dot-com investor behaviour