Board Structure and Survival of New Economy

Board Structure and Survival of New EconomyIPO Firms

Nongnit Chancharat, Chandrasekhar Krishnamurti* and Gary Tian

ABSTRACT

Manuscript Type: EmpiricalResearch Question/Issue: This study examines the relevance of currently accepted best practice recommendations regard-ing board structure on the survival likelihood of new economy initial public offering companies. We argue that industrycontext determines governance outcomes.Research Findings/Insights: We study 125 Australian new economy firms listed between 1994 and 2002. Each firm istracked until the end of 2007 for monitoring their survival. We find that board independence is associated with an increasein the likelihood of corporate survival. We also find that the benefits of board independence increase at a decreasing rate.Theoretical/Academic Implications: The standard best practice recommendation of board independence stems from themonitoring role of directors and is based on agency theory. The results from our study suggest that the recommendationregarding board independence does not work well for new economy firms. While the agency theory based model impliesa monotonic relation between board independence and performance, our research suggests that the relationship is nonlin-ear. This variation occurs because of increased monitoring costs faced by outsiders due to higher information asymmetryand complexity of new economy firms. Our empirical results suggest that inside directors play a complementary role tooutsiders in mitigating firm failure.Practitioner/Policy Implications: Our research offers insights to policy makers who are interested in setting best practicestandards regarding board structure. Our research suggests that firm/industry characteristics play a crucial role in deter-mining the optimal board structure. In firms/industries where outsiders face significantly higher information processingcosts, insiders can play a valuable complementary role to outsiders in enhancing the effectiveness of the board. Thus futurehard or soft regulations related to board structure should consider industry context.

Keywords: Corporate Governance, Board Structure, Survival Analysis, New Economy Firms, Informational Asymmetry

INTRODUCTION

O ne consequence of the high profile corporate collapseof firms such as Enron and WorldCom due to corpo-

rate governance failures is the move by regulators to con-verge to a single model of corporate governance. Recentregulations, such as the Sarbanes-Oxley Act of 2002 (SOX)and rules promulgated by the Securities and Exchange Com-mission, New York Stock Exchange (NYSE), and NationalAssociation of Securities Dealers (NASD), contained at theircore the independence of a majority of directors on theboard. Furthermore, calls for the separation of chief execu-tive officer (CEO) and chairperson positions became louder

following the spate of recent corporate scandals. Implicit inthis convergence to a single optimal structure for the boardis the assumption that one board structure should fit allfirms.

Financial economists, such as Hermalin and Weisbach(2003), Linck, Netter, and Yang (2008) and Coles, Daniel,and Naveen (2008), have questioned the optimality of asingle board structure for all firms. For instance, Faleye(2007) suggests that a unified leadership structure is notappropriate for all firms because of differences in thespecific circumstances of individual organizations. Duchin,Matsusaka, and Ozbas (2010) provide empirical support forthe view that outside directors are less effective in moni-toring and providing advice when the cost of acquiringinformation is high. Romano (2005) believes that unduehaste in imposing corporate governance convergence maylead to “quack governance.”1 In a study of the post-IPOperformance of young entrepreneurial firms, Kroll, Walters,

*Address for correspondence: Chandrasekhar Krishnamurti, Accounting, Economicsand Finance, Faculty of Business, University of Southern Queensland, Toowoomba,Qld 4350, Australia. Tel: 61-7-4631-2941; E-mail: [email protected]

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and Le (2007) recommend that a majority of board membersbe insiders.

Another feature of the board that has attracted the atten-tion of corporate governance scholars is the size of the board.Lipton and Lorsch (1992) and Jensen (1993) suggest thatlarge boards could be less effective than small boards due tocoordination problems and director free-riding. Coles et al.(2008) argue that complex firms have greater advisingrequirements. Since large boards potentially bring moreknowledge and experience and can therefore offer betteradvice, they posit that complex firms should have larger andmore independent boards. Conversely, they posit that firms,for which firm-specific knowledge of insiders is compara-tively more critical, such as knowledge-intensive neweconomy firms, are likely to gain from greater representationof insiders on the board.

Our contribution to this literature is based on two inno-vative aspects of our study. First, we examine the boardstructure of new economy firms. By focusing on neweconomy initial public offering (IPO) companies, we areable to incorporate the role of firm- and industry-specificcharacteristics on the board structure. These firms havecharacteristics that are different from other firms in severalrespects. They tend to employ recently developed tech-nology which is often not well proven. They tend to besmall firms with high growth opportunities. A number ofresearchers (Carlson, Fisher, & Giammarino, 2006; Gaver &Gaver, 1993; Myers, 1977) posit that firms with high growthopportunities have more information asymmetry than firmswhose value is mostly comprised of assets in place. Faleye(2007) characterizes organizational complexity on the basisof size, asset tangibility, and growth opportunities. Based onasset tangibility and growth opportunities, new economyIPO firms can be considered as complex firms. Therefore,information acquisition costs are likely to be higher in neweconomy firms. Since the ability of directors to governthe firm well is contingent on having access to timely infor-mation and the ability to process such information, webelieve that the board structure of new economy IPO firmsshould take organizational complexity and informationalasymmetry into account.

Second, our performance metric is survival likelihoodrather than traditional measures such as return on assets andTobin’s Q used by prior researchers. We focus on survivalrather than measures of performance such as Tobin’s Q forthe following two reasons. First, survival is the primary goalof the firm. As such, the relevance of appropriate boardstructure is more crucial in the context of survival asopposed to the performance of a firm in a stable state. Thesecond reason for choosing survival is that it is an unam-biguous measure of performance.

We develop testable hypotheses regarding optimal boardstructure taking into account three unique characteristics ofnew economy IPO firms. These are (a) high informationprocessing costs of outsiders, (b) volatile business environ-ment and (c) organizational complexity. We posit the follow-ing hypotheses: (i) the impact of board independence on thesurvival likelihood of new economy firms will increase at adecreasing rate; (ii) CEO duality will increase the survivallikelihood of new economy firms; (iii) a board led by anexecutive chairperson will have a higher likelihood of sur-

vival; and (iv) firms with either small boards or large boardswill have a higher likelihood of survival as opposed to firmswith medium-sized boards.

Our research adds further weight to the strand of litera-ture that argues that industry context is a critical determi-nant of governance outcomes (see, for instance, Lin, Yeh, &Li, 2011). Our key insight, from this paper, is that currentlyaccepted best practice recommendations, which are derivedprincipally from an agency theory perspective, must bemodified in the context of new economy firms in high veloc-ity environments. Boards typically perform several key rolessuch as monitoring, advising, resource provision, and con-tracting. Currently advocated best practice recommenda-tions stem from the monitoring role derived from an agencytheory perspective. We argue that in a specific industrycontext, such as new economy firms in the post-IPO stage,some of the other roles besides monitoring are crucial inensuring survival.

We conduct our empirical tests on new economy IPOfirms listed in Australia. Australia is chosen because itfollows the English common law tradition that is prevalentin the US and UK. Also, Australia follows free market poli-cies like the US. Furthermore, investment flows (i.e., capitalraised by IPOs and secondary market issues) in Australiaare the third largest in the world – US$86.2 billion in 2009.2In 2003, the Australian Stock Exchange released its Prin-ciples of Good Corporate Governance and Best Practice Rec-ommendations that deal directly with board structure (ASX,2003). The core recommendation of ASX is that a majority ofthe board should be independent directors. In order toavoid the impact of this exogenous event on board compo-sition, we restrict our sample to new economy companieslisted on the Australian Stock Exchange between 1994 and2002.

Sample firms are tracked until December 31, 2007 to cat-egorize them into companies that are currently trading andthose that are delisted. The Cox proportional hazards modelis then employed to identify the likelihood of survival of acompany after IPO. We conduct further analysis to see if thesame factors influence the different reasons for delisting –takeovers and financial distress – by applying the competingrisks Cox proportional hazards model. Our results show thatthe survival time of new economy IPO companies is posi-tively related to board independence. But the benefits ofboard independence increase at a decreasing rate. We alsofind weak evidence indicating that companies with eithersmall board size or large board size are more likely tosurvive than companies with medium-sized boards. In addi-tion, company size and leverage are found to be negativelyrelated to new economy IPO firms’ survival. We find thatCEO duality and independence of chairperson have noimpact on survival likelihood of new economy IPO firms.

The remainder of the paper is organized as follows. First,we review previous studies relating to corporate gover-nance structure and IPO firms’ survival and provide thetheoretical background for the development of hypothesesand identification of control variables. Second, we presentthe details of our data and the methodology. Third, we pre-sent our empirical results and discuss their implications.Finally, we offer our conclusions and discuss potentialfuture extensions.

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LITERATURE REVIEW ANDTHEORETICAL DEVELOPMENT

In this section we review the literature with respect to cor-porate governance attributes and relate them to survival ofnew economy IPOs.

Governance and Corporate SurvivalIn this study, we consider three major recommendationsthat are at the core of good governance practices enshrinedin the Principles of Good Corporate Governance and BestPractice Recommendations issued by the Australian StockExchange and consistent with international best practicessuch as the Cadbury Code of Best Practice and the recentrecommendations of the NYSE and Nasdaq. First, a majorityof the board should be independent directors. Second, thechairperson should be an independent director. Finally, theroles of chairperson and chief executive officer should notbe exercised by the same individual. In addition to theserecommendations, we also consider board size, which hasreceived a lot of research attention. We develop our testablehypotheses taking into account specific characteristics ofnew economy IPO firms such as high information process-ing costs of outsiders, volatile business environment, andorganizational complexity.

Board Independence. Researchers outline four roles forthe board of directors of a public firm (Johnson, Daily, &Ellstrand, 1996; Kumar & Sivaramakrishnan, 2008). First, theboard monitors top management on behalf of the sharehold-ers in order to reduce managerial rent-seeking behaviour(Jensen, 1986; Johnson et al., 1996). Second, the board faci-litates the formulation of strategy via an advisory role.The third role of the board is to provide resources to topmanagement and the CEO. Finally, the board performs acontracting role (Kumar & Sivaramakrishnan, 2008). Theeffectiveness of the board is determined by its ability tomonitor, advise, contract, and provide resources to the topmanagement. One of the key characteristics of effectiveboards is independence. While the independence of a direc-tor is an essential prerequisite for monitoring the managerseffectively, it is not clear if independence facilitates theperformance of the other three roles.

Byrd and Hickman (1992) contend that the results of theirempirical work are not consistent with the view that share-holders will be best served by a board comprised entirely ofindependent directors. They find a nonlinear relationshipbetween abnormal stock returns of bidding firms and theproportion of independent directors on the board. They findthat return performance increases when the proportion ofindependent directors increases up to 60 percent and there-after declines. Since the advisory role is most relevant instrategic decisions such as acquisitions, an implication ofthis finding is that board independence is not unambigu-ously beneficial for effectively executing the advisory role.

Further evidence on the interaction between the monitor-ing and advising roles of directors is provided by Faleye,Hoitash, and Hoitash (2011) who show empirically thatfirms with boards that monitor intensely exhibit worse

acquisition performance and diminished corporate innova-tion. This evidence suggests that the benefits of intensemonitoring are more than offset by the weakening of thestrategic advising role of the board. Holmstrom (2005) con-tends that intense monitoring destroys the trust essentialfor the CEO to share important strategic information withdirectors. Similarly, Adams and Ferreira (2007) put forwarda model in which the CEO does not communicate with aboard that monitors excessively, while Adams (2009) offerssurvey evidence suggesting that independent directorsreceive less strategic information from management whenthey monitor intensely. As information provided by theCEO (Adams & Ferreira, 2007; Song & Thakor, 2006) iscrucial to independent directors’ advisory role, intensemonitoring can result in poor advising. A board composedentirely of independent directors may result in excessivemonitoring and consequently perform poorly in advising.Kroll et al. (2007) posit that traditional agency issues suchas monitoring may be less critical for young firms at theentrepreneurial stage compared to later stages in the evo-lution of the firm. In fact, they prescribe an insider-controlled board comprised of the top management team.They argue that, since insiders possess considerable tacitknowledge and commitment to a shared vision that outsid-ers do not have, they will be more effective on the board ofyoung entrepreneurial firms.

In the context of new economy IPO firms, it is not clearthat independence is necessarily a virtue. Daily and Dalton(1994) argue that an outsider-dominated board could effec-tively counter CEO resistance to adopting aggressive strate-gies in the face of continuing organizational decline.Furthermore, boards dominated by outsiders are more likelyto remove the CEO of a poorly performing firm (Finkelstein& D’Aveni, 1994). A stream of theoretical research showsthat effectiveness of outside directors depends on the infor-mation environment (Harris & Raviv, 2008; Hermalin &Weisbach, 1998; Raheja, 2005). Duchin et al. (2010) find thatfirm performance increases when outsiders are added to theboard only when the cost of information acquisition is low.They find that performance worsens when outsiders areadded to the board if the cost of information is high.

Thus information asymmetry may be the crucial differen-tiating factor between new economy firms and establishedfirms in traditional industries. Kroll et al. (2007) reiteratetheir view that insiders may “more accurately assess thesubtleties of entrepreneurial endeavours” while outsidersare forced to depend upon coarse financial metrics based onpast data. Our setup is similar to theirs. They study youngentrepreneurial firms while we focus on new economyfirms. The distinguishing aspect is that they study all indus-tries whereas our focus is on new economy firms. As such,information asymmetry is expected to be greater in neweconomy firms compared to firms in established industries(Sanders & Boivie, 2004).

We weighed in the implications of the two divergentviewpoints regarding board independence – insider-controlled board is optimal versus outsider-controlled boardis best. Our view is that in the context of a new economy firmin a high velocity environment, an outsider-controlled boardis best – but not one that is packed entirely with outsiders.The board should contain a few knowledgeable insiders

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who provide firm-specific information to the largely inde-pendent board. Thus insiders serve as “side mirrors” andavert potential blindsiding arising from a board that is com-posed solely of outsiders. We do not recommend an insider-controlled board as in Kroll et al. (2007). Their view is basedon “tacit knowledge and commitment to a shared vision.” Itis possible that the desire to maintain group cohesion maytrump the exercise of critical judgment. In the context of anew economy firm in a high velocity environment, groupthink engendered by insider-controlled boards would bedeleterious. On the hand, an outsider-controlled board withsome insiders is more likely to consider alternate points ofview. We believe that diversity of viewpoints is essential inhigh velocity environments to avoid potential failure.

Kumar and Sivaramakrishnan (2008) suggest that the rela-tionship between independence of directors and perfor-mance is ambiguous. Using the information generated bymonitoring, the board contracts with the manager on behalfof shareholders. The terms of the contract determine themanager’s effort, capital investment decisions, and compen-sation. Given the twin roles of monitoring and contracting, arepresentative director’s contribution to shareholder valuedepends on the extent of monitoring effort exerted andthe optimality of the chosen contract. More independentdirectors will choose contracts that maximize shareholdervalue, but they may expend less effort in monitoring themanager. Thus delegating governance to the board createsa new agency problem due to directors’ effort aversion.Thus it is not clear that increasing directors’ independencebestows unambiguous improvements in the performance ofthe firm.

Bhagat and Black (2002) conduct a large-sample, long-horizon study of the relationship between degree of boardindependence and long-term performance of large US firms.They find no evidence indicating that greater board indepen-dence leads to improved firm performance. They proposethat including inside directors to the board could add value.They suggest that inside directors may be valuable due to thefirm-specific skills, knowledge, and information that theybring to the board. Inside directors are conflicted but wellinformed. Independent directors are not conflicted but arecomparatively ignorant about the company. Therefore, anoptimal board should contain a mix of inside and indepen-dent directors.

From a theoretical standpoint, our view is that crucialelements of agency theory, stewardship theory, and resourcedependence theory work in a complementary fashion todetermine the optimal board composition for new economyfirms. While the monitoring role enshrined in agency costtheory is emphasized by Finkelstein and D’Aveni (1994),Adams and Ferreira (2007) implicitly stress resource depen-dence theory when they focus on the advisory role of theboard. Furthermore, in their study of young entrepreneurialfirms, Kroll et al. (2007) invoke stewardship theory. For oursetup, no one theory clearly dominates the others in deter-mining governance outcomes.

Summing up, for a board to be effective it should performall four roles: monitoring, advising, resource provision, andcontracting. While board independence is essential for effec-tive monitoring, it is not as useful in fulfilling other roles. Wefavour an outsider-controlled board that includes a few

insiders. Therefore, all things considered, we expect a non-linear relationship between board independence and thelikelihood of survival of new economy firms. This is becauseinsiders and outsiders play complementary roles in enhanc-ing the effectiveness of a board. Therefore, we expect thatboard independence will improve survival odds but thereare decreasing returns to independence. We formally statethis as:

Hypothesis 1. There is a nonlinear relationship between boardindependence and survival likelihood of new economy firms.The survival likelihood of new economy IPO firms initiallyincreases with board independence. At very high levels ofboard independence, a further increase in board independence isassociated with a decrease in survival likelihood.

Leadership Structure. One of the most fiercely contestedissues in corporate governance is whether the CEO shouldalso serve as the chairperson of the board of directors. TheCEO is a firm’s chief strategist, who is in charge of initiatingand implementing company-wide plans and policies, whilethe role of the chairperson is to ensure that the board workseffectively in counselling and monitoring the CEO. Since thechairperson performs important control functions, it is oftenrecommended that a separate person distinct from the CEOshould serve in that role. Fama and Jensen (1983) suggestthat CEO duality (same person serving the dual roles ofCEO and chairperson) is detrimental to the board’s abilityto perform its monitoring functions. A similar view isespoused by Jensen (1993).

A contrasting view is provided by Anderson and Anthony(1986) and Stoeberl and Sherony (1985) who posit thatvesting the two positions in one person provides clear-cutleadership and focus in conducting a firm’s business opera-tions. Brickley, Coles, and Jarrell (1997) argue that there arecosts and benefits to separating the CEO and chairpersonroles. Finkelstein and D’Aveni (1994) postulate that thechoice of leadership structure reflects the board’s effort tobalance entrenchment avoidance with unity of command.Empirical evidence is, however, mixed on the relationbetween leadership structure and firm performance (Brick-ley et al., 1997; Dahya, 2004; Rechner & Dalton, 1991). In spiteof this inconclusive evidence, shareholder activists, institu-tional investors, and regulators hold the view that the CEOshould not serve in the role of board chairperson. Bach andSmith (2007) also hypothesize that CEO duality providesstructural power and enhances the survival likelihood ofhigh technology firms.

Faleye (2007) adopts a novel approach and examines theeffects of organizational complexity, and CEO reputation onthe relative costs and benefits of CEO duality. He hypoth-esizes that complex firms are more likely to vest the twopositions in the same individual. This is because in complexorganizations, the cost of vesting the chairperson and CEOroles in separate individuals outweighs the marginal benefitof non-duality. The cost of sharing information between theCEO and chairperson increases with organizational com-plexity. Furthermore, CEO flexibility becomes more valuableto organizations as their complexity increases. He findsevidence supporting the view that complex organizations



practice duality. Moreover, evidence is also consistent withthe view that firm performance improves for complex firmspracticing duality, ceteris paribus.

In the context of new economy IPO firms, we invoke theapproach of Faleye (2007). New economy firms can be con-sidered as complex organizations since they satisfy two ofthe three proxies suggested by him – asset intangibility, size,and growth opportunities. On average, new economy IPOfirms tend to have high growth opportunities and possessmore intangible assets but are less likely to be large.

We therefore posit the following hypothesis:

Hypothesis 2. CEO duality will increase the survival likeli-hood of new economy IPO firms.

Another aspect of leadership structure that is relevant is theindependence of the chairperson. As such, during times offinancial decline, the resource provision role of the boardbecomes paramount. The traditional view posits that anon-executive chairman can effectively bring in outsideresources much more effectively than an insider. However,based on the work of Coles et al. (2008), it appears thathaving an executive chairperson leverages on the firm-specific knowledge of insiders and may be associated withan increased likelihood of survival of IPO firms. For neweconomy firms, firm-specific knowledge of insiders is criti-cal, especially during turbulent times. We therefore posit thefollowing hypothesis:

Hypothesis 3. For new economy IPO firms, a board led by anexecutive chairperson will have a higher likelihood of survival.

Board Size. There are two major schools of thoughtregarding the relationship between board size and firm per-formance. One school suggests that small boards are morelikely to monitor management better since their membersare less able to hide in a large group (Fischer & Pollock,2004). Furthermore, small groups are able to arrive at deci-sions more quickly than larger ones.3 Smaller boards arearguably more able to fulfill the monitoring role and havethe advantage of speed in decision making in their advisingrole. Lipton and Lorsch (1992) recommend a small board toenhance effectiveness of the board. They suggest that asmaller board is most likely to allow directors to get betteracquainted with each other and to have more effective dis-cussions resulting in a true consensus on key decisions.Finally, Judge and Zeithaml (1992) find that smaller boardsare more likely to be involved in strategy formation. Theyascribe this result to a reduction in commitment and moti-vation of directors who are members of larger boards.Smaller boards are arguably more able to fulfill the monitor-ing role and have the advantage of speed in decision makingin their advising role.

On the other hand, however, larger boards have a poten-tial advantage in their advising role and are more capable ofaccomplishing the resource provision role of the board ofdirectors. They have a greater potential for multiple perspec-tives, which can facilitate their advisory role. Furthermore,they may enjoy superior access to key resources (Goodstein,Gautam, & Boeker, 1994). These advantages of larger boardsmay be particularly valuable to young, IPO firms (Fischer &Pollock, 2004). Dalton, Daily, Johnson, and Ellstrand (1999)

conduct a meta-analysis of studies of board size and perfor-mance and conclude that there is a positive relationshipbetween board size and financial performance. This impliesthat the advantages of access to additional resources due tothe large board prevail over the additional agency costs andslower decision making. Using key tenets of social psychol-ogy and group decision making, Sah and Stiglitz (1986,1991) confirm empirically that decisions of large groups areless likely to be extreme. That is, they tend to be neither verygood nor very bad. In the context of board structure, largeboards are likely to be associated with less variable corporateperformance. In corroboration with this line of argument,Cheng (2008), using a sample of US firms, shows that firmswith larger boards have lower variability of corporate per-formance. During turbulent economic circumstances, suchas those faced by new economy IPO firms, large boards willbe more effective since they are expected to avoid makingrisky decisions.

The choice of board size is thus governed by the trade-offbetween aggregate information that large boards possessand the increased costs of decision making associated withlarge boards. Lehn, Patro, and Zhao (2009) suggest that thetrade-off is likely to vary across firms and industries in sys-tematic ways that result in different optimal board sizesacross firms and industries. They propose that firm size andgrowth opportunities are two attributes that are likely toaffect the trade-off. They posit a direct relationship betweenfirm size and the size of its board. Large firms are engaged ina greater variety of activities and are typically large volumeplayers. As such, large firms have more demand for infor-mation than do small firms. Thus large boards are in a posi-tion to effectively provide this than small boards.

Furthermore, Lehn et al. (2009) conjecture that there existsan inverse relationship between growth opportunities andboard size. First, it is widely held that monitoring costsincrease with a firm’s growth opportunities (Gaver & Gaver,1993; Smith & Watts, 1992). As a consequence, large boardshave severe free-rider problems in firms with high growthopportunities. Boards must therefore be small in highgrowth firms for board members to have adequate privateincentives to bear the high monitoring costs. Second, firmswith higher growth opportunities usually require nimblergovernance structures. Since these firms tend to be youngerand function in more unpredictable business environments,they require governance structures that facilitate rapid deci-sion making. Jensen (1993) suggests that large boardsseldom function effectively and are easier for the CEO tocontrol. In an empirical study conducted on a sample oflarge US public corporations, Yermack (1996) finds that thereis an inverse relationship between firm market value and thesize of the board of directors.

These arguments espouse a positive relationship betweenboard size and effectiveness in terms of possessing expertiseand accessing resources, but a negative relationship betweenboard size and effectiveness in terms of the board’s ability toact rapidly in turbulent times and to monitor management(Goodstein et al., 1994). These contradictory relationshipsbetween board size and firm performance imply that theoverall impact of board size on survival will depend onwhich of the board’s roles is most essential in a given cir-cumstance. Considering new economy firms, it appears that



small boards are able to respond rapidly in turbulent eco-nomic times. Furthermore, new economy firms have highgrowth opportunities and therefore higher monitoring costs(Lehn et al., 2009). Members of large boards have lowerincentives to expend this cost due to the free-rider problem.On the other hand, large boards have more resources andcan provide better advice during turbulent times.

What should be the optimal size of the board to ensuresurvival of new economy firms in turbulent times? One viewis that medium-sized boards neither have the advantage ofspeed that small boards have nor the benefits of additionalresources that large boards have. They are thus “stuck in themiddle” and have lower chances of survival compared toother firms (Dowell, Shackell, & Stuart, 2007). Another viewis that mid-size boards could enjoy the “best of both worlds”and increase the probability of survival of new economy IPOfirms. Medium-sized boards could offer a balance of speedand resource provision.

In the context of new economy firms in high velocityenvironments, our view is that speed of decision making iscritical. Path-breaking work by Eisenhardt (1989) and Judgeand Miller (1991) provide evidence consistent with the viewthat decision speed is related to performance in specificindustry settings such as biotechnology. Extant researchis also of the view that small groups arrive at decisionsquicker than larger groups (Bainbridge, 2002). Thus largeand medium-sized boards are at a disadvantage compared tosmall boards with regard to decision speed. Another factorthat impacts speed of decision making is the number ofalternatives considered simultaneously. In this regard, largeboards have an advantage. Large boards have the potentialto bring in a diversity of viewpoints and are thus able togenerate a larger number of alternatives for simultaneousconsideration.

Based on these arguments, we would expect that firmswith either small boards or large boards should have ahigher likelihood of survival compared to medium-sizedboards. Intermediate-sized boards have a higher likelihoodof failure compared to boards at either ends of the spectrum.The firms in our setting can profit both from the speed withwhich small boards can arrive at decisions and take strategicaction as well as benefit from a broader range of alternativesthat large boards can spawn. We thus posit our hypothesisregarding board size as follows:

Hypothesis 4. For new economy IPO firms, small boards orlarge boards will have higher survival likelihood than medium-sized boards.

DATA AND METHODOLOGY

Data and SampleIn this study, a new economy company is defined as anentity in a high-technology related services or manufac-turing activity, including internet service provision andinfrastructure development, e-commerce, digital and multi-media, telecommunications (such as satellite and broadbandcommunications), information technology, software devel-opment, advanced medical instruments and biotechnology.

Our definition follows the OECD (2001) report. In particular,IPOs in the sectors of information technology, media, tele-communication services, and health care are examined. Ourindustry classification is based on the GICS standard (GlobalIndustry Classification Standard) which is an enhancedindustry classification system jointly developed by Standard& Poor’s and Morgan Stanley Capital International (MSCI)in 1991 to meet the needs of the investment community fora classification system that reflects a company’s financialperformance and financial analysis (Standard and Poor’s,2002). Recent work on alternate industry classificationschemes report that the GICS classification system providesa better technique for identifying industry peers as com-pared to other well-known schemes such as SIC (StandardIndustrial Classification) codes (Bhojraj, Lee, & Oler, 2003;Chan, Lakonishok, & Swaminathan, 2007).

New economy IPO companies listed in Australia between1994 and 2002 are included in estimating the Cox propor-tional hazards model. The year 2002 is chosen as the cut-offyear to avoid the impact of the exogenous event of therelease of ASX Best Practice Recommendations in 2003. EachIPO company is tracked from the listing on ASX untilDecember 31, 2007 or until it is delisted or suspended.

The sample of IPOs and their prospectuses are collectedmainly from the Annual Reports Online database. Some of theIPO prospectuses are not available on the Annual ReportsOnline database. In those cases, the prospectuses wereobtained from the Connect 4 Company Prospectuses database.Industry sector and financial information of the companieswas obtained from the FinAnalysis database.

In this study, non-survivors or failed companies aresimply defined as companies which have been delisted fromthe ASX. Survivors are companies which remain trading onthe ASX. This definition is consistent with Lamberto andRath (2008) and Welbourne and Andrews (1996). We test therobustness of our results to alternate definitions of survivorsand report them in the “Robustness Checks” subsectionbelow.

Survival time is measured as the number of years betweenthe year of listing and the year the company is delisted fromthe ASX for non-survivor IPO companies or the year-end ofthe observation period for survivor IPO companies. The finalsample consists of 125 new economy Australian IPO compa-nies. Among these companies, 93 companies are survivorsand 32 companies are non-survivors. The distribution ofnew economy IPO companies between 1994 and 2002 byindustry sector and by trading status is presented in PanelsA and B of Table 1, respectively.

Analytical ApproachIn order to analyze the factors influencing the survival ofnew economy Australian IPO companies, we employ a Coxproportional hazards model which is a semi-parametricmodel that uses survival analysis techniques.

The existing literature has employed the Cox proportionalhazards model in survival analysis of IPO firms (Cockburn& Wagner, 2007; Kauffman & Wang, 2001, 2007; Lamberto &Rath, 2008; Shumway, 2001).4 There exist two key advantagesof survival analysis compared to the traditional methods



such as MDA, logit and probit models. These advantagesinclude the ability to handle time-varying covariates andcensored observations.

In this context, time-varying covariates are the explanatoryvariables that change with time. Financial ratios used in thisstudy are time-varying covariates as their values change overtime. The event being explicitly studied here is the delistingof a firm. Censored observations are the observations thathave never experienced the event during the observationtime. Censoring occurs when the duration of the study islimited in time. In this study, censored observations are theIPO companies which are still trading on the ASX at the endof the observation period which is December 31, 2007.

In order to conduct analysis to see if the same factorsinfluence the different reasons for delisting – takeovers andfinancial distress, i.e., multiple states of corporate financialdistress – we also employ a survival analysis model withinthe competing risks framework. Under the competing risksmodel, inference is based on the cause-specific hazard rates.The competing risks model is the component of survivalanalysis where, in addition to survival time, the differentcauses of events are observed (Andersen, Abildstrom, &Rosthoj, 2002). This model will provide evidence on whetherthe effects of covariates are the same or different across themultiple states of financial distress. We use the competingrisks model for the three states, namely, active companies,delisted distressed companies, and delisted companies that

were taken over. Two separate Cox proportional hazardsmodels are estimated for the competing risks model whereother states of financial distress are considered as censoredobservations.5 We expect this analysis to augment our under-standing of the exit behavior of new firms. The existingliterature reveals that pooling exit types is a major source ofmisspecification (Prantl, 2003).

Variables and MeasuresThe dependent variable is survival time. Survival time ismeasured in number of years from the start year to the yearof financial distress for a distressed company or to the lastyear observed for an active company. However, we do notuse survival time directly as in an OLS regression model. Byapplying a Cox proportional hazards model, we use survivaltime to generate hazard rates of a new economy IPO firmand model the hazard rates as a function of various firm-specific characteristics at the time of offering. Corporate gov-ernance attributes are the key independent variables used inthis study. These variables include measures of board sizeand board independence. We measure board size (BD_SIZE)by the number of directors on the board including the chair-person and board independence (BD_INDP) as the percent-age of independent directors as listed in the IPO prospectus.For the purpose of this study, all non-executive directorsare classified as “independent directors” following Kang,Cheng, and Gray (2007).6 We measure CEO duality by thedummy variable CM_DUAL which takes the value of oneif chairperson and CEO are different persons. We signifyleadership independence by the variable CM_NEXC if thechairperson is a non-executive director as stated in the IPOprospectus.

As discussed below, a number of control variables are alsoincluded in the model. The choice of these variables is basedon prior literature. First, following prior work such as Woo,Jeffrey, and Lange (1995), we control for ownership concen-tration. Ownership concentration is measured by the pro-portion of common stock held by the top 20 shareholders(TOP20). Second, we also control for offer characteristics.These variables include offer price, offer size, age of offer-ing, retained ownership, underwriter backing, auditorreputation, and risk. Offer price is measured by the price(OF_PRICE) listed in the prospectus or the mid-point of theprice range. High-risk IPOs are underpriced more to com-pensate the investors for the higher ex-ante uncertainty.Since high-risk firms are more likely to fail, we expect apositive relationship between offer price and IPO compa-nies’ survival (Ho, Taher, Lee, & Fargher, 2001; Lamberto &Rath, 2008). Offer size (OF_SIZE) is measured by the amountlisted on the prospectus or the minimum subscriptionamount. The size of the offering is expected to be positivelyrelated to the firm’s survival. It is argued that larger offer-ings signal market confidence, more stringent monitoring(Lamberto & Rath, 2008), good prospects, and thereforehigher probability of survival (Hensler, Rutherford, &Springer, 1997; Jain & Kini, 1999, 2000; Ritter, 1991). Firmage at offering (OF_AGE) has been used as a proxy for risk(Ho et al., 2001; Ritter, 1991) and older firms performedbetter in the after-market than younger ones. Since estab-lished firms are expected to have a more stable source of

TABLE 1Composition of Sample

Panel A: Stratified by GICS industry sector

GICS industry sector N Percent

Information Technology 55 44.00Media 13 10.40Telecommunication Services 13 10.40Health Care 44 35.20Total 125 100.00

Note: N is the number of companies. Percent is the number ofcompanies in a particular industry group as a proportion of totalnumber of companies.

Panel B: Stratified by trading status

Trading status N Percent

Trading 93 74.40Delisted due to other reasons 17 13.60Delisted due to merger/

takeover/acquisition15 12.00

Total 125 100.00

Note: N is the number of companies. Percent is the number ofcompanies in a particular trading status group as a proportion oftotal number of companies.



business, and be less speculative, they are more likely tosurvive than young firms (Lamberto & Rath, 2008). There-fore, it is expected that the company age at offering shouldbe positively related to its likelihood of survival. Based onsignaling theory, viz., a higher percentage of insider owner-ship retention at IPOs serves as a certification device (Leland& Pyle, 1977), we expect the percentage of stock retained bypre-IPO shareholders (RETAIN) to be positively related tothe survival of the firm.7 Underwriter backing is measuredas a dummy variable (BACK) that takes the value of one ifthe IPO was backed by an underwriter. Since it is in the bestinterest of the underwriter to endorse companies withsound prospects (Lamberto & Rath, 2008), we expect thatcompanies with underwriter backing should be more likelyto survive than those without. Auditor reputation (BIG5) isincluded as an indicator variable with a value of one if theauditor is from one of the Big 5 accounting firms and zerootherwise. The Big 5 companies include Pricewaterhouse-Coopers, KPMG, Arthur Anderson, Deloitte Touche Tohm-atsu, and Ernst and Young (Dimovski & Brooks, 2003; How,Izan, & Monroe, 1995; Lamberto & Rath, 2008). We expectthat companies with an auditor from one of the Big 5 com-panies should have a higher likelihood of survival than thosewith a non-Big 5 auditor. Risk is proxied by the number ofrisk factors listed in the prospectus (Bhabra & Pettway, 2003).Firms with more risk factors listed in the prospectus(NUM_RISK) suggest a riskier firm and hence an increasedlikelihood of failure.8

Third, we also control for the following company specificvariables. We use the company specific characteristicsincluding company size, IPO_9900, and venture capital-backed IPOs in the analysis. We measure company size asthe natural logarithm of total assets of the firm (C_SIZE).Prior literature posits that firm failure is negatively corre-lated with firm size. The rationale for this relationship is thatlarger firms could avoid financial distress by using publicequity markets (Goktan, Kieschnick, & Moussawi, 2006).9

Therefore, it is expected that larger IPO firms will survivelonger than smaller ones. A dummy variable (IPO_9900) isused to indicate if a company went public between 1999 andApril 2000 (Ho et al., 2001; Kauffman & Wang, 2007). Weexpect that companies that went public between 1999 andApril 2000 are more likely to fail because April 2000 is thedate generally recognized by Australian financial marketparticipants as coinciding with the “bursting of the dot combubble” (Ho et al., 2001). We also use the dummy variableVC-Backed to denote the presence of venture capitalists(VCs). Venture capitalists can be an additional source ofresource and advice during periods of economic duressfaced by newly public firms.10 Alternately, young venturecapitalists could be “grandstanding” (Gompers, 1996). Thatis, they exit portfolio companies at an earlier stage in order toestablish their track records. If grandstanding occurs in Aus-tralia, then venture capital-backed IPOs are liked to havelower likelihood of survival. Another explanation regardingthe impact of venture capital backing is provided by Fischerand Pollock (2004) and Arthurs, Hoskisson, Busenitz, andJohnson (2008). From an ownership perspective, venturecapitalists can be considered as principals in the firm inwhich they invest. But they are agents to their investors inthe venture capital fund that has invested in the IPO firm.

Due to this agency role, venture capitalists have incentives toadopt a short-term focus at the IPO stage in order to showquick returns for investors. Since venture capital funds havea limited life, they face substantial pressures to show returnsquickly. Fischer and Pollock (2004) posit that venture capi-talists often enhance short-term performance to the detri-ment of long-term survival. Such an approach enhancesthe venture capitalists’ ability to extract a premium duringthe exit (IPO) but leave the new venture less viable in thefuture.

Finally, four categories of financial ratios, including liquid-ity ratio, profitability ratio, leverage ratio, and activity ratio,are used as control variables in this study. The current ratio(CUR) is used as the measure of a firm’s liquidity. Higherlevels of liquidity provide a strong defense against financialfailure. This study utilizes return on asset (ROA) as ameasure of profitability. It is expected that companies with ahigh profitability ratio will be more likely to survive. Thedebt ratio (DET) is used as a measure of leverage in thisstudy. The degree of financial risk is related to the likelihoodof financial distress (Lee & Yeh, 2004). It is expected thatcompanies with a higher leverage are more likely to gobankrupt. The activity ratios measure the efficiency of afirm’s asset utilization. They measure the ability of a firm touse assets to generate revenue or return. If firms can useassets efficiently, they will earn more revenue and increaseliquidity. Total asset turnover ratio is employed in this study(TAT). We list all the variables used in this study and providedetailed definitions in Table 2.

EMPIRICAL RESULTS

Descriptive StatisticsTable 3 presents descriptive statistics of the data employedin the study stratified by company status. We portray twosubsamples based on the trading status – active and delistedfirms.11 The descriptive statistics include the number ofobservations, means, medians, minimum, maximum, stan-dard deviations, skewness, and kurtosis for each subsample.It should be noted that because of the binary or dummyvariables that have been used for some factors, the mean forthese variables should be interpreted as the percentage ofcompanies that satisfy a given criterion. The binary variablesemployed in this study include CM_NEXC, CM_DUAL,BACK, BIG5, IPO_9900, and VC-BACKED.

In order to prevent the influence of observations withextreme values, observations are truncated at the specifiedthresholds. All observations with covariate values higherthan the 99th percentile of each covariate are set to that value.In the same way, all covariate values lower than the firstpercentile of each covariate are truncated. This procedure issimilar to the one employed by Shumway (2001). The Mann-Whitney U-test, a non-parametric test, is employed to test forsignificant differences between the group means. Variableswith significant differences in their group means willbe expected to add information to a regression analysis.The variables TOP20 (U = 7.21, p < .05) and VC-BACKED(U = 5.53, p < .05) display significant differences across thesubsamples.



According to Table 3, the median number of directors forboth survivors and non-survivors is five, which is consistentwith Lamberto and Rath (2008). They find that the majorityof IPO companies have fewer than six directors on the boardwhich is the minimum number of directors recommended

by the ASX for good governance. The mean percentages ofnon-executive directors on the board were 53.41 and 61.96for active and non-survivor companies, respectively. Thisfigure implies that the majority of directors on the neweconomy Australian IPO company boards are independent

TABLE 2The Variables Used in the Study

Variable code Variable name Definition of variable

Survival time Dependent variable: SUR_TIME Survival time is the number of years from the start year to the year offinancial distress for a distressed company or to the last yearobserved for an active company.

Corporate governance attributes:

BD_SIZE Board size Number of directors on the board, including chairperson.Board independence

BD_INDP Percentage of independentdirectors

The ratio of the number of non-executive directors to the number ofdirectors, as listed in the prospectus.

CM_NEXC Non-executive chairperson If the chairperson listed in the prospectus is a non-executive director,then a value of 1 is recorded, 0 otherwise.

CM_DUAL Dual leadership structure If the chairperson and CEO are different people then a value of 1 isrecorded, 0 otherwise.

Ownership concentrationTOP20 Top 20 shareholders The proportion of common stock held by the top 20 shareholders.

Offering characteristics:OF_PRICE Offering price The offer price listed in the prospectus, or the midpoint of the price

range.OF_SIZE Offering size The size of the offering listed in the prospectus, or the minimum

subscription amount.OF_AGE Offering age The difference between the year in which the prospectus was lodged

and the year in which the company was founded.RETAIN Retained ownership The difference between the market capitalization of the company after

listing and the size of the offering, divided by the marketcapitalization of the company after listing.

BACK Underwriter backing Initial public offerings which had an underwriter recorded a value of1, 0 otherwise.

BIG5 Auditor reputation Initial public offerings which had an auditor belonging to one of theBig 5 accounting firms recorded a value of 1, 0 otherwise.

The Big 5 accounting firms include PricewaterhouseCoopers, KPMG,Arthur Anderson, Deloitte Touche Tohmatsu and Ernst and Young.

NUM_RISK Number of risk factors in theprospectus

The number of risk factors listed in the prospectus. If there is nospecific risk factor section, the number is 0.

Financial ratios:ROA Profitability Return on asset (ROA): Earnings before interest/(total assets-outside

equity interests).CUR Liquidity ratio Current ratio: Current assets/current liabilities.DET Leverage ratio Debt ratio: Total debt/total assets.TAT Activity ratio Total asset turnover: Operating revenue/total assets.

Company-specific variables:C_SIZE Company size The logarithm of total assets of the firm.IPO_9900 IPO_9900 A dummy variable recorded a value of 1 if a company issued stock

between 1999 and April 2000, 0 otherwise.VC_BACKED Venture capital-backed IPOs A dummy variable recorded a value of 1 if a company is a venture

capital-backed IPO, 0 otherwise.



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directors. In addition, 64 and 70 percent of active and non-survivor new economy IPO companies, respectively, have anon-executive chairperson, and 86 and 85 percent of thesecompanies have the positions of CEO and chairperson heldby different persons. These results suggest that the majorityof new economy Australian IPO companies have boardswhich can be considered independent. Furthermore, themean percentages of the top 20 shareholders for activeand non-survivor companies are 65.98 and 76.77 percent,respectively.

In terms of the offering characteristics, the median offer-ing price is A$0.50 for the survivors and A$1.00 for thenon-survivors. The median offer sizes are A$8 and A$12million and the medians of offering age are 3.04 and 4.51years for the survivor and non-survivor companies, res-pectively. These results suggest that the new economyAustralian IPO companies are relatively young and small,consistent with the results reported by Lamberto and Rath(2008).

Additionally, 74 and 90 percent of the offerings by survi-vor and non-survivor companies are underwritten, while53 and 70 percent of the offerings by active and non-survivor companies have an auditor from one of the Big 5accounting firms. The median number of risk factors iden-tified in the prospectus is 13 and 14 for active and non-survivor companies, respectively. The means of retainedownership by pre-IPO owners are 62.16 and 70.48 percentfor active and non-survivor IPO companies, respectively,which implies that the control of new economy IPOcompanies was retained by the original owners. It is alsointeresting to note that 40 and 36 percent of active andnon-survivor IPOs companies are listed during the 1999 toApril 2000 period.

The profitability ratios, which show the ability of thecompany to generate profit, are negative for both groups.The means of ROA for active and non-survivor companiesare -.29 and -.35, respectively. This result suggests thatnon-survivor IPOs companies have lower earnings thanactive companies. But the difference is not statistically sig-nificant. The mean of the liquidity ratio, CUR, of non-survivor companies is higher than that of the active firmsubsample. The mean of debt ratio, DET, indicates that thenon-survivor companies have higher leverage than that ofactive companies. For the activity ratio, TAT, the mean ofnon-survivor companies is higher than that of the survi-vors. However, the Mann-Whitney U-test indicates thatthere is no significant difference in means of these ratiosbetween active and non-survivor new economy IPOcompanies.

The mean SIZE of active and non-survivor companies is7.27 and 7.41, respectively. The Mann-Whitney U-test showsthat, on average, the size of active and non-survivor neweconomy IPO companies in our sample are marginally sta-tistically significantly different (U = 3.33, p < .10). Finally, thesurvivor and non-survivor samples differ significantly withrespect to the percentage of firms backed by venture capi-talists. Only 11 percent of survivors are backed by venturecapitalists while 31 percent of the non-survivors haveVC-backing.

The Pearson correlation coefficients across the variablesare shown in Table 4. The results suggest weak relation-

ships across the variables. We do not find any large andsignificant coefficients that indicate serious problems ofmulticollinearity.

Cox Proportional Hazards ModelEstimation ResultsWe employ the Cox proportional hazards model to investi-gate the influence of corporate governance variables on thesurvival likelihood of new economy IPO companies. In addi-tion to corporate governance variables, we also include offer-ing characteristics, financial ratios, and company-specificvariables. The estimation results are presented in Table 5.12

We present the coefficients, estimated standard error ofthis estimate, Wald chi-square tests along with the relativeP-value for testing the null hypothesis that the coefficient ofeach covariate is equal to zero. Finally, the hazard ratio ispresented in the last column. The hazard ratio is obtained bycomputing eb, where b is the coefficient in the proportionalhazards model. A hazard ratio equal to one indicates that thecovariate has no effect on survival. If the hazard ratio isgreater (less) than one, then this indicates a more rapid(slower) hazard timing. We report only coefficients and teststatistics of significant control variables in order to conservespace. Our estimations include all available variables. Wecategorize survival on the basis of whether the firm contin-ues to trade in the Australian exchange as of December 31,2007. All delisted firms – regardless of the reason fordelisting – are treated as failed firms.

Since we do not have a theory regarding a functional formof the relationship between board independence and prob-ability of survival, we include quadratic and higher orderterms. We find that board independence exhibits a negativecoefficient, indicating that independence has a beneficialeffect on firm survival (b = -.11, p < .05). The quadratic termis statistically significant at the 5 percent level (b = .001,p < .05). We also tried higher order terms. These are notstatistically significant. Therefore in order to conservedegrees of freedom, we stop with the quadratic term.

Summing up, we observe a nonlinearity in the relation-ship between board independence and probability of sur-vival. It appears that the benefits of board independenceincrease at a decreasing rate. Our evidence suggests thatthere exists an optimal level of board independence – some-where in the middle, neither too little nor too much. Itappears that insiders and outsiders play complementaryroles in preventing firm failure. We find strong support forHypothesis 1.

The leadership structure variables such as CM_NEXC andCM_DUAL do not significantly alter the IPO firms’ chanceof survival. Our empirical results do not support Hypoth-eses 2 and 3. Our results imply that CEO duality, which isdeemed to be important for complex firms, neither increasesnor reduces the IPO firms’ likelihood of survival.

In order to check the robustness of our results, especi-ally in the light of non-significance of CEO duality andnon-executive chairperson, we used several alternate speci-fications. Arguably, large firms are more complex thansmall firms and may have different advising requirements.To explore this possibility, we interacted our governance



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variables with firm size (C_SIZE). We find that none of theseadditional variables are significant. Therefore, in the interestsof brevity, we do not report these results.

Another possibility is that CEO duality and the presenceof a non-executive chairperson may capture entrenchmenteffects. When the same person is both the CEO and chair-person, it increases the likelihood that the managers willresist a takeover attempt. Thus the observed coefficient cap-tures the effects of entrenchment in addition to performancethat we are essentially interested in. In our robustnesschecks, reported in the next section, we explicitly deal withthis possibility.

Our results indicate that board size has a positive estimatedcoefficient (b = 2.58, p < .10). The square of board size has anegative coefficient (b = -.25, p < .10). Board size variables aremarginally significant. Since there is no theory regarding theexact functional form of the relationship between board sizeand survival likelihood, we tried several higher order terms.These are not statistically significant. Therefore in the inter-ests of conserving degrees of freedom, we stop with thequadratic term. It appears that there is a nonlinear effect ofboard size on survival likelihood. Our empirical resultssuggest that a small size board, and to a lesser extent large sizeboard, have longer survival times compared to a medium-sized board. Our result is similar to that of Dowell et al. (2007).Thus we find weak support for Hypothesis 4.

The relationship between board size and survival isgraphically portrayed in Figure 1.13 In Panel A, we map thesurvival function for firms with small, medium and largesize boards. We characterize a board with fewer than fourmembers as small, those with between four and six asmedium, and those with more than six members as large.The graph shows the probability of survival over time (sincelisting). The graph clearly shows that firms with mediumsize boards have the lowest chance of survival at any giventime. It is seen that firms with small and large board sizes aremore likely to survive compared to firms with moderate-sized boards. We reach a similar conclusion when we lumpsmall and large boards into one category and medium intothe other group. This is portrayed in Panel B. We, therefore,conclude that Hypothesis 4 is supported by data. We findsupport for the “stuck in the middle” form of the hypothesisand reject the “best of both worlds” version.

Among the control variables, offer size, underwriterbacking, venture capital backing, debt equity ratio, andcompany size are statistically significant. The estimatedhazard ratio for the variable VC_BACKED is 2.490 whichindicates that the probability of financial distress for ven-ture capital-backed IPO companies increases by about 149percent compared to non-venture capital-backed IPO com-panies (b = .91, p < .10). Our finding of VC-backing beingassociated with higher failure likelihood could potentially

TABLE 5Estimation Results of Multivariate Cox Proportional Hazards Model of the Entire Sample

Covariate Coefficient Standard error c2 Statistic p-value Hazard ratio

BD_SIZE 2.58† 1.53 2.86 .09 13.19BD_SIZESQ -.25† .14 3.27 .07 .78BD_INDP -.11* .04 6.05 .01 .90BD_INDPSQ .00* .00 5.90 .02 1.00CM_DUAL .47 .87 .29 .59 1.60CM_NEXC .07 .50 .02 .88 1.08TOP20 -.06 .08 .66 .42 .94TOP20SQ .00 .00 1.64 .20 1.00OF_SIZE .00† .00 3.80 .05 1.00BACK 1.21† .68 3.17 .07 3.36VC_BACKED .91† .50 3.36 .07 2.49DET .67† .35 3.76 .05 1.96C_SIZE .68† .36 3.61 .06 1.97

Notes: The dependent variable is the survival time, SUR_TIME, the number of years from the start year to the year of financial distressfor a distressed company or to the last year observed for an active company. By applying a Cox proportional hazards model we usesurvival time to generate hazard rates and model the hazard rates as a function of various firm-specific characteristics at the time ofoffering. BD_SIZE is the board size calculated by number of directors on the board including chairperson. BD_SIZESQ is the square ofboard size. BD_INDP is percentage of independent directors measured by the ratio of the number of non-executive directors to thenumber of directors, as listed in the prospectus. BD_INDPSQ is the square of the percentage of independent directors. CM_DUAL is dualleadership structure and takes the value of 1 if the chairperson and CEO are different persons, 0 otherwise. CM_NEXC is non-executivechairperson and takes the value of 1 if the chairperson listed in the prospectus is a non-executive director, 0 otherwise. TOP20 is theproportion of common stock held by the top 20 shareholders. OF_SIZE is the size of the offering listed in the prospectus, or the minimumsubscription amount. BACK is underwriter backing, if the initial public offering had an underwriter it is coded as 1, 0 otherwise.VC_BACKED is venture capital-backed IPOs and takes the value of 1 if is a venture capital-backed IPO, 0 otherwise. DET is debt ratiocalculated by total debt/total assets and C_SIZE is company size measured by the logarithm of total assets of the firm.* and † denote significant at the .05 and .10 levels, respectively.



be explained by a form of grandstanding that is studied inGompers (1996). An alternate explanation is that the short-term focus displayed by venture capitalists during the IPOperiod is deleterious for long-term survival. Similarly, theestimated hazard ratio for the BACK variable is 3.36, signi-fying that firms backed by underwriters are 3.36 times aslikely to fail compared to firms which are not underwriterbacked (b = 1.21, p < .10). This counterintuitive result may beexplained by the possibility that risky firms seek under-writer backing. However, both these variables only displaymarginal significance.

Considering financial ratios, DET is the only financial ratiowhich is statistically significant in explaining the survival ofIPO firms. The parameter estimates are positive for DET,which means that the IPO companies with low debt ratio are

less likely to fail (b = .67, p < .05). The estimated hazard ratiofor DET is 1.96 which indicates that for every unit increasein debt ratio, the risk of failing increases by 96.3 percent.C_SIZE is marginally significant (b = .68, p < .10), with ahazard ratio of 1.97. The positive sign of C_SIZE means thatthe larger the size of IPO companies, the higher the likeli-hood of companies entering into financial distress. Ourresults are consistent with prior research (Lamberto & Rath,2008) but inconsistent with our expectation as outlined inthe previous section. A possible explanation for this findingis that large firms are more complex than small firms and assuch are more prone to failure, other things being equal.

Summing up, the results of our study show that neweconomy IPO companies with smaller value of total assets,lower leverage and those that are not VC-backed are morelikely to survive. Interestingly, the dictum that the majorityof the board should be composed of independent directorsproves to be useful in reducing firm failure likelihood. Wewould like to add that the benefit of board independenceincreases at a decreasing rate signifying that insiders andoutsiders act in a complementary manner to enhance theeffectiveness of the board. Another remarkable finding isthat small boards and very large boards are associated witha lower chance of corporate failure compared to mediumsize boards. The commonly touted recommendations of con-ventional leadership structure wisdom do not help in miti-gating the risk of corporate failure. These are: (a) thechairperson should be an independent director and (b) theroles of chairperson and chief executive officer should not beexercised by the same individual.

Robustness ChecksWe conduct two sets of robustness checks. These are basedon alternate methods of classifying survivors and non-survivors. Our method of classifying survivors and non-survivors on the basis of delisting is subject to criticism. Onemay argue that delisting may be due to poor performance ortakeovers. Delisting due to takeover by another firm is notnecessarily indicative of poor performance. It may be theoptimal response to increase shareholder wealth in the wakeof a lucrative bid from an acquiring firm.

First, we estimate the survival likelihood for two subsetsof firms – those that were delisted due to financial distressand those that were delisted due to takeovers and acquisi-tions by applying the competing risks model. Second, weestimate the Cox proportional hazards model excludingfirms with good performance which were taken over. In thefirst method, we exclude all firms which were delisted dueto takeovers. The resulting sample of non-survivors thusrepresents a clean sample of firms that performed poorlyprior to delisting. In the second method, we only excludefirms with good performance which were taken over. Sinceour basic motivation in this paper is to identify the boardcharacteristics that impact a new economy firm’s survivallikelihood, firms delisted due to other extraneous reasonsare best left out. One potential problem with our attempt toconstruct a “cleaner” sample of non-survivors is the loss ofsample size and the consequent reduction in the power ofour statistical tests.

FIGURE 1Graph of Survival Function for Boards of Different Size

Panel A: Small versus Medium versus Large BoardsPanel B: Small or Large Board versus Medium Size

Board

Small or large board

Medium board

0. 56

0. 58

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1 2 3 4 5 6 7 8 9 10 11 12 13

Medium board

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Note: Small board (<4), Medium size board (4–6), Large board(>6).



We report the estimation results from applying the com-peting risks Cox proportional hazards model in Table 6. Forthese tests, the set of firms delisted due to financial distressis categorized as non-survivors in Panel A. In Panel B, non-survivors are those firms delisted due to takeovers. Ourresults incorporate potential nonlinearity in the governanceand ownership structure variables.

The results in Panel A indicate that the significancelevels of the board independence (b = -.17, p < .05) andboard size (b = 6.22, p < .10) are similar to the full sampleresults reported in Table 5. As in the whole sample, C_SIZEis statistically significant (b = 1.14, p < .05). Once again, we

observe nonlinearity in the relation between board size (andboard independence) on survival likelihood. As before, wefind strong support for Hypothesis 1, weak support forHypothesis 4 and no support for the other hypotheses.In addition, age of the company (b = -.11, p < .10), andVC_BACKED (b = 1.44, p < .10) are marginally significant.OF_AGE has a hazard ratio of .90 indicating that increasingthe age of the firm by one year on the offer date reducedfinancial distress likelihood by 10.3 percent. The significanceof the dummy variable IPO_9900 (b = 2.25, p < .05) indicatesthat if a firm went public during the years 1999 or 2000, thechances of delisting increased by 848 percent.

TABLE 6Competing Risks Model of the Subsamples

Covariate Coefficient Standard error c2 Statistic p-value Hazard ratio

Panel A: Subsample of delisted firms due to financial distressBD_SIZE 6.22† 3.52 3.12 .08 501.29BD_SIZESQ -.61† .35 3.10 .08 .54BD_INDP -.17* .07 6.51 .01 .84BD_INDPSQ .00* .00 5.84 .02 1.00CM_DUAL -.87 1.01 .74 .39 .42CM_NEXC -.13 .74 .03 .86 .87TOP20 .14 .22 .42 .52 1.15TOP20SQ -.00 .00 .20 .66 1.00OF_AGE -.11† .06 3.64 .06 .90IPO_9900 2.25* .81 7.71 .01 9.48VC_BACKED 1.44† .80 3.22 .07 4.24C_SIZE 1.14* .51 4.97 .03 3.12Panel B: Subsample of delisted firms due to takeovers and acquisitionsBD_SIZE 1.51 2.00 .57 .45 4.512BD_SIZESQ -.14 .18 .65 .42 .87BD_INDP -.12† .07 2.85 .09 .89BD_INDPSQ .00† .00 3.16 .08 1.00CM_DUAL 16.90 2154 .00 .99 21887627CM_NEXC .58 .84 .48 .49 1.79TOP20 -.24* .11 4.72 .03 .79TOP20SQ .00* .00 5.54 .02 1.00DET .92† .52 3.05 .08 2.50

Notes: The dependent variable is the survival time, SUR_TIME, the number of years from the start year to the year of financial distressfor a distressed company or to the last year observed for an active company. By applying a Cox proportional hazards model we usesurvival time to generate hazard rates and model the hazard rates as a function of various firm-specific characteristics at the time ofoffering. BD_SIZE is the board size calculated by number of directors on the board including chairperson. BD_SIZESQ is the square ofboard size. BD_INDP is percentage of independent directors measured by the ratio of the number of non-executive directors to thenumber of directors, as listed in the prospectus. BD_INDPSQ is the square of the percentage of independent directors. CM_DUAL is dualleadership structure and takes the value of 1 if the chairperson and CEO are different persons, 0 otherwise. CM_NEXC is non-executivechairperson and takes the value of 1 if the chairperson listed in the prospectus is a non-executive director, 0 otherwise. TOP20 is theproportion of common stock held by the top 20 shareholders. TOP20SQ is the square of the proportion of common stock held by the top20 shareholders. OF_AGE is offering age calculated by the difference between the year in which the prospectus was lodged and the yearin which the company was founded. IPO_9900 is a dummy variable recorded a value of 1 if a company issued stock between 1999 andApril 2000, 0 otherwise. OF_SIZE is the size of the offering listed in the prospectus, or the minimum subscription amount. BACK isunderwriter backing, if the initial public offering had an underwriter it is coded as 1, 0 otherwise. VC_BACKED is venture capital-backedIPOs and takes the value of 1 if is a venture capital-backed IPO, 0 otherwise. DET is debt ratio calculated by total debt/total assets andC_SIZE is company size measured by the logarithm of total assets of the firm.* and † denote significance at the .05 and .10 levels, respectively.



In Panel B, we examine the subset of firms that delisted dueto takeovers and acquisitions. Board independence (b = -.12,p < .10) and leverage (b = .92, p < .10) have marginally signifi-cant influence on the likelihood of survival. TOP20 is signifi-cant with a negative coefficient (b = -.24, p < .05). BothBD_INDP and TOP20 reduce the likelihood of delisting whileleverage exacerbates the odds. We note that the significancelevels of board independence have dropped compared to thefull sample and financial distress subsamples. Our resultsfrom Table 5 and Panel A of Table 6 indicate that more inde-pendent boards are associated with a higher likelihood offirm survival and that the benefits of independence increaseat a decreasing rate. Arguably, board independence is alsoassociated with a higher probability of takeovers and acqui-sitions. Thus board independence is less of a distinguishingfactor explaining new economy IPO firms’ survival whendelisting due to takeovers and acquisitions is considered asnon-survival. Furthermore, board size is no longer signifi-cant. Our earlier results indicate that small boards, due totheir speed of response, and large boards, due to their greateradvising capability, are associated with a higher likelihood offirm survival. The exact same features should also be associ-ated with the increased likelihood of being taken over. Thusboard size ceases to be a distinguishing feature that explainssurvival likelihood when non-survival is characterized bydelisting due to takeovers and acquisitions.

Our results indicate that ownership concentration is asso-ciated with higher corporate longevity or lower probabilityof being taken over. Our finding with respect to TOP20 isconsistent with agency cost theory but inconsistent with thefindings of Woo et al. (1995). This is because shareholderswith significant holdings are more likely to have an influ-ence on management’s decisions and they will expend moremonitoring costs as their stake in the firm increases (Jensen& Meckling, 1976). Higher ownership concentration is alsolikely to deter takeovers and acquisitions. Thus the observedsignificance of TOP20 is due to both effects – better moni-toring and lower chance of takeovers. TOP20 is not signifi-cant in Panel A of Table 6 and in Table 5. We interpret thisfinding to imply that the takeover effect is much more sig-nificant than the monitoring effect. We find that the squaredterm (TOP20SQ) is significant (b = .002, p < .05), indicatinga nonlinear relationship between ownership concentrationand survival likelihood. Perhaps, this signifies the entrench-ment effect if TOP20 shareholders include controllingshareholders.

We conduct further robustness checks using the Cox pro-portional hazards model excluding firms which had goodperformance and were taken over. Good performance issignified by non-negative earnings during the two yearspreceding takeovers. Ostensibly, the acquired firms weretaken over not because of distress and are therefore notclassified as non-survivors. We confirm the significance ofboard size, the square of board size, board independence, thesquare of board independence, VC_BACKED, and DET.Overall, our results indicate that leadership structure doesnot significantly affect survival likelihood of new economyIPO firms. These results are not reported for the sake ofbrevity.

We also considered the possibility of simultaneity affect-ing our estimated results. Board size and other included

control variables, such as firm size (C_SIZE), offer size(OF_SIZE), and offer price (OF_PRICE), could potentially beaffected by simultaneity (Lehn et al., 2009). We consideredtwo approaches to account for potential simultaneity. First,we re-estimated our results without C_SIZE, OF_SIZE,and OF_PRICE. We obtained qualitatively similar results.Second, we used an instrumental variables approach. Weregressed board size on C_SIZE, OF_SIZE, and OF_PRICE.The residual from this estimation was then added to ouroriginal model instead of C_SIZE, OF_SIZE, and OF_PRICE.The estimated results did not indicate simultaneity. Theseresults are not reported for the sake of brevity.

DISCUSSION AND CONCLUSION

The innovative aspect of our study is that it explores therelationship between board structure and the survival like-lihood of new economy firms. While prior studies focus onsome measure of performance, such as return on assets orTobin’s Q, we use firm survival as a metric of performance.We focus our attention on three main areas of corporategovernance mechanisms – board size, board independence,and dual leadership structure. Control variables such asoffering characteristics, financial ratios and company-specific variables are also incorporated in the model. Ourchoice of new economy firms is based on the fact that firm-specific knowledge of insiders is more relevant in the case ofnew economy firms compared to other firms. Furthermore,the cost of acquiring information by outside directors islikely to be higher for new economy firms. Therefore, therelevance of board structure is much more critical for neweconomy firms than other firms.

Our empirical results, based on a sample of AustralianIPO firms utilizing the Cox proportional hazards model,show that independent boards are associated with a higherchance of survival. There is nonlinearity in the relationshipbetween board independence and likelihood of survival. Thebenefits of board independence increase at a decreasing rate.Our empirical results support the view that an outsider-controlled board is best – but not one that is packed entirelywith outsiders. Ideally, the board should contain a fewknowledgeable insiders who provide firm-specific informa-tion to the largely independent board. Insiders serve as “sidemirrors” and avert potential blindsiding arising from aboard that is composed solely of outsiders. We do notespouse an insider-controlled board to obviate the possibil-ity of groupthink in critical decision-making contexts.

This key result informs the debate on the relevance of asingle board structure for firms with widely divergent infor-mation environments. Our results lend support to the viewof Coles et al. (2008), who posit that firms for which firm-specific knowledge of insiders is comparatively more impor-tant, such as new economy firms, are likely to benefit fromrepresentation of insiders on the board. Summing up, ourempirical results confirm the existence of complementaryeffects of the expertise brought in by insiders and outsidersand their impact on firm survival.

We also find weak evidence that firms with either smalleror larger board size have a higher probability of survivalthan firms with moderate-sized boards. The benefits of a



small or a large board are relatively important and boards ateither end of the spectrum outperform those in the middle.It appears that the benefits of a smaller board, such as thelower monitoring cost and rapidity in decision making,increase the probability of survival. Likewise, the advan-tages of a larger board, such as more resources and diversityof viewpoints, also increase the likelihood of survival.

Our work is related to the recent paper of Kroll et al. (2007)who study the impact of board composition on post-IPOperformance of young entrepreneurial firms in the US.While we uphold their insight that the presence of insidersis valuable in newly public firms, our study is differentfrom theirs in three major aspects. First, by studying neweconomy firms, we emphasize the industry context. There-fore, in deriving our testable hypotheses, we rely upon infor-mation asymmetry, while they base their predictions onshared vision and tacit knowledge. Second, our performancemeasure is survival while theirs is stock return performance.Finally, we also examine CEO duality and board size whichare not examined in their study.

Our research presents useful insights to policy makerswho are interested in setting best practice standards regard-ing board structure. Our research suggests that firm/industry characteristics play a crucial role in determining theoptimal board structure. Especially crucial is the informationprocessing costs of outsiders who serve as members of theboard. In firms/industries where outsiders face significantlyhigher information processing costs, insiders can play avaluable role in enhancing the effectiveness of the board.Our results suggest that regulators and corporate gover-nance advocates should not go overboard in recommendingthat boards should be filled exclusively with outsiders.

Our findings have relevance to researchers and datavendors in the corporate governance domain. Someresearchers and database vendors (for instance, Riskmetrics)score a firm based on its corporate governance features.Typically, such measurements assume a monotonic relation-ship between a feature such as board independence andeffectiveness. Our research suggests that industry and firmcharacteristics preclude such a relationship.

Our finding of VC-backing being associated with higherfailure likelihood could potentially be explained by thepotential agency costs implicit in venture capitalists servingtheir short-term interests during the IPO stage. Thus a fruit-ful area of future research is an examination of the nature ofthe agency costs and their potential impact on future sur-vival likelihood. It is also possible that human capitalattributes of the board and senior executives play a role inthe survival of new economy firms. Thus, a potential avenuefor future research is to incorporate the characteristics ofboards such as the experience of directors in the particularindustry sector (Bach & Smith, 2007; Wilbon, 2002), thenumber of meetings held by the boards, and board remu-neration. More research on this key issue is likely to enhanceour knowledge of the factors influencing corporate survival.

ACKNOWLEDGEMENTS

We would like to thank William Judge (the editor), PraveenKumar (the associate editor), and three anonymous referees

for their insightful comments and suggestions. The authorsare grateful to the comments by participants at the 21st Aus-tralasian Finance and Banking Conference, Sydney (Decem-ber 15–18, 2008); the 13th New Zealand Finance Colloquium,Wellington (February 13–14, 2009); and seminars at theSchool of Accounting and Finance, University of Wollon-gong (May 8, 2009), the School of Investment and Finance atSun Yat-Set University in China (December 29, 2008), andSouth China University of Technology (January 4, 2009). Wewould also like to thank Pam Davy, Michael McCrae, andPing-zhou Liu for their comments on an earlier draft of thispaper. The authors remain responsible for all errors.

NOTES

1. This is because managers could choose directors who are inde-pendent according to regulatory definitions but are not strictlyindependent due to reasons such as social ties.

2. Source: World Federation of Exchanges 2009 MarketHighlights.

3. Extant studies demonstrate that smaller boards are more likelyto eliminate poorly performing CEOs (Certo, Daily, & Dalton,2001).

4. Other IPO survival studies used other techniques in survivalanalysis, e.g., Weibull model (Audretsch & Lehmann, 2004;Woo et al., 1995), log-normal model (Woo et al., 1995), log-logistic (Hensler et al., 1997), and piecewise exponential model(Yang & Sheu, 2006).

5. For the sake of brevity, the exact details of the Cox proportionalhazards model are not presented here. These are available inbasic textbooks and in prior work. The interested reader mayalso refer to Chancharat, Krishnamurti, and Tian (2008).

6. There is no consensus regarding the definition of “indepen-dence” (Brennan & McDermott, 2004; Kang et al., 2007). Previ-ous studies have used the word “outside directors” instead of“independence” to describe directors who are presumed to beindependent from management (Ajinkya, Bhojraj, & Sengupta,2005). Some existing studies simply consider the differencesbetween “executive” and “non-executive” directors (Kanget al., 2007; Lamberto & Rath, 2008).

7. However, the empirical results are mixed. Hensler et al. (1997)find that IPOs with a higher percentage of retained ownershiphave a longer survival period, while Lamberto and Rath (2008)found no relationship between ownership retention and IPOfirm survival.

8. The informational value of the number of risk factors was foundto be significant negatively related to the likelihood of survivalof US IPOs by Hensler et al. (1997) and Bhabra and Pettway(2003).

9. Schultz (1993) found an inverse relationship between theprobability of delisting and firm size.

10. Barry, Muscarella, Peavy, & Vetsuypens (1990) and Megginsonand Weiss (1991) posit that VC-backing certifies the quality ofthe IPO. Venture capitalists specialize in collecting and evalu-ating information of start-up and growth companies. Further-more, they tend to take substantial stakes in the IPO firms andfrequently sit on the boards. Jain and Kini (2000) show that thepresence of venture capitalists improves the survival chances ofIPO firms.

11. Active companies are labeled as survivors. Delisted companiesare non-survivors. We use alternate definitions to categorizenon-survivors in the robustness subsection.

12. We use the default specification for selecting the variablesmethod in PROC PHREG procedure in SAS. The SAS PROCPHREG fits the complete model as specified in the MODEL



Shoaib

Evidenziato

Shoaib

Evidenziato

statement. The covariates are selected from the full model(all variables are included in the model), instead of backward,forward, or stepwise selection procedures.

13. Since we use survival function in the graph as opposed tohazard function in the tables, the sign of the relationship isopposite.

REFERENCES

Adams, R. B. 2009. Asking directors about their dual role. Unpub-lished working paper, University of Queensland.

Adams, R. B. & Ferreira, D. 2007. A theory of friendly boards.Journal of Finance, 62: 217–250.

Ajinkya, B., Bhojraj, S., & Sengupta, P. 2005. The associationbetween outside directors, institutional investors and the prop-erties of management earnings forecasts. Journal of AccountingResearch, 43: 343–376.

Andersen, P. K., Abildstrom, S. Z., & Rosthoj, S. 2002. Competingrisks as a multi-state model. Statistical Methods in MedicalResearch, 11: 203–215.

Anderson, C. A. & Anthony, R. N. 1986. The new corporate direc-tors: Insights for board members and executives. New York:Wiley.

Arthurs, J. D., Hoskisson, R. E., Busenitz, L. W., & Johnson, R. A.2008. Managerial agents watching other agents: Multiple agencyconflicts regarding underpricing in IPO firms. Academy of Man-agement Journal, 51: 277–294.

ASX 2003. Principles of good corporate governance and best prac-tice recommendations. Sydney: ASX Corporate GovernanceCouncil.

Audretsch, D. B. & Lehmann, E. E. 2004. The effects of experience,ownership, and knowledge on IPO survival: Empirical evidencefrom Germany, Discussion Paper, The Entrepreneurship, Growthand Public Policy Group, Jena, Germany.

Bach, S. B. & Smith, A. B. 2007. Are powerful CEOs beneficial topost-IPO survival in high technology industries?: An empiricalinvestigation. The Journal of High Technology ManagementResearch, 18: 31–42.

Bainbridge, S. M. 2002. Why a board? Group decision making incorporate governance. Vanderbilt Law Review, 55: 1–55.

Barry, C. B., Muscarella, C. J., Peavy, J. W., & Vetsuypens, M. R.1990. The role of venture capital in the creation of public compa-nies: Evidence from the going-public process. Journal of Finan-cial Economics, 27: 447–471.

Bhabra, H. S. & Pettway, R. H. 2003. IPO prospectus informa-tion and subsequent performance. Financial Review, 38: 369–397.

Bhagat, S. & Black, B. 2002. The non-correlation between boardindependence and long term firm performance. Journal ofCorporation Law, 27: 231–274.

Bhojraj, S., Lee, C. M. C., & Oler, D. K. 2003. What’s my line? Acomparison of industry classification schemes for capital marketresearch. Journal of Accounting Research, 41: 745–774.

Brennan, N. & McDermott, M. 2004. Alternative perspectives onindependence of directors. Corporate Governance: An Interna-tional Review, 12: 325–336.

Brickley, J. A., Coles, J. L., & Jarrell, G. 1997. Leadership structure:Separating the CEO and chairman of the board. Journal of Cor-porate Finance, 3: 189–220.

Byrd, J. & Hickman, K. 1992. Do outside directors monitor manag-ers? Evidence from tender offer bids. Journal of FinancialEconomics, 32: 195–221.

Carlson, M. A., Fisher, A., & Giammarino, R. 2006. Corporateinvestment and asset price dynamics: Implications for SEO eventstudies and long-run performance. Journal of Finance, 61: 1009–1034.

Certo, S. T., Daily, C. M., & Dalton, D. R. 2001. Signaling firm valuethrough board structure: An investigation of initial publicofferings. Entrepreneurship: Theory & Practice, 26: 33–50.

Chan, L. K. C., Lakonishok, J., & Swaminathan, B. 2007. Industryclassification and return comovement. Financial AnalystsJournal, 63: 56–70.

Chancharat, N., Krishnamurti, C., & Tian, G. G. 2008. When thegoing gets tough: Board capital and survival of new economyIPO firms. 21st Australasian Finance and Banking Conference2008 Paper. Available at SSRN: http://ssrn.com/abstract=1253171

Cheng, S. 2008. Board size and the variability of corporate perfor-mance. Journal of Financial Economics, 87: 157–176.

Cockburn, I. M. & Wagner, S. 2007. Patents and the survival ofinternet-related IPOs, Working Paper, National Bureau of Eco-nomic Research, Cambridge, MA.

Coles, J. L., Daniel, N. D., & Naveen, L. 2008. Boards: Does one sizefit all? Journal of Financial Economics, 87: 329–356.

Dahya, J. 2004. One man two hats – What’s all the commotion!Working Paper, Baruch College.

Daily, C. M. & Dalton, D. R. 1994. Bankruptcy and corporate gov-ernance: The impact of board composition and structure.Academy of Management Journal, 37: 1603–1617.

Dalton, D. R., Daily, C. M., Johnson, J. L., & Ellstrand, A. E. 1999.Number of directors and financial performance: A meta-analysis.Academy of Management Journal, 42: 674–686.

Dimovski, W. & Brooks, R. 2003. Financial characteristics of Aus-tralian initial public offerings from 1994 to 1999. Applied Eco-nomics, 35: 1599–1607.

Dowell, G. W. S., Shackell, M. B., & Stuart, N. V. 2007. The board ofdirectors and firm survival: Evidence from the internet shakeout,Working Paper, Johnson Graduate School of Business, CornellUniversity, New York.

Duchin, R., Matsusaka, J. G., & Ozbas, O. 2010. When are outsidedirectors effective? Journal of Financial Economics, 96: 195–214.

Eisenhardt, K. M. 1989. Making fast strategic decisions in high-velocity environments. Academy of Management Journal, 32:543–577.

Faleye, O. 2007. Does one hat fit all? The case of corporate leader-ship. Journal of Management and Governance, 11: 239–259.

Faleye, O., Hoitash, R., & Hoitash, U. 2011. The costs of intenseboard monitoring. Journal of Financial Economics, 101: 160–181.

Fama, E. & Jensen, M. C. 1983. Separation of ownership and control.Journal of Law and Economics, 26: 327–349.

Finkelstein, S. & D’Aveni, R. A. 1994. CEO duality as a double-edged sword: How boards of directors balance entrenchmentavoidance and unity of command. Academy of ManagementJournal, 37: 1079–1108.

Fischer, H. M. & Pollock, T. G. 2004. Effects of social capital andpower on surviving transformational change: The case of initialpublic offerings. Academy of Management Journal, 47: 463–481.

Gaver, J. J. & Gaver, K. M. 1993. Additional evidence on the asso-ciation between the investment opportunity set and corporatefinancing, dividend, and compensation policies. Journal ofAccounting and Economics, 16: 125–160.

Goktan, M. S., Kieschnick, R., & Moussawi, R. 2006. Corporategovernance and corporate survival, Working Paper, Universityof Texas at Dallas.

Gompers, P. A. 1996. Grandstanding in the venture capital indus-try. Journal of Financial Economics, 42: 133–156.

Goodstein, J., Gautam, K., & Boeker, W. 1994. Research notes andcommunication: The effects of board size and diversity onstrategic change. Strategic Management Journal, 15: 241–250.

Harris, M. & Raviv, A. 2008. A theory of board control and size.Review of Financial Studies, 21: 1797–1832.



Hensler, D. A., Rutherford, R. C., & Springer, T. M. 1997. Thesurvival of initial public offerings in the aftermarket. Journal ofFinancial Research, 20: 93–110.

Hermalin, B. & Weisbach, M. 1998. Endogenously chosen boards ofdirectors and their monitoring of the CEO. The American Eco-nomic Review, 88: 96–118.

Hermalin, B. & Weisbach, M. 2003. Board of directors as an endog-enously determined institution. Federal Reserve Bank of NewYork Economic Policy Review, 9: 1–20.

Ho, B., Taher, M., Lee, R., & Fargher, N. L. 2001. Market sentiment,media hype and the underpricing of initial public offerings: Thecase of Australian technology IPOs, Working Paper, School ofAccounting, University of New South Wales.

Holmstrom, B. 2005. Pay without performance and the managerialpower hypothesis: A comment. Journal of Corporation Law, 30:703–713.

How, J. C. Y., Izan, H. Y., & Monroe, G. S. 1995. Differential infor-mation and the underpricing of initial public offerings: Austra-lian evidence. Accounting & Finance, 35: 87–105.

Jain, B. A. & Kini, O. 1999. The life cycle of initial public offeringfirms. Journal of Business Finance & Accounting, 26: 1281–1307.

Jain, B. A. & Kini, O. 2000. Does the presence of venture capitalistsimprove the survival profile of IPO firms? Journal of BusinessFinance & Accounting, 27: 1139–1176.

Jensen, M. C. 1986. Agency costs of free cash flow, corporate financeand takeovers. American Economic Review, 76: 323–329.

Jensen, M. C. 1993. The modern industrial revolution, exit, and thefailure of internal control systems. The Journal of Finance, 48:831–880.

Jensen, M. C. & Meckling, W. H. 1976. Theory of the firm: Mana-gerial behavior, agency costs and ownership structure. Journalof Financial Economics, 3: 305–360.

Johnson, J. L., Daily, C. M., & Ellstrand, A. E. 1996. Board of direc-tors: A review and research agenda. Journal of Management, 22:409–438.

Judge, W. Q. & Miller, A. 1991. Antecedents and outcomes ofdecision speed in different environmental contexts. Academy ofManagement Journal, 34: 449–463.

Judge, W. Q. & Zeithaml, C. P. 1992. Institutional and strategicchoice perspectives on board involvement in the strategicdecision process. Academy of Management Journal, 35: 766–794.

Kang, H., Cheng, M., & Gray, S. J. 2007. Corporate governance andboard composition: Diversity and independence of Australianboards. Corporate Governance: An International Review, 15:194–207.

Kauffman, R. J. & Wang, B. 2001. The success and failure ofdotcoms: A multi-method survival analysis. Minneapolis: Infor-mation and Decision Sciences, Carlson School of Management,University of Minnesota.

Kauffman, R. J. & Wang, B. 2007. Duration of internet firms: Asemiparametric Cox and Bayesian survival analysis, WorkingPaper, Carlson School of Management, University of Minnesota.

Kroll, M., Walters, B. A., & Le, S. A. 2007. The impact of boardcomposition and top management team ownership structure onpost-IPO performance in young entrepreneurial firms. Academyof Management Journal, 50: 1198–1216.

Kumar, P. & Sivaramakrishnan, K. 2008. Who monitors the monitor?The effect of board independence on executive compensationand firm value. Review of Financial Studies, 21: 1371–1401.

Lamberto, A. P. & Rath, S. 2008. The survival of initial publicofferings in Australia, Working Paper, Curtin University ofTechnology.

Lee, T.-S. & Yeh, Y.-H. 2004. Corporate governance and financialdistress: Evidence from Taiwan. Corporate Governance: AnInternational Review, 12: 378–388.

Lehn, K., Patro, S., & Zhao, M. 2009. Determinants of the size andstructure of corporate boards: 1935–2000. Financial ManagementJournal, 38: 747–780.

Leland, H. E. & Pyle, D. H. 1977. Informational asymmetries, finan-cial structure, and financial intermediation. Journal of Finance,32: 371–387.

Lin, Y. C., Yeh, K. S., & Li, S. 2011. Change of governance in theorganization value chain: The case of high-tech industries inTaiwan. Corporate Governance: An International Review, 19:169–182.

Linck, J. S., Netter, J., & Yang, T. 2008. The determinants of boardstructure. Journal of Financial Economics, 87: 308–328.

Lipton, M. & Lorsch, J. 1992. A modest proposal for improvedcorporate governance. Business Lawyer, 1: 59–77.

Megginson, W. L. & Weiss, K. A. 1991. Venture capitalist certifica-tion in initial public offerings. Journal of Finance, 46: 879–903.

Myers, S. 1977. Determinants of corporate borrowing. Journal ofFinancial Economics, 5: 147–175.

OECD 2001. The new economy: Beyond the hype. Final reporton the OECD Growth Project, Organisation for Economic Co-operation and Development, Paris.

Prantl, S. 2003. Bankruptcy and voluntary liquidation: Evidencefor new firms in East and West Germany after unification, Dis-cussion paper no. 03-72, ZEW, Centre for European EconomicResearch, London.

Raheja, C. 2005. Determinants of board size and composition: Atheory of corporate boards. Journal of Financial and Quantita-tive Analysis, 40: 283–306.

Rechner, P. L. & Dalton, D. R. 1991. CEO duality and organizationalperformance: A longitudinal analysis. Strategic ManagementJournal, 12: 155–160.

Ritter, J. R. 1991. The long-run performance of initial public offer-ings. Journal of Finance, 46: 3–27.

Romano, R. 2005. The Sarbanes-Oxley Act and the making of quackcorporate governance. Yale Law Review, 114: 1521–1611.

Sah, R. K. & Stiglitz, J. 1986. The architecture of economic systems:Hierarchies and polyarchies. American Economic Review, 76:716–727.

Sah, R. K. & Stiglitz, J. 1991. The quality of managers in centrali-zed versus decentralized organizations. Quarterly Journal ofEconomics, 106: 289–295.

Sanders, W. M. & Boivie, S. 2004. Sorting things out: Valuation ofnew firms in uncertain markets. Strategic Management Journal,25: 167–186.

Schultz, P. 1993. Unit initial public offerings: A form of stagedfinancing. Journal of Financial Economics, 34: 199–229.

Shumway, T. 2001. Forecasting bankruptcy more accurately: Asimple hazard model. Journal of Business, 74: 101–124.

Smith, C. & Watts, R. 1992. The investment opportunity set andcorporate financing, dividend, and compensation policies.Journal of Financial Economics, 32: 263–292.

Song, F. & Thakor, A. 2006. Information control, career concerns,and corporate governance. Journal of Finance, 61: 1845–1896.

Standard and Poor’s 2002. Understanding GICS. New York: Stan-dard and Poor’s.

Stoeberl, P. A. & Sherony, B. C. 1985. Board efficiency and effec-tiveness. In E. Mattar & M. Balls (Eds.), Handbook for corporatedirectors: 12.1–12.10. New York: McGraw-Hill.

Welbourne, T. M. & Andrews, A. O. 1996. Predicting the perfor-mance of initial public offerings: Should human resource man-agement be in the equation? Academy of Management Journal,39: 891–919.

Wilbon, A. D. 2002. Predicting survival of high technology initialpublic offering firms. The Journal of High Technology Manage-ment Research, 13: 127–141.



Woo, L.-A. E., Jeffrey, A. M., & Lange, H. P. 1995. An examinationof survival rates of newly listed firms in Australia. Research inFinance, 12: 217–229.

Yang, C.-Y. & Sheu, H.-J. 2006. Managerial ownership structure andIPO survivability. Journal of Management and Governance, 10:59–75.

Yermack, D. 1996. Higher market valuation of companies with asmall board of directors. Journal of Financial Economics, 40:185–212.

Dr Nongnit Chancharat is Lecturer in Finance and Head ofFinance Discipline, Faculty of Management Science, KhonKaen University, Thailand. She received her PhD (Finance)from the University of Wollongong, NSW, Australia, in 2008.Her thesis is entitled: “An Empirical Analysis of FinanciallyDistressed Australian Companies: The Application of Sur-vival Analysis.” She received her M.Sc. from the NationalInstitution of Development and Administration, Thailand in2001 and B.A. (First Class Honors) from Khon Kaen Univer-sity, Thailand in 1999. Her research interests include corpo-rate finance, corporate governance, and quantitative analysisin finance and wealth management.

Professor Chandrasekhar Krishnamurti is currently theProfessor, Head of Finance Discipline and Director of

Research at the University of Southern Queensland. He isalso the Vice-President (Program) of the Asian Finance Asso-ciation. He has published the following edited volumes:Mergers acquisitions, and corporate restructuring, Advanced cor-porate finance, and Investment management. He has publishedhis research in the Journal of Banking and Finance, FinancialManagement, Journal of Financial Research, International Reviewof Economics and Finance, Pacific-Basin Finance Journal, Reviewof Quantitative Finance and Accounting, and Journal of Multi-national Financial Management. He has won seven best paperawards at international conferences.

Dr Gary Tian is an Associate Professor in Finance in theSchool of Accounting and Finance at the University of Wol-longong, NSW, Australia. He is the Head of PostgraduateStudies and also the Director of the Chinese CommerceResearch Centre. He supervises eight PhD students in theareas of corporate finance, CEO compensation, and marketmicrostructure, focused mainly on Chinese financialmarkets. He has published 38 refereed articles in journalssuch as Journal of Corporate Finance, Corporate Governance: anInternational Review, Journal of Asian Pacific Economy, Multi-national Finance Journal, Review of Quantitative Finance andAccounting, and Accounting and Finance.



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Board Structure and Survival of New Economy