Does legal registration help or hurt? The effect of government … · 2019-07-08 · nascent...

Does legal registration help or hurt? The effectof government corruption on resource acquisitionby nascent ventures in an emerging economy

Li Tian1& Jing Yu Yang2

& Jiatao Li3

# Springer Science+Business Media, LLC, part of Springer Nature 2019

AbstractThis study examines the effects of pervasive and arbitrary corruption on entrepreneurs’resource acquisition during their new venture creation stages in an emerging economy.It also investigates how legal registration may alter the effects of the two dimensions ofgovernment corruption. Our analysis of 160 nascent entrepreneurs in China between2009 and 2011 shows that pervasive and arbitrary corruption both hamper resourceacquisition by nascent ventures. We highlight that the negative effects of corruptionvary among nascent ventures, and the effects are dependent on the legal status ofnascent ventures. Legal registration helps to reduce the negative effect of arbitrarycorruption, but does not reduce the negative effect of pervasive corruption.

Keywords Pervasiveness . Arbitrariness . Corruption . Nascent entrepreneurs . Resourceacquisition . Legal registration

Government corruption, broadly construed as a misuse of public power for private gain(Nye, 1967), has important implications for the emergence of new firms and firmgrowth (Dreher & Gassebner, 2013; Wei, 1997). Prior literature generally offers two

Asia Pacific Journal of Managementhttps://doi.org/10.1007/s10490-019-09673-1

* Li [email protected]

Jing Yu [email protected]

Jiatao [email protected]

1 Department of Management, School of Business, Center of Entrepreneurship Research of NankaiUniversity, Nankai University, #94 Weijin Road, Nankai District, Tianjin 300071, China

2 Department of International Business, School of Business, University of Sydney, Sydney, Australia3 Department of Management, Center for Business Strategy and Innovation, Hong Kong University

of Science and Technology, Clear Water Bay, HKSAR, Hongkong

http://crossmark.crossref.org/dialog/?doi=10.1007/s10490-019-09673-1&domain=pdf

http://orcid.org/0000-0003-1001-3895

mailto:[email protected]

views of corruption, one clearly negative and the other more positive. The negativeview suggests that corruption contaminates business environments by setting barriers,distorting resource allocation, and undermining the foundation of institutional trust,thereby inhibiting new venture creation and business growth (e.g., Anokhin & Schulze,2009; Bowen & Clercq, 2008; Dyck & Ovaska, 2011).

Other scholars take a different view, seeing corruption in a less negative and even apositive light. They argue that in a less-than-ideal world, corruption can alleviate theproblems caused by poorly functioning government institutions (Huntington, 1968;Kaufmann, 1997) and circumvent otherwise cumbersome bureaucracies and rigidgovernment regulations (e.g., Dreher & Gassebner, 2013; Krammer, 2019; Vial &Hanoteau, 2010). It is noteworthy that this relatively positive perspective of corruptionis largely contingent on the quality of government institutions and suggests thatcorruption may improve the efficiency of firms and benefit them only in poorlygoverned economies (Méon & Weill, 2010). Not surprisingly, most macro-level studieson government corruption show that government corruption generally has negativeconsequences (Galang, 2012; Mauro, 1998; Shleifer & Vishny, 1993).

By contrast, recent research at the firm level points to the heterogeneous impacts ofgovernment corruption on individual firms and emphasizes that not all firms in poorlygoverned economies suffer equally from government corruption; some can cope withpolitical deficiencies more effectively than others (Krammer, 2019; Zhou & Peng,2012). Therefore, some firms suffer less and can even benefit from governmentcorruption (Galang, 2012; Zhou & Peng, 2012).

Nevertheless, prior studies on corruption at both the macro and firm levels haveprimarily examined the impacts of government corruption on established firms. Littleattention has been paid to understanding the impact of corruption on ventures that arestill at the in-creation stage, often termed nascent ventures (Reynolds & Miller, 1992).The in-creation stage refers to the new venture creation stage where entrepreneursinitiate “serious activities that are intended to culminate in a viable business start-up buthasn’t succeeded yet” (Aldrich, 1999: 777). During the in-creation stage of newventures, many entrepreneurs fail, with only a small proportion of their nascentventures able to turn into fully-fledged firms in the end. Focusing exclusively onestablished firms, previous research examining the effect of corruption may thus besubject to sample selection bias, and the effect of corruption they found may beunderestimated because the previous research excluded from their final samples foranalysis those nascent ventures which failed during the in-creation stage. Therefore, itis important to find out whether and how government corruption affects nascentventures that are still at the in-creation stage.

During the in-creation stage, nascent ventures must decide when to undertakedifferent but necessary organizational activities, such as investing in researchand development (R&D), developing products and business models, hiringemployees, seeking funds, gathering customer information, and establishinglegal entities (Carter, Gartner, & Reynolds, 1996; Gartner, 1985; Tornikoski &Newbert, 2007). Legal registration is an important activity as it changes thelegal status of a nascent venture and confers the venture with sociopoliticallegitimacy that increases the venture’s access to a variety of resources, includ-ing financial capital, human capital, raw materials, and customers (Assenova &Sorenson, 2017).

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Recent studies on informal entrepreneurship have suggested that weak and poorlyfunctioning institutions, such as corrupt governments, can reduce the value of legalregistration to entrepreneurs (Assenova & Sorenson, 2017), because remaining infor-mal can help to avoid the costs associated with interacting with corrupt governmentsand their agents (e.g., Siqueira, Webb, & Bruton, 2016; Tonoyan, Strohmeyer, Habib,& Perlitz, 2010; Williams, Martinez-Perez, & Kedir, 2016). Yet this new subdisciplineof the entrepreneurship literature has been silent about the value of legal registration fornascent ventures in coping with the influence of government corruption. Consideringthat government corruption is largely unavoidable in an emerging economy(Transparency International, 2018), an important question for nascent ventures toconsider during their in-creation stage is: Does (non)registration help or hurt nascentventures in coping with government corruption?

To address the question, we need to examine the moderating role of formal, legalregistration on the (negative) effects of government corruption on entrepreneurship.Prior research on government corruption has been unable to examine this issue as it hasprimarily focused on established firms, which by definition are legally registered firms.Prior studies on informal entrepreneurship have unfortunately addressed a related butdifferent issue—the implications of government corruption on the value of legalregistration to entrepreneurs (Assenova & Sorenson, 2017). These studies focused onthe moderating role of government corruption, and failed to consider that governmentcorruption has different dimensions (Rodriguez, Uhlenbruck, & Eden, 2005).

In this paper, we first follow the recent development in the corruption literature (Lee& Oh, 2007; Rodriguez et al., 2005; Uhlenbruck, Rodriguez, Doh, & Eden, 2006) todifferentiate between two dimensions of government corruption: pervasiveness andarbitrariness. Then we examine to what extent the two dimensions of corruption canhamper resource acquisition by nascent ventures. Lastly, we investigate whether andhow legal registration strengthens or attenuates the negative effects of pervasive andarbitrary corruption.

We test the ideas using a unique dataset collected from a survey of 160nascent ventures from eight cities in China between 2009 and 2011. China isan appropriate context as it is a large, emerging economy with substantialvariation in government corruption across regions in the country (Fan, Wang,& Zhu, 2011). The results of our analyses show that both pervasive andarbitrary corruption hamper resource acquisition by nascent ventures. Registerednascent ventures are better off than unregistered ventures when facing greaterarbitrariness in corruption, but are similar to unregistered ventures under theinfluence of greater pervasiveness in corruption.

The contributions of this paper are twofold. First, our findings corroborate thenegative view of government corruption and extend the corruption literature to thein-creation stage of new ventures. Second, our paper highlights that nascent venturescan use legal registration as a strategic legitimation activity (Tornikoski & Newbert,2007; Zimmerman & Zeitz, 2002) to cope with the uncertainty derived from thearbitrariness of corruption, but legal registration is less effective in reducing the costsassociated with the pervasiveness of corruption. As such, our paper extends the existingresearch on informal entrepreneurship by highlighting that overall, being formal, withlegal registration, can still make nascent entrepreneurs better off, especially in copingwith the arbitrary government corruption.

Does legal registration help or hurt? The effect of government...

Theoretical background

Resource acquisition by nascent ventures in an emerging economy

Creating a new venture is a complex and idiosyncratic process that generally starts withan entrepreneur’s aspiration and involves sourcing and merging resources that anentrepreneur does not necessarily control (Stevenson & Jarillo, 1990). Because nascentventures are deficient in their initial resource endowments, acquiring needed resourcesis critical to their development and survival (Delmar & Shane, 2004). When entrepre-neurs decide to launch a new venture, their failure to obtain necessary resources canstifle any attempts, regardless of how sound the business plan may be. Resourceacquisition is important and recognized as a major barrier for entrepreneurs (Brush,Greene, & Hart, 2001; Zimmerman & Zeitz, 2002), especially in an emerging econo-my, such as China, where the government often controls major resources (Nee, 1992).Also, government delegates, such as banks, tend to favor state-owned enterprises orlarge firms over nascent and private ventures (Nee, 1992).

In addition, market intermediaries, such as financial institutions, credibility en-hancers, information analyzers and advisers, and strategic factor markets, are largelyunderdeveloped or absent in emerging economies. These absences are called “institu-tional voids” (Khanna & Palepu, 1997). These problems in an emerging economy makeit difficult for entrepreneurs to obtain necessary resources—such as personnel, com-mercial credit, and raw materials—via the market (e.g., Assenova & Sorenson, 2017;Kistruck, Webb, Sutter, & Bailey, 2015).

Government corruption increases the difficulty of resource acquisition by nascentventures

When trading resources, entrepreneurs and external resource providers are subject tothe integrity and reliability of laws, courts, regulations, and government policies(Letaifa & Goglio-Primard, 2016; North, 1990). As a result, the quality of a govern-ment system should influence whether and how entrepreneurs can effectively andefficiently acquire resources from government and from other resource providers.

Corruption indicates the poor quality of government systems (Méon & Sekkat,2005). The transitional nature and fast economic development of an emerging economyprovides more opportunities for government officials to corrupt because it is less clearwhat rules and regulations must apply (Cuervo-Cazurra, 2008). Management scholarshave recently identified two key dimensions of corruption: pervasiveness and arbitrar-iness (Rodriguez et al., 2005; Uhlenbruck et al., 2006). Pervasiveness refers to “theaverage likelihood of encountering corruption in normal interactions with governmentofficials” (Rodriguez et al., 2005, p.385). High pervasiveness implies that a substantialproportion of a firm’s interactions with government officials will involve corruption.The second dimension, arbitrariness, describes the level of uncertainty and ambiguityassociated with corrupt transactions. The arbitrariness of corruption can be independentof its pervasiveness (Uhlenbruck et al., 2006). If the arbitrariness of corruption is low,payments to corrupt officials function more like explicit taxes (Wei, 1997).

Both the pervasiveness and arbitrariness of corruption undermine people’s generaltrust in government institutions to fairly and impartially govern resource transactions

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(Anokhin & Schulze, 2009; Hakhverdian & Mayne, 2012). In the face of corruptgovernments, entrepreneurs often need to bribe to obtain needed resources. In addition,entrepreneurs also face the unfair results of illicit transactions from collusions betweencorrupt public officials and other firms (Sequeira & Djankov, 2014). Even worse,entrepreneurs and resource providers may lose trust in government institutions’ abilityto fairly and impartially regulate the resource transactions between them. This alsoimposes difficulties on entrepreneurs in acquiring resources from nongovernmentresource providers.

The role of legal registration

Establishing a legal entity is an important step that must be taken during a newventure’s in-creation stage (Gartner, 1985). Yet in an emerging economy withweak and dysfunctional government institutions, legal registration tends to havetwo-sided effects for entrepreneurs and their ventures (e.g., Kistruck et al.,2015; Williams et al., 2016).

On the positive side, legal registration confers a nascent venture with legalstatus defined by the regulatory institutions (Delmar & Shane, 2004; Dowling& Pfeffer, 1975). Having legal status is an attribute used to access sociopolit-ical legitimacy—the extent to which the public and resource providers regard anascent venture as an appropriate and reliable exchange partner (Aldrich &Fiol, 1994; Meyer & Rowan, 1977). With such sociopolitical legitimacy, regis-tered ventures are more likely to access resources, such as financial capital,labor, and materials, from governments and nongovernment resource holders(Delmar & Shane, 2004).

Without legal status, nascent ventures are largely restricted or excluded fromaccessing critical resources or services from governments. For instance, unreg-istered ventures are unable to participate in government training programs,which can be a key source of information and knowledge for nascent venturesseeking to increase their efficiency or pursue growth opportunities at low cost(McPherson & Liedholm, 1996). Investors and lenders tend to perceive unreg-istered nascent ventures as riskier than registered ones and are less likely toinvest money in them (Wellalage & Locke, 2016). Potential employees mayavoid unregistered ventures as employers (Rand & Torm, 2012). Potentialcustomers may worry that unregistered firms produce and sell goods inferiorto those of formal ones (Baum & Oliver, 1991). As such, the sociopoliticallegitimacy that legal registration confers should benefit nascent ventures. In-deed, Delmar and Shane (2004) found that in Sweden, new ventures establish-ing a legal entity are 42% less likely to fail than those that do not establish alegal entity.

On the downside, the time and effort spent in formally registering a businessin an emerging economy is significant (de Soto, 1989; Grosh & Somolekae,1996). Also legally registered ventures must comply with regulatory require-ments, such as paying tax and applying for licenses, which are often overlyburdensome in an emerging economy (de Soto, 1989; Siqueira et al., 2016;Tian, Yang, & Wei, 2019). For instance, Maloney (2004) showed that theinstitutional benefits of operating a registered business in Latin American


countries are much less than in a developed market. Analyzing data from 127countries, Williams et al. (2016) found that ventures that delay registering canavoid the formal institutional costs of registration, such as paying direct andindirect taxes and abiding by burdensome regulations, as well as avoiding theadditional ancillary costs that corrupt government officials often impose onformal enterprises.

Prior studies have shown that government corruption, as a reflection ofdysfunctional formal institutions in an emerging economy, can reduce the valueof legal registration to entrepreneurs (Assenova & Sorenson, 2017). Rather thanfocusing on the implications of government corruption for the value of legalregistration to entrepreneurs, which prior studies have done, our study focuseson the other side of the story: the role of (non)registration on the negativeeffects of government corruption, including both pervasive and arbitrary cor-ruption, on nascent ventures. This issue has received little attention, but is animportant one. Examining the issue would inform us whether nascent venturesin a corrupt emerging economy can use legal registration, as a strategy, toreduce the negative effects of the different dimensions of government corrup-tion within an emerging economy.

Hypothesis development

Pervasive corruption increases the difficulty of resource acquisition by nascentventures

When corruption is pervasive, corrupt transactions often become an institutionalizedpart of commercial activity. In such context, entrepreneurs are likely to encounterextortion when they interact with government officials (Tonoyan et al., 2010) andshould expect them to ask for bribes frequently. Even worse, such requests are often notone-off events and may occur throughout the whole process of new venture creation.Therefore, pervasive corruption tends to substantially increase nascent ventures’ costswhen they interact with corrupt government officials to obtain government-controlledresources.

Moreover, we argue that the increased costs of dealing with corrupt govern-ment officials ultimately spill over to the transactions between entrepreneursand other external resource providers. In analyzing 64 nations, Anokhin andSchulze (2009) found that when corruption prevails, entrepreneurs face in-creased costs and risk because those involved in their value chain becomemore opportunistic and appropriate the benefits to which the prospective entre-preneurs are entitled.

Taking the arguments together, we reason that pervasive government corrup-tion increases numerous direct and indirect costs for nascent ventures. Thedirect costs mainly include bribes and queuing costs (Fisman & Svensson,2007). The indirect costs, which result from distrust of government institutions,mainly pertain to the transaction and monitoring costs paid by entrepreneurs tothe resource providers to curb their opportunistic behaviors (Anokhin &Schulze, 2009; Hakhverdian & Mayne, 2012). For instance, Kraar (1995) found

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that (pervasive) corruption generally adds 5% to the cost of conducting businessin Asia. Economists also found that (pervasive) corruption acts as a tax onforeign direct investments and may increase the tax paid by over 20%, increasethe operating costs of corporations by 10%–20%, and reduce the profits byapproximately one-third (e.g., Tanzi & Davoodi, 1997). It is generally hard fornascent ventures to bear such additional costs, as they usually have limitedfunding in the in-creation stage. We thus propose:

Hypothesis 1: The greater the pervasive corruption, the more difficult it will be fornascent ventures to acquire resources during their in-creation stages.

Arbitrary corruption increases the difficulty of resource acquisition by nascentventures

Other than the costs associated with pervasive corruption, the pronouncednegative effects of government corruption can also stem from the ambiguityand uncertainty (i.e., arbitrariness) of corrupt transactions. When corruption isarbitrary, government regulations, rules, and policies are subject to capriciousinterpretation or tenuous jurisdiction by governments. A briber may be uncer-tain about whom to bribe, how to bribe, and the minimum bribe required toachieve a desired outcome (Uhlenbruck et al., 2006). Such uncertainty increasesthe difficulty that bribers face in predicting the outcomes of their bribery,resulting in ineffective bribes (Ahlstrom & Bruton, 2001; Méon & Sekkat,2005). In response, nascent entrepreneurs need to invest additional time andeffort in monitoring the uncertainty in their corrupt transactions with govern-ment officials to achieve their desired resource outcomes.

Similarly, such uncertainty in dealing with corrupt government officials and theiragents can contaminate transactions between nascent ventures and other resourceproviders. The arbitrariness of corruption tends to damage the trust of both entrepre-neurs and resource providers in the integrity and reliability of government systems(Hakhverdian & Mayne, 2012), and leads to resource providers’ increased opportunis-tic behavior, such as misappropriation of the benefits to which nascent ventures areentitled (Anokhin & Schulze, 2009). We thus propose:

Hypothesis 2: The greater the arbitrary corruption, the more difficult it will be fornascent ventures to acquire resources during their in-creation stages.

The moderating effects of legal registration

Furthermore, we examine whether registered and unregistered nascent ventures areequally subject to the negative effects of pervasive and arbitrary government corruptionin terms of resource acquisition. Legal registration indicates a legitimization attempt bynascent entrepreneurs in the in-creation process of their new ventures. We argue thesociopolitical legitimacy obtained from registering with the corrupt government maystill allow nascent ventures to cope better with the arbitrariness of government corrup-tion in terms of resource acquisition, but they may cope less well with the pervasive-ness of corruption.


Legal registration moderates the negative effect of pervasive corruption

Pervasiveness in government corruption increases the costs that nascent ven-tures must pay to obtain resources from corrupt government officials and otherresource holders. We argue such increase in costs differs between registered andunregistered ventures. Specifically, pervasiveness of corruption will increaseresource acquisition costs more for registered ventures than for unregisteredventures.

By avoiding registration-induced compliance activities, unregistered nascentventures do not need to acquire as many resources from governments asregistered ventures do; they can thus avoid paying the increasing amount ofbribes that corrupt public officials impose on registered ventures due to thepervasiveness of corruption (Friedman, Johnson, Kaufmann, & Zoido-Lobaton,2000; Williams et al., 2016). However, because governments in an emergingeconomy often control some exclusive resources necessary for the growth ofnew ventures, unregistered nascent ventures must interact with governments andtheir agents to obtain these otherwise unavailable resources. When the perva-siveness of corruption is low, unregistered ventures will find it extremelydifficult to obtain any resources from governments even if they are willing topay bribes. The increasing pervasiveness of corruption provides opportunitiesfor unregistered nascent ventures to obtain the needed resources from govern-ments; although when this happens, the nascent ventures, due to their infor-mality, perhaps need to pay higher bribes than their registered peers to acquirethe same amount of resources controlled by the governments and their agents(e.g., de Soto, 2000). Hence, overall, we expect that unregistered venturesgenerally are better off, while registered ones are worse off in acquiringresources from governments with higher pervasiveness.

When nascent ventures acquire resources from nongovernment resourceholders, we argue that pervasiveness of government corruption increases thecost more substantially for registered than for unregistered ventures. This isbecause pervasiveness of government corruption undermines people’s trust ingovernment institutions and in their ability to regulate resource transactionsimpartially and effectively (Djankov, La Porta, Lopez-de-Silanes, & Shleifer,2002). As a result of this undermined trust, nascent ventures need to payadditional costs to monitor and avoid the opportunistic and shirking behaviorsof nongovernment resource providers when transacting with them. We arguesuch cost increases due to the higher pervasiveness of government corruptionare greater for registered nascent ventures than for unregistered ones who haveto pay the added costs anyway due to their informality even when pervasive-ness is low. Therefore, legal status becomes less helpful for nascent ventures incoping with greater pervasiveness in corruption. When the pervasiveness incorruption is high, registered ventures are likely to pay more additional coststhat are nearly what unregistered ventures need to pay to monitor and avoid theopportunistic behaviors and misappropriation of nongovernment resource pro-viders. In other words, greater pervasiveness of government corruption is moredeleterious for registered ventures than for unregistered ones when they transactwith other resource providers.

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Combining the arguments above, we expect that, overall, legal registration exacer-bates the negative effect of pervasive corruption on nascent ventures’ resource acqui-sition from both governments and nongovernment resource holders.

Hypothesis 3a: Legal registration will strengthen the positive relationship betweenpervasive corruption and the difficulty of nascent ventures in resource acquisition.

Legal registration moderates the negative effect of arbitrary corruption

As discussed, arbitrariness in government corruption mainly increases the uncertaintythat nascent ventures face in obtaining resources from governments and other resourceholders. We argue such uncertainty is more deleterious for unregistered nascentventures than for registered ones.

When a nascent venture acquires resources directly from governments, legalstatus is useful as it can help to reduce the uncertainty of arbitrary corruption.We argue the sociopolitical legitimacy which legal status confers can protectnascent ventures against the abuse of corrupt officials in a corrupt governmentsystem (Ahlstrom & Bruton, 2001), although such protection may becomeincreasingly weaker as the arbitrariness in corruption increases. Governmentofficials face a higher risk when they fail to deliver promised outcomes incorrupt transactions or try to abuse the registered nascent ventures. As such, thesame level of arbitrariness in corruption is more deleterious for unregisterednascent ventures than registered ones as they acquire resources fromgovernments.

It is important to note that although unregistered nascent ventures can avoidpaying bribes and save on some of the costs that corrupt government officialsimpose on registered ventures, they are unlikely to avoid the uncertainty thatarbitrariness of corruption induces. Such uncertainty remains whenever nascentventures must acquire resources from corrupt government officials. Therefore,higher arbitrariness in corruption tends to incur a greater increase in theuncertainty for unregistered ventures than for registered ones in their resourceacquisition from governments.

Similarly when nascent ventures acquire resources from nongovernmentresource providers, higher arbitrariness in government corruption adds moreuncertainty for unregistered nascent ventures than for registered ones. Arbitrar-iness in government corruption undermines the trust of entrepreneurs and otherresource holders in government institutions, and imposes additional uncertaintyon nascent ventures as it stimulates opportunistic and shirking behaviors amongresource providers that transact with nascent ventures. Legal status may stillhelp to reduce such uncertainty by safeguarding against other resource pro-viders’ opportunistic and shirking behaviors (Kistruck et al., 2015), even thoughthe safeguard effect of legal status weakens as arbitrariness increases. Yetwithout such a safeguard, unregistered ventures face greater risks of beingabused by other resource providers. Therefore, we argue that the same levelof arbitrariness in corruption is more deleterious for unregistered nascent ven-tures than for registered ones as they acquire resources from other resourceproviders.


Taking the above arguments together, we construe that the sociopolitical legitimacyconferred via legal registration can help nascent ventures to curb the uncertainty andambiguity derived from arbitrary corruption. Therefore, we hypothesize:

Hypothesis 3b: Legal registration will weaken the positive relationship betweenarbitrary corruption and the difficulty of nascent ventures in resource acquisition.

Methods

Data and sample

Data from the Chinese Panel Study of Entrepreneurial Dynamics (CPSED) wereanalyzed to test these hypotheses. The study is part of an international project organizedby Babson College (Reynolds & Miller, 1992) to elucidate the new venture-creationprocess. CPSED used stratified sampling and a random digit dialing method to selectnascent entrepreneurs aged 18 or above and tracked them in three waves over a periodof 3 years as they created new ventures. CPSED divided China into four regionsaccording to the intensity of entrepreneurial activity, as reported in the Global Entre-preneurship Monitor report on China in 2008 (Gao, Li, & Jiang, 2008). Beijing,Tianjin, Hangzhou, and Guangzhou were the cities surveyed in the eastern region.The midland region was represented by Wuhan and the northeastern region by Shen-yang. The western region included Chengdu and Xi’an. In each city, CPSED set asampling quota based on the city population and selected nascent entrepreneurs asrespondents. Computer-aided telephone interviews were conducted.

Consistent with the methods of PSED research conducted in the United States(Reynolds & Miller, 1992),1 the CPSED project considered an individual as a nascententrepreneur 1) if he/she had taken actions to create a new venture in the previous12 months; 2) if he/she owned a new venture as the business owner; or 3) if anentrepreneurial activity had begun, even if no sales revenue had yet been earned atthe time of the first round of the survey. After a pre-test of the Chinese version of theinstrument, the first wave of the CPSED survey was conducted simultaneously in theeight cities in the first half of 2009. We contacted a total of 69,990 households byphone, and interviewed 22,045 people (a response rate of 31.5%), from which 974nascent entrepreneurs were identified. A total of 601 nascent entrepreneurs finished thefirst wave of computer-aided telephone interviews, giving a response rate of 61.7%.The second wave of tracking surveys was conducted from July to September 2010 andsuccessfully tracked 321 of the 601 original respondents (53.4%).

In the second wave, the 321 respondents were divided into three cohorts based onthe progress of their new venture creation. At that point, 175 cases were still in thegestation period, 29 cases had become operational ventures, and 117 endeavors hadalready been abandoned. The gestating and operating cohorts were used for the base

1 The U.S. PSED and the new five countries’ harmonized dataset, including CSPED is available athttp://www.psed.isr.umich.edu/psed/home

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http://www.psed.isr.umich.edu/psed/home

sample of 204 cases. After eliminating cases with missing data, 160 cases remained inthe final sample for analysis. The potential sample bias attributed to missing cases isdiscussed in a later section.

Data attrition and weighting

Attrition of respondents is unavoidable in any longitudinal research and it may yieldspurious findings (Greenland, 1977). The U.S. PSED reported a 20% attrition rate in itssecond wave of interviews (Reynolds & Curtin, 2011). The high attrition rate (280 of601, 46%) in CPSED was not surprising because of the generally low response rates inemerging economies (Zhang, Yang, Tang, Au, & Xue, 2013). Among the 280 drop-outs in the second wave, 103 could not be located and 177 either refused to be re-interviewed or terminated the second interview early.

One common method to deal with the attrition problem is to examine the differencesbetween the respondents who remained in the surveys and those who dropped out(Schafer & Graham, 2002). Specifically, we conducted an ANOVA analysis to comparewhether the entrepreneurs included in our final sample were different from thoseentrepreneurs who dropped out of the second wave survey. Entrepreneurs’ personalcharacteristics—such as gender, age, education and motivation to enter entrepreneur-ship, along with attributes of their new ventures, such as number of activities finishedand initial performance, were compared. The results of the tests suggest an agedifference between the nascent entrepreneurs who completed the second survey andthose who did not (F = 5.00, p < .05). Young entrepreneurs were significantly morelikely to refuse or terminate interviews than their older counterparts, making our finalsample slightly biased toward older entrepreneurs.

In addition, the CPSED data set has a relatively lower representation of femaleentrepreneurs (32% in wave one and 18% in our final sample of 160 nascent entrepre-neurs) when compared to the PSED data in other countries and GEM (Global Entre-preneurship Monitor) data collected from China. To correct for such potential under-sampling of young and female entrepreneurs in our final sample, we followed priorstudies to adopt a weighting method (Winship & Radbill, 1994), and used the same ageand gender weights as used in prior studies to examine nascent ventures in China(Reynolds & Hechavarria, 2015; Tian et al., 2019). Table 1 summarizes the weightsused to reflect the gender and age distribution in the general population of nascententrepreneurs in China.

Table 1 Weights from China GEM screening applied to CPSED case

Age Range (years) Male Female

18–24 1.24 1.00

25–34 1.08 .92

35–44 1.08 .93

45–54 .95 .92

55–70 .94 1.05

Adapted from Global Entrepreneurship Monitor China report (Reynolds & Hechavarria, 2015; Tian et al., 2019)


Measures

Dependent variable We used a nine-item 5-point Likert scale (Tan& Litschert, 1994) tomeasure Resource acquisition difficulty. The scale asks respondents to evaluate thedifficulties of gaining resources, ranging from 1 (very difficult) to 5 (very easy), in thesecond wave of survey, including raw materials, skilled workers, distribution channels,customers, technological information, venture capital, bank loans, and local and nationalgovernment support. The ratings were then reverse-coded and averaged to produce acontinuous dependent variable. A high score indicates that the difficulty perceived by arespondent in acquiring resources is high. The Cronbach’s alpha for the scale was .79.

Independent variables The central concepts of interest are the pervasiveness andarbitrariness of corruption. The measures, collected from the second survey, weredeveloped from the two sets of questions that were used in the 1998 World BusinessEnvironment Survey (Lee & Oh, 2007; Uhlenbruck et al., 2006). The first set ofquestions was related to pervasiveness, and asked the respondents whether they neededto make extra and unofficial payments to public officials when dealing with six types ofproblems during venture creation: settling their tax bills, customs services, courts orjudges, law enforcement agencies, gaining government contracts, and dealing withbusiness regulators and city inspectors. The responses were coded using 0 for “no” and1 for “yes” in each case. We then averaged the six items to quantify the pervasivenessof corruption. The reliability (Cronbach’s alpha) of the scale was .82.

A second set of questions asked whether respondents usually knew in advance howlarge an unofficial payment must be to secure certain government services. The ques-tions were as follows: “Does the respondent usually know in advance how large anunofficial payment will be required to secure the same government services?”, “If thatunofficial payment was made, did another government agent also require an unofficialpayment for the same service?” and “Are the services or items for which a bribe was paidusually delivered as agreed?” The responses to the first and third questions were codedusing 1 for “no” and 0 for “yes” The responses to the second question were reverse-coded with 1 for “yes” and 0 for “no” Therefore, the arbitrariness of corruption is highwhen the average of the three items is high. The reliability of the scale was .77.

To capture the variation of government corruption in different regions and industrieswithin a large transition economy, we followed the lead of prior research (e.g., Fisman &Svensson, 2007; Krammer, 2019) to aggregate the perceptions of nascent entrepreneursregarding corruption in a specific industry sector (i.e., manufacturing vs. non-manufactur-ing) and a particular region (i.e., city), excluding the focal respondent’s own perception.

Moderators Consistent with the prior research (Delmar & Shane, 2004), legal registra-tion was represented by a dummy variable, which was coded as 1 to indicate that a newventure was legally registered and 0 otherwise.

Controls Three groups of controls were included in the analyses. At the macro level, wecontrolled environmental munificence (Pfeffer & Salancik, 1978; Tan & Litschert,1994), which measured nascent entrepreneurs’ assessments of whether the local eco-nomic environment was deteriorating, improving, or stable. A dummy variable wasgenerated, with 0 indicating the local environment was viewed as deteriorating and 1

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otherwise. Industry type was another control variable, with 1 indicating manufacturingand 0 for other industries. The National Economic Research Institute’s Marketizationindex was also included in the analysis to control for the progress of institutionaldevelopment in different provinces where the entrepreneurs were based (Fan et al.,2011). The index has been used extensively to indicate sub-national differences acrossChina in recent management scholarship (e.g., Wang & Qian, 2011).

At the business level, we controlled a venture’s type, because different types ofventures demand various resources (Maidique & Patch, 1982). Based on an entrepre-neur’s claims about whether his/her venture was conducting any R&D, whether itoffered high-technology products or services, or employed R&D staff, we created adummy indicator with 1 indicating a technology venture if the respondent claimed theventure met any of the three criteria, and 0 otherwise (Samuelsson, 2004).

At the individual level, each respondent’s demographic characteristics, such asgender, education, and previous working affiliations, were controlled. Gender was adummy variable, with 1 indicating females and 0 males. Education was an ordinalvariable, with values of 1, 2, 3, 4, and 5 indicating middle school graduation, highschool, a professional college diploma, a bachelor’s degree, and a master’s degree orabove, respectively. Prior work affiliations are especially important in China, becausethey provide valuable networks which new ventures can rely on to access importantsocial resources. Prior research has demonstrated that political affiliations provideflexibility in resource allocations in China (Luo, 2005). A count variable was con-structed to indicate whether a nascent entrepreneur previously worked in any govern-ment position in a public institution and/or in a state-owned company. This variablewas labeled as “political experience.” Another count variable, “market experience,”was constructed to measure whether a nascent entrepreneur previously worked in anywholly-owned foreign firm or in a joint venture or in a private firm. The two variablesboth ranged between 0 and 3, with 0 indicating no experience, and 3 denoting that anentrepreneur previously worked in all three types of organizations.

Reliability, validity and common method variance

We took several steps to ensure the reliability and validity of our data. We pretested thequestionnaire before the official survey. In 2009, we conducted three pilot surveys tocheck if there were any items that respondents considered to be unclear and thenrevised and improved them accordingly. In all, we screened a total of 2351 adults (18–64 years old) and identified 43 nascent entrepreneurs who were actively involved in anew venture creation process. In the questionnaire, we used validated scales wheneverpossible.

We conducted both exploratory factor analysis and confirmatory factor analysis(CFA) for each key construct included in our model. All of their Cronbach’s alphaare greater than the recommended .70. We also used CFA to check the convergentvalidity and discriminant validity. Each CFA factor loading was above .6, indicatingthat our measurements have high convergent validity. All the values for averagevariance extracted, often used to assess the discriminant validity, are over the .5threshold. Overall, these results indicate that our measures display adequate reliabilityand validity.


This study relies on self-reported data from single informants. This can potentiallycause the problem of common method variance (CMV: Podsakoff, MacKenzie, Lee, &Podsakoff, 2003) that may inflate the observed relationships between the researchvariables. Scholars recommend both procedural and statistical methods to minimizethe CMV problem (Lindell & Whitney, 2001; Podsakoff et al., 2003). In terms ofprocedures, we conducted three pilot studies before the formal survey, through whichwe reduced the ambiguity of scales used in the formal survey (Podsakoff et al., 2003).Then, during the formal survey, we ensured the confidentiality and anonymity ofrespondents to further reduce the CMV problem (a procedure recommended byPodsakoff et al., 2003). This is especially important for our survey because we askednascent entrepreneurs to report their experience with government corruption, which is asensitive issue.

Statistically, we conducted the latent variable approach as described by Podsakoffet al. (2003: 894) to test for common method variance by “controlling for the effects ofa single unmeasured latent method factor.” In this procedure, all the items were loadedon their specific constructs and on a latent common method variance factor. Bycomparing the structural parameters with and without the latent common methodsvariance factor in the model, we found that all significant relationships held aftercontrolling for the latent common methods variance factor. Therefore, we concludedthat common method variance does not appear to be an issue in this study (Krammer,2019; Zhang & Li, 2010).

Model estimation

The final sample was confined to nascent ventures, which were either in operation orstill in gestation. Ventures abandoned before the second-wave survey in 2010 wereexcluded. A Heckman two-stage model was thus conducted to assess the potentialsample selection bias due to the limited dependent variables and the non-randomsampling (Guo & Fraser, 2010). A probit model was first estimated to predict thelikelihood of an entrepreneur’s persistence in the creation process of new ventures. Thesample was sorted into two groups—those already abandoned and those still inoperation or gestation—and an inverse Mills ratio (IMR) was calculated. In the secondstage, the sample was reduced to ventures still in operation or gestation. At that stage,the models predicting the difficulty of resource acquisition were estimated, with theinclusion of IMR as a control variable, to correct for the potential selection bias in thereduced sample (Heckman, 1976).

All the other control variables from the second-stage analysis and the two dimen-sions of government corruption, i.e. its pervasiveness and arbitrariness, were includedin the first-stage analysis. The computation of the IMR needs to include at least onecovariate (called an exclusion restriction) that significantly influences entrepreneurs’persistence to continue their business but does not necessarily influence their difficul-ties in resource acquisition (Bascle, 2008). Two exclusion restrictions were identified inthe first stage of the analysis: sales expectations and full time involvement. The twovariables indicate the level of motivation and commitment shown by an entrepreneur increating a new venture, which can influence his/her persistence in staying in business.For instance, venture abandonment has been found to more likely occur amongfounders who worked only part time (Bosma & Levie, 2010). Entrepreneurs who have

L. Tian et al.

higher sales expectations are generally more motivated and, thus, are more likely topersist in their start-up activities (Evans & Leighton, 1990; Edelman, Brush, Manolova,& Greene, 2010). Nevertheless, entrepreneurs working full time on their start-upbusiness or those who expect more sales have no reason to find resource acquisitionany easier or more difficult than others.

Results

Tables 2 and 3 report the means, standard deviations, and inter-correlations of thevariables included in the first and second stages of the Heckman analyses, respectively.

Table 4 shows the results of the first-stage probit regression on factors affecting thelikelihood of a nascent venture’s persistence. We found that nascent ventures located ina more developed community (with higher marketization index) are more likely topersist (β = .20, p = .04) and technological ventures are more likely to persist than non-technological ones (β = .48, p = .04). Moreover, female entrepreneurs are less likely topersist than male entrepreneurs (β = −.70, p = .008). Nascent entrepreneurs reportinggood sales prospects are more likely to persist (β = .22, p = .04). Both pervasivenessand arbitrariness in government corruption reduce nascent ventures’ persistence.

Table 5 presents the second-stage estimation on resource acquisition difficulty.Model 1 summarizes the regression results with only the controls included. Models 2and 3 introduce the two dimensions of corruption — pervasiveness and arbitrariness,respectively. Model 4 includes the moderator, legal registration. Models 5 and 6 add aninteraction between the moderator and each dimension of corruption. Model 7 is thefull model.

The significant coefficients of the pervasiveness and arbitrariness terms acrossmodels indicate that pervasiveness and arbitrariness in corruption are positively relatedto the resource acquisition difficulty perceived by nascent entrepreneurs. Hypotheses 1and 2 are thus supported. Legal registration does not exhibit a significant relationshipwith resource acquisition difficulty. Results of Models 5, 6 and 7 show that legalregistration reduces the positive effect of arbitrary corruption on resource acquisitiondifficulty (β = −.54, p = .03) but not the effect of pervasive corruption. Therefore,Hypothesis 3b is supported.

Among the control variables, environmental munificence shows a negative effectthat reduces nascent entrepreneurs’ perceived difficulty in gaining access to the re-sources they need. The significant IMRs across all models show that the self-selectionin the sample indeed exhibits a significant and negative effect: entrepreneurs whoremained in business in our final sample tended to perceive relatively less difficultyin obtaining resources than those who dropped out.

We also used the approach of Aiken and West (1991) to plot the significantmoderating effect. Figure 1 shows that the relationship between arbitrary corruptionand resource acquisition difficulty is generally weaker for legally registered newventures than for unregistered ones. This effect is not only statistically significant butalso practically meaningful. As arbitrariness increases from the minimum (zero) to themaximum score of one, resource acquisition difficulty increases .45 for entrepreneurswith unregistered ventures, whereas it decreases .09 for ventures that are legallyregistered.


Table2

Means,standarddeviations

andcorrelations

forthefirst-stageanalysis

Mean

s.d

12

34

56

78

910

1112

13

1.Venture

persistence

.64

.48

1

2.Environmentmunificence

2.40

.72

−.08

1

3.Industry

.07

.26

.11*

.05

1

4.Marketization

9.03

1.61

.02

−.13

*−.03

1

5.Technology

venture

.40

.49

.19*

*.06

.27*

*−.03

1

6.Age

31.89

10.67

−.02

.09

.01

−.06

.28*

1

7.Gender(Fem

ale=1)

.30

.46

−.23

**−.00

.00

−.01

−.08

−.06

1

8.Educatio

n2.96

1.07

−.10

.02

−.04

−.03

−.04

−.07

.05

1

9.Po

liticalexperience

.60

.79

.10

−.02

.09

.08

.07

.31*

*−.03

.14*

1

10.M

arketexperience

1.00

.90

.07

−.17

**−.01

.01

−.17

**−.19

*−.08

.13*

.16*

*1

11.Pervasiveness

ofcorruptio

n2.41

1.77

−.31

*−.05

.02

−.04

−.04

.11

−.09

.06

−.01

−.01

1

12.Arbitrarinessof

corruption

1.56

.91

−.26

*−.09

−.05

.12*

.03

−.02

−.06

−.07

−.13

*.04

−.12

*1

13.S

ales

expectation

301.01

2356.79

.06

.06

−.02

−.06

−.02

.15

−.07

−.05

−.03

−.05

.11

−.14

1

14.F

ulltim

einvolvem

ent

.44

.49

.13*

.03

.11

.08

.18*

*.06

−.02

.01

.03

.03

.11

.01

−.03

n=321.

*p≤.05;

**p≤.01

L. Tian et al.

Table3

Means,standarddeviations

andcorrelations

forthesecond-stage

analysis

Mean

s.d

12

34

56

78

910

1112

1.Resourceacquisition

difficulty

3.09

.58

1

2.Pervasivenessof

corruption

.34

.34

.11

1

3.Arbitrarinessof

corruption

.63

.30

.12

−.39

*1

4.Legalidentity

.26

.44

.03

.13

.07

1

5.Gender(Fem

ale=1)

.18

1.04

−.04

−.11

.10

−.18

*1

6.Age

31.89

10.67

.07

−.12

.26*

*.16*

−.06

1

7.Educatio

n3.01

1.04

−.04

.00

−.14

.07

.07

−.07

1

8.Po

liticalexperience

.81

.86

−.09

−.01

.13

.10

.10

.31*

.09

1

9.Marketexperience

1.28

.86

−.05

.14

−.15

.10

.10

−.19

*.05

−.02

1

10.T

echnologyventure

.44

.50

.03

−.05

.10

.25*

*.25*

*.28*

.00

.08

−.19

*1

11.E

nvironmentmunificence

2.31

.74

−.21

*−.01

.01

−.07

−.07

.09

−.07

.06

−.22

**.04

1

12.M

arketization

9.09

1.59

.03

−.03

.04

−.06

−.06

−.06

−.08

.03

.03

.05

−.01

1

13.Industry

14.35

−.06

−.05

−.03

.01

.01

.01

.07

−.05

.02

.12

.00

.04

n=160.

*p≤.05;

**p≤.01


Robustness analyses

Additional analyses were conducted to check the robustness of these findings. Firstly, ourcurrent sample excluded 44 respondent entrepreneurs who did not respond to the surveyquestions on government corruption. Excluding the cases withmissing information could bebiased and lead to spurious findings. To address this concern, we first replaced the missingcases with the median values of pervasiveness and arbitrariness, and re-ran the analyses(Babble, 2012: 165). The core results remained largely the same as those reported in Table 5.In addition, the known characteristics of the 44 nascent ventures were compared with thoseof the other 160. Significant differences were not observed between the two groups.

Another potential concern is that legal registration may not be an independentdecision but strongly correlated with the other characteristics of nascent ventures, suchas the stage of development and revenue potential. The decision of nascent ventures toseek legal registration is likely to be affected by government corruption (the indepen-dent variable). Legal registration may be an endogenous decision, and this endogeneitymay have confounded the analyses.

To address this potential endogeneity, we employed the instrumental variable (IV)approach. Based on prior studies (e.g., Cai, Fang, & Xu, 2011), we used the averagerate of legal registration of other nascent ventures in the same city-industry as theinstrumental variable. We identified this variable as an appropriate instrumental vari-able that is correlated with legal registration (r = .29, p < .01) but independent ofresource acquisition difficulty (Guo & Fraser, 2010: 101). The results show thatendogeneity exists in legal registration, but it does not confound the moderating effectsof legal registration on the negative effects of government corruption on nascentventures’ resource acquisition. We also conducted several additional tests to checkthe relevance, exogeneity, and strength of the instruments (Bascle, 2008).

Table 4 Stage-one probit estimates on the persistence of a nascent venture

Independent variable Coefficient

Environment munificence .17(.18)

Industry (Manufacturing = 1) .16(.18)

Marketization .20*(.08)

Technology venture .48*(.23)

Age .03(.10)

Gender (Female = 1) −.70**(.26)Education −.20(.11)Political experience .22(.17)

Market experience .19(.15)

Pervasiveness of corruption −.19*(.09)Arbitrariness of corruption −.33*(.12)Full time involvement .11(.07)

Sales expectation .22*(.11)

Log likelihood 380.36

n = 321. Parameter estimates are unstandardized coefficients; standard errors are in parentheses.* p ≤ .05; **

p ≤ .01

L. Tian et al.

Table5

Stage-twoanalysisof

corruptionandresource

acquisition

difficulty

Model1

Model2

Model3

Model4

Model5

Model6

Model7

Environmentmunificence

−.18

**(.0

6)−.18

**(.07)

−.17

**(.06)

−.19

**(.0

6)−.19

**(.06)

−.17

* (.07)

−.18

* (.07)

Industry

(Manufacturing

=1)

−.10(.1

3)−.12(.12)

−.10(.12)

−.08(.12)

−.09(.12)

−.10(.14)

−.12

(.13)

Marketization

.01(.03)

.02(.03)

.02(.03)

.02(.03)

.02(.03)

.02(.03)

.02(.03)

Technology

venture

.03(.10)

.03(.10)

.02(.10)

.04(.10)

.03(.10)

.03(.1

0).04(.09)

(.10)

Age

.01(.01)

.01(.01)

.01(.01)

.01(.01)

.01(.01)

.01(.01)

.02(.02)

Gender(Fem

ale=1)

.02(.15)

.04(.15)

.02(.12)

.02(.15)

.02(.15)

.01(.15)

.05(.05)

Educatio

n−.03(.0

5)−.06(.05)

−.04(.05)

−.04(.05)

−.04

(.05)

−.04

(.05)

−.04

(.05)

Politicalexperience

−.06(.0

6)−.05(.06)

−.05(.06)

−.06(.06)

−.05

(.06)

−.08

(.06)

−.06

(.05)

Marketexperience

−.07(.0

6)−.06(.30)

−.05(.05)

−.06(.05)

−.05

(.05)

−.06

(.06)

−.04

(.05)

Pervasivenessof

corruption

.42*(.18)

.36*(.18)

.42*

(.18)

.42*(.18)

.36*

(.18)

Arbitrarinessof

corruptio

n.36*

(.18)

.33*(.15)

.33*

(.15)

.42*

(.18)

.45*

(.21)

Legalregistration(LR)

−.01(.11)

−.02(.10)

.01(.1

0).05(.11)

Pervasiveness×LR

−.30(.30)

−.36

(.30)

Arbitrariness×LR

−.51

* (.21)

−.54

* (.24)

InverseMillsratio

−.12

* (.06)

−.13

* (.06)

−.14

* (.07)

−.12

* (.06)

−.13

* (.07)

−.13

* (.06)

−.14

*(.07)

AdjustedR2

.06

.08

.09

.10

.11

.17

.19

ModelF

2.23

*2.39

**2.38

**2.32

**2.37

**2.46

*2.77

**

n=160.

Parameter

estim

ates

areunstandardized

coefficients;standard

errorsarein

parentheses

*p≤.05;

**p≤.01


Lastly, as aggregating respondents’ perception to measure government corruptionmay mask the variance in the richness of our survey data, we re-analyzed all the modelsby replacing the aggregated measures of government corruption, including both per-vasiveness and arbitrariness, with each nascent entrepreneur’s own perception ofgovernment corruption. The results remain similar to those reported in Table 5.

Discussion

The results of our study illustrate that government corruption—including its pervasive-ness and its arbitrariness—hampers resource acquisition by new ventures by increasingboth the costs and the uncertainties. Our empirical analyses corroborate the idea thatlegal registration can mitigate the uncertainty associated with arbitrary corruption moreeffectively than it can reduce the costs derived from pervasive corruption.

Theoretical implications

The findings of our study primarily make two contributions to the literature ongovernment corruption and entrepreneurship. First, previous research mainly focusedon the effects of government corruption on various country-level outcomes, primarilybecause of the difficulty of collecting reliable data on firm bribery (e.g., Anokhin &Schulze, 2009; Bowen & Clercq, 2008). Management scholars have recently started tofocus on the micro outcomes of corruption, such as the foreign entry strategies, exportdecisions, and growth rates of firms (e.g., Lee & Oh, 2007; Tonoyan et al., 2010; Wang& You, 2012). However, both macro and firm level studies have primarily examinedthe impacts of government corruption on established firms. Little attention has beenpaid to understanding its impacts on ventures that are still at the in-creation stage(Reynolds & Miller, 1992). Following this new line of inquiry, our paper advanced the

Fig. 1 The moderation effect of legal registration

L. Tian et al.

discussion to the context of nascent ventures, i.e., ventures still at the in-creation stage.By examining how the two dimensions of government corruption, i.e., its pervasivenessand arbitrariness, influence resource acquisition by nascent ventures, this study bridgesthe macro and micro levels of scholarship that focuses on the influences of governmentcorruption on entrepreneurship, and extends the corruption research to the in-creationstage of new ventures.

Second, our results highlight an important and complex role of legal registra-tion in coping with the detrimental effects of government corruption during thenew venture creation process. Previous research on informal economies finds thatdistrust of government is a key motivation force in entrepreneurs’ decision todevelop an informal rather than a formal business (Bruton, Ireland, & Ketchen,2012; Maloney, 2004; Rosser, Rosser, & Ahmed, 2000). In this study, we high-light the strategic choice to be a formal or an informal business affects a newventure’s resource acquisition in the face of corrupt government. With the nuancedfindings about the interplay between legal registration and the two dimensions ofgovernment corruption, our study highlights that legal registration plays an un-equal role in mitigating the uncertainty associated with arbitrariness and the costsderived from pervasiveness in government corruption. As such, we advance thescholarship on the informal economy by showing that legal registration constitutesa strategic component to determine the extent to which an entrepreneur is vulner-able to or defensive toward the negative influences of arbitrary and pervasivegovernment corruption.

Practical implications

The findings of this study suggest a number of important implications forgovernments and entrepreneurs. First, governments often play an indispensablerole in facilitating entrepreneurship in emerging economies, where they controland allocate critical resources. Both pervasive and arbitrary corruption increasethe difficulty of entrepreneurs in obtaining resources from their environment,seriously inhibiting their success in creating new ventures. Thus, our researchcorroborates the classic wisdom that efforts to foster entrepreneurship within anemerging economy should generally begin with policy reforms aimed at con-trolling corruption.

Our findings also suggest that individual entrepreneurs should pay special attentionto the important effects of legal registration in an emerging economy. Conventionally,legal registration has been viewed as enhancing legitimacy and helping to get access toexternal resources (Delmar & Shane, 2004). Our findings reveal the need to rethink thisrelationship in corrupt emerging economies, where registration may result in morecomplicated impacts.

Limitations and future research

The limitations of this study inform further research. First, using the CPSED data toaddress the effect of government corruption on firm-level outcomes in China is anunprecedented trial, but the single-country context inhibits generalization. Governmentcorruption is a complex phenomenon, particularly in an emerging economy where


government institutions evolve at different rates across different regions and sectors.Different norms and cultural values may affect the relationships examined in this study.Future research is needed to replicate these findings in other emerging countries.

Second, we acknowledge the geographical limitation of the CPSED survey, al-though in our study, the eight surveyed cities are all capital cities of provinces, eachplaying an essential role in the economic development of its province in China (Zhanget al., 2013). With only eight cities, there is limited scope to properly control for othersub-national influences. Future research is expected to generalize the regional coverageand determine if there are potential regional level confounders that bias our results.

Finally, creating a new venture is a complex and idiosyncratic process (Reynolds &Curtin, 2011). This study focuses entirely on resource acquisition during the in-creationstage of nascent ventures. However, future research may extend the study to the effectsof corruption on other key steps in the creation of new ventures, particularly persistencein the adolescent stage.

Conclusions

By focusing on new ventures’ resource acquisition, this study differentiates pervasive-ness and arbitrariness in government corruption, and examines how legal registrationaffects the hampering effects of the two types of corruption differently. By analyzing160 new ventures from a data set of Chinese Panel Study of Entrepreneurial Dynamics(CPSED), we found that both pervasiveness and arbitrariness in corruption hamperentrepreneurs’ acquisition of resources, including both government controlled re-sources and other resources. Furthermore, legal registration can mitigate the uncertaintyassociated with arbitrary corruption more effectively than the cost associated withpervasiveness in corruption. Therefore, our findings corroborate the notion that gov-ernment corruption has generally negative effects on nascent ventures in an emergingeconomy. More importantly, this study highlights that the negative effects of corruptionvary among nascent ventures, and the effects are dependent on a nascent venture’s legalstatus.

Acknowledgements The authors specially appreciated the financial support and great effort from ProfessorZhang Yuli, School of Business, Nankai University, and the Entrepreneurial Research Center on building upthe CPSED data set used in this paper. The current study is part of the research results of National NaturalScience Foundation Project 71532005, 71472099, and 71602128.The research is also supported in part by theResearch Grants Council of Hong Kong (HKUST#16505817).

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Publisher’s note Springer Nature remains neutral with regard to jurisdictional claims in published mapsand institutional affiliations.

Li Tian is an associate professor in the Department of Management, Business School at the NankaiUniversity.


https://www.transparency.org/cpi2018

https://www.transparency.org/cpi2018

https://doi.org/10.1111/etap.12238

Jing Yu (Gracy) Yang is a senior lecturer in the International Business at the University of Sydney BusinessSchool.

Jiatao Li is Chair Professor of Management, Lee Quo Wei Professor of Business, and Director of Center forBusiness Strategy and Innovation, and Institute of Advanced Studies (IAS) Senior Fellow, Hong KongUniversity of Science and Technology. He served as Senior Associate Dean of the HKUST Business Schoolfrom 2013 to July 2017; Associate Dean (Faculty) from 2009 to 2013; and Head of the ManagementDepartment from 2006 to August 2017

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