Gossip and Reputation inBusiness NetworksGerrit Rooks, Frits Tazelaar and Chris Snijders

In this article we examine the determinants of gossip in purchasing and supply

management, where gossip is defined as talking about your business partner (in a

negative way) to a third party. Although gossip is often conceived as mere small talk,

we argue and show that gossip can be analysed and is being used as a rational response

in the management of business transactions. The hypotheses are tested using a dataset

consisting of about 400 problematic purchase transactions of over 350 buying firms,

collected in Germany. Consistent with our hypotheses, gossip is in general more likely

when the problem is larger, when there are many common third parties available to

buyer and supplier, and when the business network is dense. Also, gossip is less likely

when buyer and supplier have been in business together for a longer time, and more

likely when buyer and supplier expect to do future business. We discuss the implications

of our findings in light of the literature on informal management mechanisms in business.

Introduction

In the social sciences gossip is seen as a potentially

important, but under researched area of inquiry (Noon

and Delbridge, 1993). Gossip typically gets the role

of being a coincidental by-product of research into

other organizational matters [for an overview, see

Waddington and Michelson (2007)]. It is then mostly

seen as problematic, taking away attention from the

real work (e.g. Baker and Jones, 1996; Therrien, 2004).

There are, however, arguments that allow for the

economic analysis of gossip as one mechanism to

safeguard business relations: gossip as the vehicle of

reputations.In his classic article ‘‘Non-contractual relations in

business: A preliminary study,’’ Stewart Macaulay

(1963) observed that businessmen often prefer to rely

on ‘a man’s word’ in a brief letter, a handshake, or on

‘common honesty and decency’ instead of contracts.

Business was supported by a norm that was widely

accepted: commitments were to be honoured in almost

all situations, and one should produce a good product

and stand behind it. Macaulay suggested that such

norms of good conduct are enforced by the wish to

continue successfully in business. Reneging on deals

and delivering low-quality products tarnishes one’s

general business reputation, and a good reputation is

the magical recipe for surviving in inscrutable markets.

All firms enjoying a good name are spared from

repeating the burden of proof at every transaction and

are relatively sheltered from competitive threats, which

makes few things more valuable that a good reputation

(cf. Gambetta, 1994, p. 227; Burt, 2008, p. 27).

Reputation also facilitates collaborations by creating a

cost for misbehaviour, and defines social obligation

and identity (Burt, 2005, pp. 107–108). Burt posits

that it is the positive and negative stories (‘gossip’)

exchanged about you that defines your reputation

(cf. Burt and Knez, 1996; Burt, 2008, p. 27). Poor

performances may become the subject of discussion in

the gossip exchanged by managers. In this way, gossip

becomes the vehicle of reputations.

European Sociological Review VOLUME 27 NUMBER 1 2011 90–106 90

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Many scholars agree that reputations help stabilizerelations and safeguard transactions (Lorenz, 1988;Coleman, 1990; Kreps, 1990; Raub and Weesie, 1990;Ellickson, 1991; Jones, Hesterly and Borgatti, 1997;Richman, 2004; Bolton, Katok and Ockenfels, 2005).However, there is mixed empirical evidence and adebate concerning the precise merits of reputations inbusiness relationships. Some authors find that innetworks of buyer–supplier relationships firms aremore trusting than in ‘isolated’ buyer–supplier trans-actions (e.g. Lorenz, 1988; Rooks et al., 2000; Gierl andBaumbacher, 2002). Other authors however find norelation between embeddedness within a businessnetworks and trust (e.g. Blumberg, 2001; Buskens,2002). As a possible explanation for the absence ofnetwork effects on trust, Blumberg (2001) remarks thatnetwork-embedded firms are not only able to damagea partner’s reputation, but that in the process ofspreading information, its own reputation may beharmed as well: ‘‘Once gossip is spread, people will notnecessarily apply the principle ‘in dubio pro reo’ tojudge the truth of the gossip’’ (Blumberg, 2001,p. 845). Hence, gossip should be used with cautionbecause it may be costly, and whether gossip workswell is dependent on contextual factors. A similarpoint was made by Williamson (1996, pp. 153–154):third parties may not be willing to contribute theirown resources to help the spread the information orthey may even use such information strategically totheir own advantage.

Although gossip is a fundamental process in thecreation of reputations (Emler, 1994), it has beenneglected as a research topic in inter-firm relations andbusiness networks. The aim of this study is to fill thisgap and contribute to the literature by studying theconditions under which business gossip emerges. Wefirst review the literature on gossip and then derivehypotheses about conditions under which gossip islikely to occur. To test our hypotheses empirically, weanalyse a comprehensive dataset on purchases ofinformation technology in Germany. The article con-cludes with a discussion and recommendations forfurther research.

Gossip in the ScientificLiterature

Gossip traditionally has a negative connotation, and isoften merely seen as idle talk, chitchat, slander, orscandal mongering (Fine and Rosnow, 1978). In socialscientific definitions of gossip it is seen as small talkwith a (social) purpose. Gossip is accordingly defined

in more neutral terms, such as ‘‘evaluative talk about aperson who is not present’’ (Eder and Enke, 1991,p. 494), or ‘‘. . . the process of informally communicat-ing value-laden information about members of a socialsetting’’ (Noon and Delbridge, 1993, p. 25). Somedefinitions are related to a specific field of study. Forinstance, Kurland and Pelled (2000, p. 429) definegossip as ‘‘. . . informal and evaluative talk in anorganization, usually among no more than a fewindividuals, about another member of that organiza-tion who is not present.’’

Gossip is everywhere. Gluckman (1963, p. 308) forexample notes: ‘‘I imagine that if we were to keep arecord of how we use our waking-time, gossipingwould come only after ‘work’—for some of us—in thescore.’’ Likewise, Wilson et al., (2000, p. 347) thinkthat ‘‘. . . people in all cultures gossip with an appetitethat rivals their interest in food and sex’’. Gambetta(1994) claims that ‘‘gossip is universal; people indulgein it regardless of culture.’’ Moreover, he states thatevidence suggests that its content also may be univer-sally shared: ‘‘most topics which, say, Zinacantecos(a native Mexican people) gossip about coincide withthe topics we gossip about’’ (Gambetta, 1994: 214).

According to Michelson and Mouly (2004, p. 189)extant research on gossip is primarily divided amonganthropology, sociology, social psychology, literature,and communication. Especially in a business context,gossip is widely practiced but surprisingly little under-stood (Michelson and Mouly, 2004, pp. 197–198). Asan activity in management and organizational studies,scholars have considered reputation but largely ignoredgossip (Noon and Delbridge, 1993, p. 31; Kurland andPelled, 2000, p. 428). What little organization-basedresearch was conducted, tends to be narrowly focusedor lacks analytical rigor (Michelson and Mouly, 2004:190). We are clearly in need of theory equipped withsolid micro-foundations that can enable us to makenon-trivial predictions about gossip’s social dynamics(Gambetta, 1994, p. 204).1

Although plenty of rich qualitatively accounts ofgossip in the literature can be found, the occurrence ofgossip has hardly been studied quantitatively. Inorganization sciences, from an empirical point ofview gossip has been studied mainly as a phenomenonthat takes place within organizations (to the best ofour knowledge no systematic empirical studies ofinter-organizational gossip have been carried out).Wittek and Wielers (1998) find that gossip flourishesin social networks that have a large number ofso-called coalition triads. That is, the gossipers havegood relationships among themselves, but bothgossipers have bad relationships with the object of

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gossip. Gossip in the workplace has repeatedly been

characterized as a tool of abuse in the context of

workplaces (e.g. Davenport, Schwartz and Elliot, 1999).

Kurland and Pelled (2000) argue that in the workplace

gossip enhances the power of a gossiper over a gossip

recipient.Although at first sight gossip seems to have only

negative side-effects or at best has no purpose other

than social entertainment, it certainly has positive

side-effects as well, as has been noted by many social

scientists (Michelson and Mouly, 2004: 199). Most

researchers point to gossip’s ability to deter opportu-

nistic behaviour: if one knows that opportunistic

behaviour will become known, opportunistic behaviour

itself is deterred. For this mechanism to work, one

needs a network that is ‘dense enough’ so that the

threat of gossip is strong enough to deter opportunistic

behaviour. One can look at this as a form of informal

social capital: the network is such that it facilitates the

flow of gossip, which itself precludes opportunism

(Coleman, 1990, 1991). So instead of considering

gossip as a nasty by-product of the cohabitation of

gossip-loving humans, it can be considered a

useful governance mechanism that can work side-

by-side with more formal governing mechanisms

(Merry, 1984; Waddington and Michelson, 2007).

Interpreting gossip in that sense, we now derive

hypotheses on the conditions under which gossip is

likely to occur.

Hypotheses

In this study we define gossip as talk between business

people from distinct firms about a problematic trans-

action with an absent third party (Merry, 1984, p. 275;

Burt, 2005, p. 105).2 Permeating all derivations of the

hypotheses is the notion that problems in business are

a violation of the norm that one should live up to the

promise of providing adequate goods and services.

This gives rise to three reasons why one would use

gossip in a business context (cf. Merry, 1984). The first

reason is that people tend to spread negative infor-

mation about others when they feel they are treated

badly, as an emotional response. The second reason is

that spreading gossip allows network members to

mutually agree and confirm which kinds of behaviour

are considered acceptable, and which not. Gossip is

used as a way of testing and reconfirming the

industry’s norms with peers. The third reason is a

more instrumental one: gossiping about a business

partner to a third party is a way to maintain the

sanctioning system and to harm the reputation of the

cheating partner.

Opportunism and the Size of Problems

One factor that might affect gossip is simply the size of

the problems encountered. The more matters went

wrong, the more likely it is that business people will

experience that the norm ‘you should deliver as

promised’ is violated—irrespective of whether the

partner is to blame for all problems. As a consequence,

the stronger the incentive to talk about the problem to

others will be. All reasons to be willing to gossip are in

place: a transaction that has lead to a huge amount of

trouble creates hostile feelings (see below) and makes

for an attractive war story during social talk. Moreover,

the more and bigger the problems are, the higher the

need is to effectuate the implicit gossip threat: for the

gossip mechanism to work it is necessary that

especially the bigger problems get sanctioned through

active gossiping.In addition, it is likely that there exists an effect of

the perceived cause of the ex post transaction problem.

It makes a difference whether a problem was caused by

circumstances beyond the control of the transaction

partner, such as misunderstandings or force majeure,

or whether the problem was caused by active oppor-

tunistic behaviour of the transaction partner. When

‘‘deceit-oriented violation of implicit or explicit prom-

ises’’ (Williamson, 1985, p. 47) occurs it is known to

have detrimental effects. Besides the direct damage

caused by the opportunistic behaviour, it decreases

trust in both the competence and the general trust-

worthiness of the other party that itself has a negative

effect on relationship commitment (Morgan and Hunt,

1994). It is also well documented that deceitful

violation of promises often leads to feelings of

being treated unfairly and the urge to retaliate

(Kaufman and Stern, 1988; Stirling, 1956). Recent

research in experimental economics also supports

the idea that unfair behaviour is likely to be informally

sanctioned by gossip, even at the expense of costs

to ego (Falk, Fehr and Fischbacher, 2005). In a

prisoners’ dilemma with punishment possibilities,

Falk et al. find that cooperator’s punishment is

mainly motivated by the wish to harm those who

acted unfairly. We see no reason why the same

arguments should not apply to managers. This leads

to the following hypotheses:

Hypothesis 1a: The more problems arise during or

after a transaction, the higher the probability that

gossip will occur.

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Hypothesis 1b: If a transaction problem is

(perceived to be) caused by opportunistic behaviour

of a transaction partner, the probability of gossip

is higher.

Size and Kinds of Business Networks

In theories of social control, gossip is often seen as a

strategy to enforce norms in close-knit groups of

individuals (Merry, 1984; Ellickson, 1991; Wittek,

1999). When a group norm is violated, gossip is

used as a first mild form of control in a sequence of

steps, gradually increasing in force (Ellickson, 1991,

p. 214).3 Gossip as such is a form of punishment, since

it can damage a valuable reputation. This implies that

the likelihood that a manager will talk with a third

party about a problematic transaction will be greater if

this third party itself is related to the object of gossip:

only then will the gossip have its strongest effect. If a

norm violation occurs, then gossiping to a complete

outsider has no group serving function, and will

therefore be less likely (Ellickson, 1991, p. 177). This

argument also follows from a more evolutionary

perspective. Gossip can be seen as fitness enhancing

behaviour, which can be group serving, as well as

self-serving. Since in settings without common third

parties there is no coherent group in which to use

gossip instrumentally, one reason for gossip vanishes,

so gossip will be less likely in settings where a mutual

network tie does not exist. Moreover, we can also

relate gossip to the size of the network of common

third parties. As Nee and Ingram (1998) note, network

size affects a group’s ability to establish, coordinate,

and enforce incentives. In a triad, the costs of

sanctioning are large, but the costs will be smaller if

the group is larger. In our case, the risk that gossip will

be detected, and the gossiper will be identified by the

target of the gossip, is greater in the triad than in a set

of four firms. Hence, the more third parties will be

present, the more likely gossip will be, because both

the effectiveness of and the opportunities to gossip are

higher. In all likelihood this effect will not be linear.

However, the marginal effect of a 10th mutual tie in

the network will be smaller than the marginal effect of

a fourth member in a network.

Hypothesis 2a: The more third parties a buyer and

seller have in common, the more likely that gossip will

occur.

Hypothesis 2b: The relation between the numbers

of third parties on the probability that gossip

occurs, shows a decreasing slope. The marginal

effect of an additional third party will diminish to

zero.

The above two hypotheses concern effects of the

number of third parties on the likelihood of gossip.

Another characteristic of a business network that may

affect gossip is the degree to which firms interact and

have close connections with each other in a given

sector. In accordance with the social network literature,

we refer to such connectivity as network density. The

closure’s reputation mechanism is the reason why

dense networks increase the potential costs to unco-

operative behaviour (Coleman, 1988a,b; Granovetter,

1985; Putnam, 1993, pp. 173–174). The more closed a

network, the more likely that misbehaviour will be

detected through gossip and punished (Merry, 1984,

p. 297; Burt, 2005, p. 110; Burt, 2008, p. 162). Gossip

about an absent person or organization often occurs as

a by-product of social interactions. The more frequent

interactions between members of a business network

are, the more opportunities there are for gossip about

problematic transactions and the more effective and

efficient gossip can be.

Hypothesis 3: The denser the network of common

third parties, the more likely it is that gossip will

occur.

The occurrence of opportunism is a serious norm

violation. As Ellickson (1991, p. 191) notes, most

scholars agree that there is a universalistic norm, so

also in business, against lying and deceit. Hence, if

opportunism occurs within a network there will be a

strong motive to gossip, besides the earlier discussed

emotional incentive. Furthermore, there may be a

norm operative to spread information about opportu-

nistic behaviour of actors within a network (Ellickson,

1991, p. 232). Hence, opportunistic behaviour should

lead to gossip especially if the transaction is embedded

in a business network. In isolated transactions oppor-

tunism will not (or less likely) lead to gossip, since in

that setting there is no group, and gossip serves no

control function. This leads to the following

hypothesis.

Hypothesis 4: The effect of opportunism on the

likelihood that gossip occurs is higher within a

network, than outside a network.

Dyadic Relationships and Gossip

Another factor that can influence the extent to which

gossip will be used is the relation between the business

partners. When business partners have done business

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before, a certain degree of common understanding isusually present, and spreading negative informationcan seriously backfire if the business partner finds outabout the gossiping. Under such conditions, gossipputs a long-standing business relationship on the line.Indeed, experimental evidence has shown that gossi-pers are more likely to withhold negative informationabout their long-term business partner (McAndrewand Milenkovic, 2002). The same kind of argumentholds in case business partners can foresee that futurebusiness together is likely. The benefits of all possiblesanctions, including gossip, should be weighed againstthe risk of a break-up in the relation. For single-shotinteractions where no business has been done togetherbefore and future business encounters are unlikely, thisargument does not hold and gossip will be less likely tobackfire and hence more easily used.

Hypothesis 5: If a common past between buyer andsupplier exists, gossip is less likely to occur.

Hypothesis 6: The higher the expected rela-tionship continuity, the less likely it is that gossipoccurs.

Monitoring Capacity

Buyers face monitoring problems if they cannot easilyassess the quality of the product or service to bepurchased. Note that such monitoring problems can beclearly distinguished from ex post problems duringcontract execution such as delivery delays, compatibil-ity problems, or inadequate service. A lack of moni-toring capacity serves as an indicator for the buyer’sbehavioural uncertainty and makes opportunism fea-sible and attractive for the supplier (Batenburg, Rauband Snijders, 2003, p. 148). For instance, delivering aproduct of inferior quality might go unnoticed whenthe business partner has no clue what to expect.

Transaction cost theory argues that behaviouraluncertainty will affect contractual ex ante governance(Williamson, 1985). Using transaction cost theory and

theory on embeddedness effects in economic exchange

Batenburg, Raub and Snijders (2003) investigated the

extent to which effort invested by the buyer in writing

and negotiating a contract can be explained by a lack

of the buyer’s monitoring capacity. Based on a

comprehensive survey on the management of IT

transactions in the Netherlands (N¼ 964) they find

that the more difficult it is for the buyer to monitor

the transaction, the larger the effort invested in

negotiating and contracting is (Batenburg, Raub and

Snijders, 2003, p. 164).Starting from a similar framework Rooks, Raub and

Tazelaar (2006) and Raub, Rooks and Tazelaar (2007)

focused on the direct effect of monitoring capacity on

the occurrence of ex post problems. Based on similar

data (1205 IT-transactions of 775 buyers) they find

that a lack of expertise and limited monitoring

capacity of the buyer has a significant and substantial

positive effect on the likelihood and size of ex post

problems, even after controlling for the effort invested

in ex ante contracting (Rooks, Raub and Tazelaar,

2006, p. 262; Raub, Rooks and Tazelaar, 2007,

pp. 260–261). Here we continue this line of research,

and focus on the effects of monitoring capacity on ex

post problem management through gossip and infor-

mal sanctions. Although there are cases where the

(cause of the) transaction problem is obvious, in

practice matters are not always that clear cut. We

assume that, especially when the buyer (or more

general: receiver) of a good or service has limited

expertise and relatively few ways to monitor the extent

to which the good or service lives up to its promise, ex

post problem management becomes more difficult. In

order for sanctions to be credible and effective the

buyer must be able to present his argument in a clear

and unambiguous way. If not, sanctions in general and

gossip and informal sanctions in particular are less

likely. This argument holds in particular in the IT

sector, where the amount of knowledge and expertise

on the side of the supplier can contrast strongly with

the lack of knowledge and expertise of the buyer.

Table 1 Responses to the telephone interview

Refusal Willing toparticipate inface-to-faceinterview

Willing toparticipate inpostal interview

Does not meetrequirements

Total

Halle/Leipzig 187 (11.8 per cent) 428 (27.1 per cent) 72 (4.6 per cent) 894 (56.5 per cent) 1,581 (100.0 per cent)

Munich 421 (14.5 per cent) 479 (16.5 per cent) 115 (4.0 per cent) 1,883 (65.0 per cent) 2,898 (100.0 per cent)

Total 608 (13.6 per cent) 907 (20.3 per cent) 187 (4.2 per cent) 2,777 (62.0 per cent) 4,479 (100.0 per cent)

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Hypothesis 7: The higher the buyer’s monitoring

capacity, the more likely that gossip occurs

Data and Method

To test the hypotheses, we make use of a database

resulting from a comprehensive survey of IT purchases

by German small and medium-sized business (Berger,

Kropp and Voss, 2002). This multi-purpose survey was

based on two earlier surveys that were conducted in a

related research project in the Netherlands (Batenburg

and Raub, 1995; Batenburg, 1997; Batenburg and Van

de Rijt, 1998). The questionnaire contained six major

parts, concerning (i) the product and/or service,

(ii) product and supplier selection, (iii) the relation-

ship between the buyer and the supplier, (iv) the

agreement and contracting, (v) the performance of the

supplier, problems, and problem management, and

(vi) the buyer and his or her relation to the supplier.

In total, per transaction more than 300 items were

scored. In the survey buyers of information technology

in two regions, Halle/Leipzig and Munich, in (then

East and West) Germany were sampled. At the time of

the survey both of the regions (Halle/Leipzig and

Munich) were economically prosperous regions

(Berger, Kropp and Voss, 2001/2). The sample con-

sisted of small- and medium-sized firms with 4–500

employees.In order for a transaction from a given firm to be

included in the survey, the (respondent of the) firm

had to meet the following requirements: (i) the firm

had managed the purchase itself, that is, the decisions

about the product and supplier had been taken by the

firm instead of a mother company; (ii) an employee of

the firm who could give detailed information about the

transaction had to be present; (iii) the transaction was

completed not too long ago—if possible not longer

than 3 years; (iv) the transaction should involve only

one supplier. To compile the sampling frame the

yellow pages were used (‘Gelben Seiten fur

Deutschland. Fruhjahr 1999’).

The data collection was conducted in two phases.

First, a member of the research team contacted the

firm in the sample by phone to determine whether the

firm met the requirements to be part of the survey,

and if this was the case, whether the firm was willing

to cooperate in the survey. If a firm refused to

cooperate in the survey (608 times), some questions

were asked about reasons not to cooperate. A large

fraction of these firms indicated that they had too little

time to cooperate (43 per cent), another part of the

firms indicated that they saw no personal interest to

cooperate (26 per cent), and a third reason that was

often given was that the firm never participated in

surveys (17 per cent). If a firm agreed to cooperate

with the survey, and met the requirements, then a

knowledgeable contact person who had been respon-

sible for purchases of information technology was

selected and an appointment was made for a

face-to-face interview (if firms refused a face-to-face

interview a questionnaire was mailed to them). The

telephone interviews started in March 1999 and were

concluded in August 1999 (Berger, Kropp and Voss,

2001/2; Berger, Kropp and Voss, 2002).All firms who agreed to cooperate were sent a letter

of confirmation immediately after the phone interview.

In this letter the selected transaction and the date and

time of the appointment were named again. Shortly

before the agreed face-to-face interview a member of

the research team phoned the firm once more to

confirm the appointment. If possible the respondent

was asked after the interview whether he or she was

willing to fill out a second (written) questionnaire.

As a result of the high-care intensity and the personal

assistance in filling out the questionnaires, the response

rates to the face-to-face interview were high. The

survey team realized 84.2 per cent of all the promised

interviews. Additionally, 24.5 per cent of the respon-

dents filled out a second questionnaire. The response

to the mail questionnaire was clearly smaller (36.4 per

cent).The response rates are presented in Table 2.

The overall response rate was 49 per cent which is

Table 2 Response rates

Contactedfirms

Gross responserate (per cent)

Firms thatmet therequirements

Net responserate (per cent)

Number offirms withinterview(s)

Number oftransactions

Halle/Leipzig 1,581 24.7 687 56.8 390 477Munich 2,898 15.3 1,015 43.5 442 570Total 4,479 18.6 1,702 48.9 832 1047

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high in comparison with the standard response rates in

organization research (see Kalleberg et al., 1996). Theresponse rates in the region of Halle/Leipzig were

higher than in the region of Munich.Our dataset contains complete and detailed data on

N¼ 1,019 IT transactions from 832 buying firms. Fromthese 832 buying firms, 645 (¼78 per cent) provided

data on a single IT transaction and 187 (¼22 per cent)provided data on a second IT transaction as well.

Compared to firms in the region of Halle/Leipzig,firms in the region of Munich provided more second

questionnaires (29 vs. 15 per cent).After completing the first four sections of the

questionnaire, the respondents were presented with alist of 11 types of possible problems (‘issues’) that

might occur after the contract was signed and thegoods were delivered. For each and every issue the

question was asked whether, and if so to what extent,these problems actually were experienced during the

supply of the product or service. In Table 3 anoverview is presented of the various issues and the

incidence of problems reported (percentages and rankorder).

In 435 out of the N¼ 1,019 transactions (¼43 percent), at least one problem occurred at least to a

certain degree (see ‘Measurements’ section, below).These N¼ 435 ‘problematic’ transactions form the core

database on which our hypotheses will be tested.

Measurements

In this section the construction of the empirical

variables is discussed. First we elaborate on thedependent variable, gossip, and then on the

construction of the explanatory variables. We end

this section with a brief discussion of the control

variables that are included in the analyses.

Gossip

The occurrence of gossip is measured by taking

answers from two sets of questions. First, if a

transaction was problematic, the respondent was

asked how those problems had been managed. A

comprehensive list of different problem management

possibilities was presented to the respondents. This list

was successfully used in two related research projects

on purchase management in the Netherlands (Rooks

and Snijders, 2001; Snijders and Tazelaar, 2009, ch. 5).

It included questions such as ‘‘Has the supplier been

contacted about this problem?’’, ‘‘Has there been any

form of discussion about the problem with the

supplier?’’, ‘‘Were any kind of sanctions executed,

and if yes, which ones?’’, ‘‘Were these measures limited

to delaying or withholding payment, or were more

severe measures (also) taken, such as involving lawyers,

mediators, arbitrators, etc. or ultimately the court?’’. In

this list of issues the question was also put forward

whether the respondent had notified other customers

of the supplier. In almost 5 per cent of the cases the

buyer had notified one or more other customers of the

supplier. Second, a question was asked as to whether

the respondent had talked with colleagues in other

firms about the problems. The variable GOSSIP is

constructed on the basis of the answers to both

questions: gossip is defined to have occurred if during

problem management other customers of the supplier

were notified or if there had been informal commu-

nication with colleagues in other firms. GOSSIP is a

binary variable (1¼ yes, it occurred, 0¼ no, it did

not). Measured as such, gossip took place in 26 per

cent of all 435 problematic cases.

Ex post Problems

The occurrence of ex post problems is measured

using detailed information on problems that occurred

during and after the focal transaction. In the survey,

questions were asked about 11 typical problematic

issues that are often associated with IT transactions

(Riesewijk and Warmerdam, 1988; Rooks, 2002, ch. 4).

Respondents could indicate for each issue to what

extent it had occurred and how serious the problem

had been. The eleven issues are measured on a

five-point scale (ranging from ‘not whatsoever’ to

‘very severe’). The variable PROBLEM SIZE is derived

as a scale score on these eleven issues (Cronbach’s

Table 3 Percentages of respondents reporting atleast some problems on various issues, and rankorder (N¼ 1,019)

Issue/type of problem: Per cent Rank order

Slow or late service 24.9 1Improper accompaniment 24.8 2Improper documentation 24.6 3Slow or late adjustment 23.3 4Late delivery 20.5 5Improper installation 17.7 6Incomplete product 17.2 7Deviation from specification 16.7 8Incompatibility 15.9 9Product too slow 15.4 10Costs exceeding expectation 9.8 11

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alpha¼ 0.92; higher represent more and/or more

serious problems). To examine validity, we used

additional data from the survey. Buyers were asked

to indicate their satisfaction with both the product and

the supplier by providing a grade between 1 and 6—

the scale used for grades in German schools—for the

product and the supplier. Both satisfaction variables

correlate strongly and significantly with PROBLEM

SIZE (average correlation coefficient¼ 0.52; P50.001).

In 43 per cent of the transactions (435 out of

N¼ 1,019) at least one problem occurred at least to

a certain degree [variable: PROBLEM DUMMY].

Opportunism

The degree of opportunism was measured by taking

answers from two sets of questions. The first set

consists of four questions, which were based on items

used in Provan and Skinner (1989). The respondents

were asked whether, during the focal transaction, the

supplier ‘always gave a reliable image of business’,

‘obscured facts’, ‘did not keep promises’, and ‘was

honest and frank’. The respondents could answer on a

five-point scale ranging from ‘not at all’ to ‘very much

so’. The second set consists of three questions, which

were based on items used in Rooks and Snijders (2001)

and Rooks (2002). The respondents were asked what

they thought would be the cause(s) of the problems

that they had encountered: ‘supplier’s indolence’,

‘supplier’s incompetence’, and ‘supplier’s self-interest

and opportunism’. Here too, the respondents could

answer on a five-point scale (ranging from ‘certainly

not’ to ‘certainly true’). Factor analyses showed that

the seven items measure a single dimension.

Cronbach’s alpha scale reliability coefficient of these

items is 0.84, which is an indication of a reliable scale

(Nunnaly, 1978): OPPORTUNISM.

Number of Common Third Parties

A number of questions were asked about the business

network in which the transaction was embedded. The

purchase manager was asked to take in mind the other

firms (s)he knew who customers of the supplier were

at that time. We used the resulting number of

common third parties as an estimate of the size of

the business network. An alternative and more elab-

orate method to estimate the network size is to use a

name-generator, however in a large-scale quantitative

study Fu (2003) showed that a single-item measure of

the kind we also use here was comparable and

consistent with more complicated network measures.

The distribution of the number of third parties known

by the respondent was highly skewed. To cope withthis and possible outlier effects the number of firmswas maximized to seven: OUTDEGREE.

Density of Network of Third Parties

When the respondent indicated that there was a socialnetwork surrounding the dyadic relation a number ofquestions were asked about the density of this network.Respondents were asked to indicate the degree towhich they agreed (on a five-point scale) with thefollowing statements about the network: ‘there arefrequent contacts’, and ‘like knows like’. The reliabilityof this scale is somewhat low; only two items areincluded (r¼ 0.44; Cronbach’s alpha¼ 0.61 forDENSITY).

Network Acquaintance

The respondent was asked whether (s)he wasacquainted with any of the business partners of thesupplier, and if so, which type of business partner(s)(s)he was acquainted with. Five types were given:(i) (other) customers of the supplier [yes/no],(ii) suppliers of the supplier [yes/no], (iii) bank(s) ofthe supplier [yes/no], (iv) accountants and/or taxconsultants of the supplier [yes/no], and (v) othertypes of business partners of the supplier [yes/no]. Ifany of these categories was labelled ‘yes’ by therespondent, the dummy variable NETWORKACQUAINTANCE was given a ‘1’, if not a ‘0’.

Common Past

The questionnaire contained four questions concerningthe previous relation and transactions with the focalsupplier. The questions concerned the length of therelationship, the frequency of previous transactions,the volume of previous transactions, and the satisfac-tion with previous transactions. Factor analysesindicated that there was one dimension underlyingthese items. A consistency analysis indicates that thescale is reliable (Cronbach’s alpha¼ 0.89 for PAST).

Expected Relationship Continuity

The questionnaire included a question on whether thepurchase manager had expected, before the focaltransaction was concluded, that future transactionswith the supplier would be likely. Respondents couldchoose between five response categories (ranging from‘no expectation of future transactions’ to ‘very regularand/or very sizeable future transactions wereexpected’). We use the score of the buyer on this

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question for the construction of the variable FUTURE.

Note that the measurement of this variable is prob-

lematic (see Batenburg, Raub and Snijders, 2003, p.

168; Buskens, 2002, pp. 135–136). The respondent had

to recall an expectation; often from a number of years

ago. The accuracy of answers to such retrospective

questions on attitudes rather than behaviour is

doubtful (Bernard et al. 1985), but no better measure-

ment is available in the given data.

Monitoring Capacity Of the Buyer

We measure the monitoring capacity of the buyer as a

factor score, based on five questions. These questions

ask for the difficulty to judge the quality of the

product(s) (five-point scale), the difficulty to compare

the different tenders for the product(s) (five-point

scale), the buyer’s experience with IT-products and

services relative to similar other firms (five-point

scale), whether the buyer firm had one or more

employees with specific knowledge and experience in

IT, and whether the buying firm would be capable to

assemble and/or produce the product(s) itself

(five-point scale). These five items lead to a single

factor MONITOR.

Control Variables

Based on the extant literature about inter-firm rela-

tionships and transactions we include five control

variables in the analyses, three of which are derived

from transaction cost theory (Williamson, 1985;

Williamson, 1991), and two from social theory

(Coleman, 1990, ch. 11; Coleman, 1991):

Switching costs

One of the core concepts of transaction cost theory is

that of switching costs. Whenever switching to an

alternative partner would be costly, a form of depen-

dency is created that might affect the extent to which

informal mechanisms such as gossip will be used. We

use four questions on different types of switching costs.

A principal component analysis revealed that these

form one cluster of variables (factor 1 explains 63 per

cent of the variance). Furthermore, the resulting scale

is reliable (Cronbach’s alpha¼ 0.80 for SWITCHING

COSTS).

Financial volume

To control for the volume of the transaction, we

include the answer to the question ‘How much money

did you have to pay the supplier for this product and/or service in total (all later extensions excluded)?’:TRANSACTION SIZE.

Product complexity

To control for confounding effects of product charac-teristics we include PRODUCT COMPLEXITY, avariable based on 20 characteristics of the purchasedIT-product(s) and/or service(s), classified in fivecategories, from (i) ‘straightforward and standard’ to(v) ‘highly complex’.

Power differences and reputation

Coleman asserts that powerful actors in communitiesare less likely to obey the norms of that communityand are also less likely to be sanctioned if they doviolate the norm (Coleman, 1990, pp. 286–287).Moreover, he also suggests that informal sanctionswill be less effective against those who already have abad reputation (Coleman, 1990, p. 287). We constructthe variable SUPPLIER POWER based on thelog-difference between the size of the supplier andthe size of the buyer in terms of full time equivalents.The perception of the buyer of the supplier’s reputa-tion is measured by providing a grade between 1 and6—the scale used for grading in German schools—forthe reputation of the supplier. The variable LOWREPUTATION SUPPLIER is constructed as a dummyvariable by taking the firms with the three lowestgrades.

Table 4 shows the descriptive statistics for thevariables used in the analyses. Cases with missingvalues on the ‘gossip’ variable are excluded from thedescriptive and explanatory analyses.

Results

Since gossip is a binary variable, it either occurred ornot, logistic regression analysis was used to test ourhypotheses. Table 5 lists the results of five logisticregression models of gossip between business people.The first model concerns all problematic transactions,restricted to those of which we have data for all othervariables and controls (N¼ 387). In the second modelwe replace the variable OUTDEGREE by a dummyvariable, capturing whether the respondent knows atleast two other buyers from the supplier (OUTD_BIG).This is because closer inspection of the data, usingdummies for the separate OUTDEGREE categories,showed that in fact there is virtually no effect for smallvalues of OUTDEGREE and a fixed-size positive effectfor larger values of OUTDEGREE. In the third model

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we include the variable DENSITY. It has a lot ofmissing values, so it decreases our estimation samplesize dramatically, but we wanted to at least show it forthe cases where we have measured this variable. Inmodel 4 and 5 we run our analyses on two separatesamples: the isolated encounters (model 4) and theembedded encounters (model 5).

We see that across all models except 3 and 4, there isa positive and significant effect of the size of theproblem on the probability of gossip (P50.05). Inmodel 3, apparently the inclusion of the density of thenetwork moderates the effect of the size of the problem.Furthermore we see that the effect of the size of theproblem occurs mainly in embedded transactions, notin isolated ones. This suggests that indeed more andlarger problems lead to voice more often. This impliesthat the effect in models 1 and 2 is largely determinedby the embedded cases, rendering partial support ofour Hypothesis 1a. Hypothesis 1b is not supported.After controlling for problem size and other variables,there is no additional effect of the fact that theproblems were caused by opportunism (P440.10).Some caution is warranted here, because of the largecorrelation between the size of the problem and thedegree of opportunism (r¼ 0.65, P50.001). Analyseswith problem size and opportunism included sepa-rately show an effect of each. However, when includedtogether the effect of the problem size clearly wins.Hypothesis 2a is supported by our results: it is indeedthe case that a larger network (a higher OUTDEGREE)leads to gossip more often (P50.05). However, as faras we can determine, the effect is stepwise:non-existent for small networks and significant andpositive if the network is large enough. We hadactually expected a concave shape of this effect(marginal returns decreasing to zero), so in thatsense Hypothesis 2b is not supported, but the effectis indeed non-linear.

The density of the network has a strong positiveeffect on the probability of gossip (P50.001), sup-porting Hypothesis 3. Some caution is in order herebecause there were some measurement problems withthis variable and a large fraction of missing values, butfor those cases where we have a measurement, theeffect is highly significant (P50.001). Hypothesis 4concerns the differential impact of the effect ofopportunism on gossip. Although a direct test cannotbe seen in the table, the differential impact is notstatistically significant (P40.1) and even in the wrongdirection, rejecting Hypothesis 4. We do see that thegist of the arguments underlying Hypothesis 4 doeshold when we consider the size and severity of theproblems. Then we do see a significant difference: aT

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strong positive effect of the size of problems in

embedded settings versus a weak positive effect inisolated settings (difference significant at P50.05; not

reported in Table).The past and expected future of a relationship also

affects the likelihood of gossip. A relation with a longerhistory leads to less gossip across all models, with the

exception of the cases where we consider isolatedbusiness transactions. This clearly supports Hypothesis

5. However, Hypothesis 6 is refuted. In all but theisolated business settings there is a positive effect of

having high expectations of the likelihood of doingfuture business with the same supplier on gossip,

contrary to our hypothesis. The more the respondentexpects to deal with this particular business partner in

the future, the more gossip occurs.A higher monitoring capacity indeed goes with an

increased likelihood of gossiping. The effect is not that

strong. Again we see that effects, if they exist, occur inthe embedded settings, giving Hypothesis 7 some

partial support.Finally, we find that our control variables do not

add much to the explanation of gossip: switching costs,transaction size, differences in power between supplier

and buyer, and whether the partner has a lowreputation, have no significant effect whatsoever on

the likelihood of gossip. We only find a small positiveeffect of the product’s complexity: more complex

products go with an increased probability of gossip.

Once again we find that the effect occurs mainly in an

embedded context.

Conclusion and Discussion

In this study we examined determinants of the

likelihood that managers will gossip, defined as talking

in a negative way about an absent business partner

with a third party. Contrary to what is commonly

thought, we show that gossip is a fundamental process

in the creation of reputations and can be used as a

viable governance mechanism. We tested hypotheses

about determinants of gossip using a dataset with

about 400 problematic transactions between German

buyers and suppliers. Consistent with the hypotheses,

it appears that gossip about a problematic transaction

is in general more likely when the problem is bigger

and more severe. Gossip is also more likely to occur if

the problematic transaction is embedded in a diverse

and dense enough network. Gossip is less likely when

monitoring problems for the buyer are high and occur

in existing business relations. Our findings are stronger

precisely in embedded relations, which highlights that

gossip can indeed be understood as (also) instrumental

and managerial in nature, as opposed to only an

emotional response based on feelings of being

double-crossed. This is somewhat surprising because

Table 5 Logistic regression models. Dependent variable¼GOSSIP

Variable Model-1 Model-2 Model-3 Model-4 Model-5

Problem size 0.44��� 0.41��� 0.29 0.15 0.46��

Opportunism 0.07 0.13 0.05 0.81 �0.02Outdegree 0.19���

Outd_big 1.00���� 0.90�� 0.70��

Past �0.19�� �0.17�� �0.26�� 0.04 �0.21���

Future 0.28� 0.29� 0.27 �0.06 0.36��

Monitor 0.23� 0.21 0.37�� �0.19 0.34��

Product Complexity 0.24� 0.21� 0.36�� �0.24 0.32��

Switching costs 0.08 0.08 0.18 0.24 0.09Transaction size 0.04 0.04 0.06 0.15 0.03Low repu.partner 0.23 0.30 0.72 0.04 0.46Power 0.10 0.10 0.14 0.03 0.10Density 0.65����

_cons �1.70���� �2.06���� �2.06���� �2.79���� �1.81����

N 387 387 212 115 272

Legend: �P50.10; ��P50.05; ���P50.01; ����P50.001.

Model 1: all main effects and controls included.

Model 2: dummy-variable OUTD_BIG (¼‘‘large outdegree’’) captures effect of outdegree.

Model 3: density added (decreasing N because of missing variables).

Model 4: as model 2, but estimated for isolated transactions [dummy NETWORK ACQUAINTANCE¼ 0].

Model 5: as model 2, but estimated for embedded transactions only [dummy NETWORK ACQUAINTANCE¼ 1].

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especially when gossip is the topic under study onemight think that personal and relational rather thaninstrumental or socioeconomic arguments play a majorrole. When we measure the closeness of the personalrelationship between the individuals involved in thedeal, using questions such as how well they know eachother, whether they know each other’s birthday, whatkinds of things they do together outside work, and soon, we find a strong scale (seven items, Mokken’sH¼ 0.70, alpha¼ 0.82). However, the closeness of thepersonal relation has no effect whatsoever, linear ornon-linear, on the likelihood of gossip. We feel thisstrengthens our results on the economic correlates ofgossip. Apparently, it is not just the case thatsocioeconomic variables might have an extra effect inaddition to a main relational effect (you gossip withthe ones you are close to). In fact the relational effectis simply not there and the socioeconomic variables arethe only ones correlating with gossip.

An unexpected finding was that gossip is more likelyin those cases where the expected future with the samebusiness partner is long. With hindsight, there are tworeasons we can think of that might be causing thisresult. First, a possible reason is that in such cases thetransaction partners expect their relation to continuebecause of the fact that they are likely to meet and dobusiness again. Given this, the relationship can with-stand some ‘noise’. In that sense, strongly interdepen-dent actors can benefit more from actively controllingand sanctioning each other because the risk of a breachis negligible. Another possible reason is based onanother instrumental advantage of gossip. Thus far, weemphasized that the instrumental advantage of gossipis based on maintaining the sanctioning system anddeliberately harming the reputation of the other party.This argument loosely follows the typical logic ofconditional cooperation and game-theoretic rationality(although sanctioning itself creates a second-order freerider problem that we neglected). However, there isanother kind of instrumental purpose of gossip. That isthat one might want to use gossip to test or calibrateone’s own opinions about the other party (Gambetta,1994, p. 213; Gulati and Westphal, 1999, pp.: 481–482;). The aim then is to gain or renew informationabout the capacities and credibility of the businesspartner, information that is otherwise difficult toobtain (cf. Levin and Arluke, 1987; Michelson andMouly, 2004, p. 195). In such a way gossip may help tobecome more certain about the partner (Labianca,Brass and Gray, 1998). The more likely it is that futurebusiness with the same partner can occur, the morenecessary it is to be certain about the business partner,and the more likely it is that gossip will occur.

Although we are aware that the measurement of such

intentions is notoriously difficult in a survey (cf. Jaeger

et al., 1994), in particular when the topic itself, gossip,

might have a dubious connotation (Fine and Rosnow,

1978; Michelson and Mouly, 2004, pp. 196–199), we

have some evidence that is consistent with this claim.

When asked why there had been talk with a third

party, one out of every four gossipers gave the

instrumental reason ‘‘we wanted to warn third parties

for the misconduct of the supplier.’’ Three out of four

did not make an explicit reference to such an informal

sanctioning intention. However, the vast majority of

these other gossipers (79 per cent) had other instru-

mental reasons to gossip. They stated that they

‘‘wanted to get information of third parties concerning

opinions on such misconduct or on such problems

occurring.’’ Only a small minority of these other

gossipers (the remaining 21 per cent) did not make

such a reference to an intention to calibrate. For these

others, gossip was simply small talk. When we redo

our analyses and confine ourselves to only the cases

where informal sanctioning intentions were mentioned,

the positive effect of the shadow of the future largely

disappears. And, the positive effect of the shadow of

the future on gossip surfaces precisely in those cases

where no explicit reference to such an informalsanctioning intention was given.

Another intriguing finding in the light of standard

theories of business interaction is that we find not

much evidence of a separate role of opportunism in

predicting gossip. That is, when the business partner

has behaved opportunistically there will of course be

more problems, and when there are more problems

there is a higher likelihood of gossip. But, the fact that

the problem was largely caused by opportunistic

behaviour has no separate effect after controlling for

the number and severity of problems that it caused.

We leave it up to the reader whether this particular

finding is in line with standard economic theory,

transaction cost theory, or other theories of the firm.

We feel that it largely corroborates those theories

arguing that opportunistic behaviour can lead to

problems that should be managed efficiently through

transaction governance. When, as we find in our data,

there is no separate effect of opportunism remaining,

apparently the number and size of problems that

occurs mediates the effect of opportunism on gossip.

Or, stated differently, we find no effect of a psycho-

logical effect of opportunistic behaviour: it is not the

case that buyers are more likely to gossip when the

cause of the problem is opportunistic behaviour: it is

the fact that there is a problem that matters.

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In his overview on gossip Gambetta (1994, pp. 199–200) reaches the conclusion that it is hard to find aphenomenon which has been attributed as manyfunctions as gossip has. In future studies, an additionalunderstanding of the role of gossip could be gainedfrom distinguishing between different kinds of sanc-tions in more detail. Preliminary analyses on our datasuggest that all findings are stronger when we onlyconsider gossip that was intended to harm the buyer ina network context (for instance, a buyer explicitly talksto other clients of the seller, in an attempt to preventthe client from choosing that particular seller again).In these cases, gossip truly functions as a managementinstrument, as opposed to mere small talk. A morefine-grained measurement instrument is necessary tobe able to disentangle the different roles that gossipcan have.

This study has a number of obvious weaknesses.A first one is that the current dataset containsno information about the third party with whomthere was talk about the problematic transaction.Who was informed about the problematic transactionand what was said? How strong was the relationshipof the buyer and the supplier with this third party?Only future research can help answer such questions.Future research may also reveal more details aboutthe process of gossiping in business networks andthe general issue of the effectiveness and efficiencyof gossip as a management tool. Data collection thatis more elaborate than ours might be necessary. Asa suggestion for future research one could think ofa longitudinal research design, following a relativelylarge number of firms, each and every one with a(limited, but more than just one or two) numberof transactions, for a longer time. An additionaladvantage of such a longitudinal approach would bethat both the dyadic embeddedness of thebuyer-supplier relation, the network embeddedness(cf. Buskens, Batenburg and Weesie, 2003, p. 128)and the social process of gossiping could be followedmore closely.

A second weakness is that although with 400 casesand 200 business networks the dataset is relatively largeand detailed for a survey analysis on this topic, thesample is limited to (two regions within) Germany(Halle/Leipzig and Munich). We see no obvious reasonwhy our results would be confined to only thisparticular research setting, but they might be. Anobviously interesting question is whether these resultscan be replicated using data collected in othercountries and other types of networks, in particularbecause cultural differences might play an importantrole. Recently, Henrich et al. (2006, p. 1770) find that

the degree of sanctioning of uncooperative behaviourvaries substantially among human societies, and intheir comparative study of German and Dutch businesstransactions. Rooks and Matzat (2010, forthcoming)find that some aspects of social embeddedness havedifferent effects on trust and the severity of ex postconflict resolution in the two countries. In theirexplanation they explicitly refer to cultural differencesbetween Germany and the Netherlands. Such differ-ences may be found not only between countries, butalso within countries as well: between regions, businessnetworks, and/or organizations. Concerning the use ofgossip in business networks, more elaborate quantita-tive empirical research can shed light on such issues.

A third weakness may be found in the possibleresponse bias in the measurement of some focalvariables, partly due to the single informant approachthat was used in this study. To enhance the externalvalidity of the measurements one could think of atriangulated methodology using a multiple informantapproach (cf. Rooks, Raub and Tazelaar, 2006, p. 267),asking several informants within the focal organization,or collecting data on both sides of the dyad, thusincluding the buying as well as the supplying perspec-tive. In our case the most knowledgeable personavailable in the buying company was contactedand interviewed. Although the multiple informantapproach is intuitively appealing, the potential benefitscan be disputed. The few studies that are availablepresent contradictory results on the existence ofperceptual differences between actors on differentsides of the dyad (Van der Vijver, 2009: 49). Theempirical findings presented by Barnes et al. (2007)support the view that buyers and sellers often sharecommon views within relationships. The perceptualgaps between the parties tend to be small, withsuppliers overall having stronger views of the relation-ship than the buyers (Barnes, Naude and Michell,2007, p. 666). Van der Vijver (2009) however does findsome perceptual differences: suppliers as a category areless negative than the buyers (Van der Vijver, 2009,pp. 57–62). Secondly, there are convincing reasonsfor using single informants in survey research onbusiness relations and transactions, such as thereluctance to get permission to interview businesspartners, practical problems of obtaining answers frommultiple informants, and the limited knowledgeabilityof informants. (cf. Blumberg, 1998, pp. 99–100;Tatikonda and Montoya-Weiss, 2001; Capron andHulland, 1999).

Our findings may have notable ramifications fortheories about network governance (Jones, Hesterlyand Borgatti, 1997: 924; Lorenz, 1999; Buskens, 2002).

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Network governance is defined as coordination and

cooperation characterized by informal social systems

rather than by formal contractual relationships. Our

results reveal evidence for the strategic and instrumen-

tal use of gossip in a business context, adding one

potential tool to the network governance toolbox.

This suggests the natural follow-up question which

kind of governance, either formal or informal, works

best under which conditions. Although in principle our

data could be used for a rough comparison, an

improved understanding of the different ways in

which gossip can be and is implemented, would be

necessary for such an endeavor.

Notes

1. Gambetta (1994) acknowledges that the work of

Coleman (1990) and Ellickson (1991) forms a

solid starting point: publications ‘‘in which gossip

constitutes a device which both aids in establish-

ing a norm and overcomes the second-order

public-good problem of sanctioning’’ (Coleman,

1990, p. 284), while Ellickson (1991) offers

evidence that some people seem conscious of the

role of gossip in social control and report using it

intentionally (Ellickson, 1991, p. 57).

2. We acknowledge that talk about positive events

can be an important element of gossip as well.

However, the dataset that will be used to test the

hypotheses does not contain information on

positive talk, and hence does not permit us to

study positive talk empirically. Note also that in

studies of reputation effects most often the focus

is on the spread of information about untrust-

worthy or opportunistic behaviour (e.g. Lorenz,

1988; Rooks et al., 2000; Blumberg, 2001; Gierl

and Baumbacher, 2002; Buskens, 2002).

3. Based on their empirical research on purchasing

management and buyer–supplier relations in the

Netherlands, Rooks and Snijders (2001) and

Snijders and Tazelaar (2009) come to the conclu-

sion that informing third parties should not be

categorized as ‘a first mild step’ in a cascade of

sanctions ranging from light to heavy, but as one

of the last and rather heavy steps in problem

resolution between business firms.

REFERENCES

Baker, J. S. and Jones, M. A. (1996). The poison

grapevine: how destructive are gossip and rumor in

the workplace. Human Resource Development

Quarterly, 7, 75–86.Barnes, B. R., Naude, P. and Michell, P. (2007).

Perceptual gaps and similarities in buyer-seller

dyadic relationships. Industrial Marketing

Management, 36, 662–678.Batenburg, R. S. (1997). The External Management Of

Automation 1995: Codebook of MAT95. ISCORE

Paper No. 58, Department of Sociology, Utrecht

University.Batenburg, R. S. and Raub, W. (1995). The External

Management of Automation - Codebook of MAT95.

ISCORE Paper, 1996, Utrecht University.Batenburg, R. S., Raub, W. and Snijders, C. C. P.

(2003). Contacts and contracts: dyadic embedded-

ness and the contractual behavior of firms.

Research in the Sociology of Organizations, 20,

135–188.Batenburg, R. S. and Van de Rijt, A. (1998). The

External Management of Automation 1998:

Codebook of MAT98. ISCORE Paper No. 155,

Department of Sociology, Utrecht University.Berger, R., Kropp, P. and Voss, T. (2001/2). [in

German] Das Management des EDV-Einkaufs.

Soziale Einbettung und Gestaltung wirtschaftlicher

Transaktionen. Eine empirische Untersuchung am

Beispiel der Beschaffung informationstechnischer

Leistungen und Produkte durch Klein und

Mittelbetriebe. Abschlussbericht and die deutsche

Forschungsgemeinschaft. Leipzig: Arbeitsbericht des

Instituts fur Soziologie (2001)/ISCORE Paper

No.198 (2002), Utrecht University.Berger, R., Kropp, P. and Voss, T. (2002). [in German]

Das Management des EDV-Einkaufs 1999.

Codebook. ISCORE Paper No. 199, Utrecht

University.Bernard, H. R. et al. (1985). On the validity of

retrospective data: the problem of informant

accuracy. Annual Review of Anthropology, 13,

495–517.Blumberg, B. F. (1998). [in German] Management von

Technologiekooperationen: Partnersuche und vertra-

gliche Planung. Wiesbaden: Gabler Verlag/

Deutscher Universitats-Verlag.Blumberg, B. F. (2001). Cooperation contracts between

embedded firms. Organization Studies, 22, 825–852.Bolton, G. E., Katok, E. and Ockenfels, A. (2005).

Cooperation among strangers with limited

GOSSIP AND REPUTATION IN BUSINESS NETWORKS 103 at U

niversity Library Utrecht on F

ebruary 11, 2011esr.oxfordjournals.org

Dow

nloaded from

information about reputation. Journal of PoliticalEconomy, 89, 1457–1468.

Burt, R. S. (2005). Brokerage and Closure. Oxford:Oxford University Press.

Burt, R. S. (2008). Commerages et reputation [‘Gossipand reputation’]. In Lecoutre, M. and Lievre, P.

(Eds.), Management et Reseaux Sociaux: RessourcePour l’Action ou Outil de Gestion? London:Hermes-Lavoisier, pp. 27–42.

Burt, R. S. and Knez, M. (1996). Trust and third-party

gossip. In Kramer, R. M. and Tyler, T. M. (Eds.),Trust in Organizations. Frontiers of Theory andResearch. Thousand Oaks/London: SagePublications, pp. 68–89.

Buskens, V. (2002). Social Networks and Trust. Boston,

MA: Kluwer.Buskens, V., Batenburg, R. S. and Weesie, J. (2003).

Embedded partner selection in relations betweenfirms. Research in the Sociology of Organizations, 20,

107–134.Capron, L. and Hulland, J. (1999). Redeployment of

brands, sales forces, and general marketing man-agement expertise following horizontal acquisi-

tions: a resource-based view. Journal of Marketing,63, 41–54.

Coleman, J. S. (1988a). Free riders and zealots: therole of social networks. Sociological Theory, 6,52–57.

Coleman, J. S. (1988b). Social capital in the relationsof human capital. American Journal of Sociology, 94,S95–S120.

Coleman, J. S. (1990). Foundations of Social Theory.

Cambridge, MA: Belknap.Coleman, J. S. (1991). Constructed organization:

first principles. Journal of Law, Economics andOrganization, 7, 7–23.

Davenport, N., Schwartz, R. D. and Elliott, G. P.(1999). Mobbing: Emotional Abuse in the AmericanWorkplace. Ames (IO): Civil Society Publishing.

Eder, D. and Enke, J. L. (1991). The structure of

gossip: opportunities and constraints on collectiveexpressions among adolescents. AmericanSociological Review, 56, 494–508.

Ellickson, R. (1991). Order without Law. HowNeighbors Settle Disputes. Cambridge, MA:

Harvard University Press.Emler, N. (1994). Gossip, reputations, and social

adaption. In Goodman, R. and Ben-Ze’ev, A.(Eds.), Good Gossip, Kansas: University Press of

Kansas, pp. 117–138.Falk, A., Fehr, E. and Fischbacher, U. (2005). Driving

forces behind informal sanctions. Econometrica, 73,2017–2030.

Fine, G. A. and Rosnow, R. L. (1978). Gossip,gossipers, and gossiping. Personality and Social

Psychology Bulletin, 4, 161–168.Fu, Y-C. (2003). Measuring personal networks with

daily contacts: a single-item survey question andthe contact diary. Social Networks, 27, 169–186.

Gambetta, D. (1994). Godfather’s gossip. Archives

Europeennes de Sociologie, 35, 199–223.Gierl, H. and Bambauer, S. (2002). Information

networks as a safeguard from opportunism inindustrial supplier-buyer relationships.Schmalenbach Business Review, 54, 335–350.

Gluckman, M. (1963). Gossip and scandal. CurrentAnthropology, 4, 307–316.

Granovetter, M. (1985). Economic action, socialstructure, and embeddedness. American Journal ofSociology, 91, 481–510.

Gulati, R. and Westphal, J. D. (1999). Cooperative orcontrolling? The effects of CEO-board relationsand the content of interlocks on the formation ofjoint ventures. Administrative Science Quarterly, 44,473–506.

Henrich, J. et al. (2006). Costly punishment acrosshuman societies. Science, 312, 1767–1770.

Jaeger, M. E. et al. (1994). Gossip, gossipers, gossipees.In Goodman, R.F. and Ben-Ze’ev, A. (Eds.), GoodGossip. Lawrence, KS: University Press of Kansas,

pp. 154–168.Jones, C., Hesterly, W. S. and Borgatti, S. P. (1997). A

general theory of network governance: exchangeconditions and social mechanisms. Academy ofManagement Review, 22, 911–945.

Kalleberg, A. L. et al. (1996). Organizational propertiesand practices. In Kalleberg, A. L., Knoke, D.,Marsden, P. V. and Spaeth, J. L. (Eds.),Organizations in America: Analyzing theirStructures and Human Resource Practices.Thousand Oaks, CA: Sage, pp. 3–22.

Kaufman, P. J. and Stern, L. W. (1988). Relationalexchange norms, perceptions of unfairness, andretained hostility in commercial litigation. Journalof Conflict Resolution, 32, 534–552.

Kreps, D. M. (1990). Corporate culture and economic

theory. In Alt, J. E. and Shepsle, K. A. (Eds.),Perspectives on Positive Political Economy.Cambridge, MA: Cambridge University Press,pp. 90–143.

Kurland, N. B. and Pelled, L. H. (2000). Passing theword: toward a model of gossip and power in the

workplace. Academy of Management Review, 25,428–438.

Labianca, G., Brass, D. J. and Gray, B. (1998).Social networks and perceptions of inter-group

104 ROOKS, TAZELAAR AND SNIJDERS at U

niversity Library Utrecht on F

ebruary 11, 2011esr.oxfordjournals.org

Dow

nloaded from

conflict: the role of negative relationships and thirdparties. Academy of Management Journal, 41, 56–67.

Levin, J. and Arluke, A. (1987). Gossip: The InsideScoop. New York: Plenum.

Lorenz, E. H. (1988). Neither friends nor strangers:informal networks of subcontracting in Frenchindustry. In Gambetta, D. (Ed.), Trust: Making and

Breaking Cooperative Relations. Oxford: BasilBlackwell, pp. 194–210.

Lorenz, E. (1999). Trust, contract and economiccooperation. Cambridge Journal of Economics, 23,301–315.

Macaulay, S. (1963). Non-contractual relations inbusiness. American Sociological Review, 28, 55–67.

McAndrew, F. T. and Milenkovic, M. E. (2002). Oftabloids and family secrets: the evolutionarypsychology of gossip. Journal of Applied Social

Psychology, 32, 1064–1082.Merry, S. E. (1984). Rethinking gossip and scandal. In

Black, D. (Ed.), Toward A General Theory of SocialControl: Fundamentals. Orlando, FL: AcademicPress, pp. 271–302.

Michelson, G. and Mouly, V. S. (2004). Do loose lipssink ships? The meaning. antecedents and con-sequences of rumour and gossip in organizations.Corporate Communications: An InternationalJournal, 9, 189–201.

Morgan, R. M. and Hunt, S. D. (1994). Thecommitment-trust theory of relationship market-ing. Journal of Marketing, 58, 20–38.

Nee, V. and Ingram, P. (1998). Embeddedness andbeyond: institutions, exchange, and social structure.In Brinton, M.C. and Nee, V. (Eds.), The New

Institutionalism in Sociology. New York: RussellSage Foundation, pp. 19–45.

Noon, M. and Delbridge, R. (1993). News from behindmy hand: gossip in organizations. OrganizationStudies, 14, 23–36.

Nunnaly, J. C. (1978). Psychometric Theory. New York:McGraw-Hill.

Provan, K. G. and Skinner, S. J. (1989). Interorganiza-tional dependence and control as predictors ofopportunism in dealer-supplier relations. Academy

of Management Journal, 32, 202–212.Putnam, R. D. (1993). Making Democracy Work.

Princeton. NJ: Princeton University Press.Raub, W., Rooks, G. and Tazelaar, F. (2007).

[in German] Ertrage des Sozialkapitals in zwischen-

betrieblichen Beziehungen: eine empirisch-theore-tische Studie. In Franzen, A. und Freitag, M. (Hrg.)Sozialkapital. Grundlagen und Anwendungen,Kolner Zeitschrift fur Soziologie undSozialpsychologie, Sonderheft, 47, 241–271.

Raub, W. and Weesie, J. (1990). Reputation andefficiency in social interactions: an example ofnetwork effects. American Journal of Sociology, 96,

626–654.Richman, B. D. (2004). Firms, courts, and reputation

mechanisms: towards a positive theory of privateordering. Columbia Law Review, 104, 2328–2368.

Riesewijk, B. and en Warmerdam, J. (1988). [in Dutch]Het slagen en falen van automatiseringsprojecten

[‘‘Succes and failure of projects of automation’’].Nijmegen: Instituut voor Toegepaste SocialeWetenschappen.

Rooks, G. (2002). [in Dutch] Contract en conflict.Strategisch management van inkooptransacties.[‘‘Contract and conflict. Strategic management inpurchasing’’] Dissertation. Amsterdam: ThelaThesis.

Rooks, G. and Matzat, U. (2010, forthcoming). Cross-national differences in effects of social embedded-ness on trust: a comparative study of German andDutch business transactions. The Social ScienceJournal.

Rooks, G. et al. (2000). How inter-firm cooperationdepends on social embeddedness: a vignette study.Acta Sociologica, 43, 123–137.

Rooks, G., Raub, W. and Tazelaar, F. (2006). Ex postproblems in buyer–supplier transactions: effectsof transaction characteristics, social embeddedness,and contractual governance. Journal ofManagement and Governance, 10, 239–276.

Rooks, G. and Snijders, C. (2001). The purchase ofinformation technology products by Dutch SMEs:problem resolution. The Journal of Supply ChainManagement, 37, 34–41.

Snijders, C. and Tazelaar, F. (2009). [in Dutch]Klapschaatsen in management [‘‘Klapskates in

management’’]. Leidschendam: Quist Uitgevers.Stirling, R. B. (1956). Some psychological mechanisms

operative in gossip. Social Forces, 34, 262–267.Tatikonda, M. V. and Montoya-Weiss, M. M. (2001).

Integrating operations and marketing perspectivesof product innovation: the influence of organiza-

tional process factors and capabilities on develop-ment performance. Management Science, 47,151–172.

Therrien, D. (2004). Rid your office of back-stabbers.Canadian Business, 77, 109–110.

Van der Vijver, M. A. G. (2009). Collaboration in

Buyer-Supplier Relationships. Dissertation, Tilburg:Tilburg University.

Waddington, K. and Michelson, G. (2007). AnalysingGossip to Reveal and Understand PowerRelationships, Political Action and Reaction to

GOSSIP AND REPUTATION IN BUSINESS NETWORKS 105 at U

niversity Library Utrecht on F

ebruary 11, 2011esr.oxfordjournals.org

Dow

nloaded from

Change Inside. Paper for the CMS Conference,Manchester, July 2007.

Williamson, O. E. (1985). The Economic Institutions ofCapitalism. New York: Free Press.

Williamson, O. E. (1991). Economic institutions:spontaneous and intentional governance. Journalof Law, Economics, and Organization, 7, 159–187.

Williamson, O. E. (1996). The Mechanisms ofGovernance. New York: Oxford University Press.

Wilson, D. S. et al. (2000). Gossip and other aspects oflanguage as group-level adaptions. In Heyes, C.(Ed.), Cognition and Evolution. Cambridge, MA:MIT Press, pp. 347–366.

Wittek, R. (1999). Interdependence and InformalControl in Organizations. Amsterdam: Thesis.

Wittek, R. and Wielers, R. (1998). Gossip in organi-zations. Computational and MathematicalOrganization Theory, 4, 189–204.

Authors’ Addresses

Gerrit Rooks (to whom correspondence should be

addressed), School of Innovation Sciences,

Eindhoven University of Technology, P.O. Box

513, 5600 MB, Eindhoven, The Netherlands, Tel:

þ31 40 247 5509, Email: g.rooks@tue.nlFrits Tazelaar, Department of Sociology, Utrecht

University, P.O. Box 80.140, 3508 TC Utrecht,

The Netherlands, Email: f.tazelaar@uu.nlChris Snijders, School of Innovation Sciences,

Eindhoven University of Technology, P.O. Box

513, 5600 MB Eindhoven, The Netherlands,

Email: c.c.p.snijders@tue.nl

Manuscript received: June 2009

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