0. Using Complementary Research Designs: The Example of Effects of Social Embeddedness on Trust and Cooperation
Werner Raub
Workshop on Social Theory, Trust, Social Networks, and Social Capital II National Chengchi University – NCCU April 2011

1. Overview Theory Trust problems in economic exchange
Embeddedness effects on trust
2. Empirical evidence from studies using different and complementary research designs
A survey on buyer-supplier relations
A vignette study on buyer-supplier relations

2. Background: a rational choice perspective on embeddedness effects
“… while the assumption of rational action must always be problematic, it is a good working hypothesis that should not easily be abandoned. What looks to the analyst like nonrational behavior may be quite sensible when situational constraints, especially those of embeddedness, are fully appreciated […] My claim here is that however naive that psychology [of rational choice] may be, this is not where the main difficulty lies – it is rather in the neglect of social structure.”
Mark Granovetter (1985) Economic Action and Social Structure: The Problem of Embeddedness
This is a quote from Mark Granovetter’s meanwhile classic paper. Granovetter nicely summarizes the spirit of the approach I’m going to employ.
Granovetter nicely highlights two features:
First, the focus on social conditions, namely, embeddedness characteristics, for behavior in the Trust Game and in economic exchange.
Second, the aim to explain behavior in trust problems and in economic exchange as much as possible as a result of “enlightened self-interest”, rather than as non-rational behavior and/or as a result of other than selfish preferences.
It is striking that Granovetter’s approach is very similar to Jim Coleman’s.

3. Empirical evidence on embeddedness effects from complementary research designs
Aim: use complementary research designs (survey, vignette study, lab experiment) for multiple tests of the same hypotheses (cf.: triangulation, cross validation)
Similar perspective:
Sociology: J.H. Goldthorpe (1996) The Quantitative Analysis of Large-scale Data Sets and Rational Action Theory: For a Sociological Alliance, ESR 12
Economics: G.W. Harrison & J.L. List (2004) Field Experiments, JEL 42(4)
This is about the core feature of my presentation from an empirical perspective.

4. Bringing rational choice models and empirical research closer together
In many respects, what I’m trying to do is to bring rational choice theory and empirical research in sociology a bit closer together.
The new feature of my talk compared to Goldthorpe’s well-known paper is that I suggest to conceive of “data analysis” more broadly, including not only survey data but also other and complementary research designs such as experiments and vignette studies.

5. Some theory

6. Let me start the theory part with a brief “appetizer”
Let me start the theory part with a brief “appetizer”. Later on, I will present quite some evidence from quantitative empirical studies on trust in economic exchange and trust in the lab. However, my appetizer comes from a meanwhile famous historical study on 19th century Germany.
This is Fritz Stern’s well-known monograph ‘Gold and Iron. Bismarck, Bleichröder and the Building of the German Empire’. The book appeared in 1977.
As I said, it’s a book about 19th century Germany. Bismarck became the German “Reichskanzler”. Gerson von Bleichröder was Bismarck’s private banker. The two men collaborated closely for many decades. In his Introduction (p. xv), Stern describes his study as follows: “This is a book about Germans and Jews, about power and money. It is a book focused on Bismarck and Bleichröder, Junker and Jew, statesman and banker, collaborators for over thirty years. The setting is that of a Germany where two worlds clashed: the new world of capitalism and an earlier world with its ancient feudal ethos; gradually a new and broadened elite emerged, and Bismarck’s tie with Bleichröder epitomized that regrouping. It is the story of the founding of the new German Empire, in whose midst a Jewish minority rose to embattled prominence.”

7. Fritz Stern,
Gold and Iron: Bismarck, Bleichröder, and the Building of the German Empire – 1
“In the private banking world of those days, personal ties were of the greatest importance. Common ventures depended on mutual trust, and that trust had to be established by direct personal knowledge.” (p. 9)
Two brief quotes from the book that are related to my talk:
The first quote: <READ SLIDE>

8. Fritz Stern,
Gold and Iron: Bismarck, Bleichröder, and the Building of the German Empire – 2
“In Bismarck’s world, then, Bleichröder was a welcome supplement to official channels (…) Bismarck used him freely and continuously as a special emissary, as an additional and informal link to foreign powers and statesmen. Statesmen always like to have a multiplicity of contacts – to solicit reactions, to convey hints, to reinforce threats or allay fears.” (p. 311)
I’ll briefly return to these two quotes later on in my talk.
My point will be that the social situations illustrated in these two quotes are structurally similar to the social situations I’m going to focus on. Also, the core theoretical assumptions on human behavior employed by Stern are quite close to the theory I’ll develop in this talk.

9. Trust Game as a stylized model of exchange
Trustee (supplier)
Trustor (buyer)
No trust
Trust
Honor
Abuse
S1 < P1 < R1
P2 < R2 < T2
Theoretical background
From now on, I use the Trust Game as a stylized model of social and economic exchange.
In the rest of the talk, I apply this model specifically to buyer-supplier relations.
<CONTINUE WITH ADDITIONAL NOTES PAGES>

10. Substantive interpretation of the Trust Game for buyer-supplier relations
Moves of the trustor (buyer)
No trust: safeguard transaction with an extensive but costly contract
Trust: use less extensive and less costly contractual safeguards
Moves of the trustee (supplier)
Honor trust: deliver appropriate quality and deliver in due time
Abuse trust: deliver inferior quality and/or deliver with a delay
This is how I interpret the Trust Game for the case of buyer-supplier relations.
I assume that the buyer is in the role of the trustor, while the supplier is the trustee.

11. Extensions of the Trust Game
More than only two moves for trustor and trustee (e.g., Investment Game)
Incomplete information of the trustor on incentives or opportunities of trustee for abusing trust
Ex post-problems due to incompetence of trustee or unfavorable external contingencies rather than abuse of trust (opportunism)
Incentives and opportunities for “defection” of trustor (e.g., delayed payment)
Etc.
Of course, a real life transaction often has features that are not covered by the simple model of the standard Trust Game. For example…
I don’t go into the details of modeling such more complex features. I focus on hypotheses that are quite similar for different versions of the Trust Game.

12. Relation with Stern’s historical study on Bismarck and his banker Bleichröder
Stern claims that interactions between private bankers involve trust problems.
Stern likewise claims that interactions between states and between politicians involve trust problems.

13. Embeddedness mechanisms
Dyadic
embeddedness
Network
Learning
Common history of past interactions:
information about the partner from own experiences
Information from third parties about their past experiences with the partner
Control
Expected future interactions:
opportunities for conditional cooperation via, e.g., “tit for tat”
Opportunities for conditional cooperation involving third parties: “voice” (reputation effects)
This is about embeddedness effects in Trust Games and in exchange.
I distinguish two types or levels of social embeddedness (the columns of the table):
First, dyadic embeddedness: a sequence of Trust Games between the same two players. For example: the buyer repeatedly purchases products from the supplier.
Second, network embeddedness. For example, a buyer as trustor has contacts with other customers of the supplier.
Dyadic embeddedness and network embeddedness provide at least two mechanisms for mitigating trust problems. I label these mechanisms “learning” and “control” (these are the rows of the table).
<CONTINUE WITH ADDITIONAL NOTES-PAGE>

14. Research problem Distinguish between different embeddedness effects
theoretically
empirically
We neglect:
strategic network formation: embeddedness is assumed to be exogenous
“non-selfish utility”: focus on trust as a result of “enlightened self-interest”
Now the underlying research problem becomes transparent.
We want to distinguish between different embeddedness effects on trust and we want to do so
theoretically
as well as
empirically
Note: There is much theoretical emphasis on embeddedness effects in economic sociology and in organization studies. There is also quite a bit of empirical evidence that such effects exist. However, the problem is hardly addressed until now how embeddedness affects trust and through which mechanisms this works.
I also mention here, what I neglect completely in the following. First, networks are assumed to be exogenous.
I focus exclusively on network effects. I disregard network dynamics and strategic network formation.
Second, I focus exclusively on trust and trustworthiness as a result of “enlightened self-interest”. I neglect non-standard utility assumptions like assumptions on social preferences, inequity aversion, and the like.

15. Trust and Embeddedness
Fritz Stern,
Gold and Iron: Bismarck, Bleichröder, and the Building of the German Empire – 1
Trust and Embeddedness
“In the private banking world of those days, personal ties were of the greatest importance. Common ventures depended on mutual trust, and that trust had to be established by direct personal knowledge.” (p. 9)
Note Stern’s claim: dyadic embeddedness affects trust.
Let us briefly return to the quotes from Stern’s book on Bismarck and his banker Bleichröder.

16. Trust and Embeddedness
Fritz Stern,
Gold and Iron: Bismarck, Bleichröder, and the Building of the German Empire – 2
Trust and Embeddedness
“In Bismarck’s world, then, Bleichröder was a welcome supplement to official channels (…) Bismarck used him freely and continuously as a special emissary, as an additional and informal link to foreign powers and statesmen. Statesmen always like to have a multiplicity of contacts – to solicit reactions, to convey hints, to reinforce threats or allay fears.” (p. 311)
Note Stern’s claim: Network embeddedness allows for learning and control (informal reciprocity).
My claim would be that the theory I’m sketching here, when elaborated in more detail, complements propositions such as Fritz Stern’s in at least two useful ways:
First, the theory allows to integrate such propositions in a more general theory of incentive-guided behavior. This also allows to make such propositions more precise by highlighting conditions under which such propositions do or do not apply.
Second, the theory shows that such propositions – or related propositions – are likewise applicable in very different contexts.

17. Available formal theories
Dyadic
embeddedness
Network embeddedness
Learning
Adaptive learning models;
information diffusion models
Learning and control
Models for repeated games with incomplete information
Control
Models for repeated games with complete information
This is a rough overview of available formal theories on embeddedness effects.
We can distinguish three types of work:
First, there are various types of learning models as well as information diffusion models that can be used to generate hypotheses on learning effects on trust through embeddedness. These models abstract from control effects.
Second, there are game-theoretic models such as repeated games with complete information that can be used to generate hypotheses on control effects. Most of these models focus on dyadic embeddedness. There are also some models that include network embeddedness. These models abstract from learning effects.
Third, there are models such as finitely repeated games with incomplete information. These models address learning and control simultaneously. These are also typically models for dyadic embeddedness. There are only few models that also address network embeddedness.

18. Examples of hypotheses
Effects of dyadic embeddedness:
Trust increases with positive experiences of trustor with trustee (learning effect)
Trust and trustworthiness increase with expected future transactions (control effect)
Effects of network embeddedness:
Trust increases with positive information of trustor on trustee from third parties (learning effect)
Trust and trustworthiness increase with sanction opportunities of trustor (e.g., “voice”) involving third parties (control effect)
Now I make a large step and jump to hypotheses. These are hypotheses on major effects on trust through dyadic embeddedness and through network embeddedness that follow from or are at least consistent with different learning and control models.
It is perfectly conceivable to come up with additional hypotheses. However, these are the hypotheses on which I’m going to focus in this talk.

19. Empirical evidence
Let’s now move on to empirical evidence.

20. Evidence from a survey, a lab experiment, and a vignette study
Advantages
Disadvantages
Survey
Actual interactions
Measurement problems; less control over variables
Lab experiment
Control over incentives and embeddedness variables
Abstract; external validity
Vignette study
Less abstract than lab experiments; control over variables
Hypothetical interactions; lack of “incentive compatibility”
This slide refers to the major methodological message of the talk.
I present evidence from a number of studies, three in total. These studies use very different research designs: a survey study, a vignette study, and a lab experiment.
Each of these designs has advantages and disadvantages.
Underlying idea here is to use different and complementary designs to collect indicators for basically the same set of independent and dependent variables. Thus: to use different and complementary designs for repeated empirical tests of basically the same set of hypotheses. Aim: check for robustness of findings.
<COMMENT ON THE DIFFERENT DESIGNS AND THEIR ADVANTAGES AND DISADVANTAGES>
Conceiving of “quantitative analysis of data” more broadly: not only survey data, but also experimental designs and quasi-experimental designs such as vignette studies.

21. A survey on IT-transactions
Evidence on effects of
dyadic embeddedness:
A survey on IT-transactions
More information:
Batenburg, Raub & Snijders (2003) Contacts and Contracts: Dyadic Embeddedness and the Contractual Behavior of Firms, Research in the Sociology of Organizations 20:
This is the major reference to more information on our survey study.
More precisely, this is a survey on a specific kind of transactions in buyer-supplier relations, namely transactions involving IT-products.

22. A survey on IT-transactions
Data on the purchase of hard- and software, standard and complex products
ca 1000 transactions (“Trust Games”)
ca 800 buyers (trustors): Dutch SMEs
600+ suppliers (trustees)
various replications and extensions of the study in the Netherlands and Germany
We have collected survey-data on the purchase of IT-products (hard- and software). These are data on approximately 1000 purchases of such products by approximately 800 Dutch small- and medium-sized enterprises. Each of these transactions is assumed to be a Trust Game between buyer and supplier, with the buyer in the role of the trustor and the supplier in the role of the trustee.
SMEs: Small and medium-sized enterprises.
The small and medium-sized enterprises are the buyers.
The survey focuses on how buyers cope with trust problems in their transactions with IT-suppliers.
Respondents are typically IT-managers of the buyer firm.
We replicated and extended this study various times in the Netherlands and also in Germany. I’ll neglect these replications and extensions in this talk.

23. Survey: variables and measurements I
Trust of buyer: “Lack of trust” measured by buyer’s costly INVESTMENTS IN CONTRACTING with supplier (person-days and departments involved, financial and legal clauses and technical specifications included in contract)
Dyadic learning: (positive) experiences of buyer from previous transactions with supplier – PAST
Dyadic control: expectations of buyer on future transactions with supplier – FUTURE
Basically, we consider an IT-transaction as a variant of a Trust Game with the buyer in the role of the trustor and the supplier in the role of the trustee.

24. Survey: variables and measurements II
Control variables:
Transaction characteristics (e.g., specific investments, uncertainty, volume)
Marginal costs of contracting
Characteristics of buyer and supplier, including respondent characteristics

25. Investments in contracting: assumptions I
IT transactions are associated with risks
Focus on risks of the buyer (such as delayed delivery, inferior quality etc.) due to:
opportunistic behavior of supplier
incompetence of supplier
external contingencies
Contracting as a device to mitigate risks:
reduction of incentives for opportunistic behavior of supplier
compensation for buyer if risks “materialize”
In the next step, I would like to provide some more intuition on theory, hypotheses, and empirical evidence by focusing on effects of dyadic embeddedness on trust in exchange.
In particular, I would like to focus on the hypothesis on the dyadic control effect.
As you will see, the reason for elaborating on the dyadic control effect is that we measure trust in this survey by using costly investments of time and money in the contractual safeguarding of a transaction as an indicator of “lack of trust”. This leads to some complications.
Let me briefly sketch how we can derive hypotheses on such investments in contractual planning.
<READ SLIDE>

26. Investments in contracting: assumptions II
Core assumptions for deriving hypotheses:
Investments in contracting are costly and actors will economize on these costs
Investments in contracting will increase in risks

27. Hypotheses on effects of dyadic embeddedness I
Effects of a positive past relationship:
Dyadic learning: reduced probability of supplier incompetence
Also: mutual relationship specific investments
Availability of costless safeguards from prior transactions (e.g., reuse of contract for a prior transaction)
Good working relations between employees of the two firms
 Decreasing investments in contracting

28. Hypotheses on effects of dyadic embeddedness II
Two effects of expected future transactions:
Reciprocity effect: conditional cooperation becomes an alternative for costly investments in contracting
Decreasing investments in contracting
Reusability effect: investments in contracting can be (partly) reused for future transactions (e.g., reuse of adapted version of the contract)
Increasing investments in contracting
Note: reusability effect larger when contractual safeguards are not yet available, i.e., larger for transactions without prior business between buyer and supplier
Two opposite effects of expected future transactions.
Empirical indication for reusability effect: about 50% of the transactions in the sample are transactions such that the buyer had already previously purchased products from the supplier. In about 25% of these cases, the contract for the focal transaction is a more or less adapted version of a contract for a previous transaction between buyer and supplier.

29. Hypotheses on effects of dyadic embeddedness III
Without additional assumptions on strength of reciprocity effect and reusability effect: no hypothesis on main effect of FUTURE on INVESTMENTS IN CONTRACTING
Due to larger reusability effect for transactions without prior business between buyer and supplier: negative interaction effect PAST x FUTURE on INVESTMENTS IN CONTRACTING (dyadic control)
This is how we expect to see “dyadic control” in the data on IT-transactions.

30. Survey: empirical evidence on effects of dyadic embeddedness
Robust result for various statistical models, for alternative operationalizations of variables, and controlling for transaction characteristics, marginal costs of contracting, and characteristics of buyer and supplier:
INVESTMENTS IN CONTRACTING decrease with:
PAST: positive past experiences of buyer
PAST x FUTURE: expected future transactions if positive past experiences exist
Support for hypotheses on dyadic learning and control effects

31. buyer-supplier relations
Evidence on effects of
dyadic embeddedness:
A vignette study on
buyer-supplier relations
More information:
Buskens & Raub (2002) Embedded Trust, Advances in Group Processes 19:
Our second study is a vignette study.
Again, you also find a core reference for more detailed information on this slide.

32. Data: a vignette study on buyer- supplier relations
Respondents: 40 purchase managers of Dutch medium-sized and large companies
Judgments on 348 virtual transactions (= vignettes; 8-10 vignettes per respondent)
Data on
transaction management
transaction characteristics
dyadic embeddedness
network embeddedness
characteristics of purchase managers
This is again a study on buyer-supplier relations.
We have data from 40 purchase managers of Dutch medium-sized and large companies.
These managers provided judgments on almost 350 virtual transactions. Each transaction is described on a separate vignette. These transactions are our data points.

33. Example of a vignette The transaction concerns a product:
vignette number: xxx
The transaction concerns
a product:
- about which your firm has only very limited expertise.
- for which there are no alternative suppliers on the market.
a transaction:
- with a small volume, namely, less than US$ 5.000,= on a yearly basis.
- where extra investments by your firm are not necessary.
a supplier:
- from the Netherlands.
- from whom your firm knows some business partners, but your firm does not do business with them.
- with whom your firm has had a relationship in which minor problems sometimes occurred.
- with whom your firm expects to do business for a long period.
This is an example of a vignette.
Each manager provided judgments on 8-10 of such virtual transactions or vignettes. The manager assessed how much time and effort would be invested in contractual planning of such a transaction.
The characteristics mentioned on the vignette represent our independent variables.
On the vignettes, we manipulate the characteristics and thus obtain variance in the values of the independent variables.
Example of a vignette

34. Buyer-supplier vignettes: variables
Value
Text
Volume 1 2
A transaction with a small volume, namely less than US$ on a yearly basis.
A transaction with a considerable volume, namely, about 5% of the total purchase volume of your firm.
A transaction with a very large volume, namely, 18% of the total purchase volume of your firm.
Specific
Investments
A transaction for which extra investments by your firm are not necessary.
A transaction for which your firm has to make small investments, such as investments in specific machines and equipment.
A transaction for which your firm has to make considerable in-vestments, such as investments in specific machines and equipment.
Uncertainty
A known product about which your firm has the required expertise.
A known product but one about which your firm has only limited expertise.
A brand new product about which your firm has only very limited expertise.
Past
A supplier with whom your firm has never done business before.
A supplier with whom your firm has a relationship in which minor problems occurred.
A supplier with whom your firm has a long and successful relationship.
Future
It is uncertain how long your firm will continue with the supplier.
Your firm expects to do business for a long period with the supplier.
Degree
You do not know any business partners of the supplier.
You know some business partners of your supplier, but your firm does not do business with them.
You do business with other business partners of the supplier.
Exit opportunities
A product for which there are no alternative suppliers on the market.
A product for which there are some alternative suppliers on the market.
A product for which there are many alternative suppliers on the market.
Country 3 4
A supplier from Eastern Europe.
A supplier from Japan.
A supplier from the United States.
A supplier from Germany.
A supplier from the Netherlands.
This is a complete overview of our independent variables and their possible values.

35. Buyer-supplier vignettes: variables and measurements I
Trust of buyer: “Lack of trust” measured for each vignette by buyer’s costly INVESTMENTS IN CONTRACTING with supplier (duration of negotiation with supplier and departments of buyer involved in negotiations)
Dyadic learning: (positive) experiences of buyer from previous transactions with supplier – PAST
Dyadic control: expectations of buyer on future transactions with supplier – FUTURE
Let’s have a brief look at our major variables.
Note that we measure trust or lack of trust in basically the same way as in our survey on IT-transactions.

36. Buyer-supplier vignettes: variables and measurements II
Control variables:
Transaction characteristics (e.g., specific investments, uncertainty, volume)
Characteristics of buyer and supplier, including respondent characteristics (e.g., experience with transactions like described on vignettes)

37. Buyer-supplier vignettes and survey on IT-transactions
Note:
Vignette study on buyer-supplier relations and survey on IT-transaction allow to test same hypotheses on effects of dyadic embeddedness with two different but complementary data sets based on different designs

38. Buyer-supplier vignettes: empirical evidence on effects of dyadic embeddedness
Robust result for various statistical models and controlling for transaction characteristics as well as respondent characteristics:
INVESTMENTS IN CONTRACTING decrease with:
PAST: positive past experiences of buyer
PAST x FUTURE: expected future transactions if positive past experiences exist
Renewed support for hypotheses on dyadic learning and control effects with data based on different research design

39. network embeddedness: survey on IT-transactions
Evidence on effects of
network embeddedness:
survey on IT-transactions
More information:
Rooks, Raub & Tazelaar (2006) Ex Post Problems in Buyer-Supplier Transactions, Journal of Management and Governance 10:

40. Survey: variables and measurements III
Network embeddedness:
DEGREE: ties of buyer with other buyers of supplier
SECTOR DENSITY: contacts among firms in business sector of buyer
VISIBILITY of supplier in the market (as assessed by buyer)
Note: these are indicators for network learning as well as network control opportunities (“voice opportunities”) of buyer

41. Survey: variables and measurements IV
Trustworthiness of supplier:
PERFORMANCE of supplier, e.g., delivery in due time, quality of product, quality of after-sales service (Rooks et al. (2006): EX POST PROBLEMS instead of PERFORMANCE)

42. Survey: empirical evidence on effects of network embeddedness on trustworthiness of supplier
Robust result for various statistical models and controlling for transaction characteristics, buyer’s INVESTMENTS IN CONTRACTING, and characteristics of buyer and supplier:
PERFORMANCE of supplier increases (i.e., EX POST PROBLEMS decrease) with network embeddedness (DEGREE, SECTOR DENSITY, VISIBILITY)
Support for hypotheses on network control effects on supplier (trustee) behavior

43. Survey: empirical evidence on effects of network embeddedness on trust of buyer
Robust result for various statistical models, for alternative operationalizations of variables, and controlling for transaction characteristics, marginal costs of contracting, and characteristics of buyer and supplier:
network embeddedness (DEGREE, SECTOR DENSITY, VISIBILITY) has no effect on buyer’s INVESTMENTS IN CONTRACTING
No support for hypotheses on network learning or control effects on buyer (trustor) behavior

44. Puzzle
Suppliers seemingly react to incentives from network embeddedness (suppliers seemingly take reputation effects of their performance into account).
How to explain that buyers seemingly do not anticipate on this feature?
Data and/or measurement problems (including sample selectivity and endogeneity of network embeddedness)?
Lack of “strategic rationality”?
The lack of network embeddedness effects on buyer behavior could be due to various data and measurement problems. I don’t go into the details now.
However, the lack of such effects could also have another source. Note: the focal trustor has to anticipate on how the trustee anticipates on the effects of his present behavior vis-à-vis the focal trustor on the future behavior of other trustors. And this may just be too many steps of iterated reasoning for the trustor.

45. Another summary of the puzzle
Trustee reacts to trustor’s opportunities for
dyadic control and
network control
Focal trustor reacts to her own opportunities for dyadic control: she seemingly anticipates that trustee anticipates on effects of his present behavior on future behavior of focal trustor
Focal trustor does not react to her own opportunities for network control: she seemingly does not anticipate that trustee also anticipates on effects of his present behavior on future behavior of other trustors

46. Another vignette experiment:
buying a used car
More information:
Buskens, V. & J. Weesie (2000) An Experiment on the Effects of Embeddedness in Trust Situations: Buying a Used Car, Rationality and Society 12:

47. Buying a used car
Buyer chooses between trust or no trust (buy or not buy).
Trust gives the dealer the opportunity to honor or abuse trust (sell a decent or inferior car). In both situations he is better off than when trust would not be placed
Buyer gains from honored trust, but regrets trust if trust is abused.
Dealer earns an extra profit from abusing trust (too much money for a bad car).

48. Variables to be manipulated and related hypotheses
Sanction opportunities w.r.t. third parties
Buyer’s sanction opportunities
Control
Prior third-party experiences
Prior buyer’s experiences
Learning
Network Embeddedness
Dyadic Embeddedness
Trust increases with
positive own experiences (dyad)‏
expected future transactions (dyad)‏
positive information from third parties (network)‏
sanction opportunities w.r.t. third parties (network)‏
We focus in this presentation on two mechanisms through which embeddedness can affect trust: learning and control. Both mechanisms can work at two levels: the dyad and the network.
Learning about capabilities, unknown properties of the supplier……
Control indicates sanction opportunities depending on the behavior of the dealer: positive or negative…….

49. The set-up of the vignettes
Pairs of vignettes including six variables.
Price
Past (own experience)‏
Future (own expected future interactions)‏
Density (general reputation)‏
Indegree (friends experiences)‏
Outdegree (own third-party sanction opportunities)‏
Subjects compare pairs of situations to buy a used car.
Some additional questions.

50. A pair of vignettes You can buy a car for $4000.
You never bought a car from The Autoshop before.
You will move to the other side of the country in a few weeks.
The Autoshop is an unknown garage in your neighborhood.
As far as you know, none of your friends have bought a car from The Autoshop before.
You do not have a close social link with the owner of The Autoshop.
You can buy a car for $4000.
You bought a car from The Autoshop before and you were satisfied.
You do not expect to move out of town soon.
The Autoshop is a well-known garage and has many customers in your neighborhood.
You have friends who bought a car from The Autoshop before and they were satisfied.
The owner of the garage and you are members of the same football team.

51. Experimental design Choices of pairs
Price is constant within a pair (only for interactions)
No “ordered” pairs (not too easy)‏
Between 2 and 4 variables that differ (not too complex)‏
Ten pairs per subject
Considerable variation in comparisons within subjects
Ultimately 125 students rating 1249 vignettes

52. Statistical model Random utility model.
Probit model on choices for vignettes.
Independent variables are the differences between the values at the vignettes (0: type of embeddedness to same on two vignettes, 1 or -1: type of embeddedness present on one vignette but not on the other)‏
Coefficients are interpretable as indicators for the increase in utility assigned to a vignette related to the given type of embeddedness
Standard errors modified for clustering (alternatively multilevel analysis could have been done)‏

53. Results: main effects

54. Results: interaction effects

55. Additional analyses No differences between sessions
No differences related to timing of a pair of vignettes or time spent on a decision
No effects of age, gender, field of study
Outdegree has larger effect for subjects who are more concerned about “reputation” issues
Subjects with knowledge of game theory tend to value control variables higher

56. Conclusion Support for main effects of embeddedness
control and learning
dyadic and in networks
No support for interaction effects

57. Discussion
Motivation of behavior (no direct incentives and students might not be experts)‏
Interpretation of variables
Future: moving has more side-effects than loss of sanction possibilities alone
Possible extension
Similar experiment with experts
Moving to an abstract laboratory experiment

58. Buyer-supplier vignettes
Overview of Results
Not tested +
Incentives
Dyadic control
Network control
learning and control hard to disentangle
Network learning
Dyadic learning
Used-car vignettes
Buyer-supplier vignettes
Short summary of the results.

59. Summary of empirical evidence
Survey
Vignette study
Lab
experiment
Dyadic
learning
Consistent support for dyadic learning and control effects on trust of trustor
control
Network learning
Quite some support for network learning effects on trust of trustor
Hardly support for network control effects on trust of trustor
Consistent support for network control effects on trustworthiness of trustee
Network
Summary and conclusion
This is a summary of the empirical evidence on embeddedness effects on trust from our three studies.
We find consistent support for dyadic learning effects on trustor behavior.
We find quite some evidence for dyadic control effects on trustor behavior and on trustee behavior.
We find not always but quite sometimes evidence for network learning effects on trustor behavior.
And we have the puzzle that there is consistent evidence for network control effects on trustee behavior, while we hardly find such effects on trustor behavior.
From a more methodological perspective, I tried to highlight the usefulness of employing complementary research designs for testing basically the same hypotheses.

60. Additional slides

61. survey on IT-transactions
Additional slides on
survey on IT-transactions

62. Survey on IT-transactions: data collection I
Nationally representative survey on the purchase of IT-products (hard- and software) by Dutch SMEs
Data collection via buyers
CATI-interview (selection of transaction)
Structured questionnaire, usually administered via site visit
Additional archival information, sometimes including a rough content analysis of contracts
Data quality
total response rate: 58%
non-response not selective
low partial non-response

63. Survey on IT-transactions: descriptives
‘Average transaction’:
a product worth 50,000 US-$
purchased by a firm with ca 80 employees
negotiating and contracting required ca 5 mendays of buyer’s employees…
and involved ca 2 divisions of buyer’s firm
for about two thirds of buyers, transaction is of ‘great’ or ‘very great’ importance for their IT-situation

64. Survey on IT-transactions: descriptives
Future

65. Survey on IT-transactions: variables I
Transaction characteristics (indicators for trust problems, opportunism problems, and other risks associated with the transaction), e.g., monitoring problems, switching costs, importance of durability of product, importance of product for profitability buyer, volume of transaction
Costs of contracting
E.g., in-house legal expertise
Dyadic embeddedness
Prior transactions with the supplier (duration, frequency, volume, satisfaction)
Expected future business (frequency, volume)

66. Survey on IT-transactions: variables II
Network embeddedness
Indicators for density of buyer’s network of business contacts
Relations of buyer with other clients of supplier
Availability of and relations of buyer with other suppliers
Various control variables
E.g., ‘demography’ of buyer and supplier, other suppliers involved in transaction…

67. Survey on IT-transactions: variables III
Ex ante management: search and selection
Investments in search
E.g., mendays, departments involved
Extensive and intensive search
E.g., number and specificity of offers, number and kind of information channels
used
Ex ante management: contractual planning
Investments in negotiating and contracting
Legal, financial, and technical issues addressed during negotiations and in the contract

68. Survey on IT-transactions: variables IV
Ex post management – contract execution
Supplier performance, ex post problems (type and seriousness)
conflict resolution (type and seriousness of sanctions, ‘legal’ vs. ‘extra-legal’)
New business between buyer and supplier after focal transaction

69. Independent Variables Hypothesis Coefficient |t-value|
This is a representative OLS-regression on investments in contractual planning.

70. Standardized Coefficients from the Ordinary Least Squares Regression on management
Independent Variables
Hypothesis
Coefficient
|t-value|
Dyadic Embeddedness
Past (1 = yes) –
–0.09**
3.12
Future ?
0.05
1.28
Past × Future –
–0.12**
3.33
Here you see the effect of positive past experiences.
And you also see the interaction effect of previous transactions and expected future business.
These results are quite stable over a broad range of implementations of the analysis, for different operationalizations of our variables and for different statistical models.
This ‘message 2’ of the talk.
Of course, you may now tend to think “first these guys found the interaction effect in their data and then they figured out some ad hoc theory on such an effect”. I will return to this suspicion in a minute.

71. These are results from a representative analysis.

72. Three-Stage Least Squares Regression Analysis of EX POST PROBLEMS
TABLE 2
Three-Stage Least Squares Regression Analysis of EX POST PROBLEMS
(1205 transactions of 775 buyers)
-0.085**
(0.034)
-0.088** –
EXIT NETWORK
-0.054*
(0.028)
-0.052*
VISIBILITY
-0.055*
(0.029)
-0.068**
SECTOR DENSITY
-0.059*
(0.035)
-0.063*
DEGREE
0.066*
(0.032)
0.054~
(0.031)
EXPECTED FUTURE
-0.206***
(0.038)
SATISFACTION*
-0.045~
(0.033)
-0.042 ?
PAST
Embeddedness characteristics
Model 2
Model 1
Hypothesis
Variable
Here you see that network embeddedness of the buyer is associated with less ex post problems after the transaction and is thus associated with better supplier performance.

73. Survey on IT-transactions: why no effects of network embeddedness on buyer behavior?
Endogeneity of network embeddedness: before buying, buyers search for information on product and supplier, with network embeddedness changing as a by-product of search
Unmeasured variance in the trust problem: network embeddedness seemingly measures a part of the trust problem
Sample selectivity: buyers avoid transactions with “large” trust problems when network embeddedness is low
Supplier effects on investments in contracting: suppliers may contract more “carefully” with well-embedded buyers

74. buyer-supplier relations
Additional slides on
vignette study on
buyer-supplier relations

75. Buyer-supplier vignettes: regression analysis of INVESTMENTS IN CONTRACTING
Independent variable
Hypothesis
Model 1
Model 2
Volume
Specific investments
Uncertainty
Past
Future
Degree
Exit opportunities
Institutional embeddedness
Past x Future
Constant +  ?
0.63**
0.16**
0.16*
-0.14*
-0.02
-0.08~
-0.04
-0.10**
-1.27
0.64**
0.14*
0.17**
-0.13*
-0.09*
-0.32**
-1.26
Explained variance
Number of subjects
Number of observations
0.49 40
348
0.51
This is again a representative analysis.
Here you see:
the Past-effect
the Past x Future-interaction effect
**,*, and ~ represent two-sided significance at respectively p < 0.01, p < 0.05, and p < 0.10 based on Huber standard errors modified for clustering.