Skip to main content
SpringerLink
Log in

Ex Post Problems in Buyer–Supplier Transactions: Effects of Transaction Characteristics, Social Embeddedness, and Contractual Governance

  • Published:
Journal of Management & Governance Aims and scope Submit manuscript

Abstract

This paper focuses on ex post governance of inter-firm transactions. We develop and test hypotheses on the occurrence of ex post problems like delivery delays, inferior quality, and insufficient service in buyer–supplier transactions. Our hypotheses address effects of transaction characteristics, of social embeddedness, and of contractual governance on the occurrence of problems. Other than earlier research on embeddedness effects in this field, we consider not only effects of dyadic embeddedness but also effects of network embeddedness. We test hypotheses using rich survey data on more than 1200 purchases of information technology (IT) products: hardware and software, both standard and complex. We find evidence for effects of transaction characteristics on the occurrence of problems, while our data do not support hypotheses on effects of contractual governance. Our data provide rather consistent support for hypotheses on the effects of embeddedness. Specifically, we find evidence that network embeddedness reduces problems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Axelrod R. (1984). The Evolution of Cooperation Basic Books, New York

    Google Scholar 

  • Batenburg, R.S.: 1997a, The external management of automation 1995: Codebook of MAT95. ISCORE paper no. 58. Department of Sociology, Utrecht University

  • Batenburg, R.S.: 1997b, The external management of automation 1995. Fieldwork, response and non-response. ISCORE paper no. 59. Department of Sociology, Utrecht University

  • Batenburg R.S., Raub W., Snijders C.C.P. (2003). Contacts and Contracts: Dyadic Embeddedness and the Contractual Behavior of Firms. Research in the Sociology of Organizations 20: 135–188

    Google Scholar 

  • Batenburg, R.S. and A. van de Rijt: 1998, The external management of automation 1998: Codebook of MAT98. ISCORE paper no. 155. Department of Sociology, Utrecht University

  • Bernard H.R., Killworth P.D., Kronenfeld D., Sailer L. (1985). On the Validity of Retrospective Data: The Problem of Informant Accuracy. Annual Review of Anthropology 13: 495–517

    Article  Google Scholar 

  • Blumberg B.F. (2001). Cooperation Contracts Between Embedded Firms. Organization Studies 22: 825–852

    Google Scholar 

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

    Google Scholar 

  • Buskens V., Batenburg R.S., Weesie. J. (2003). Embedded Partner Selection in Relations Between Firms. Research in the Sociology of Organizations 20: 107–133

    Article  Google Scholar 

  • Buskens V., Raub. W. (2002). Embedded Trust: Control and Learning. Advances in Group Processes 19: 167–202

    Google Scholar 

  • Claro D.P., Hagelaar G., Omta O. (2003). The Determinants of Relational Governance and Performance: How to Manage Business Relationships? Industrial Marketing Management 32: 703–716

    Article  Google Scholar 

  • David R.J., Han. S.-K. (2004). A Systematic Assessment of the Empirical Support for Transaction Cost Economics. Strategic Management Journal 25: 39–58

    Article  Google Scholar 

  • Durkheim E. (1893). De la division du travail social 9th edn. PUF, Paris

    Google Scholar 

  • Dutta B., Jackson M.O. (Eds). (2003). Networks and Groups. Models of Strategic Formation Springer, Berlin

    Google Scholar 

  • Flap H. (2004). Creation and Returns of Social Capital: A New Research Program. in: Flap H., Völker B. (eds.), Creation and Returns of Social Capital Routledge, London, 3–23

    Google Scholar 

  • Gierl H., Bambauer. S. (2002). Information Networks as a Safeguard from Opportunism in Industrial Supplier–Buyer Relationships Schmalenbach Business Review 54: 335–350

    Google Scholar 

  • Grandori A. (1997). Governance Structures, Coordination Mechanisms and Cognitive Models. Journal of Management and Governance 1: 29–47

    Article  Google Scholar 

  • Grandori A. (2000). Conjectures for a New Research Agenda on Governance. Journal of Management and Governance 4: 1–9

    Article  Google Scholar 

  • Granovetter M.S. (1985) Economic Action and Social Structure: The Problem of Embeddedness. American Journal of Sociology 91: 481–510

    Article  Google Scholar 

  • Greene W.H. (1997). Econometric Analysis 3rd edn. Upper Saddle River, NJ: Prentice-Hall

    Google Scholar 

  • Gulati R. (1995). Does Familiarity Breed Trust? Academy of Management Journal 38: 85–112

    Article  Google Scholar 

  • Hart O. (1987). Incomplete Contracts. In: Eatwell J., Milgate M., Newman P. (eds.), The New Palgrave. Allocation, information and markets. Macmillan, London, 163–179

    Google Scholar 

  • Heide J.B., Stump. R.L. (1995). Performance Implications of Buyer–Supplier Relationships in Industrial Markets: A Transaction Cost Explanation. Journal of Business Research 32: 57–66

    Article  Google Scholar 

  • Helper S. (1993). An Exit-Voice Analysis of Supplier Relations: The Case of the US Automobile Industry in: Grabher G. (ed.), The Embedded Firm. Routledge, London, 141–160

    Google Scholar 

  • Hirschman A.O. (1970). Exit, Voice, and Loyalty Harvard University Press, Cambridge MA

    Google Scholar 

  • Huber P.J. (1967). The Behavior of Maximum Likelihood Estimates Under Non-Standard Conditions. Proceedings of the Fifth Berkeley Symposium on Mathematical Statistics and Probability 1: 221–233

    Google Scholar 

  • Jap S.D., Anderson E. (2003) Safeguarding Interorganizational Performance and Continuity Under Ex Post Opportunism. Management Science 49: 1684–1701

    Article  Google Scholar 

  • Kalleberg A.L., Knoke D., Marsden P.V., Spaeth. J.L. (1996). Organizations in America Sage, Thousand Oaks CA

    Google Scholar 

  • Kogut B. (1989). The Stability Of Joint Ventures. Journal of Industrial Economics 38:183–198

    Article  Google Scholar 

  • Kotabe M., Martin X., Domoto. H. (2003). Gaining from vertical partnerships: Knowledge Transfer, Relationship Duration, and Supplier Performance Improvement in the U.S. and Japanese Automotive Industries. Strategic Management Journal 24: 293–316

    Article  Google Scholar 

  • Kreps D.M. (1990). Corporate Culture and Economic Theory. In: Alt J.E., Shepsle K. (eds), Perspectives on Positive Political Economy. Cambridge University Press, Cambridge, 90–143

    Google Scholar 

  • Larson A. (1992). Network Dyads in Entrepreneurial Settings. Administrative Science Quarterly 37: 76–114

    Article  Google Scholar 

  • Leenders M.R., H.E. Fearon (1993). Purchasing and Materials Management, 10th edn. Homewood, IL: Irwin

    Google Scholar 

  • Leiblein M.J., Reuer J.R., Dalsace F. (2002). Do Make or Buy Decisions Matter? The Influence of Organizational Governance on Technological Performance. Strategic Management Journal 23: 817–833

    Article  Google Scholar 

  • Lorenz E.H. (1988). Neither Friends Nor Strangers: Informal Networks of Subcontracting. In: Gambetta D. (ed), French industry in Trust: Making and Breaking Cooperative Relations. Blackwell, Oxford, 94–107

    Google Scholar 

  • Macaulay S. (1963). Non-Contractual Relations in Business. American Sociological Review 28: 55–67

    Article  Google Scholar 

  • Malhotra D., Murnighan J.K. (2002). The Effects of Contracts on Interpersonal Trust. Administrative Science Quarterly 47: 534–559

    Article  Google Scholar 

  • Masten S.E. (ed.). (1996a). Case Studies in Contracting and Organization. Oxford University Press, New York

    Google Scholar 

  • Masten S.E. (1996b). Empirical Research in Transaction Cost Economics in: Groenewegen J. (ed.), Transaction Cost Economics and Beyond. Kluwer, Boston MA, 43–64

    Google Scholar 

  • Mokken R.J. (1970). A Theory and Procedures of Scale Analysis: With Applications in Political Research. The Hague, Mouton

    Google Scholar 

  • Noordewier T.G., John G., Nevin. J.R. (1990). Performance Outcomes of Purchasing Arrangements in Industrial Buyer–Vendor Relationships. Journal of Marketing 54: 80–93

    Article  Google Scholar 

  • Parkhe A. (1993). Strategic Alliance Structuring: A Game Theoretic and Transaction Cost Examination of Interfirm Cooperation. Academy of Management Journal 36: 794–829

    Article  Google Scholar 

  • Pindyck R.S., Rubinfeld. D.L. (1991). Economic Models and Economic Forecasts. McGraw-Hill, New York

    Google Scholar 

  • Podsakoff P.M., MacKenzie S.B., Lee J.-Y., Podsakoff. N.P. (2003). Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies. Journal of Applied Psychology 88: 879–903

    Article  Google Scholar 

  • Podsakoff P.M., Organ D.W. (1986). Self-Reports in Organizational Research: Problems and Prospects. Journal of Management 12: 69–82

    Article  Google Scholar 

  • Poppo L., Zenger. T. (2002). Do Formal Contracts and Relational Governance Function as Substitutes Or Complements? Strategic Management Journal 23: 707–725

    Article  Google Scholar 

  • Prendergast C. (1999). The Provision of Incentives in Firms. Journal of Economic Literature 37: 7–63

    Google Scholar 

  • Provan K.G., Skinner. S.J. (1989) Interorganizational Dependence and Control as Predictors of Opportunism in Dealer–Supplier Relations. Academy of Management Journal 32: 202–212

    Article  Google Scholar 

  • Raub W., Weesie. J. (1990). Reputation and Efficiency in Social Interactions: An Example of Network Effects. American Journal of Sociology 96: 626–654

    Article  Google Scholar 

  • Riesewijk B., Warmerdam J. (1988). Het slagen en falen van automatiseringsprojecten (Success and failure of automation projects). ITS, Nijmegen

    Google Scholar 

  • Rogers W.M. (1993). Regression Standard Errors in Clustered Samples. Stata Technical Bulletin 13: 19–23

    Google Scholar 

  • Rooks G. (2002). Contract en conflict. Strategisch management van inkooptransacties (Contract and conflict. Strategic management of purchasing). ThelaThesis, Amsterdam

    Google Scholar 

  • Rooks G., Raub W., Tazelaar F., Selten. R. (2000). How Inter-Firm Cooperation Depends on Social Embeddedness: A Vignette Study. Acta Sociologica 43: 123–137

    Article  Google Scholar 

  • Rooks G., Snijders. C. (2001). The Purchase of IT-Products by Dutch SMEs: A Quantitative Study. Journal of Supply Chain Management 37: 34–42

    Article  Google Scholar 

  • Schary P.B., Skjøtt-Larsen. T. (2001). Managing the Global Supply Chain. Copenhagen: Business School Press, Copenhagen

    Google Scholar 

  • Schellekens R., Verschuur J., van Vuren B. (2000). Trends in ICT 2000. Ernst & Young, Rotterdam

    Google Scholar 

  • Shelanski H.A., Klein. P.G. (1999). Empirical Research in Transaction Cost Economics: A Review And Assessment. In: Carroll G.R., Teece D.J. (eds.), Firms, markets, and hierarchies. Oxford University Press, New York, 89–118

    Google Scholar 

  • Smelser, N.J. and R. Swedberg (eds): (2005), The Handbook of Economic Sociology, 2nd and rev. ed. (New York: Russell Sage)

  • Snijders T.A.B. (2001). The Statistical Evaluation of Social Network Dynamics. Sociological Methodology 2001: 361–395

    Article  Google Scholar 

  • Sribney, W., V. Wiggins and D. Drukker: 2003, For two-stage least squares (2SLS/IV/ivreg) estimates, why is the model sum of squares sometimes negative? http://www.stata.com/support/faqs/stat/2sls.html (accessed January 16, 2006)

  • StataCorp (2003). Stata Statistical Software: Release 8.0.College Station, TX: Stata Corporation

    Google Scholar 

  • Sutcliffe K.M., Zaheer. A. (1998). Uncertainty in the Transaction Environment: an Empirical Test. Strategic Management Journal 19: 1–23

    Article  Google Scholar 

  • Szroeter J. (1978). A Class of Parametric Tests for Heteroscedasticity in Linear Econometric Models. Econometrica 46: 1311–1328

    Article  Google Scholar 

  • Taylor M. (1987). The Possibility of Cooperation. Cambridge University Press, Cambridge

    Google Scholar 

  • Tazelaar F., Snijders. C. (2004). The Myth of Purchasing Professionals’ Expertise. More Evidence on Whether Computers Can Make Better Procurement Decisions. Journal of Purchasing and Supply Management 10: 211–222

    Article  Google Scholar 

  • Uzzi B. (1996). The Sources and Consequences of Embeddedness for the Economic Performance of Organizations: The Network Effect. American Sociological Review 61: 674–698

    Article  Google Scholar 

  • Uzzi B. (1997). Social Structure and Competition in Interfirm Networks: The Paradox of Embeddedness. Administrative Science Quarterly 42: 35–67

    Article  Google Scholar 

  • Wathne K.H., Heide. J.B. (2000). Opportunism in Interfirm Relationships: Forms, Outcomes, and Solutions Journal of Marketing 64(October): 36–51

    Article  Google Scholar 

  • Weber, M.: 1921, Wirtschaft und Gesellschaft, 5th ed. (Tübingen: Mohr 1976)

  • Weesie J. (1999). Seemingly Unrelated Estimation. Stata Technical Bulletin 52:19–23

    Google Scholar 

  • Williamson O.E. (1985). The Economic Institutions of Capitalism. Free Press.New York

    Google Scholar 

  • Williamson O.E. (1996). The Mechanisms of Governance. Oxford University Press, New York

    Google Scholar 

  • Williamson, O.E. 2001, ``Transaction Costs and Property Rights’’, in N.J. Smelser and P.B. Baltes (eds.), International Encyclopedia of the Social and Behavioral Sciences, vol. 23. (Amsterdam: Elsevier), pp. 15840–15845

  • Zukin S., DiMaggio. P. (1990). Introduction In: Zukin S., DiMaggio P. (eds.), Structures of Capital. The Social Organization of the Economy. Cambridge University Press, Cambridge, 1–36

    Google Scholar 

Download references

Acknowledgements

The authors acknowledge valuable suggestions by Jeroen Weesie, Chris Snijders, and Vincent Buskens. An earlier version of the paper benefited from valuable comments by Anna Grandori, the JMG editorial team, and two anonymous reviewers. This research was made possible through funds of the Netherlands Organization for Scientific Research (NWO; PGS 50–370) for the PIONIER program “The Management of Matches” and the NEVI Research Foundation (NRS) of the Dutch Association for Purchase Management (NEVI) for the project “Purchase of IT-Products.”

Author information

Authors and Affiliations

  1. Department of Technology and Policy/ECIS, Technical University Eindhoven, Den Dolech 2, 5600 MB, Eindhoven, Netherlands

    Gerrit Rooks

  2. Department of Sociology/ICS, Utrecht University, Heidelberglaan 2, 3584 CS, Utrecht, Netherlands

    Werner Raub & Frits Tazelaar

Authors
  1. Gerrit Rooks
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Werner Raub
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Frits Tazelaar
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Werner Raub.

Appendix: Variable Construction

Appendix: Variable Construction

In the following, “product” refers to the focal transaction.

EX POST PROBLEMS (11-item measure): Original questions: These are possible problems associated with purchasing such products and with service. To what degree did you experience each of these problems? Delivery delay – exceeding of price/budget – product incomplete – product too slow/limited – deviation from agreed upon specifications – incompatibility with other IT-products – installation too quick/careless – insufficient support – service too slow/too late – updates too slow/too late – documentation incomplete/unclear. Answer categories per item (5-point scale): problem did not occur at all (=1) – hardly (=2) – to a certain degree (=3) – to a high degree (=4) – to a very high degree (=5). Variable construction: EX POST PROBLEMS is the sum of the 11 items on problems. Cronbach’s α = .90. Note: Using factor scores for constructing an alternative EX POST PROBLEMS-variable does not affect our results (analyses not reported here). Both constructs correlate highly (r = 0.998).

SWITCHING COSTS (4-item measure): Original questions [variable construction label]: Assume that the product had failed to function and had had to be replaced. What would have been the damage, in terms of time and money, associated with: purchasing another product [new product] – training of personnel [training] – new data entry [data entry] – idle production [idle production]. Answer categories per item (5-point scale): minimal (=1) – small (=2) – moderate (=3) – large (=4) – very large (=5). Variable construction: SWITCHING COSTS is the main principal component of the 4 items mentioned (eigenvalue first component 2.38, second component 0.67). SWITCHING COSTS = .52[new product] + .52[training] + .50[data entry] + .45[idle production]. Cronbach’s α = 0.77.

MONITORING PROBLEMS (4-item measure): Original questions [variable construction label]: Was it difficult for you and your employees to judge the quality of the product at the time of delivery? [quality] – Was it difficult for your firm to compare tenders? [tenders] – Was it difficult for your firm to compare the product with other products? [other products] – Was it difficult for your firm to compare the price-quality relation of potential suppliers? [price-quality]. Answer categories per item (5-point scale): very easy (=1) – easy (=2) – somewhat difficult (=3) – difficult (=4) – very difficult (=5). Variable construction: MONITORING PROBLEMS is the main principal component of the 4 items mentioned (eigenvalue first component 2.02, second component 0.53). MONITORING PROBLEMS = .41[quality] + .51[tenders] + .54[other products] + .53[price-quality]. Cronbach’s α = 0.83.

PAST (single-item measure): Original question: Has your firm had any kind of business relation with this supplier before the purchase of this product? Answer categories: no (=0) – yes (=1). Variable construction: PAST is a dummy variable using the score on this question.

SATISFACTION (single-item measure): Original question: How satisfied was your firm with previous business with the supplier? Answer categories (5-point scale): very unsatisfied – unsatisfied – moderately satisfied – satisfied – very satisfied. Variable construction: SATISFACTION is a dummy variable with 1 = satisfied or very satisfied, and 0 = very unsatisfied, unsatisfied, or moderately satisfied. Note: We constructed a dummy variable because the distribution of the answers is bimodal.

EXPECTED FUTURE (single-item measure): Original question: To what extent did you expect, before the purchase of this product, that your firm would continue business with this supplier? Answer categories (5-point scale): no business (=1) – incidental business of limited size (=2) – some business of limited size (=3) – regular and/or extensive business (=4) – very regular and/or very extensive business (=5). Variable construction: EXPECTED FUTURE is the score of the chosen answer category.

DEGREE (single-item measure): Original question: Please think about other firms that have (likely) been clients of the supplier at the time of the purchase of the product. How many of such firms did you know? Open answer category: number of firms. Variable construction: DEGREE = number of firms mentioned by respondent (with a maximum of 7 to account for outlier-effects).

SECTOR DENSITY: This variable is based on judgments of 21 experts (see Rooks, 2002: 139–142 for a detailed discussion). These experts provided estimates for 35 sectors of industry with respect to contacts and information exchange between firms in the respective sector. Sectors were defined employing the classification used by Statistics Netherlands. The experts were asked to consider business contacts as well as informal contacts. They were also asked to consider the number of contacts as well as the frequency, intensity, and reliability of information exchange through these contacts. Based on these expert judgments, we distinguish three categories with respect to SECTOR DENSITY: weak (=1) – medium (=2) – strong (=3).

VISIBILITY (single-item measure): Original question: How visible was the supplier in the market before the purchase of the product? Consider visibility through the media, through fairs, as well as through business with other firms you are in contact with or through business with your own clients. Answer categories (5-point scale): not at all visible (=1) – hardly visible (=2) – reasonably visible (=3) – visible (=4) – very visible (=5). Variable construction: VISIBILITY is the score of the chosen answer category.

EXIT NETWORK (2-item measure): Original questions: Considering the situation before purchasing the product, how large was the number of potential suppliers? – Considering the situation before purchasing the product, how large was the number of alternatives for the product? Answer categories per item (5-point scale): minimal (=1) – small (=2) – reasonable (=3) – large (=4) – very large (=5). Variable construction: EXIT NETWORK is the mean value of the scores on the two questions. Correlation between the scores: r = 0.58, p < 0.001. Cronbach’s α = .74.

EFFORT (single-item measure): Original question: How much time did you and your colleagues spend): on writing down the agreement and on the negotiations with the supplier of this product? Open answer category: number of person-days. Variable construction: EFFORT = natural logarithm of the number of person-days mentioned by respondent.

COMPLETENESS (24-item measure): Original questions. For each of the following financial and legal clauses, can you indicate how they were arranged? Price determination – price level – price changes – payment terms – sanctions on late payment – delivery time – liability supplier – force majeure – warranties supplier – quality (norms) – intellectual property (escrow) – piracy protection – restrictions on product use – non-disclosure – insurance supplier – duration service – reservation spare-parts – duration maintenance – updating – arbitration – calculation R&D costs – joint management during transaction – technical specifications – termination. Answer categories per item (3-point scale): not arranged at all (=0) – only verbally arranged (=1) – written arrangement (=2). Variable construction: COMPLETENESS = sum of the scores on the 24 items. A non-parametric item response analysis for polytomous items (Mokken analysis) reveals that the contract items together form one scale. None of the items has a Loevinger’s H smaller than 0.30 and the overall scale coefficient equals 0.51, which is indicative of a strong scale (see Mokken, 1970).

TAILOR SOFTWARE (3-item measure): The questionnaire included questions on what the product included. Among other things, the respondent was asked if the product included adjusted software and/or tailor made software and/or industry-specific software. TAILOR SOFTWARE is a dummy variable with 1 = product includes adjusted software and/or tailor made software and/or industry-specific software and 0 = otherwise.

TAILOR HARDWARE (4-item measure): The respondent was likewise asked if the product included the design of hardware. TAILOR HARDWARE is a dummy variable with 1 = product includes design of hardware and TAILOR SOFTWARE = 0, while TAILOR HARDWARE = 0 otherwise.

VOLUME (single-item measure): Original question: How much was paid to the supplier, not including later supplements? Answer categories (5-point scale): up to 10,000 US$ (midpoint = 0.125) – 10,000–20,000 US$ (midpoint = 0.375) – 20,000–50,000 US$ (midpoint = 0.75) – 50,000–100,000 US$ (midpoint = 1.5) – more than 100,000 US$ (midpoint = 3.5). Variable construction: VOLUME is the midpoint of the chosen answer category, with midpoints of the price classes expressed in NLG (1 US$ = 2.5 NLG at the time of data collection) divided by 100,000 and using an estimate for the highest category that does not have an upperbound.

SIZE BUYER (single-item measure): Original question: How many full-time employees were working at your firm at the time of the purchase of this product? Open answer category: number of full-time employees. Variable construction: SIZE BUYER = natural logarithm of the score on this question.

SIZE SUPPLIER (single-item measure): Original question: How many employees were working at the supplier at the time of the purchase of this product? Answer categories (5-point scale): less than 5 (=1) – 5–9 (=2) – 10–19 (=3) – 20–49 (=4) – 50 or more (=5). Variable construction: SIZE SUPPLIER is the score of the chosen answer category.

PERIOD: Dummy variable with 0 = data collected in 1995 and 1 = data collected in 1998.

CONTRACT SUPPLIER: Dummy variable with 1 = contract designed by supplier and 0 = otherwise.

LEGAL DEPARTMENT: Dummy variable with 1 = buyer has an in-house legal department and 0 = otherwise.

LEGAL EXPERTISE: Dummy variable with 1 = buyer has employees with legal expertise and 0 = otherwise.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Rooks, G., Raub, W. & Tazelaar, F. Ex Post Problems in Buyer–Supplier Transactions: Effects of Transaction Characteristics, Social Embeddedness, and Contractual Governance. J Manage Governance 10, 239–276 (2006). https://doi.org/10.1007/s10997-006-9000-7

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10997-006-9000-7

Keywords

Search

Navigation