Supply Chain Integration under Uncertainty: The Role of Asset Specific Investment with Suppliers

Transcription

1 Supply Chain Integration under Uncertainty: The Role of Asset Specific Investment with Suppliers Taco Van der Vaart The University of Groningen Damien Power The University of Melbourne Dirk Pieter Van Donk The University of Groningen Abstract This study uses data from the 2009 round of the International Manufacturing Strategy Survey (IMSS-V). Transaction Cost Economics (TCE) is the theoretical framework. The results show that under low uncertainty managers have a wider set of options in pursuing integration. Specifically they are free to use multiple contractors and to be more aggressive in their pursuit of outsourcing. Under high uncertainty integration takes the form of a higher level of asset specific investment with fewer trading partners. Results indicate that the effectiveness of combinations of asset specific investment, outsourcing and control mechanisms will change significantly contingent on specific environmental conditions. Keywords: Integration, Uncertainty, Transaction Cost Economics, Asset Specificity Introduction The purpose of this paper is to assess the role of asset specific investment with suppliers in determining plant level cost performance under conditions of high and low demand uncertainty. Transaction Cost Economic theory (TCE) is used as the lens by empirically testing the effect on plant cost performance of the interaction between asset specific investment with suppliers, outsourcing and investment in coordination and control mechanisms. The specific contextual focus of this paper is on demand uncertainty, a factor that has been identified in prior studies to be of significance in determining the nature of transaction costs (Buvik and Grønhaug, 2000, Joshi and Stump, 1999), and of the propensity of firms to invest in transaction specific assets (Williamson, 2008). Our position is that in the context of supply chain integration TCE provides a framework for better understanding both the drivers and nature of effective supply chain integration under demand uncertainty. This position is consistent with recent writings of Williamson s where he has highlighted the importance of uncertainty (or the fundamental 1

2 economic problem of adaptation) as being both fundamental to understanding TCE, and for understanding the role of asset specific investment in a supply chain management context (Williamson, 2008). This also adds to a recent boy of research linking complexity to firm structure and/or integration with trading partners (Bozarth et al., 2009, Germain et al., 2008). In this paper we propose that TCE provides a strong theoretical basis for explaining the dynamics of supply chain integration. In this study we use plant cost elements as dependent variables allowing the results to be interpreted in the context of the transaction cost effects that can be expected to be important antecedents of plant cost performance. By using plant based measures of cost performance we are therefore making the assumption that changes in transaction costs external to the plant are reflected in cost based performance internally. This assumption is based on the logic that any cost external to the firm (Demsetz, 2003) incurred relevant to transacting business between trading partners including transportation costs, fees and time etc. (EUCE, 2009) will impact on internal plant costs. More specifically, plant manufacturing cost drivers used in this study (unit manufacturing cost, procurement cost, manufacturing lead time, procurement lead time, labor productivity, inventory turnover and capacity utilization) are taken to be dependent on factors such as the extent of asset specific investment with suppliers, the propensity for outsourcing and the controls (coordination mechanisms) put in place to ensure contingent on levels of environmental uncertainty. In this study we also take the two underlying conditions of bounded rationality (no contract is ever complete) and potential to default (opportunism) to be fundamental underlying conditions such that The positive transaction costs of principal interest... would vanish but for bounds on rationality and contingent opportunism (which give rise to incomplete contracts and defection, respectively) (Williamson, 2008) p.8. Hypothesis Development Background There is a significant body of work in the supply chain management literature promoting the benefits of closer collaboration and co-operation with suppliers (Derrouiche et al., 2008, Ketchen and Hult, 2007, Sarmah, 2006, Cousins and Menguc, 2006, Rosenzweig et al., 2003). On the other hand there is also a body of work indicating that the effectiveness of collaborative strategies varies contingent on environmental, organizational and competitive conditions (Rossetti and Choi, 2008, Power and Singh, 2007). This paper has the objective of testing the effectiveness of integration (asset specific investment) with suppliers under environmental uncertainty using a TCE lens. TCE is incorporated into the study through the development of constructs representing Asset Specific Investment at the operational level, outsourcing (expressed as a % of the manufacturing cost structure) and investment in coordination and control mechanisms. The problem much of the SCM literature is that while integration between trading partners is proposed to provide significant benefits to trading partners, the form of such integration, and more particularly the match between appropriate forms and environmental contingencies, is less well understood (van Donk and van der Vaart, 2005). TCE provides an established, empirically verified and robust framework within which to assess appropriate means by which trading partners can manage the delicate balance of risk and return in pursuing supply chain integration. 2

3 Transaction Cost Economics Transaction Cost Economics as a theory traces its origins back to early writings on the law and nature of contracts (Llewellyn, 1931, McAulay, 1963) as well as writings in the field of institutional economics (Commons, 1931, Coase, 1937, Coase, 1960). The theory has found more precise definition and operationalization in the work of Williamson (Williamson, 1985, Williamson, 1975, Williamson, 1993) such that empirical testing of the theory has been both widespread and general confirmative of its general principles (Geyskens et al., 2006). In particular, TCE as proposed by Williamson is underpinned by two fundamental assumptions bounded rationality and opportunism that have both provided significant predictive power for the theory (Geyskens et al., 2006), while at the same time attracting significant criticism and academic angst (Tsai and Ghoshal, 1998, Nahapiet and Ghoshal, 1998, Ghoshal and Moran, 1996). The controversy has focused mainly on the assumption of opportunism, and in particular on some early writings of Williamson s where this trait is defined as a variety of self-interest seeking but extends simple self-interest seeking to include self-interest seeking with guile (Williamson, 1979) p.234. This assumption has attracted criticism for its focus on a particular negative human trait, while the broader theory has been criticized for reducing the role of the firm to that of the governance structure of last resort (Ghoshal and Moran, 1996). In more recent writings Williamson has addressed these issues by indicating the contingent nature of the assumption of opportunism, and also recognizing the inherent value of the organizational form (in particular deferring to the early work of Barnard (Barnard, 1938)) contingent on the nature of the firms environment. In essence the theory proposes that the boundaries of the firm (or the make vs. buy decision) can be broken into three basic forms market ( the ideal transaction in law and economics: there being an absence of dependency, governance is accomplished through competition and, in the event of disputes, by court awarded damages (Williamson, 2008) p.9), hybrid contracting ( where continuity matters and adaptations are accomplished with the support of credible contracting mechanisms (Williamson, 2008) p.10) and hierarchy (or the firm that comes in only as higher degrees of asset specificity and added uncertainty pose greater needs for cooperative adaptation (Williamson, 2008) p.9). In essence Williamson concedes that the Market and Hierarchy options in their pure form is just a theoretical construct leading to there being in reality a continuum comprised mostly of many different forms of hybrid contracting. Transaction costs (any cost incurred as a result of economic exchange) vary across each of these three governance forms contingent on extent of asset specific investment (investment in assets dedicated to a transaction that create bi-lateral dependencies), uncertainty and complexity (or frequency of transactions). The fundamental conditions underpinning this variation are that humans (though intentionally rational) are bounded in their rationality (no contract can be complete), and all contracts are subject to the potential for default (opportunism). Of the three factors determining potential for positive transaction costs under each governance form, asset specific investment has often been isolated as of primary importance largely because Williamson has indicated that much of the explanatory power of the theory turns on asset 3

4 specificity..which gives rise to bilateral dependency (or lack thereof) (Williamson, 2008) p.8. Given the assumption that no contract is complete and there is always potential for default such bilateral dependence can prove to be problematic. However, Williamson also notes that more fundamental to the problem of appropriate governance form is the need to adapt to change (uncertainty), rather than asset specificity per se: Of these three, uncertainty is widely conceded to be a critical attribute, and that frequency matters is at least plausible (Williamson, 1979) p.239, and further bilateral dependency by itself would not pose a problem were it not for the need for the parties to an incomplete contract to adapt to disturbances (Williamson, 2008) p.8. As such, TCE proposes that the effect of asset specific investment on the efficacy of a particular governance form cannot be separated from the extent of uncertainty existing in the firm s environment. Further, this inter-relationship infers the need for there to be control mechanisms in place that will either facilitate coordination of multiple contractors with varying incentives to maintain continuity in the relationship (as a result of asset specific investment with trading partners under hybrid contracting) or to manage efficiently higher levels of asset specificity internally as firm boundaries expand. Finally, TCE proposes that this relationship is such that as uncertainty increases adaptation through contractual relations becomes increasingly problematic leading to more cooperative adaptation. Supply Chain Integration Integration between trading partners of processes and technologies, along with the sharing and co-location of resources is widely identified in the supply chain management literature as a source of potential competitive advantage (Mitra and Singhal, 2008, Swink et al., 2007, Paulraj and Chen, 2007, Koufteros et al., 2007). One problem that confronts researchers in this area, however, are the myriad definitions of integration used (Giunipero et al., 2008), and the need for greater understanding of the contingent factors determining the when, where, how, and what of integration between trading partners (Sousa and Voss, 2008). In some papers integration is characterized by tightly interlinked processes and shared resources. In others outsourcing facilitated by collaborative trading partner agreements and use of technology to link trading partners are represented also to characterize integration in the supply chain. In this paper we propose that TCE provides a simple means by which major elements of supply chain integration can be operationalized in order to both simplify the model (reduce degrees of freedom) and to provide a theory based set of inter-relationships facilitating meaningful interpretation. We propose a simple model of supply chain integration based on three elements of the TCE framework. Asset specific investment captures the form of supply chain integration represented by investment in physical and human resources that are specific to a particular trading partner relationship. Outsourcing captures the extent to which trading partner relations are contractually based, and the breadth of the supply chain network. In TCE this represents the extent to which hybrid contracting is used. Our third factor is coordination or in an SCM sense the use of contracts and information technology to coordinate and control trading partner relationships. In TCE this is what Williamson calls contractual supports that take the form of interfirm contractual safeguards (Williamson, 2008) p.9. 4

5 By reducing the concept of supply chain integration down to these three elements we are able to develop hypotheses based in TCE theory for the expected effect of each of the three on plant based cost performance. In particular this allows us to hypothesize how each will differ in effect, and how they will interact, under varying conditions of uncertainty. The importance of this as a contingent factor is reinforced by Williamson when he notes that Only when the need to make unprogrammed adaptations is introduced does the market versus internal organization issue become engaging (Williamson, 1971) p.113. As a measure of uncertainty we use Demand Uncertainty as it is a pivotal issue of importance to supply chain managers, and it has also been identified in prior studies to be of primary importance when assessing TCE based explanations (De Treville et al., 2004, Jones et al., 1997). As demand uncertainty increases we expect that the ability for a plant manager to effectively outsource to multiple contractors will decrease. This will in part be due to there being an increased requirement for continuity in supplier relations leading to higher levels of asset specific investment. Under high levels of demand uncertainty a strategy based on postponement, for example, as a means of managing demand will require a stable supply base and thus higher levels of asset specific investment with (likely) fewer suppliers. TCE would also indicate that under such circumstances the risk of hold up associated with behavioral risk (the combination of incomplete contracts and potential for default - bounded rationality combined with potential for opportunism) is further amplified. Under such circumstances we would therefore expect that plant costs would be most impacted by asset specific investment under high uncertainty, and conversely by outsourcing and contracting under low uncertainty. In the latter case we propose that the opposite scenario will play out with behavioral risk being lower, continuity being less problematic and therefore contracting and outsourcing being a more viable cost reduction strategy. We expect some asset specific investment to be viable under these conditions but that the impact of such investment will be in combination with outsourcing rather than in isolation. Coordination under both scenarios we expect to be important but in different ways and for different reasons. Under low uncertainty coordination is a means of controlling multiple trading partners through a combination of contractual means and information exchange, whereas under high uncertainty the focus will be on coordinating asset specific investments to ensure continuity. We articulate these arguments into the following hypotheses: H1: The interaction between asset specific investment with suppliers and contracting and outsourcing with suppliers will have a positive effect on plant cost performance under low demand uncertainty H2: The interaction between asset specific investment with suppliers and contracting and outsourcing with suppliers will not have a positive effect on plant cost performance under high demand uncertainty H3: The interaction between asset specific investment with suppliers and coordination and control mechanisms with suppliers will not have a positive effect on plant cost performance under low demand uncertainty H4: The interaction between asset specific investment with suppliers and coordination and control mechanisms with suppliers will have a positive effect on plant cost performance under high demand uncertainty 5

6 H5: The interaction between contracting and outsourcing with suppliers and coordination and control mechanisms with suppliers will have a positive effect on plant cost performance under low demand uncertainty H6: The interaction between contracting and outsourcing with suppliers and coordination and control mechanisms with suppliers will not have a positive effect on plant cost performance under high demand uncertainty H7: The interaction between asset specific investment with suppliers and contracting and outsourcing with suppliers and coordination and control mechanisms with suppliers will have a positive effect on plant cost performance under low demand uncertainty H8: The interaction between asset specific investment with suppliers and contracting and outsourcing with suppliers and coordination and control mechanisms with suppliers will not have a positive effect on plant cost performance under high demand uncertainty Method This study uses data from the 2009 round of the International Manufacturing Strategy Survey (IMSS-V). IMSS is carried out by an international network of manufacturing strategy researchers. IMSS-V included responses from 21 countries and from 718 companies. This study uses the full dataset and in order to test the hypotheses a series of interaction terms within a hierarchical regression model are used incorporating all combination of the three integration elements identified. This is done in order to reflect the systemic nature of their interaction in supply chains (i.e. it is more realistic to model how they interact rather than just direct effects), as well as the interrelationships indicated by TCE theory. The measures used are presented in Appendix 1 and in all but one case are multiitem scales exhibiting acceptable levels of reliability and validity. One dependent variables is used, it being a measure of current cost performance compared to competitors. Three control variables are also used to extract variance assignable to firm size, process type and competitive intensity. Results The results of the analysis are presented below in Table 1. Table 1: DV: Current performance compared to competitors: Operational Cost (Size = Firm size (number of employees); CompetInt = Competitive intensity; Process = % mass production; OpS = Operational asset specific investment with suppliers; OutCost% = % manufacturing costs for outsourced/contract work; Coord = Coordination and control mechanisms with suppliers) Low Demand Uncertainty High Demand Uncertainty Step 1 Size Process CompetInt Step 2 OpS OutCost% Coord Step 3 OpSx OutCost% Step 4 OpSx Coord Step 5 OutCost%x Coord Adj. R 2 R 2 F Sig. F Beta Sig. t Adj. R 2 R 2 F Sig. F Beta Sig. t

7 Step 6 OpSx OutCost%x Coord The results show that there is no direct effect recorded under low uncertainty for asset specific investment on the cost performance metric. On the other hand a direct effect is recorded under high uncertainty. No direct effect is recorded for both outsourcing and coordination, however, they provide important evidence of their effect on cost performance through their interactions with asset specificity. Under conditions of low uncertainty outsourcing has a positive interaction with asset specific investment, while under high demand uncertainty there is no interaction evident. These results are supportive of both H1 and H2 with the caveat that outsourcing without asset specific investment adds little value. Coordination is shown to have a positive interactive effect under both low and high uncertainty but in different ways. Under low uncertainty coordination interacts positively with outsourcing (for current cost performance against competitors it amplifies the interaction between asset specific investment and outsourcing). Under high demand uncertainty coordination interacts positively with asset specific investment but not with outsourcing. This provides support for H3, H4 and H7 and further indicates that coordination and control will play a different role under varying levels of demand uncertainty. H6 and H8 are also supported as no interaction is recorded, whereas H5 is not supported. Discussion The results show that under low uncertainty managers have a wider set of options in pursuing integration. In particular they are free to use multiple contractors and to be more aggressive in their pursuit of outsourcing. Combined with this they can use asset specific investment as a means of providing continuity and leverage the benefits of a more distributed supply chain network. Coordination under these conditions is focused on control of the multiple outsourced transactions they are involved in. Integration under these conditions takes the form of a more loosely configured network delivering cost improvements largely through external contracting. Asset specific investment plays an important role, albeit as an interaction with outsourcing rather than directly. Under high uncertainty integration takes the form of a higher level of asset specific investment with fewer trading partners. Coordination focuses on coordinating these investments rather than coordinating contractual arrangements, and integration takes the form of a more tightly integrated network delivering continuity and cost benefits through certainty. Asset specific investment plays a pivotal role under high uncertainty in that it provides a means by which managers faced with demand uncertainty can at least create certainty on the supply side. This would be consistent with developing strategies for delay of differentiation, or moving the de-coupling point up-stream, as a means of combating demand fluctuations. Integration, as shown by this study, can take many forms under different environmental conditions. Our results indicate that the effectiveness of combinations of asset specific investment, outsourcing and control mechanisms will change significantly contingent on specific environmental conditions. TCE explains this concept in terms of the expansion or contraction of firm boundaries. This study provides evidence to suggest that in simple terms this provides a useful predictive analogy for supply chain integration. 7

8 Conclusions Supply chain integration has been the subject of much research, assertion and speculation in all forms of business and academic literature. In particular the need to understand what form integration should take under a given set of environmental conditions is critical for practicing managers. Our understanding of integration needs to be informed by extant theory. Our results indicate the TCE provides a simple means for assessing the efficacy of different integration strategies under demand uncertainty. As predicted by TCE asset specific investment is both a critical determining factor in understanding integration, and an important strategic choice for managers pursuing integration. References BARNARD, C The Functions of the Executive, Cambridge, Mass, Harvard University Press. BOZARTH, C. C., WARSING, D. P., FLYNN, B. B. & FLYNN, E. J The impact of supply chain complexity on manufacturing plant performance. Journal of Operations Management, 27, BUVIK, A. & GRØNHAUG, K Inter-firm dependence, environmental uncertainty and vertical co-ordination in industrial buyer-seller relationships. Omega, 28, COASE, R The Nature of the Firm. Economica, 4, COASE, R The problem of social cost. Journal of Law and Economics, 3, COMMONS, J. R Institutional Economics. American Economic Review, 21, COUSINS, P. D. & MENGUC, B The implications of socialization and integration in supply chain management. Journal of Operations Management, 24, DE TREVILLE, S., SHAPIRO, R. D. & HAMERI, A. P From supply chain to demand chain: The role of lead time reduction in improving demand chain performance. Journal of Operations Management, 21, DEMSETZ, H Ownership and the Externality Problem. In: F.S., A. T. L. A. M. (ed.) Property Rights: Cooperation, Conflict, and Law. Princeton, N.J: Princeton University Press. DERROUICHE, R., NEUBERT, G. & BOURAS, A Supply chain management: a framework to characterize the collaborative strategies. International Journal of Computer Integrated Manufacturing, 21, EUCE Euro Economics Glossary of Terms [Online]. Available: [Accessed 29/03/2011]. GERMAIN, R., CLAYCOMB, C. & DRÖGE, C Supply chain variability, organizational structure, and performance: The moderating effect of demand unpredictability. Journal of Operations Management, 26, GEYSKENS, I., STEENKAMP, J. E. M. & KUMAR, N Make, Buy, or Ally: A Meta- Analysis of Transaction Cost Theory. Academy of Management Journal, 49, GHOSHAL, S. & MORAN, P Bad for practice: A critique of transaction cost theory. Academy of Management Review, 21, GIUNIPERO, L. C., HOOKER, R. E., JOSEPH-MATTHEWS, S., YOON, T. E. & BRUDVIG, S A decade of supply chain management literature: Past, present and future implications. Journal of Supply Chain Management, 44, JONES, C., HESTERLY, W. S. & BORGATTI, S. P A general theory of network governance: Exchange conditions and social mechanisms. Academy of Management Review, 22,

9 JOSHI, A. W. & STUMP, R. L The contingent effect of asset specific investments on joint action in manufacturer supplier relationships: An empirical test of the moderating role of reciprocal asset investments, uncertainty and trust. Journal of the Academy of Marketing Science, 27, KETCHEN, D. J. & HULT, G. T. M Toward greater integration of insights from organization theory and supply chain management. Journal of Operations Management, 25, KOUFTEROS, X. A., EDWIN CHENG, T. C. & LAI, K.-H "Black-box" and "gray-box" supplier integration in product development: Antecedents, consequences and the moderating role of firm size. Journal of Operations Management, 25, LLEWELLYN, K. N What price contract? An essay in perspective. Yale Law Journal, 40, MCAULAY, S Non-Contractual relations in business. American Sociological Review, 28, MITRA, S. & SINGHAL, V Supply chain integration and shareholder value: Evidence from consortium based industry exchanges. Journal of Operations Management, 26, NAHAPIET, J. & GHOSHAL, S Social capital, intellectual capital and the organizational advantage. Academy of Management Review, 23, PAULRAJ, A. & CHEN, I. J Strategic Buyer Supplier Relationships, Information Technology and External Logistics Integration. Journal of Supply Chain Management, 43, POWER, D. J. & SINGH, P. J The E-integration dilemma: the linkages between Internet technology application, trading partner relationships and structural change. Journal of Operations Management, 25, ROSENZWEIG, E. D., ROTH, A. V. & DEAN, J. W The influence of integration strategy on competitive capabilities and business performance: An exploratory study of consumer products manufacturers. Journal of Operations Management, 21, ROSSETTI, C. L. & CHOI, T. Y Supply management under high goal incongruence: An empirical examination of disintermediation in the aerospace supply chain. Decision Sciences, 39, SARMAH, S Buyer vendor coordination models in supply chain management. European Journal of Operational Research, 175, SOUSA, R. & VOSS, C. A Contingency research in operations management practices. Journal of Operations Management, 26, SWINK, M., NARASIMHAN, R. & WANG, C Managing beyond the factory walls: Effects of four types of strategic integration on manufacturing plant performance. Journal of Operations Management, 25, TSAI, W. & GHOSHAL, S Social capital and value creation: The role of intra-firm networks. Academy of Management Journal, 31, VAN DONK, D. & VAN DER VAART, T A critical discussion on the theoretical and methodological advancements in supply chain integration research. In: KOTZAB, H., SEURING, S., MÜLLER, M. & REINER, G. (eds.) Research Methodologies in Supply Chain Management. Heidleberg: Physica-Verlag. WILLIAMSON, O The Mechanisms of Governance, New York, Oxford University Press. WILLIAMSON, O. E The vertical integration of production: Market failure considerations. American Economic Review, 61, WILLIAMSON, O. E Markets and hierarchies, New York, Free Press. WILLIAMSON, O. E Transaction-Cost Economics: The governance of contractual relations. Journal of Law and Economics, 22, WILLIAMSON, O. E The economic institutions of capitalism, New York, Free Press. 9

10 WILLIAMSON, O. E Outsourcing: Transaction Cost Economics and Supply Chain Management. Journal of Supply Chain Management, 44, Appendix 1: Measures Control variables Number of employees Competition intensity (5 point scale: Low intensity High intensity) Process type: % mass production Asset Specific investment with suppliers: KMO.810 Bartlett s Test.000 (5 point Likert scale anchoring None High) Alpha =.800 Dedicated capacity for suppliers.709 VMI or consignment stock with suppliers.745 CPFR with suppliers.783 JIT with suppliers.774 Physical integration within the same plant with.712 suppliers % Manufacturing costs for outsourced/contract work Estimate the present cost structure in manufacturing: % Outsourced / contract work (measured as %) Demand Uncertainty: KMO.643 Bartlett s Test.000 (5 point Likert scale anchoring: Not at all - To a great extent) Alpha =.766 Our demand fluctuates drastically from week to week.885 Our supply requirements vary drastically from week to week.858 Our master production schedule has a high percentage of variation in demand.729 Current performance compared to competitors - Operational Cost: KMO.878 Bartlett s Test.000 (5 point Likert scale: Much worse - Much Better) Alpha =.866 Current performance compared to competitors: Unit manufacturing cost.740 Current performance compared to competitors: Procurement cost.759 Current performance compared to competitors: Manufacturing lead time.773 Current performance compared to competitors: Procurement lead time.794 Current performance compared to competitors: Labor productivity.718 Current performance compared to competitors: Inventory turnover.727 Current performance compared to competitors: Capacity utilization.718 Improvement in performance over the past 3 years: Operational Cost: KMO.871 Bartlett s Test.000 (5 point scale: Deteriorated >5% - Improved >25%) Alpha =.858 Change in operational performance over the past three years: Unit manufacturing cost.745 Change in operational performance over the past three years: Procurement cost.729 Change in operational performance over the past three years: Manufacturing lead time.753 Change in operational performance over the past three years: Procurement lead time.761 Change in operational performance over the past three years: Labor productivity.776 Change in operational performance over the past three years: Inventory turnover.697 Change in operational performance over the past three years: Capacity utilization.705 Coordination and Control: KMO.743 Bartlett s Test.000 (5 point Likert scale anchoring None High) Alpha =.756 Share inventory level information with suppliers.786 Share production planning and demand forecast information with suppliers.819 Order tracking / tracing with suppliers.719 Agreements on delivery frequency with suppliers