Research on Core Competency of Dynamic Strategic Alliance in Supply Chain Management

Transcription

1 Research on Core of Dynamic Strategic Alliance in Supply Chain Management GUO Xiaoying College of Economics, Tianjin University of Commerce, Tianjin, China, ; & Urban and Regional Economic Research Institute, Nankai University, Abstract: With the globalization of economics and rapid development of science technology, increasing corporations become to strategically adjust the global competitive relationships by patterns of replacing opposite competition with cooperative competition. Based on the theory of Supply Chain Management and Transaction Cost Theory, this paper thoroughly probes into the formative cause and the transformation process from the static strategic alliance to the dynamic strategic alliance. TOICC Model is established by the disassembly of core competency of supply chain strategic alliance, the analysis on choice factors on optimizing partners combination, and the measurement on evaluation factors on influencing alliance performance. On the groundwork of above model, this paper carries out Description Analysis, Factor Analysis, Multiple Linear Regression Analysis with high Validity and sufficient Reliability on basis of Questionnaire Survey as data collection method. After that, the function relationship in the multiple linear regression equation reveals the findings that all of the five kinds of competency in TOICC Model have the positive influence on the core competency of supply chain strategic alliance. Furthermore, the degree of influence is exhibited as bellows from heavily to slightly: Organization, Technology, Cognition, Capital, Institution. At last, this paper deeply discusses and systematically makes a logical conclusion, and clearly points out the limitation and future direction. Keywords: Core competency, Dynamic strategic alliance, Supply chain management 1. Introduction With the globalization of economics and rapid development of science technology, increasing corporations become to strategically adjust the global competitive relationships by patterns of replacing opposite competition with cooperative competition. However, based on coopetition consciousness, strategic alliance, as an innovation of organizational relationship, has been playing a vital role in strengthening the supply chain competitive advantages. Overseas researches on supply chain strategic alliance have been provided with the certain systematic method, not only systematically summed up overall feature of strategic alliance, but also clearly pointed out research direction in the future. For example, most of researches on strategic alliance emphasize on static characteristics, but almost don t involve in the dynamic specialty in the process of implementation. As alliance model in 1980 s, Walmart and P&G carried out Direct Transaction Institution by mode of VMI as the core of supply chain strategic alliance. But in pace with Kimberly s participation, Walmart as alliance leader must be confronted with the problem on choosing strategic partner once more. Thus it can be seen that alliance dynamic trait is mainly reflected by restructuring the whole supply chain, yet this key problem is still short of thorough study that how improve the whole supply chain core competency by optimizing partners combination. 2. Literature Review 2.1 Theory Basis In opinion of Porter, strategy is to create the integration on the activities of all enterprises, which is represented as tradeoff effect on choosing what can not be done; alliance is a long term agreement beyond normal market transaction, but not amalgamated directly. Spekman et al.(1998) [1] defined strategic alliance as a close, long-term, mutually beneficial agreement between two or more partners in 246

2 which resources, knowledge, and capabilities are shared with the objective of enhancing the competitive position of each partner. The application of strategic alliance to supply chain is one of the most abundant expressive modality in respects of management pattern of system optimization, which regards Transaction Cost Theory as the most essential theory basis. Coase(1937) [2] innovatively put forward that transaction expense exists during the exchange of market, which lays solid foundations for Transaction Cost Theory. Williams(1985) [3] pointed out by a completely new analysis paradigm that: Any economics issue that can be formulated as contract may be made a deepgoing discussion on reducing transaction expense. Therefore, as a new institution arrangement in supply chain, strategic alliance is to essentially satisfy the needs of partners for reducing transaction expense by amalgamating mutually complementary resources and capabilities from the view of whole chain. 2.2 Dynamic Transformation Process Spekman(1998) [1] indicated that strategic alliance has life cycle with the different activities in each stage as bellows:partner search, partner identification, Valuation initiating, Coordination interfacing, Expansion growth, Adjustment, Reevaluation. It can be seen that the first five stages have the static characteristics of alliance with the relatively stable balanced state in process of building and implementing alliance. But the last two stages possess the dynamic traits of alliance with the relatively fluctuant unbalanced state in process of adjusting and rebuilding alliance. In view of Christopher, the competition in the market is not the competition among enterprises, but supply chains. The competitive advantage on product can only make supply chain achieve the short-term benefit, while the competitive advantage on resources and capabilities can take shape into the long-term foundation of supply chain. Consequently, Prahalad and Hamel(1990) [4] brought forward Core Theory, which is the system of knowledge on basis of resources and capabilities. Because the accumulation of knowledge needs to be supported by organization learning, the establishment of competitive advantage on supply chain by core competency takes on a dynamic process. 3. The Toicc Model of Core 3.1 Establishing the TOICC model Porter s value chain analysis method can break up supply chain into all kinds of basic activities, which makes a great contribution to revealing the differences of competitive advantage among the different supply chains. But this kind of disassembly on supply chain is only based on the nature of structure. Zhou Jian(2002) [5] held that the disassembly of Core can start with the view of capabilities. Building on above achievements, we restructure the supply chain strategic alliance core competency from the following five aspects. Institution refers to the capability of adapting the current outer institution arrangements binding its behavior rule, which is related to operation circumstances. Organization refers to the capability of integrating the resources on supply chain from the dynamic angle, which is related to resources allocation. Capital refers to the capability of risk pooling among the supply chain partners, which is related to the mutual complementary on resources and capabilities. Technology refers to the capability of creating productivity by supply chain integrated technology, which is related to the accumulation and creation of knowledge. Cognition refers to the capability of effectively harmonizing the culture and value on supply chain, which is related to the mode of thinking. In brief, research on how to create the value for supply chain strategic alliance by core competency is essential to study how to add to the total value reflected by the respective competitive advantage from each five competencies. In the light of above statement, we establish TOICC Model as Figure1: 247

3 Institution Evaluation Factors on Influencing Alliance Performance Supply Chain Strategic Alliance Core Organization Capital Choice Factors on Optimizing Partners Combination Technology Cognition Figure 1. Establishment of TOICC Model Source: Made by author 3.2. Optimizing Partners Combination of Strategic Alliance Overseas scholars carried out some certain researches on choice criterion of supply chain partners. Dickson(1966) [6] abstracted 23 considerable standards when the enterprise chose one supplier. Ghodsypour (1998) [7] analyzed the influence on choice decision of supply chain partners by the attribute of product with the actual example. Handfield (2002) [8] demonstrated the viewpoint of multi-criterions choice decision, and measured the degree of carrying weight for the different criterions. However, above researches are short of the deep going discussion on optimizing partners combination from view of capability. One Japanese scholar considered that the deep fountainhead of alliance failure is the improper partner choice. Thus, many alliance failures can be remedied by optimizing partners combination. The author finds out that there is not a whole set of summary on optimizing partners combination factors after widely consulting a number of literature materials throughout the country and overseas. Therefore, in this paper we sifts out 63 standpoints from more than 90 famous scholars, abstracts 25 viewpoints and tries to classify as Table 1: Institution X1 Organization X2 Capital X3 Table 1 Main Choice Factors on Optimizing Partners Combination X11: Change of social circumstances or government policy X12: Lack of supply chain coopetition idea X13: Breakup of equal relationship due to the emergence of power control X14: Indistinct evaluation standard of alliance performance X15: Imperfect allocation mechanism of alliance benefit X21: Be short of common alliance leader X22: Lack of flexibility on organization structure X23: Be deficient in communication X24: Inconsistent on working procedure X25: Be wanting in the mutual learning mechanism X31: Slightly poor mutual complementarity on resources and capabilities X32: High dependency among partners X33: Be difficult in risk pooling among partners X34: Financial instability X35: Unequal gain of knowledge and transition of negotiation power 248

4 Technology X4 Cognition X5 Source: Made by author X41: Lack of continuous technology innovation X42: Worse matching on technology procedure among partners X43: Poor permeability on knowledge among partners X44: Lack of the share of technology knowledge X45: Inferior quality of technology personnel X51:Be short of objective consistency X52:Lack of confidence X53:Worse culture compatibility among partners X54:Be different decision-making style and operation idea X55:Be inharmonious interpersonal relationship among partners 3.3 Measurement Factors on Influencing Alliance Performance In this paper, the performance level of supply chain strategic alliance is reflected by measuring the satisfaction degree on upper and lower supply chain partners in the questionnaire survey. Furthermore, we regard this as the data basis on supply chain strategic alliance core competency. 4. Research Methodology 4.1 Research Objective and Method Research objective is to study the influence degree on supply chain strategic alliance core competency by five competencies in TOICC Model. Research method is to carry out the explanatory transverse study by the quantitative method on basis of sampling survey and econometric analysis. 4.2 Data Collection Method Questionnaire Survey is our data collection method in this paper. In the questionnaire, Part One is about the survey on company background, alliance state and performance. Part Two is regarding the survey on reason for optimizing partners combination. Part Three is concerning contact means. This survey was in progress by spot reply from December 10 th to January 9 th, This sample is more than two hundred trainees in six classes, which is randomly derived from Tianjin Training & Examining Centre, China Professional Manager Authentication Commission. These informants widely have high quality, university educational background, over five years working experience, middle or high rank in the enterprise, grasped the basic knowledge of supply chain strategic alliance from two lectures in this college, and took in one hour centralized training for purpose of this survey. The expected sample capacity for this survey is 200, 179 for actual recovery, 126 for effective questionnaire with the percent rate of 70.39, 96 for spot reply with the percent rate of Validity and Reliability Validity refers to the accurate degree of variable by measuring instrument; Reliability directs at the stability and consistency of the measuring instrument. Validity is embodied in the following four aspects in this paper. Consensus Validity means the effective degree subjectively judged by respondents. This paper modified the partial special terms and adjusted questions sequence according to the feedback of pre-test. Simultaneously, the centralized training also got a deeper understanding on the concepts in the questionnaire. Content Validity means the random sample should typically represent the population. Almost all respondents are the member of supply chain, and have the experience of alliance cooperation and partner optimization. Also, the random sample can avoid this paper s subjective intention. Predictive Validity means the future forecast can be executed in accordance with the research result. The correlation coefficient in the regression equation deduced by our data analysis can be used to effectively forecast in the future. Construct Validity means the test by observing the correlation coefficient between one concept and the relevant concept in the other theory. (Zou Nongjian, 2002). Owing to the resources limitation of this survey, certain assumptions to achieving construct validity can not be realized. But the scale of this survey is enough small and the same set of questionnaire was distributed to the respondents within the same time, so the test bias should have been maintained in a minimal level. Reliability in this 249

5 paper is incarnated by the Cronbach's Alpha Test, which shows higher in the data analysis chapter, hence, the better reliability can be naturally explained. 4.4 Data Analysis Method Description Analysis The aim is to validate whether the result from this survey possesses the universal applicability. Judging from the result in frequency analysis on the background of the informants, all items in the questionnaire possess the better universal applicability. Especially, it is obvious that Item Supply Chain Strategic Alliance Type involves all listed types and Item Informant Post has middle or high rank director at the percent rate of Known from the result in frequency analysis on five competencies, most of the informants agree all the opinions besides Item X25, X43, X53, among which the maximum means is Item X12 and minimum Item is X43. It seems from the score of Means and Standard Deviation that the data choice on five competencies possesses the universal applicability. Moreover, judged from the result of Cronbach s Alpha Test, organization competency, technology competency and cognition competency satisfy the needs of reliability and possess the inner consistency Factor Analysis The aim is to classify all the subjectively prescribed variables again in order to make all kinds of variables possess the inner consistency, avoid the multicollinearity and increase the precise extent on regression analysis. We adopt Equamax method, consequently, gain five factors by SPSS software and the concrete variables as bellows: Factor 1(X1):X12, X13 Factor 2(X2):X14, X21, X22, X23, X24 Factor 3(X3):X33, X34, X35 Factor 4(X4):X41, X42, X43, X44, X45 Factor 5(X5):X52, X53, X54, X55 In addition, judged from the result of Cronbach s Alpha Test on each factor, organization competency and technology competency satisfy the needs of reliability and possess the inner consistency Regression Analysis It can be seen from their scatter diagram that the dependent variable significantly has the relationship of linearity correlation with each independent variable. Therefore, the multiple linear regression analysis model is established by five competencies as independent variable and supply chain strategic alliance core competency as dependent variable. Independent variable equals the arithmetical average of all inner homologous factors values and dependent variable is reflected by measuring the satisfaction degree on upper and lower supply chain partners in the questionnaire survey. Four basic hypotheses for multiple regression analysis are: Residuals u t, as a stochastic variable whose expected value equals zero, is normally distributed. Residuals u t has no Heteroscedasticity. Residuals u t has no Autocorrelation. Residuals u t has no Multicollinearity. So in this paper we set up regression analysis equation as follow: Y = X X X X X5 t: (4.88) (2.29) (5.54) (2.93) (5.45) (3.44) R 2 = 0.88 DW = 2.02 F=50.33 As for regression analysis test, we can conclude as follow: Test on Regression Coefficient Significance On this condition that level of significance α is 0.05, degree of freedom is 120, the critical of t distribution is 1.98, all of which is smaller than t value in the parentheses under equation regression coefficient. Therefore, each regression coefficient has the significance; furthermore, the dependent variable significantly has the relationship of linearity correlation with each independent variable. Test on Residual Normal Distribution It can be seen from the regression equation statistical distribution diagram and JB statistical capacity that residuals are approximately normally distributed, means of which equals zero. Also, JB statistical capacity is 0.61, which is far smaller than in the equation. Therefore, residuals are coincided with the normal distribution. 250

6 Test on Heteroscedasticity It can be seen from the scatter diagram between u t 2 and Y that u t 2 does not vary as Y changes. Therefore, Residuals u t has no Heteroscedasticity. Test on Autocorrelation On this condition that level of significance α is 0.05, volume of sample is 126, and the number of independent variable is 5, the critical of DW test is: d L =1.57, d U =1.78, 4-d U =2.22. DW in regression equation is 2.02, which is between 1.78 and Therefore, Residuals u t has no Autocorrelation. Test on Regression Equation Significance On this condition that level of significance α is 0.05, F(5, 120) is 2.29, which is far smaller than F value with in the equation. Therefore, the whole regression equation significantly has the relationship of linearity correlation. Test on Regression Equation Goodness of Fit R 2 is 0.88 in the paper, which clearly shows the better condition of regression equation goodness of fit. Moreover, it can be seen from comparing the sample actual observed value curve with the fitted value curve that regression equation goodness of fit is also better. 5. Conclusion and Implications 5.1 Conclusion This research is provided with the guidance meaning on continuously improving Chinese enterprise s core competency on the supply chain as WTO goes deep into development. Especially, we are aware from the study that, to set up the supply chain coopetition idea is a pressing matter of the moment, and to develop organization competency and technology competency is a task of top priority. This research conclusion and contribution is: TOICC Model, as research tool for supply chain dynamic strategic alliance core competency, is initiated by author after consulting a number of literature materials. It is demonstrated by the quantitative method with function relationship in multiple linear regression equation that: All of five competencies have the positive influence on supply chain strategic alliance core competency, each of which can be improved to strengthen the supply chain strategic alliance core competency. And the influence degree from heavily to slightly is Organization, Technology, Cognition, Capital and Institution, that is to say, the heaviest influence degree refers to Organization and the slightest refers to Institution. 5.2 Implications of Further Research There are some limitations in this research. Firstly, institution competency and capital competency do not satisfy the needs of reliability which is remained to be improved by adjusting optimizing partners combination factors in future survey. Secondly, the measure of alliance performance is only a general evaluation, which can be made further research on basis of balanced supply chain scorecard method. Finally, the informants come from the medium-sized and small enterprises in Tianjin with the limited alliance experience, so it is necessary to broaden the range of survey and select more mature informants in the future. References [1]. Spekman, R. E., Forbes, T. M., Isabella, L. A. and Macavoy, T. C. (1998). Alliance management: a view from the past and a look to the future, Journal of Management Studies, 35(6): [2]. Coase, R. H. (1937). The nature of the firm. Economica, 4: [3]. Williamson, O. E. (1985). The Economic Institutions of Capitalism. New York: Free Press. [4]. Prahalad, C.K., Hamel, G. (1990). The core competence of the corporation. Harvard Business Review, 68(3): [5]. Zhou Jian(2002). Strategic Alliances and Business Competitiveness (in Chinese). Shanghai: Fudan 251

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