The Effects of Product Diversification on R&D Intensity in Emerging Economies: The Mediate Role of Slack Resources

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2016 2 nd Asia-Pacific Management and Engineering Conference (APME 2016) ISBN: 978-1-60595-434-9 The Effects of Product Diversification on R&D Intensity in Emerging Economies: The Mediate Role of Slack Resources XIN SU and HAO-LONG LIU ABSTRACT Product diversification has become a vital operational strategy for firms in emerging economies to achieve competitive advantages. However, insufficient attention has been paid to the impacts of product diversification on research and development. Based on resource-based view, this paper empirically examines whether product diversification influences the intensity of firms R&D investment and further discusses the functions of slack resources as a mediator. By employing a large sample of Chinese manufacturing firms, the investigation demonstrates that the product diversification has significant negative effects on firms R&D intensity, and slack resources plays a full mediating role between them. INTRODUCTION Proper allocation of R&D resources across strategic business units is a challenge for each diversified firm. Pursuing scale and scope economies, product diversification contributes considerably to financial performance and competitive advantages. But owing to increasing competition levels and decreasing product lifecycles, R&D has been recognized as an important source of sustainable competitive advantage. The continuous conflicts and upgrading collaboration in resource allocation between diversification and R&D grow with each passing day, which induces a question that whether product diversification motivates or inhibits R&D innovation actually. It is convinced that product diversification has negative impacts on R&D intensity by many scholars. Due to the different types of corporate diversification strategies on the management of corporate-strategic-business-unit relations, R&D intensity in dominant-business firms is found significantly higher than in related- and unrelated-business firms 1. Moreover, diversification strategies create organizational inefficiencies and restructuring firms might increase R&D intensity by reducing diversified scope 2. In addition, firms with a higher degree of diversification are more likely to innovate through acquisition than through R&D 3. However, many scholars hold opposite or more complex views. Technologydiversified firms can receive more spillovers and reduce risks from technological Xin Su and Haolong Liu, Shandong University of Finance and Economics, 40 Shungeng Road, Jinan, Shandong 250014, P R China. 7

investments in different fields 4. Moreover, the effect of related diversification on R&D intensity is positive but marginally decreasing for moderate levels of relation 5. In addition, searching for and transferring knowledge across divisions in a diversified firm can cultivate innovation 6. The researches concerning organization slack resources might explain the inconsistent relationship of the product diversification and R&D intensity. Slack fosters greater experimentation but also diminishes discipline over innovative projects 7. Level of slack reduction following downsizing has only temporary effects on innovation output and large downsizing has great negative impacts on innovation 8. When slack is eliminated, there is a danger that knowledge creation will be severely hindered 9. Slack resources would enhance the radical innovation by increasing the distal knowledge search activity 10. THEORY AND HYPOTHESIS Diversified firms facing more demanding requirements for successful implementation 11 are forced to adopt tight financial controls within the firm and pursuing strategies that deemphasize high-risk innovations 12. In this environment, considering increasing the pressures on top management, the firms would pay more attention to good short-term financial performance, and reduce the expenditure of research, development, investigation of new product and investment of new equipment 13. Moreover, highly diversified firms pay more attention to distant search and exploration of new knowledge and novel opportunities instead of the local search and development, therefore their levels of R&D intensity are lower 14. In some degree, the internal R&D is just the supplement of external knowledge acquisition 15. Hypothesis 1: Product diversification has a negative association with R&D intensity. Because slack is a reserve of resources that are not consumed by the necessity of the continued daily operation of the firm 16, firms possessing abundant slack resources focus on the exploitation of available resources and are less likely to engage in radical innovation and strategic change 17. Instead, the resource-constraint firms engage in exploration of the market opportunities and R&D 18. But from the perspectives of resource-based view, slack resources enhance firms conditions and motivations to response to technological evolution and demand change by R&D innovation, increase the degree of freedom to search market opportunities 19, and facilitate the innovative experiments for the products, services, processes and concepts 20. Some scholars regard organizational slack as an antecedent of product diversification, and discuss the incentive effects of slack resources on diversified operations, but few scholars explore the impacts of diversified levels on slack stocks. The product-diversified firms usually entry the industries that they are not quite familiar with or cannot adapt to quickly, which might lead various mistakes and fails. As a result, they have to invoke and employ the slack resources to relieve financial tension, correct operational disfigurement and compensate the loss caused information asymmetry. 8

Hypothesis 2: Slack resources mediate the negative relationship between product diversification and R&D intensity. Figure 1. Research model and expected effects. Figure 1 provides the empirical procedure of this research. The mediating role of slack resources between product diversification is and R&D intensity demonstrated when the following conditions are met: (1) There is a significant relationship between product diversification and R&D intensity at step 1. (2) There is a significant relationship between product diversification and slack resources at step 2. (3) There is a significant relationship between slack resources and R&D intensity at step 3. (4) The effect of product diversification on R&D intensity at step 1 is less than the effect of product diversification on R&D intensity at step 4, in which product diversification and slack resources are both independent variables. DATA AND METHODOLOGY Information on firms R&D investment and product diversification was obtained from China Center for Economic Research (CCER). After merging the databases and excluding unusable or unreliable observations, a final sample of 715 firms with complete information for 2012-2014 is constructed. R&D Intensity In the similar prior researches, the R&D intensity is usually defined as a firm s R&D expenditure divided by their annual sales or total assets. But in emerging economies, R&D expenditure divided by sales might not reflect the R&D intensity comprehensively and objectively, therefore the method of R&D expenditure divided by assets is accepted in this paper. Product Diversification = & 100 Sufficient evidence and results indicate strong convergent, discriminated and criterion related validity for the entropy measure of diversification. So the entropy method is adopted to measure the product diversification in this paper. Suppose a firm operates in N different market segments and Pi denotes the sales of the firm in market segment I, then the entropy index of product diversification (EIPD) is measured as follows: 1 = ( ) 9

Slack Resources This paper focuses on financial slack as a key indicator of organization slack, which could be measured as the amount of cash available within a firm scaled by total assets. According to insights of the fundamental works of organization slack, we use current ratio (current assets divided by current liabilities) to measure slack resources (SLAR). 1 =(1 ) 100 Control Variables A variety of variables that are regularly associated with the intensity of R&D investment and abundance of slack resources are controlled in this paper, as in the similar prior researches. (1) First, we control the quality of earnings, asset use efficiency, profitability, growth and scale of a firm. (2) Second, we control ownership concentration and ownership structure by using the main indicators. (3) Third, we control the duality of COB & CEO, the percentage of independent directors and the average reward of managers, to reflect the basic information about corporate governance. RESULTS TABLE I. REGRESSION RESULTS AND MEDIATING EFFECTS. Dependent variable RDIA Dependent variable SLAR Model 1 Model 3 Model 4 Model 2 CVF_SSCOI 0.082 0.074 0.074 CVF_SSCOI 2.565 (0.588) (0.625) (0.627) (0.313) CVF_TAR 0.395 *** 0.429 *** 0.427 *** CVF_TAR -7.641 *** (0.001) (0.000) (0.000) (0.000) CVF_ROE 0.583 * 0.329 0.342 CVF_ROE 56.558 *** (0.076) (0.326) (0.308) (0.000) CVF_GRTA -0.317 *** -0.323 *** -0.323 *** CVF_GRTA 1.030 (0.000) (0.000) (0.000) (0.407) CVF_NLTA -0.528 *** -0.444 *** -0.438 *** CVF_NLTA -19.252 *** (0.000) (0.000) (0.000) (0.000) CVS_T10SH -1.246 *** -1.347 *** -1.363 *** CVS_T10SH 22.798 *** (0.000) (0.000) (0.000) (0.000) CVS_DIESH 0.275 0.226 0.216 CVS_DIESH 12.177 ** (0.360) (0.451) (0.470) (0.012) CVS_EXESH 0.275 0.271 0.281 CVS_EXESH 0.519 (0.379) (0.386) (0.369) (0.921) CVS_INSSH 0.115 0.032 0.027 CVS_INSSH 18.491 *** (0.435) (0.829) (0.854) (0.000) CVS_STASH -0.266-0.298-0.299 CVS_STASH 7.829 (0.509) (0.459) (0.457) (0.248) CVG_DUALI -0.086-0.088-0.089 CVG_DUALI 0.712 (0.351) (0.339) (0.329) (0.639) CVG_PCIND -0.336-0.266-0.266 CVG_PCIND -15.202 (0.605) (0.681) (0.682) (0.157) CVG_ART3D 0.006 ** 0.006 ** 0.005 ** CVG_ART3D 0.013 (0.010) (0.012) (0.012) (0.713) CVG_ART4E 0.007 ** 0.007 ** 0.007 ** CVG_ART4E 0.031 10

(0.011) (0.012) (0.013) (0.502) CVG_ARDES 0.007 0.007 0.007 CVG_ARDES 0.076 (0.280) (0.305) (0.284) (0.489) EIPD -0.094 * -0.084 EIPD -2.639 *** (0.092) (0.132) (0.003) SLAR 0.005 *** 0.005 *** SLAR (0.000) (0.000) _cons 13.620 *** 11.607 *** 11.544 *** _cons 445.272 *** (0.000) (0.000) (0.000) (0.000) N 2145 2145 2145 N 2145 Table I provides the regression results of each model. (1) In model 1, the dependent variable is R&D intensity (RDIA) and the independent variable is only the entropy index of product diversification (EIPD). The result shows that EIPD has a significant and negative effect on RDIA as expected. The coefficient is -0.094 and the P-value is 0.092. Therefore the Hypothesis 1 is supported. (2) In model 2, the dependent variable is slack resources (SLAR) and the independent variable is the entropy index of product diversification (EIPD). The result shows that EIPD also has a significant and negative effect on SLAR as expected. The coefficient is -2.639 and the P-value is 0.003. (3) In model 3, the dependent variable is R&D intensity (RDIA) and the independent variable is only slack resources (SLAR). The result shows that SLAR has a significant and positive effect on RDIA as expected. The coefficient is 0.005 and the P-value is 0.000. (4) In model 4 (full model), the dependent variable is R&D intensity (RDIA) and the independent variables include product diversification (EIPD) and slack resources (SLAR). The result shows that EIPD has an insignificant and negative effect on RDIA and SLAR still has a significant and positive effect on RDIA. Therefore the Hypothesis 2 is supported. DISCUSSION AND CONCLUSION According to the empirical examination, both hypothesis 1 & 2 are completely supported, which means product diversification has a negative association with R&D intensity and slack resources fully mediate the negative relationship between them. (1) Usually, the high-product-diversified firms are huge in size and complex in structure, so they adopt divisional structures to keep operational efficiency, which leads the achievements of R&D innovation in some specific technical fields could hardly be shared by each strategic business unit. As a result, the high-product-diversified firms with fair capital strength are more inclined to rely on mergers and acquisitions to obtain new technologies, new patterns and new products, instead of R&D innovation through internal investment. (2) Away from the initial core business, the high-product-diversified firms usually adopt tight financial controls within the firm, because the original advantages in information and technology are quite limited in new business, leading the risks of R&D activities are greatly increased. Therefore, in order to maintain own interests, corporate managers are more likely to debase evaluation value of expected R&D achievements deliberately so that they could avoid operational risk as much as possible. (3) With the level of product diversification increasing, firms might entry the industries that they are not quite familiar with or cannot adapt to quickly so they 11

could hardly come to success in a short time in new business fields. Owing to the immature markets in emerging economies, the business failure in new fields even would involve and impede the initial core business, resulting in the operational deterioration and financial strain. Thus the conditions and motivations for R&D innovation are further weakened. ACKNOWLEDGMENTS This work is supported by National Philosophy and Social Science Foundation, the Assurance Mechanism of Agricultural Product Quality and Safety based on Multi-agent Coordination (15AGL014). It is also supported by Important R&D Program of Shandong Province, Key Issues and System Implementation of Early Warning for Agricultural Product Quality Safety under the Trend of Intelligent Agriculture (2016GSF120013). REFERENCES 1. Baysinger B, Hoskisson R E. Diversification Strategy and R&D Intensity in Multiproduct Firms[J]. Academy of Management Journal, 1989, 32(2):310-332. 2. Hoskisson R O, Johnson R A. Corporate Restructuring and Strategic Change: The Effect on Strategy and R & D Intensity[J]. Strategic Management Journal, 1992, 13(8):625-634. 3. Banker R D, Wattal S, Plehndujowich J M. R&D Versus Acquisitions: Role of Diversification in the Choice of Innovation Strategy by Information Technology Firms[J]. Journal of Management Information Systems, 2011, 126(28):109-144. 4. Garcia-Vega M. Does technological diversification promote innovation? An empirical analysis for European firms[j]. Research Policy, 2006, 35(2):230-246. 5. Alonsoborrego C, Forcadell F J. Related diversification and R&D intensity dynamics[j]. Research Policy, 2010. 6. Miller D J, Cardinal L B. The Use of Knowledge for Technological Innovation within Diversified Firms[J]. Academy of Management Journal, 2007, 50(2):307-325. 7. Kim H, Lee P M. Ownership Structure and the Relationship Between Financial Slack and R&D Investments: Evidence from Korean Firms[J]. Organization Science, 2008, 19(3):404-418. 8. Mellahi K, Wilkinson A. Slash and burn or nip and tuck? Downsizing, innovation and human resources[j]. International Journal of Human Resource Management, 2010, 21(13):2291-2305. 9. Richtnér A, Åhlström P, Goffin K. Squeezing R&D : A Study of Organizational Slack and Knowledge Creation in NPD, Using the SECI Model [J]. Journal of Product Innovation Management, 2013, 31(6):1268 1290. 10. Troilo G, Luca L M D, Atuahene-Gima K. More Innovation with Less? A Strategic Contingency View of Slack Resources, Information Search, and Radical Innovation [J]. Journal of Product Innovation Management, 2014, 31(2):259-277. 11. Dundas K N M, Richardson P R. Implementing the unrelated product strategy[j]. Strategic Management Journal, 1982, 3(4):287-301. 12. Hoskisson R E, Hitt M A. Strategic control systems and relative R&D investment in large multiproduct firms[j]. Strategic Management Journal, 1988, 9(6):605-621. 13. Baliga B R, Jaeger A M. Multinational Corporations: Control Systems and Delegation Issues[J]. Journal of International Business Studies, 1984, 15(2):25-40. 14. Miller D J. Technological diversity, related diversification, and firm performance[j]. Strategic Management Journal, 2006, 27(7):601-619. 15. Dahlander L, Gann D M. How open is innovation?[j]. Research Policy, 2010, 39(6):699-709. 16. Danneels E. Organizational antecedents of second-order competences[j]. Strategic Management Journal, 2008, 29(29):519-543. 17. Kraatz M S, Zajac E J. How Organizational Resources Affect Strategic Change and Performance in Turbulent Environments: Theory and Evidence[J]. Organization Science, 2001, 12(5):632-657. 12

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