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Optimization design and computer simulation of enterprise R&D decision model under resource allocation

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Abstract

Taking into account enterprises’ investment on commodity quality and advertisements as important factors that affect sales volume, and the R&D activities are effective measures to reduce production costs and improve commodity competitiveness. Based on the game theory, this paper establishes the price game model among enterprises, and analyzes the relationship of relevant parameters under different competition modes by using computer simulation technology. The simulation results show that the two enterprises will obtain relatively high sales volume and profits in the Stackelberg competition mode, but the absorptive capacity makes the coordination strategy of the R&D stage become unstable. The non-coordination strategy can not only effectively stimulate enterprises to expand the scale of R&D investment to further reduce the cost of production, but also has a positive effect on the follower enterprises in improving sales volume and profits.

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References

  1. Amir, R.: Modelling imperfectly appropriable R&D via spillovers. Int. J. Ind. Organ. 18(7), 1013–1032 (2000)

    Google Scholar 

  2. Aschhoff, B., Schmidt, T.: Empirical evidence on the success of R&D cooperation–happy together? Rev. Ind. Organ. 33(1), 41–62 (2008)

    Google Scholar 

  3. Atallah, G.: R&D cooperation with asymmetric spillovers. Can. J. Econ. 38(3), 919–936 (2005)

    Google Scholar 

  4. Aviv, Y., Pazgal, A.: Optimal pricing of seasonal products in the presence of forward-looking consumers. Manuf. Serv. Oper. Manag. 10(3), 339–359 (2008)

    Google Scholar 

  5. Balasubramanian, S., Bhardwaj, P.: When not all conflict is bad: manufacturing-marketing conflict and strategic incentive design. Manag. Sci. 50(4), 489–502 (2004)

    Google Scholar 

  6. Bernstein, J.I., Nadiri, M.I.: Interindustry R&D spillovers, rates of return, and production in high-tech industries. Am. Econ. Rev. 78(2), 429–434 (1988)

    Google Scholar 

  7. Boardman, P.C.: Government centrality to university-industry interactions: university research centers and the industry involvement of academic researchers. Res. Policy 38(10), 1505–1516 (2009)

    Google Scholar 

  8. Cachon, G.P., Swinney, R.: Purchasing, pricing, and quick response in the presence of strategic consumers. Manag. Sci. 55(3), 497–511 (2009)

    MATH  Google Scholar 

  9. Cachon, G.P., Harker, P.T.: Competition and outsourcing with scale economies. Manag. Sci. 48(10), 1314–1333 (2002)

    MATH  Google Scholar 

  10. Chesbrough, H.W.: The era of open innovation. MIT Sloan Manag. Rev. 44(3), 35–41 (2003)

    Google Scholar 

  11. Dahl, D.W., Moreau, P.: The influence and value of analogical thinking during new product ideation. J. Mark. Res. 39(1), 47–60 (2002)

    Google Scholar 

  12. D’Aspremont, C., Jacquemin, A.: Cooperative and noncooperative R&D in duopoly with spillovers. Am. Econ. Rev. 78(78), 1133–1137 (1988)

    Google Scholar 

  13. Dumrongsiri, A., Fan, M., Jain, A., Moinzadeh, K.: A supply chain model with direct and retail channels. Eur. J. Oper. Res. 187(3), 691–718 (2008)

    MathSciNet  MATH  Google Scholar 

  14. Gabszewicz, J.J., Thisse, J.F.: Price competition, quality and income disparities. J. Econ. Theory 20(3), 340–359 (1979)

    MATH  Google Scholar 

  15. Goel, R.K.: Spillovers, rivalry and r&d investment. South. Econ. J. 62(1), 71–76 (1995)

    MathSciNet  Google Scholar 

  16. Grünfeld, L.A.: Meet me halfway but don’t rush: absorptive capacity and strategic r&d investment revisited. Int. J. Ind. Organ. 21(8), 1091–1109 (2003)

    Google Scholar 

  17. Grünfeld, L.A.: Multinational production, absorptive capacity, and endogenous r&d spillovers. Rev. Int. Econ. 14(5), 922–940 (2006)

    Google Scholar 

  18. Hao, L., Yangjian, J., Gu, X., Zhigang, B., Guoning, Q.: A universal enterprise manufacturing services maturity model: a case study in a chinese company. Int. J. Comput. Integr. Manuf. 27(5), 434–449 (2014)

    Google Scholar 

  19. He, X., Krishnamoorthy, A., Prasad, A., Sethi, S.P.: Retail competition and cooperative advertising. Oper. Res. Lett. 39(1), 11–16 (2011)

    MathSciNet  MATH  Google Scholar 

  20. Jan, V., Raymond, D.B.: Asymmetric spillovers and investments in research and development of leaders and followers. Econ. Innov. New Technol. 17(17), 417–433 (2008)

    Google Scholar 

  21. Miklós-Thal, J.: Optimal collusion under cost asymmetry. Econ. Theor. 46(1), 99–125 (2011)

    MathSciNet  MATH  Google Scholar 

  22. Joglekar, N.R., Lévesque, M.: Marketing, r&d, and startup valuation. IEEE Trans. Eng. Manag. 56(2), 229–242 (2009)

    Google Scholar 

  23. Kamien, M.I., Muller, E., Zang, I.: Research joint ventures and r&d cartels. Am. Econ. Rev. 82(5), 1293–1306 (1992)

    Google Scholar 

  24. Karray, S., Martín-Herránb, G.: A dynamic model for advertising and pricing competition between national and store brands. Eur. J. Oper. Res. 193(2), 451–467 (2009)

    MathSciNet  MATH  Google Scholar 

  25. Kunz, W., Schmitt, B., Meyer, A.: How does perceived firm innovativeness affect the consumer? J. Bus. Res. 64(8), 816–822 (2011)

    Google Scholar 

  26. Lambertini, L., Orsini, R.: Quality improvement and process innovation in monopoly: a dynamic analysis. Oper. Res. Lett. 43(4), 370–373 (2015)

    MathSciNet  MATH  Google Scholar 

  27. Li, H., Ji, Y., Gu, X., Qi, G., Tang, R.: Module partition process model and method of integrated service product. Comput. Ind. 63(4), 298–308 (2012)

    Google Scholar 

  28. Lu, J.C., Tsao, Y.C., Charoensiriwath, C.: Competition under manufacturer service and retail price. Econ. Model. 28(3), 1256–1264 (2011)

    Google Scholar 

  29. Lyons, A.C., Ma’Aram, A.: An examination of multi-tier supply chain strategy alignment in the food industry. Int. J. Prod. Res. 52(7), 1911–1925 (2014)

    Google Scholar 

  30. Mitra, S.: Revenue management for remanufactured products. Omega 35(5), 553–562 (2007)

    Google Scholar 

  31. Moukrim, A., Quilliot, A., Toussaint, H.: An effective branch-and-price algorithm for the preemptive resource constrained project scheduling problem based on minimal interval order enumeration. Eur. J. Oper. Res. 244(2), 360–368 (2015)

    MathSciNet  MATH  Google Scholar 

  32. Nguyen, D., Shi, L.: Competitive advertising strategies and market-size dynamics: a research note on theory and evidence. Manag. Sci. 52(6), 965–973 (2006)

    MATH  Google Scholar 

  33. Piga, C., Poyago-Theotoky, J.: Endogenous R&D spillovers and locational choice. Reg. Sci. Urban Econ. 35(2), 127–139 (2005)

    Google Scholar 

  34. Ouardighi, F.E., Kogan, K.: Dynamic conformance and design quality in a supply chain: an assessment of contracts’ coordinating power. Ann. Oper. Res. 211(1), 137–166 (2013)

    MathSciNet  MATH  Google Scholar 

  35. Radford, S.K., Bloch, P.H.: Linking innovation to design: consumer responses to visual product newness. J. Prod. Innov. Manag. 28(s1), 208–220 (2011)

    Google Scholar 

  36. Rindova, V.P., Williamson, I.O., Petkova, A.P., Sever, J.M.: Being good or being known: an empirical examination of the dimensions, antecedents, and consequences of organizational reputation. Acad. Manag. J. 48(6), 1033–1049 (2005)

    Google Scholar 

  37. Sandberg, B.: Customer-related proactiveness in the radical innovation development process. Eur. J. Innov. Manag. 10(2), 252–267 (2007)

    Google Scholar 

  38. Smith, K.G., Collins, C.J., Clark, K.D.: Existing knowledge, knowledge creation capability, and the rate of new product introduction in high-technology firms. Acad. Manag. J. 48(2), 346–357 (2005)

    Google Scholar 

  39. Spence, M.: Cost reduction, competition, and industry performance. Econometrica 52(52), 101–121 (1984)

    Google Scholar 

  40. Stone-Romero, E.F., Stone, D.L., Grewal, D.: Development of a multidimensional measure of perceived product quality. J. Qual. Manag. 2(1), 87–111 (1997)

    Google Scholar 

  41. Su, X., Zhang, F.: Strategic customer behavior, commitment, and supply chain performance. Soc. Sci. Electron. Publ. 54(10), 1759–1773 (2008)

    MATH  Google Scholar 

  42. Szmerekovsky, J.G., Zhang, J.: Pricing and two-tier advertising with one manufacturer and one retailer. Eur. J. Oper. Res. 192(3), 904–917 (2009)

    MathSciNet  MATH  Google Scholar 

  43. Yu, M., Debo, L.G., Kapuscinski, R.: Strategic waiting for consumer-generated quality information: dynamic pricing of new experience goods. SSRN Electron. J. 62(2), 410–435 (2016)

    Google Scholar 

  44. Ulaga, W., Chacour, S.: Measuring customer-perceived value in business markets: a prerequisite for marketing strategy development and implementation. Ind. Mark. Manag. 30(6), 525–540 (2001)

    Google Scholar 

  45. Xie, G., Yue, W., Wang, S., Lai, K.K.: Quality investment and price decision in a risk-averse supply chain. Eur. J. Oper. Res. 214(2), 403–410 (2011)

    MathSciNet  MATH  Google Scholar 

  46. Xie, J., Wei, J.C.: Coordinating advertising and pricing in a manufacturer-retailer channel. Eur. J. Oper. Res. 197(2), 785–791 (2009)

    MathSciNet  MATH  Google Scholar 

  47. Zahra, S.A., George, G.: Absorptive capacity: a review and reconceptualization, and extension. Acad. Manag. Rev. 27(2), 185–203 (2002)

    Google Scholar 

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Acknowledgements

This work was supported by the National Science Foundation for Young Scientists of China (71602041).

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  1. School of Economics and Management, Harbin Engineering University, Harbin, 150001, China

    Qi Na & Jian-Yu Zhao

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  1. Qi Na
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Correspondence to Jian-Yu Zhao.

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Na, Q., Zhao, JY. Optimization design and computer simulation of enterprise R&D decision model under resource allocation. Cluster Comput 22 (Suppl 4), 7841–7860 (2019). https://doi.org/10.1007/s10586-017-1462-7

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