【作者】 邓鳞波；

【导师】 刘伟；

【作者基本信息】 重庆大学 ， 企业管理， 2014， 博士

【摘要】 供应商研发决策研究包括供应商自主研发决策与供应商被动参与研发决策两大类，本文在Bhaskaran和Krishnan研究结论的基础上通过：①供应商进行以降低成本为目的的研发；②供应商进行以提升产品质量为目的的研发；③供应商分担制造商研发成本三种形式来研究供应商研发决策问题。供应商分担制造商研发成本是供应商被动参与研发的常见方式之一，供应商应制造商的要求投入资源参与研发以达到降低成本和分担风险的目的，但随着产品技术的日益复杂以及供应商技术能力的不断提高，供应商开始承担越来越多的研发任务，并在研发决策中面临更大的挑战。供应商不仅参与研发，而且在面向多制造商供货的现实场景中进行自主研发决策，其自主研发决策不仅受到自身资源约束，还受到外部环境，特别是制造商的约束。在资源一定的情况下，供应商在自主研发决策时面临选择共性技术还是专用性技术路线的两难选择，即：供应商针对面向所有制造商进行的提升产品质量或降低部件成本的共性技术研发决策；或供应商针对某一个特定制造商进行的提升产品质量或降低部件成本的专用性技术研发决策。本文以我国汽车行业为对象，以汽车零部件企业为案例，通过对重庆万里蓄电池企业三种场景下的研发决策进行分析，基于供应商研发的视角，分别构造了供应商进行以降低部件成本为目的的自主研发和供应商进行以提升最终产品质量为目的的自主研发两种情形，得出供应商在两种场景中选择共性技术和专用性技术情形下各自对应的最优研发决策。并针对供应商应制造商要求被动参与研发的场景，考虑多供应商不同分担意愿下，研究了供应商如何决策最优研发成本分担比例。重点研究了供应商在面临选择共性技术还是专用性技术路线的两难选择下如何进行自主研发决策。在供应商进行以降低部件成本为目的的研发中，针对面向多制造商的供应商自主研发决策问题，分别构造了供应商在选择共性技术和专用性技术研发决策情形下与两个制造商组成的三阶段非合作博弈模型，得到了供应商在这两种情形下各自的最优研发决策，通过对这两种不同技术路线中供应商最优研发程度比较，给出了这两种情形下供应商研发程度相等的条件和各自的占优区间。供应商选择不同技术路线，会在市场容量不变的情况下带来不同的部件成本降低幅度。进一步讨论了各参数变动对这两种情形下供应商最优研发决策的影响，并给出了相应的数值解，表明采用不同技术研发决策时供应商最优研发程度与制造商单位成本存在显著差异，即：采用共技术性研发决策时，与两个制造商单位成本负相关；采用专用性技术研发决策时，与面向专用性的制造商单位成本正相关，无专用性面向的制造商单位成本负相关。研究了在供应商进行以提升最终产品质量为目的的研发场景中，供应商选择共性技术和专用性技术下如何进行最优研发程度、最大化利润、参与约束的决策。供应商并非直接面向市场而是面向不同的制造商，供应商自主研发决策目标选择的不同导致了不同的技术路线，会带来不同的市场变化。通过建立两阶段非合作博弈模型得到供应商选择两种技术下各自的最大化利润、最优研发程度和参与约束条件，并对两种决策情形下供应商最大化利润进行比较，给出了这两种情形下供应商最大化利润相等的条件和各自的占优区间。最后运用算例对供应商在选择不同技术下影响其进行研发决策的各类参数进行敏感性分析，得出供应部件单位成本、供应部件价格、最终产品替代率、单位研发成本变动对这两种技术路线中供应商最优研发决策的影响。在考虑供应商不同分担意愿条件下，通过设计参与成本分担的供应商会获得供货比例增加的激励机制，研究了供应商在参与制造商研发成本分担中如何决策最优研发成本分担比例。针对在两家供应商与一家制造商组成的供应链体系中，并非所有的供应商会做出一致性的决策，考虑只有一家供应商参与研发成本分担的情形。制造商对参与分担的供应商实施增加供货比例的奖励机制，但保证未参与成本分担的供应商的供货量不少于分担前的供货量。通过逆向归纳法得到供应商最优研发成本分担比例和增加的供货比例区间，区间大小取决于参与成本分担的供应商与制造商的谈判能力，且参与分担研发成本的供应商在单位产品利润大于制造商单位产品利润的一定比例才有动机进行投资。最后运用算例对影响供应商最优研发成本分担比例的参数进行敏感性分析。更多还原

【Abstract】 R&D decision-making of supplier is included of independent R&D decision andpassively participate decision. Based on research conclusion of Bhaskaran and Krishnan,R&D Decision-making of supplier is divided into3purposes: reducing the cost,improveing product quality, sharing development costs of manufacturer.Sharing R&D cost is a common way suppliers passively taking part in the R&Dprocess. Manufacturer has long called for the input from suppliers to decreasemanufacturing cost and share risk. Sharing R&D cost is a common way supplierspassively taking part in the R&D process. Manufacturer has long called for the inputfrom suppliers to decrease manufacturing cost and share risk. However, with theincreasingly complex of product technology and the suppliers’ technical ability,Suppliers is taking more and more research and development tasks and confronted withbigger challenges in R&D. Supplier is not only involved in R&D, but also makingindependent R&D decision in a real scene with many manufacturers. So its R&Ddecisions is constrainted by internal and externalities, especially the manufacturers.Given the practical universality that suppliers may simultaneously face multiplemanufacturers, suppliers confront a dilemma between choosing generic technology andspecial technology when conducting independent R&D with fixed resources, namelychoosing the generic technology with which suppliers increase product quality anddecrease cost for all manufacturers, or choosing the special technology particularlycrafted for a certain manufacturer.From the optic angle of China automobile industry, this paper collects will theoryof suppliers’ participation with the practice of China auto parts industry with a casestudy of Wan Li, an auto battery company participating in the automobilemanufacturer’s R&D decision-making process. Based on three R&D scenes of Wan Li,this paper constructs two R&D purpose situations of reducing part cost and improvingfinal product quality. Suppliers’ optimal decision-making regarding the selection isanalyzed between generic technology and special technology in those twoaforementioned situations. With the third situation of suppliers’ passive participationrequired by manufacturers, suppliers’ optimal R&D cost sharing proportion is studiedwith different share willings.This paper further discusses how suppliers conduct independent R&D decision-making when facing the dilemma between choosing the generic technologyand special technology.Focusing on the R&D issue of supplier dealing with multiple manufacturers in asituation that decreasing the cost becomes the goal, this paper establishes two dynamicgame models based on supplier’s selection between the generic technology and specialtechnology, and provides the optimal R&D decision-making. Based on these twodifferent technological choices, two conditions that supplier would reach the optimalR&D level and their respective priori intervals are offered through the comparison ofthe optimal R&D level between the two choices. Supplier’s different technology choiceswill result in different component cost decreasing ranges. This paper subsequentlydiscusses the impacts on supplier’s optimal R&D decision-making under two situationsbrought by the change of parameters, and gives the corresponding numerical solutions,which indicates a stark contrast between supplier’s optimal R&D level andmanufacturer’s unit cost when supplier chooses different technology. When choosingthe generic technology, it is negatively related to two manufacturers’ unit cost, on theother hand, when choosing the special technology, it is positively related tomanufacturer dealing with special orientation, while negatively related to manufacturerwithout specialized orientation.The second participation form of supplier deals with enhancing the product quality.With this being the premise, this paper then discusses how supplier could reach theoptimal R&D level, maximum profit and the decision-making about participation andrestriction when making different choices between the generic and special technology.Instead of directly dealing with the consumer market, supplier faces differentmanufacturers, and supplier’s different choices on R&D goals will result in differenttechnology paths, consequently bringing in different market changes. By establishingthe two-stage non-cooperative game model, this paper addresses the maximized profit,the optimal R&D level and the participation and restriction conditions when makingdifferent choices, and by comparing the maximized profits resulted in differenttechnology choices, this paper therefore offers the priori interval for each technologychoice and the condition under which the supplier’s maximized profit will stay the same.A sensibility analysis is conducted for those parameters impacting the R&Ddecision-makings under different technology choices by using computational example,which indicates the impacts on the supplier’s optimal R&D decision-making under these two selections brought by supplying component unit cost, supplying componentprice, end product substitution rate and unit R&D cost change.Considering suppliers with different share willing, incentive mechanism ofdelivery increased ratio is obtained by sharing cost while suppliers participate in thedesigning. The optimal sharing proportion of R&D cost is studied while supplier sharethe manufacturer R&D cost.In a supply chain consisted of two suppliers and onemanufacturer, it is clear that not all suppliers will make the same decision, therefore thispaper only considers the situation that only one supplier takes part in the R&D costsharing. By increasing the supplying ratio for suppliers participating the sharing, themanufacturer introduces an incentive mechanism, while still guarantees that thesupplying volume from suppliers not taking in part of the sharing, will not be less thanthe supplying volume before sharing. Through the reverse induction method, this papercomes up with suppliers’ optimal R&D cost sharing ratio and the increased supplyingratio interval whose range is determined by suppliers’ ability to negotiate with themanufacturer. In the meantime, supplies participating sharing the R&D cost will only bemotivated to invest when unit product profit exceeds manufacturer unit product profit toa certain percentage. The sensibility analysis is conducted for parameters impacting thesupplier’s optimal R&D cost sharing ratio through computational example.更多还原