本章参考文献
[1]陈逢文,付龙望,张露,于晓宇.创业者个体学习、组织学习如何交互影响企业创新行为?——基于整合视角的纵向单案例研究[J].管理世界,2020,36(3):142-164.
[2]刁雅静,何有世,盛永祥.社交网络情景下新产品扩散的两阶段模型——微信与微博的对比研究[J].软科学,2017,31(10):115-119.
[3]盛亚.技术创新扩散与新产品营销[M].北京:中国发展出版社,2002:179-180.
[4]危小超,李岩峰,聂规划,陈冬林.基于后悔理论与多Agent模拟的新产品扩散消费者决策互动行为研究[J].中国管理科学,2017,25(11):66-75.
[5]张涛,庄贵军,黄缘缘.新产品对老产品的替代度[J].系统工程,2010,28(3):59-63.
[6]张运生,杜怡靖,陈瑟.专利池联盟合作对高技术企业技术创新的激励效应研究[J].研究与发展管理,2019,31(6):1-12.
[7]AFUAH A. Are network effects really all about size? The role of structure and conduct [J]. Strategic Management Journal, 2013, 34 (3): 257-273.
[8]ARGO JENNIFER, DAHL DARREN W, MANCHANDA RAJESH V. The influence of a Mere Social presence in a retail context [J]. Journal of Consumer Research, 2005, 32 (2): 207-212.
[9]ARROW K J. The economic implications of learning by doing [J]. The Review of Economic Studies, 1962, 29 (3): 155-173.
[10]BASS F M. A new product growth model for consumer durables [J]. Management Science, 1969, 29 (3): 215-227.
[11]BASS F M. Comments on“A new product growth for model consumer durables”: The bass model [J]. Management Science, 2004, 50 (12): 1833-1840.
[12]BEARDEN W O, ETZEL M J. Reference group influence on product and brand purchase decisions [J]. Journal of Consumer Research, 1982, 9 (2): 183-194.
[13]BINKEN J L G, STREMERSCH S. The effect of superstar software on hardware sales in system markets [J]. Journal of Marketing, 2009, 73 (2): 88-104.
[14]BOURDIEU J, ROSA J, BOLTON R, QUALLS W. The effect of group interactions on satisfaction judgments: Satisfaction escalation [J]. Marketing Science, 2006, 25 (4): 301-321.
[15]BOURDIEU P. Distinction: A social critique of the judgment of taste [M]. Cambridge: Harvard University Press, 1984.
[16]BURT R S.A note on missing network data in the general social survey [J]. Social Networks, 1987, 9 (1): 63-73.
[17]CANCIAN F. The innovator's situation: Upper-middle-class conservatism in agriculture communities [M]. Stanford: University Press, 1979: 49-56.
[18]CHANDRASEKARAN D, TELLIS G J. Getting a grip on the saddle: Chasms or cycles? [J]. Journal of Marketing, 2011, 75 (4): 21-34.
[19]CHEN Y, WANG Q, XIE J. Online social interactions: A natural experiment on word of mouth versus observational learning [J]. Journal of Marketing Research, 2011 (48): 238-254.
[20]CHEVALIER J A, MAYZLIN D. The effect of word of mouth on sales: Online book reviews [J]. Journal of Marketing Research, 2006, 43 (3): 345-354.
[21]COLEMAN J S, KATZ E, MENZEL H. Medical innovation: A diffusion study [M]. New York: Bobbs-Merrill, 1966.
[22]DAVIES S. The diffusion of process innovations [M]. Cambridge: Cambridge University Press, 1979.
[23]DIMAGGIO P J, POWELL W W. The iron cage revisited: Institutional isomorphism and collective rationality in organizational fields [J]. American Sociological Review, 1983, 48 (2): 147-160.
[24]DOSI G. Sources, procedures, and microeconomic effects of innovation [J]. Journal of Economic Literature, 1988, 26 (3): 1120-1171.
[25]DOU Y, NICULESCU M F, WU D J. Engineering optimal network effects via social media features and seeding in markets for digital goods and services [J]. Information Systems Research, 2013, 24 (1): 164-185.
[26]FENG Z, XIAOQUAN Z. Impact of online consumer reviews on sales: The moderating role of product and consumer characteristics [J]. Journal of Marketing, 2010, 74 (2): 133-148.
[27]FISHER J C, PRY R H.A simple substitution model of technological change [J]. Technological Forecasting & Social Change, 1971, 3 (C): 75-88.
[28]FOSTER J A, GOLDER P N, TELLIS G J. Predicting sales takeoff for whirlpool's new personal valet [J]. Marketing Science, 2004, 23 (2): 182-185.
[29]FUENTELASAZ L, MAICAS J P, POLO Y. Switching costs, network effects, and competition in the european mobile telecommunications industry [J]. Information Systems Research, 2012, 23 (1): 93-108.
[30]GERARD J T, STEFAN S, EDEN Y. The international takeoff of new products: The role of economics, culture, and country innovativeness [J]. Marketing Science, 2003, 22 (2): 188-208.
[31]GODES D, MAYZLIN D. Using online conversations to study word-of-mouth communication [J]. Marketing Science, 2004, 23 (4): 545-560.
[32]GODES D, MAYZLIN D. Firm-created word-of-mouth communication: Evidence from a field test [J]. Marketing Science, 2009, 28 (4): 721-739.
[33]GOLDENBERG J, OREG S. Laggards in disguise: Resistance to adopt and the leapfrogging effect [J]. Technological Forecasting & Social Change, 2007, 74 (8): 1272-1281.
[34]KALAITZANDONAKES N G, BOGGESS W G.A dynamic decision-theoretic model of technology adoption for the competitive firm [J]. Technological Forecasting & Social Change, 1993, 44 (1): 17-25.
[35]KAPLAN, F M, MILLER, E C. Group decision making and normative versus informational influence: Effects of type of issue and assigned decision rule [J]. Journal of Personality and Social Psychology, 1987, 53 (2): 306-313.
[36]KARNAS M, STONEMAN P L. Rank, stock, order and epidemic effects in the diffusion of new process technologies: An empirical model [J]. The RAND Journal of Economics, 1993, 24 (4): 503-528.
[37]KATONA Z, ZUBCESK P P, SARVARY M. Network effects and personal influences: The diffusion of an online social network [J]. Journal of Marketing Research, 2011, 48 (3): 425-443.
[38]KATZ E, LAZARSFELD P F. Personal influence: The part played by people in the flow of mass communication [M]. Glencoe: The Free Press, 1955.
[39]KIM T, HONG J. Bass model with integration constant and its applications on initial demand and left-truncated data [J]. Technological Forecasting and Social Change, 2015 (95): 120-134.
[40]LAZARSFELD P, BERELSON B, GAUDET H. The people's choice: How the voter makes up his mind in a presidential campaign [M]. New York: Columbia University Press, 1948.
[41]LEE H, KIM S G, PARK H-W, KANG P. Pre-launch new product demand forecasting using the bass model: A statistical and machine learning-based approach [J]. Technological Forecasting and Social Change, 2014 (86): 49-64.
[42]LIU X-F, JIANG T, ZHOU T-S. Research on the optimal path of product innovation diffusion model based on game theory [C]. International Conference on Management Science & Engineering 21th Annual Conference Proceedings., New York: Ieee, 2014: 1759-1765.
[43]LIU Y, DIAO S-M, ZHU Y-X, LIU Q. SHIR competitive information diffusion model for online social media [J]. Physica A, 2016 (461): 543-553.
[44]LIU Y. Word-of-mouth for movies: Its dynamics and impact on box office revenue [J]. Journal of Marketing, 2006 (70): 74-89.
[45]MANSFIELD E. Technical change and the rate of imitation [J]. Econometrica, 1961, 29 (4): 741-766.
[46]MANSFIELD E. The economics of technological change [M]. London: Longmans, Green and Co, 1969.
[47]MARQUES J M, ABRAMA D, SERôDIO R G. Being better by being right: Subjective group dynamics and derogation of in-group deviants when generic norms are undermined [J]. Journal of Personality and Social Psychology, 2001, 81 (3): 436-447.
[48]MOORE G A. Crossing the chasm: Marketing and selling technology products to mainstream customers [M]. New York: HarperCollins, 1991.
[49]NORTON J, BASS F.A diffusion theory model of adoption and sub-stitution for successive generations of high-technology products [J]. Management Science, 1987, 33 (9): 1069-1086.
[50]PARK C S. Revisiting the two-step flow model on twitter: Interconnection of self-identified south korean twitter opinion leadership, news consumption, news Links, and news curation [J]. Electron News, 2019, 13 (2): 63-77.
[51]PERES R, MULLER E, MAHAJAN V. Innovation diffusion and new product growth: Critical review and research directions [J]. International Journal of Research in Marketing, 2010, 27 (2): 91-106.
[52]PETER N G, GERARD J T. Will it ever fly? Modeling the takeoff of really new consumer durables [J]. Marketing Science, 1997, 16 (3): 256-270.
[53]PETER N G, GERARD J T. Growing, growing, gone: Cascades, diffusion and turning points in the product life cycle [J]. Marketing Science, 2004, 23 (2): 207-218.
[54]PHILLIPS D, ZUCKERMAN E. Middle-status conformity: Theoretical restatement and empirical demonstration in two markets [J]. American Journal of Sociology, 2001, 107 (2): 379-429.
[55]QIN Y, MA J, GAO S. Efficient influence maximization under TSCM: A suitable diffusion model in online social networks [J]. Soft Computing—A Fusion of Foundations, Methodologies & Applications, 2017, 21 (4): 827-838.
[56]RAMIREZ-HASSAN A, MONTOYA-BLANDON S. Forecasting from others'experience: Bayesian estimation of the generalized Bass model [J]. International Journal of Forecasting, 2020, 36 (2): 442-465.
[57]REINGANUM J F. The timing of innovation research, development, and diffusion [A] //R. Schmalensee & R. Willig: Handbook of Industrial Organization [M]. 1989.
[58]REINGANUM M R. Misspecification of capital asset pricing: Empirical anomalies based on earnings'yields and market values [J]. Journal of Financial Economics, 1981, 9 (1): 19-46.
[59]ROGERS E M. The diffusion of innovations [M]. New York: Free Press, 1995.
[60]ROHLFS. Bandwagon effects in high-Technology industries [M]. Cambridge: MIT Press, 2001.
[61]SRINIVASAN R, LILIEN G L, RANGASWAMY A. First in, first out? The effects of network externalities on pioneer survival [J]. Journal of Marketing, 2004, 68 (1): 41-58.
[62]STREMERSCH S, TELLIS G, FRANSES P, BINKEN J. Indirect network effects in new product growth [J]. Journal of Marketing, 2007, 71 (3): 52-74.
[63]TRUSOV M, BUCKLIN R E, PAUWELS K H. Effects of word-of-mouth versus traditional marketing: Findings from an internet social networking site [J]. Journal of Marketing, 2009, 73 (5): 90-102.
[64]VAN DEN BULTE C, JOSHI Y V. New product diffusion with influentials and imitators [J]. Marketing Science, 2007, 26 (3): 400-421.
[65]VANDENBULTE C, LILIEN G. Medical innovation revisited: Social contagion versus marketing effort [J]. American Journal of Sociology, 2001, 106 (5): 1409-1435.
[66]VILLANUEVA J, SHIJIN Y, HANSSENS D M. The impact of marketing-induced versus word-of-mouth customer acquisition on customer equity growth [J]. Journal of Marketing Research, 2008, 45 (1): 48-59.
[67]XU X B, CHEN R, ZHANG J. Effectiveness of trade-ins and price discounts: A moderating role of substitutability [J]. Journal of Economic Psychology, 2019 (70): 80-89.