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Electronic Commerce Research
Erschienen in: Electronic Commerce Research 3/2020

17.07.2020

An extended Bass Model on consumer quantity of B2C commerce platforms

verfasst von: Xiaoyu Li, Jiahong Yuan, Yan Shi, Tianteng Wang, Xiangpei Hu, Felix Tung Sun Chan, Junhu Ruan

Erschienen in: Electronic Commerce Research | Ausgabe 3/2020

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Abstract

For B2C (Business to Customer) commerce platforms, quickly attracting enough consumers is an extremely important issue. However, existing studies mainly analyze whether consumers make online purchase and its influencing factors, but pay less attention to the changes in consumer size. Therefore, this paper aims to study the changing law of consumer quantity from the macro level, which may help E-commerce platforms reasonably predict it. Firstly, we point out the unique feature of the B2C commerce platforms compared with traditional products or technologies, namely indirect network externality. And we combine this feature and the factors that influence consumers and enterprises’ adoption of B2C commerce to build an extended Bass Model. Finally, we verify the validity of our model with the data of Chinese online shoppers. In addition, we put forward some suggestions on the future research of this extended Bass Model.
Vorheriger Artikel Examining the role of the marketing activity and eWOM in the movie diffusion: the decomposition perspective
Nächster Artikel The market impacts of sharing economy entrants: evidence from USA and China

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Literatur
1.
2.
Cozzarin, B. P., & Dimitrov, S. (2016). Mobile commerce and device specific perceived risk. Electronic Commerce Research,16(3), 335–354.
3.
Zhu, K., Kraemer, K. L., & Xu, G. S. X. (2006). Migration to open-standard interorganizational systems: network effects, switching costs, and path dependency. Mis Quarterly,30, 515–539.
4.
Gefen, D., Karahanna, E., & Straub, D. W. (2003). Trust and TAM in online shopping: An integrated model. Mis Quarterly,27(1), 51–90.
5.
Armstrong, M. (2006). Competition in two-sided markets. RAND Journal of Economics,37(3), 668–691.
6.
Zhu, K., Kraemer, K. L., & Xu, S. (2006). The process of innovation assimilation by firms in different countries: A technology diffusion perspective on E-business. Management Science,52(10), 1557–1576.
7.
Maduku, D. K., Mpinganjira, M., & Duh, H. (2016). Understanding mobile marketing adoption intention by South African SMEs: A multi-perspective framework. International Journal Of Information Management,36(5), 711–723.
8.
Choshin, M., & Ghaffari, A. (2017). An investigation of the impact of effective factors on the success of e-commerce in small- and medium-sized companies. Computers in Human Behavior,66, 67–74.
9.
Dearing, J. W., & Cox, J. G. (2016). Diffusion of innovations theory, principles and practice. Health Affairs,37(2), 183–190.
10.
Mansfield, E. (1961). Technical change and the rate of imitation. Econometrica,29(4), 741–766.
11.
Liu, M., Li, B., & Sun, B. (2010). Literature review on the related theory and influence factors of E-business technology diffusion. Journal of Intelligence,29(08), 14–18.
12.
Balasubramanian, S., Raghunathan, R., & Mahajan, V. (2010). Consumers in a multichannel environment: Product utility, process utility, and channel choice. Journal of Interactive Marketing, 19(2)
13.
14.
15.
Gao, Y. (2014). A study about Behavior of Intergrated Develpoment of Oppprtunities and Resources[D], Jilin University.
16.
Orus, C., Gurrea, R., & Flavian, C. (2017). Facilitating imaginations through online product presentation videos: Effects on imagery fluency, product attitude and purchase intention. Electronic Commerce Research,17(4), 661–700.
17.
Bass, F. M. A. (2004). New product growth for model consumer durables. Management Science,50(12), 1825–1832.
18.
Smith, R. B. W. (1954). The propagation of innovation Waves. The Town Planning Review,24(4), 330–331.
19.
Bass, F. M., Krishnan, T. V., & Jain, D. C. (1994). Why the bass model fits without decision variables. Marketing Science,13(3), 203–223.
20.
Sandberg, M. (2011). Soft power, world system dynamics, and democratization: A bass model of democracy diffusion 1800–2000. Journal of Artificial Societies and Social Simulation,14(1), 4.
21.
Olson, J. S., & Olson, G. M. (2000). i2i trust in E-commerce. Communications of the Acm,43(12), 41–44.
22.
Gagnon, J., & Goyal, S. (2017). Networks, markets, and inequality. American Economic Review,107(1), 1–30.
23.
Zhou, R. G., Wang, X. R., Shi, Y. H., Zhang, R. Q., Zhang, L. Y., & Guo, H. Y. (2019). Measuring e-service quality and its importance to customer satisfaction and loyalty: An empirical study in a telecom setting. Electronic Commerce Research,19(3), 477–499.
24.
Xu, J., & Zhang, J. (2006). Survey on platform economics. China Industrial Economy,05, 40–47.
25.
26.
27.
Fourt, L. A., & Woodlock, J. W. (1960). Early prediction of market success for new grocery products. Journal of Marketing,25(2), 31–38.
28.
Tsai, H. T., Chang, H. C., & Tsai, M. T. (2019). Predicting repurchase intention for online clothing brands in Taiwan: Quality disconfirmation, satisfaction, and corporate social responsibility. Electronic Commerce Research,16(3), 375–399.
29.
Fan, Z. P., Che, Y. J., & Chen, Z. Y. (2017). Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis. Journal of Business Research,74(May), 90–100.
30.
Gopinath, S., Thomas, J. S., & Krishnamurthi, L. (2014). Investigating the relationship between the content of online word of mouth, advertising, and brand performance. Marketing Science, 33.
31.
Hong, J., Koo, H., & Kim, T. (2016). Easy, reliable method for mid-term demand forecasting based on the Bass model: A hybrid approach of NLS and OLS. European Journal of Operational Research,248(2), 681–690.
32.
Wu, X., Gong, Y. M., Xu, H. X., Chu, C. B., & Zhang, J. L. (2017). Dynamic lot-sizing models with pricing for new products. European Journal of Operational Research,260(1), 81–92.
33.
Fan, Z. P., Che, Y. J., & Chen, Z. Y. (2017). Product sales forecasting using online reviews and historical sales data: A method combining the Bass model and sentiment analysis. Journal of Business Research,74, 90–100.
34.
Bass, F. M., & Alain, V. B. (1982). Technical note: A note on optimal strategic pricing of technological innovations. Marketing Science,1(4), 371–378.
35.
Jiang, Z., & Jain, D. C. (2012). A generalized norton-bass model for multigeneration diffusion. Management Science,58(10), 1887–1897.
36.
Guo, X. (2014). A novel bass-type model for product life cycle quantification using aggregate market data. International Journal of Production Economics,158, 208–216.
37.
Renato, G., & Cinzia, M. (2013). Within-brand and cross-brand word-of-mouth for sequential multi-innovation diffusions. Ima Journal of Management Mathematics,25(3), 287–311.
38.
Balakrishnan, P. V., & Pathak, S. (2017). Impeding the juggernaut of innovation diffusion: A production-constrained model. Production and Operations Management,23(7), 1183–1197.
39.
40.
Chen, H. L., Zhang, J. X., & Liu, X. (2019). Review of the frontier researches on platform economy and the future prospects. Journal of Yunnan University of Finance and Economics,35(05), 3–11.
41.
Rosario, A. B., Sotgiu, F., De Valck, K., & Bijmolt, T. H. A. (2016). The effect of electronic word of mouth on sales: A meta-analytic review of platform, product, and metric factors. Journal of Marketing Research,53(3), 297–318.
42.
Katz, M. L., & Shapiro, C. (1985). Network externalities, competition, and compatibility. American Economic Review,75(3), 424–440.
43.
Shapiro, K. C. (1992). Product introduction with network externalities. Journal of Industrial Economics,40(1), 55–83.
44.
Roson, R. (2005). Auctions in a two-sided network: The market for meal voucher services. Networks Spatial Economics,5(4), 339–350.
45.
Hajli, M. (2013). A research framework for social commerce adoption. Information Management & Computer Security,21(3), 144–154.
46.
Beldad, A., Jong, M. D. M. I., & Steehouder, (2010). How shall I trust the faceless and the intangible? A literature review on the antecedents of online trust. Computers in Human Behavior,26(5), 857–869.
47.
Lee, J., Ryu, M. H., & Lee, D. (2019). A study on the reciprocal relationship between user perception and retailer perception on platform-based mobile payment service. Journal of Retailing and Consumer Services,48, 7–15.
48.
Mou, J., Shin, D. H., & Cohen, J. F. (2017). Trust and risk in consumer acceptance of e-services. Electronic Commerce Research,17(2), 255–288.
49.
Gilly, W., & Celsi, M. (2001). Shopping online for freedom, control, and fun. California Management Review,43(2), 34–55.
50.
Yoon, S. J. (2002). The antecedents and consequences of trust in online-purchase decisions. Journal of Interactive Marketing,16(2), 47–63.
51.
Lee, M. K. O., & Turban, E. (2001). A trust model for consumer internet shopping. International Journal of Electronic Commerce,6(1), 75–91.
52.
Luo, Y. K. (2019). Overview of E-commerce research. Journal of Commercial Economics,21, 5–10.
53.
Tobias, H. E., Patrick, W., & Michael, S. (2015). Understanding online product ratings: A customer satisfaction model. Journal of Retailing and Consumer Services,27, 113–120.
54.
Walia, N., Srite, M., & Huddleston, W. (2016). Eyeing the web interface: The influence of price, product, and personal involvement. Electronic Commerce Research,16(3), 297–333.
55.
Frik, A., & Mittone, L. (2019). Factors influencing the perception of website privacy trustworthiness and users' purchasing intentions: The behavioural economics perspective. Journal of Theoretical and Applied Electronic Commerce Research,14(3), 89–125.
56.
Balasubramanian, S., Konana, P., & Menon, N. (2003). customer satisfaction in virtual environments: A study of online investing. Management Science,49(7), 871–889.
57.
Evans, D. S. (2003). some empirical aspects of multi–sided platform industries. Review of Network Economics,2(3), 191–209.
58.
Jin, S. A. A. (2012). The roles of modality richness and involvement in shopping behaviour in 3D virtual stores. Journal of Interactive Marketing,23(3), 234–246.
59.
Eric, B. (2009). Introducing media richness into an integrated model of consumers' intentions to use online stores in their purchase process. Journal of Internet Commerce,8(3–4), 222–245.
60.
61.
Zhu, K., Kraemer, K. L., Xu, S., & Dedrick, J. (2004). Information technology payoff in E-business environments: An international perspective on value creation of E-business in the financial services industry. Journal of Management Information Systems,21(1), 17–54.
62.
Deng, Z. L., & Wang, Z. Y. (2016). Early-mover advantages at cross-border business-to-business e-commerce portals. Journal of Business Research,69(12), 6002–6011.
63.
Kavak, B., & Demirsoy, C. (2009). Identification of adopter categories for online banking in turkey. Service Industries Journal,29(8), 1037–1051.
64.
Nöldeke, G., & Tröger, T. (2006). A characterization of the distributions that imply existence of linear equilibria in the kyle-model. Annals of Finance,2, 73–85.
65.
Liu, Q. L. (2004). Product diffusion model analysis based on network externality. China Industrial Economy,4, 88–93.
66.
67.
Wang, Z. X., Dang, Y. G., & Pei, L. L. (2011). On greying bass model and its application. Journal of Grey System,23(1), 7–14.
68.
69.
Mahajan, V., Muller, E., & Bass, F. M. (1990). New product diffusion models in marketing: A review and directions for research. Journal of Marketing,54(1), 1–26.
Metadaten
Titel
An extended Bass Model on consumer quantity of B2C commerce platforms
verfasst von
Xiaoyu Li
Jiahong Yuan
Yan Shi
Tianteng Wang
Xiangpei Hu
Felix Tung Sun Chan
Junhu Ruan
Publikationsdatum
17.07.2020
Verlag
Springer US
Erschienen in
Electronic Commerce Research / Ausgabe 3/2020
Print ISSN: 1389-5753
Elektronische ISSN: 1572-9362
DOI
https://doi.org/10.1007/s10660-020-09428-x

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