×

zbMATH — the first resource for mathematics

Merchant selection and pricing strategy for a platform firm in the online group buying market. (English) Zbl 1391.91091
Summary: The online group-buying market is characterized by intense competition between brokers, called platform firms, which function as intermediaries between merchants and consumers. In an environment of intense competition, merchant selection and pricing strategies are critical for platform firms. This paper employs business analytics to support strategy formulation for these firms by forecasting market demand and analyzing competitive environments. We apply the proposed decision framework, which relies on business analytics, to a study of the online group-buying market in Japan.
MSC:
91B24 Microeconomic theory (price theory and economic markets)
62P20 Applications of statistics to economics
PDF BibTeX XML Cite
Full Text: DOI
References:
[1] Amemiya, T, The nonlinear two-stage least-squares estimator, Journal of Econometrics, 2, 105-110, (1974) · Zbl 0282.62089
[2] Amemiya, T. (1985). Advanced Econometrics. Cambridge, MA: Harvard University Press.
[3] Ando, T. (2014a). High-dimensional data analysis: Statistical modeling and model averaging with R. Tokyo: Asakura Publishing. (in Japanese).
[4] Ando, T. (2014b). A statistical analysis of the online group-buying market. In Proceedings of the 2014 INFORMS workshop on data mining and analytics. San Francisco, CA.
[5] Atanasova, CV; Wilson, N, Disequilibrium in the UK corporate loan market, Journal of Banking and Finance, 28, 595-614, (2004)
[6] Berry, S, Estimating discrete-choice models of product differentiation, RAND Journal of Economics, 25, 242-262, (1994)
[7] Berry, S; Levinsohn, J; Pakes, A, Automobile prices in market equilibrium, Econometrica, 63, 841-890, (1995) · Zbl 0836.90057
[8] Besanko, D; Gupta, S; Jain, D, Logit demand estimation under competitive pricing behavior: an equilibrium framework, Management Science, 44, 1533-1547, (1998) · Zbl 0989.90525
[9] Cao, P; Li, J; Yan, H, Optimal dynamic pricing of inventories with stochastic demand and discounted criterion, European Journal of Operational Research, 217, 580-588, (2012) · Zbl 1244.90014
[10] Chang, H-J; Teng, J-T; Ouyang, L-Y; Dye, C-Y, Retailer’s optimal pricing and lot-sizing policies for deteriorating items with partial backlogging, European Journal of Operational Research, 168, 51-64, (2006) · Zbl 1077.90002
[11] Chintagunta, P, Endogeneity and heterogeneity in a probit demand model: estimation using aggregate data, Marketing Science, 20, 442-456, (2001)
[12] Chintagunta, P; Dube, JP; Goh, KY, Beyond the endogeneity bias: the effect of unmeasured brand characteristics on household-level brand choice models, Management Science, 51, 832-849, (2005)
[13] Davis, P, Spatial competition in retail markets: movie theaters, RAND Journal of Economics, 37, 964-982, (2006)
[14] Fair, RC; Jaffee, DM, Methods of estimation for markets in disequilibrium, Econometrica, 40, 497-514, (1972)
[15] Fair, RC; Kelejian, HH, Methods of estimation for markets in disequilibrium: A further study, Econometrica, 42, 177-190, (1974) · Zbl 0284.90011
[16] Hartley, MJ, The estimation of markets in disequilibrium: the fixed supply case, International Economic Review, 17, 687-699, (1976)
[17] Hsu, M-H; Chang, C-M; Chu, KK; Lee, Y-J, Determinants of repurchase intention in online group-buying: the perspectives of Delone & Mclean IS success model and trust, Computers in Human Behavior, 36, 234-245, (2014)
[18] Hsu, M-H; Chang, C-M; Chuang, L-W, Understanding the determinants of online repeat purchase intention and moderating role of habit: the case of online group-buying in Taiwan, International Journal of Information Management, 35, 45-56, (2015)
[19] Hurlin, C; Kierzenkowski, R, Credit market disequilibrium in Poland: can we find what we expect? non-stationarity and the short-side rule, Economic Systems, 31, 157-183, (2007)
[20] Jiang, R; Manchanda, P; Rossi, PE, Bayesian analysis of random coefficient logit models using aggregate data, Journal of Econometrics, 149, 136-148, (2009) · Zbl 1429.62673
[21] Khouja, M; Robbins, SS, Optimal pricing and quantity of products with two offerings, European Journal of Operational Research, 163, 530-544, (2005) · Zbl 1105.91304
[22] Khouja, M; Smith, MA, Optimal pricing for information goods with piracy and saturation effect, European Journal of Operational Research, 176, 482-497, (2007) · Zbl 1137.91390
[23] Liao, S-H; Chu, PH; Chen, Y-J; Chang, C-C, Mining customer knowledge for exploring online group buying behavior, Expert Systems with Applications, 39, 3708-3716, (2012)
[24] Meir, R; Lub, T; Tennenholtz, M; Boutilier, C, On the value of using group discounts under price competition, Artificial Intelligence, 216, 163-178, (2015) · Zbl 1408.91082
[25] Nevo, A, Mergers with differentiated products: the case of the ready-to-eat cereal industry, RAND Journal of Economics, 31, 395-421, (2000)
[26] Nevo, A, Measuring market power in the ready-to-eat cereal industry, Econometrica, 69, 307-342, (2001)
[27] Parsons, A; Ballantine, PW; Ali, A; Grey, H, Deal is on! why people buy from daily deal websites, Journal of Retailing and Consumer Services, 21, 37-42, (2014)
[28] Phillips, R; Simsek, AS; Ryzin, G, The effectiveness of field price discretion: empirical evidence from auto lending, Management Science, 61, 1741-1759, (2015)
[29] Riddel, M, Housing-market disequilibrium: an examination of housing-market price and stock dynamics 1967-1998, Journal of Housing Economics, 13, 120-135, (2004)
[30] Sudhir, K, Competitive pricing behavior in the auto market: A structural analysis, Marketing Science, 20, 42-60, (2001)
[31] Velupillai, KV, A disequilibrium macrodynamic model of fluctuations, Journal of Macroeconomics, 28, 752-767, (2006)
[32] Xing, W; Wang, S; Liu, L, Optimal ordering and pricing strategies in the presence of a B2B spot market, European Journal of Operational Research, 216, 87-98, (2012) · Zbl 1253.91181
[33] Zhang, Z; Zhang, Z; Wang, F; Law, R; Li, D, Factors influencing the effectiveness of online group buying in the restaurant industry, International Journal of Hospitality Management, 35, 237-245, (2013)
This reference list is based on information provided by the publisher or from digital mathematics libraries. Its items are heuristically matched to zbMATH identifiers and may contain data conversion errors. It attempts to reflect the references listed in the original paper as accurately as possible without claiming the completeness or perfect precision of the matching.