Optimizing Advertising Using Wireless Communication Technology: A Zero-Inflated Poisson Approach

Pin Jia Zou; Yan Yan Xu; Jue Wang; Zheng Fang

doi:10.4028/www.scientific.net/AMM.411-414.739

Paper Titles

A Provably Secure ID-Based Designated Verifier Proxy Signature Scheme Based on DLP
p.721

Researches on the Application Value and Practical Exploration of SNS Used in Rural Information Service
p.725

The Research of Virtualization Emulator Based on Open Shortest Path First
p.729

Protection Strategy for Two-Stage Cascaded Passive Optical Networks with Various Topologies
p.735

Optimizing Advertising Using Wireless Communication Technology: A Zero-Inflated Poisson Approach
p.739

Noise-Robust Voice Activity Detector Based on Four States-Based HMM
p.743

Investigation of the Performance of OOK, 2DPSK, QDPSK in Downlink of Ground-to-Satellite Laser Communication Systems
p.749

Performance of OOK, 2PSK, QPSK Modulation Format in Downlink of Ground-to-Satellite Laser Communication under the Fluctuation of Atmosphere
p.753

The Performance of MSK in Downlink of Ground-to-Satellite Laser Communication Systems
p.757

HomeApplied Mechanics and MaterialsApplied Mechanics and Materials Vols. 411-414Optimizing Advertising Using Wireless...

Optimizing Advertising Using Wireless Communication Technology: A Zero-Inflated Poisson Approach

Abstract:

Recently, more and more companies are using wireless location technology to improve advertising effectiveness. Although location-targeted advertising seemingly offers practitioners tremendous potential given the ubiquitous nature of mobile devices, we know very little about it. Base on field experiment data, the developed zero-inflated Poisson model reveals that distance, discount and CSR(Corporate Social Responsibility) could affect sales impact of advertising while using wireless communication technology. These results have implications for mobile marketing research and practice while using wireless communication technology.

You might also be interested in these eBooks

View Preview

Info:

Periodical:

Applied Mechanics and Materials (Volumes 411-414)

Pages:

739-742

DOI:

https://doi.org/10.4028/www.scientific.net/AMM.411-414.739

Citation:

Cite this paper

Online since:

September 2013

Authors:

Pin Jia Zou, Yan Yan Xu, Jue Wang, Zheng Fang

Keywords:

Mobile Advertising, Wireless Communication Technology, Zero-Inflated Poisson

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] Kai Li., Timon C, Du Building a targeted mobile advertising system for location-based services. Decision Support Systems 54 (2012)1-8.

DOI: 10.1016/j.dss.2012.02.002

Google Scholar

[2] Patrick. Barwise, Colin. Strong. Permission-based mobile advertising. Journal of Interactive Marketing 16 (1)(2002)14–24.

DOI: 10.1002/dir.10000

Google Scholar

[3] M.M. Tsang, S.C. Ho, T.P. Liang. Consumer attitudes toward mobile advertising: an empirical study. International Journal of Electronic Commerce 8 (3) (2004)65–78.

DOI: 10.1080/10864415.2004.11044301

Google Scholar

[4] M. Leppaniemi, H. Karjaluoto. Factors influencing consumers' willingness to accept mobile advertising: a conceptual model. International Journal of Mobile Communications 3 (3)(2005), 197–213.

DOI: 10.1504/ijmc.2005.006580

Google Scholar

[5] M. Merisavo, S. Kajalo, A. Arponen,S. Kajalo, M. Raulas. The effectiveness of targeted mobile advertising in selling mobile services: an empirical study. Journal of Mobile Communications 4 (2)(2006), 119-127.

DOI: 10.1504/ijmc.2006.008604

Google Scholar

[6] T. Park, R. Shenoy, G. Salvendy. Effective advertising onmobile phones: a literature reviewand presentation of results from53 case studies. Behavior& Information Technology 27(5) (2008), 355–373.

DOI: 10.1080/01449290600958882

Google Scholar

[7] Ramin Vataparast, Ali Hasan Butt. An empirical study of factors affecting use of mobile advertising. International of Mobile Marketing 5(1) (2010), 28-40.

Google Scholar

[8] Chen, P. -T. and H. -P. HsiehPersonalized mobile advertising: Its key attributes, trends, and social impact. Technological Forecasting and Social Change 79(3)(2012), 543-557.

DOI: 10.1016/j.techfore.2011.08.011

Google Scholar

[9] S.T. Yuan, Y.W. Tsao. A recommendation mechanism for contextualized mobile advertising. Expert Systemswith Applications 24 (4) (2003), 399–414.

DOI: 10.1016/s0957-4174(02)00189-6

Google Scholar

[10] D.J. Xu, S.S. Liao, Q. Li, Combining empirical experimentation andmodeling techniques: a design research approach for personalizedmobile advertising applications. Decision SupportSystems 44 (3) (2008), 710–724.

DOI: 10.1016/j.dss.2007.10.002

Google Scholar

[11] Colin Cameron & Pravin K. Trivedi, Regression Analysis of Count Data, Econometric Society Monogragh No 30(1998), Cambridge University Press.

Google Scholar