Authors: Yanbin Tu; Min Lu; Y. Alex Tung
Addresses: Department of Marketing, School of Business, Robert Morris University, Moon Township, Pennsylvania, 15108, USA. ' Department of Economics and Legal Studies, School of Business, Robert Morris University, Moon Township, Pennsylvania, 15108, USA. ' Department of Operations and Information Management, School of Business, University of Connecticut, Storrs, CT 06269, USA
Abstract: Product sampling is an important marketing strategy in the software industry. In this work, we propose a dynamic model to study consumer behaviour in software product sampling. The model shows that the demand for dynamic sample is in two equilibrium states. The result of the comparative static analysis indicates that factors such as sampling effectiveness and network externality effect can result in converting samplers into software buyers. Other factors, however, have the opposite impact. These factors include attrition (forgetting) rate, software price, and learning cost. Managerial implications of our findings are provided to the software vendors. We recommend that the software vendor should design an effective and user-friendly sampling mechanism and provide good learning tutorials, courses and demos for the samplers. The software vendor can increase the network effect of software product sampling through increasing of sampler base and knowledge sharing with social media. The vendor should carefully plan the pricing policy so that the effective sampling and maximum total revenue can be achieved.
Keywords: product sampling; dynamic sampling; consumer behaviour; marketing strategies; software industry; dynamic models; equilibrium states; comparative analysis; static analysis; sampling effectiveness; network externality effect; software samplers; software buyers; attrition rates; forgetting rates; software prices; learning costs; managerial implications; software vendors; user-friendly mechanisms; sampling mechanisms; learning tutorials; learning courses; learning demonstrations; sampler base; knowledge sharing; pricing policies; maximum revenues; total revenues; social media; internet; world wide web; social networking; networks; technology marketing; strategic practices.
International Journal of Technology Marketing, 2012 Vol.7 No.3, pp.306 - 323
Received: 11 Feb 2012
Accepted: 26 Mar 2012
Published online: 29 Aug 2014 *