The take-off of an interactive innovation: Evidence from China Marina Yue Zhang ⁎, Jian Gao School of Economics and Management, Tsinghua University, Beijing, 100084, China article info abstract Article history: Received 15 April 2010 Received in revised form 21 January 2011 Accepted 9 February 2011 Available online 21 March 2011 An interactive innovation can be defined as an end-user application which is subject to network effects at both the demand and supply sides. As a result of network effects, the diffusion of such an innovation is predicted to follow a take-off curve coinciding with the advent of a critical mass of adopters. The current literature on innovation diffusion, mainly focusing on the demand-side dynamics, such as information cascades and herding behaviors among potential adopters, is not sufficient to explain the take-off (or the failure) of interactive innovations. In this paper, we present and examine a case study of the take-off of an interactive innovation, namely the caller-ring-back-tone (CRBT) and mobile music – mobile value-added services (MVAS) – in China. We find that supply-side dynamics, such as choices of platform strategies, helped drive the take-off of this innovation within China's institutional boundaries. The paper makes a contribution in two ways: first, it presents an ‘inside-out’ view of a unique case of take- off phenomenon; and, second it provides an integrated view combining factors from both the demand and supply sides to explain the take-off phenomenon, which is rare in empirical studies. © 2011 Elsevier Inc. All rights reserved. Keywords: Interactive innovation Diffusion Take-off Platforms Institutions Mobile value-added services 1. Introduction At the end of the 20th century, the forecast for the growth of third-generation (3G) mobile communications networks led to massive investment associated with the construction of the new infrastructure [1]. 1 This investment can be described as the largest ‘technology push’ ever witnessed. The 3G broadband networks enable consumers to enjoy mobile value-added services (MVAS) – high-speed data communications such as multimedia messages and audio/video – in a wireless environment. MVAS became the hope for mobile operators to generate new revenue streams to fight against declining ARPU (average revenue per user) 2 and to adjust their sunk investment in 3G infrastructure. While mobile operators worldwide worked hard to search for ‘killer applications’ with the hope that it would trigger the take-off of 3G, industry analysts and academics tried to forecast the diffusion curve of any such ‘killer applications’, if any. However, the effort to forecast turned out to be very challenging. Mobile value-added services (MVAS) are user applications, which emerged from the convergence between mobile networks and the Internet. They are interactive or network-based innovations which are subject to network effects at both the demand and supply sides. From the demand side, MVAS rely on interactions with other users in the network to create network effects. Therefore, from a user's viewpoint, decisions to adopt such an application reflect not just a personal choice, but also the result of interactions with other users in the network, which is moderated by the way information is communicated among the users. From the supply side, an MVAS application is composed of multiple components and functionalities governed by standards, interfaces/ Technological Forecasting & Social Change 78 (2011) 1115–1129 ⁎ Corresponding author. Tel.: +86 18601020848; fax: +86 10 52089848, +86 10 52321268. E-mail addresses: zhangyue@sem.tsinghua.edu.cn (M.Y. Zhang), gaoj@sem.tsinghua.edu.cn (J. Gao). 1 By 2001, telecom operators worldwide had committed an estimated US$1000 billion (including licensing fees, infrastructure and marketing expenses) in 3G systems, according to a report published by Frost & Sullivan. 2 ARPU, average revenue per user, is a commonly accepted index used in the telecommunications industry to measure the value of a certain service or application. It is also used in rating and differentiating users. 0040-1625/$ – see front matter © 2011 Elsevier Inc. All rights reserved. doi:10.1016/j.techfore.2011.02.004 Contents lists available at ScienceDirect Technological Forecasting & Social Change