A structured scenario approach to multi-screen ecosystem forecasting in Korean communications market

Abstract

Ecosystem forecasting is a challenge for any forecaster since it has a large number of variables, which vary dynamically, tightly coupled with environmental factors under a complex ecosystem architecture. The ecosystem behaves like a complex system as a whole where one variable may serve as a hierarchical pillar to other variables, while others interact with each other in non-linear forms of substitution, complementarity, synergy and externalities. This paper is targeted to develop a profound structured approach to the ecosystem forecasting which combines scenario planning with technological forecasting. Three key planning principles are derived and incorporated into the structured ecosystem forecasting methodology. To demonstrate its effectiveness, the Korean multi-screen service market is analyzed and prospected toward the year 2016. Policy and strategic implications from the structured ecosystem forecasting are also discussed to validate the practicality of the suggested methodology.

Explicating user behavior toward multi-screen adoption and diffusion

“…Finally, the results illustrate the need for multilevel analysis with multiple methods and multiple data sets. As with the emphasis by Chang (2015) on the ecosystem, the variables identified in this study imply the need for an ecological view when considering the diffusion of multi-screen services. In order to fully capture the drastic innovation that has occurred at diverse levels, multilevel analysis is necessary to integrate different data for heterogeneous phenomena.…”

“…N-screen evolved from the broader concept of multi-screen services and it enables users to utilize multiple devices; thus, it should comprise integrated platforms for multi-devices. The emergence of multi-screen services represents a media ecology where content can be approached and consumed at any time and in any location regardless of the device or platform (Chang, 2015; Lai et al , 2014).…”

A scenario-based roadmapping method for strategic planning and forecasting: A case study in a testing, inspection and certification company

“…For flexible strategic planning, the scenario plays an important role to provide different descriptive stories of the business environment and scenario planning can be applied as an effective approach to deal with a complex and rapidly changing business environment (Chermack, 2005;Geum et al, 2014). The scenario planning method is widely adopted by government, academia, researchers, and many different sectors, particularly in the public domain (Bañuls et al, 2013;Dong et al, 2013;Raford, 2015;Schoemaker et al, 2013;Weigand et al, 2014), energy (Fortes et al, 2015), healthcare (MacKay and Tambeau, 2013;Phadnis et al, 2014), telecommunications (Chang, 2015), and urban planning (Viguié et al, 2014;von Wirth et al, 2014), and is spreading to many other areas (Dorrestijn et al, 2014;O'Brien and Meadows, 2013;Palo and Tähtinen, 2011;Tapinos, 2013;von der Gracht and Darkow, 2010;Yuan et al, 2012). Moreover, some researchers have provided insight into generating future scenarios (Dong et al, 2013;Fortes et al, 2015;Phadnis et al, 2014;Raford, 2015;Viguié et al, 2014;von der Gracht and Darkow, 2010;von Wirth et al, 2014), sensing and interacting with the environment (e.g.…”

“…Moreover, some researchers have provided insight into generating future scenarios (Dong et al, 2013;Fortes et al, 2015;Phadnis et al, 2014;Raford, 2015;Viguié et al, 2014;von der Gracht and Darkow, 2010;von Wirth et al, 2014), sensing and interacting with the environment (e.g. emerging trends) Palo and Tähtinen, 2011;Raford, 2015;Ramírez et al, 2013;Schoemaker et al, 2013), conducting forecasting and foresight (Bañuls et al, 2013;Chang, 2015;Dorrestijn et al, 2014;Weigand et al, 2014;Yuan et al, 2012) as well as facilitating decision support and making Fortes et al, 2015;Parker et al, 2015;Ram and Montibeller, 2013;Wright et al, 2013).…”

Improving Forecasts for Better Decision-Making

“…More recently, Becker [7] argues that managers must apply some discriminatory procedure when selecting a preferred forecasting model. Chang [10] suggests that the forecasting process is complex, subject to many influences. While findings vary, the message is a call for a deeper understanding of forecasting.…”