Kurt Matzler

Strategy development has traditionally been exclusive and secretive. Social software offers new opportunities to harness the collective intelligence of the crowd within organizations and allows more open, participatory modes of strategizing. This paper describes this new phenomenon of open strategy though crowdsourcing and discusses its implications for research and practice. It draws on first examples of crowdsourcing strategy and is further based on observations and theoretical reflections. To understand the phenomenon with its requirements and consequences, a number of questions and challenges are identified which remain to be investigated. These include how the process of opening up needs to be designed, how individuals can be motivated to engage, for which topics and under which conditions crowdsourcing strategy is a suitable approach, how strategies emerge in such initiatives, the appropriate role of management, and how corporate culture affects and is affected by crowdsourcing strategy. Open strategy through crowdsourcing is a newly emerging empirical phenomenon, which seems to fundamentally change the strategist’s work. More open and inclusive ways of strategizing not only offer new opportunities, but also create some challenges for organizations. This paper deepens the insights in this new phenomenon and identifies seven topics critical for research and management practice.

Keywords: strategy, crowdsourcing, collective intelligence.
JEL Classification: M19

Customer satisfaction is one of the most important success drivers. Managers need to understand how satisfaction is formed, which factors to focus on, and how to increase the performance. The Kano model offers useful guidance for managers to increase customer satisfaction. It assumes that there are three different factors, which influence overall satisfaction, and that the weight of these factors changes over time. This study adds to limited empirical evidence on temporal changes of nonlinear relationships between attribute performance and customer satisfaction. The data comprise two waves of a large-scale sample of more than 40,000 skiers in 55 Alpine ski resorts in 2012 and 2016. Applying nonlinear structural equation modeling, Ski Core and Value-for-Money were identified as basic factors (dissatisfiers) and Ski Peripherals as a performance factor. Change in skiers’ satisfaction levels operates at a slow pace and, besides general industry trends, time-related segmentation criteria like loyalty and skier skills play a salient role. Especially, the attribute Value-for-Money is prone to temporal changes.

Acknowledgments
We thank Michael Partel from Mountain-Management C. Est for granting access to the data.