Factors for Dominance during a Standards Battle

Abstract

When competing standards are introduced into the market, the firms that introduce the standards often put considerable effort into becoming dominant. Such a face-off is called a standards battle. This level of competition can slow market adoption and increases costs for all those involved. It is therefore important to better understand standards battles and analyze possibilities to better approach them in the future. Scholars have worked to create frameworks of factors for dominance and some have even combined these with a view of the dominance process to reach a progress-based overview of battles in general. Such an overview can help standard supporters, those firms that introduce and promote a standard, to identify and leverage factors in their battles at the correct time.

This research is a continuation of this approach, working towards a general template for future battles and attempting to validate previous results. A literature review was conducted to select a framework of factors for dominance, to find a selection of phases to divide the progression of a standards battle, and to review previous research’s statements regarding the importance of factors during specific phases. The framework constructed by v.d. Kaa (Van de Kaa et al., 2011) was selected as the framework of factors and the division of phases as described by Suarez (Suarez, 2004) was chosen. An overview of the existing literature on the combination of both factors and phases was then constructed. This provided a reference against which the results of this research were later compared. A selection of factors was then made for each phase using previous literature and an expert interview. Ten experts from the consumer electronics, information technology and telecommunications industries were selected using convenience sampling. The experts were asked to weigh the selected factors against each other in each phase using the Best-Worst Method. This is a Multi Criteria Decision Making method that provides a set of weights from two different comparisons made for each phase. From the responses, the weights of the separate factors were calculated. From this calculation a consistency indicator was also derived. All results met the required consistency. The sets of weights were combined to reach average weights for each phase. These results were analyzed and interpreted to provide further understanding. The highest rated factors are: technological superiority for the first and second phase, timing of entry for the third phase, complementary goods for the fourth phase and installed base for the fifth phase. A comparison with existing literature was performed. This showed an indication for dynamics observed by den Uijl (Den Uijl, 2015) and a general match with statements made by Suarez (Suarez, 2004).

The novel approach of this research to consider factors for dominance in combination with the phases of a battle using expert interviews to reach a view on battles in general has not been used before. It therefore also has interesting implications. The results of this research provide a partial validation of claims from other scholars regarding the importance of factors for dominance during phases of a standards battle. They also provide additional information on the progression of the contribution of factors and are the first step towards a progress-based template for battles in general. It was shown that there are similarities and differences between different industries in which standards battles take place. The findings of this thesis can be used by industry actors to better adjust their standard and standard supporter characteristics to what is required at each stage of a battle. It will also help them identify factors that competition may be lacking, opening up new possibilities for targeted competition. Future research is this field is required. A fully quantitative approach using a complete set of factors can give a more definitive answer to the posed research questions. This research provides the starting point towards a cross-industry applicable selection of highly contributive and lowly contributive factors depending on the stage of the technology. More research could be done on the differences and similarities between industries using a historical approach.