Answer to the research questions

The conceptual model, illustrated in figure 10, reveals unique and interesting findings, visually summarized by associating the exact independent factor with the exact outcome factor.

What was predicted to be a simple relationship between platform performance and TPA retention (figure 3) reveals significant detailed findings on which performance sub-factor has an effect on which outcome. Furthermore, the platform competition, also predicted in the primary

48 concept, shows significant effect on the relationship between innovation or growth and a TPA retention.

To answer the research question ‘What is the effect of platform performance on the TPA choice to extend, exit or mix several platforms?’, the earlier introduced propositions will be covered individually.

Proposition 1: How would platform performance motivate a TPA to extend participation in a platform?

It is concluded that the three main factors that have direct influence on the TPA extend mechanism are: Innovation, Growth and Governance, as illustrated in figure 7. A good performing platform in one of these factors will encourage a TPA to keep participating.

Proposition 2: How would platform performance be a reason for a TPA to leave a platform?

As demonstrated in section 4.2.2, both governance and technology have a direct effect on the TPA exit mechanism (figure 8). Bad performance in one of these factors will motivate a TPA to consider an exit choice.

Proposition 3: How would platform performance be a reason for a TPA to mix several platforms?

In section 4.2.3, the data analysis concluded that only governance (platform lock-in) could have a direct effect on the TPA hybrid mechanism (figure 9). A TPA that fears the platform lock-in practice will mix platforms or extract separate app components to a second platform. For example, by building an app in Salesforce and using Google for storage.

Proposition 4: Does a competitor platform have an effect on the relationship between platform performance and TPA retention?

49 Findings presented in section 4.3 lead to the conclusion that platform competition is an important moderator. This factor has a direct effect on the relationship between platform performance and TPA retention. When a competitor platform outperforms the primary platform in innovation or in financial growth, a TPA will consider in both cases leaving its platform.

5.2 Theoretical contribution

The theoretical discussion will be summarized in four contributions.

First, this research has been very precise about the platform performance indicators (table 3) examined by other authors: innovation (a.o. Parker et al., 2018), governance (Tiwana, 2014) and growth (Cusumano et al., 2018) and added to that the relationship between these indicators and the TPA retention.

Second, this study agrees with the findings of Kim et al. (2016) that TPA retention is related to two factors: 1) dedication, in this study treated as engagement, and 2) constraints, in this study treated as platform lock-in practice. This paper adds to Kim et al. (2016) finding the exit and hybrid mechanism and concludes that a TPA has other choices than to continue participating. This study disagrees with their findings that the lock-in practice (constraint) leads to the ‘extend’ mechanism only. In that context this paper demonstrated that the lock-in practice motivates a TPA to choose for multiple platforms, in order to be platform independent.

Third, this study agrees with the findings of Zhou et al. (2018) that causality is influenced by the competitive platform entry and adds to their finding by 1) defining the platform performance indicators in question: innovation and growth and 2) showing the direction of the change (P4) from an extend to an exit mechanism. In addition Zhou et al. (2018) examined the response to competitive enty by examining both sides of the platform business; the TPA side and the end-user side (multi-sidedness response). This study confirms the response of a TPA to

50 a platform competitive entry, but lacks evidence on the response of the end-users to this competition. This could be the beginning of a new area for future research.

Fourth, this study agrees with Cusumano (2019) findings that platform owners could depend on their own products on the platform (e.g. Salesforce selling its own apps on the AppExchange). This study adds to the above findings that having their own apps next a TPA app leads to competition between the platform owner and its TPA. This competition is experienced as bad governance, thus bad performance, and is the primary reason for a TPA to leave a platform.

5.3 Practical contribution

This study contributes to practitioners and especially TPAs within the hybrid software platform business. This contribution will be summarized in four recommendations.

First, this research recommends acknowledging the existence of platform competitors and their competitive power such as competitive innovation (e.g. Machine learning, AI Big data) and competitive financial performance (e.g. market share and mass access). This knowledge helps TPAs to make sure a switch could be quickly implemented when needed. This could be done by strategically determining the right app structure and building flexible and agile layers.

The rapid technical change could cause a disadvantage if not switching fully or partially (e.g.

build an app in Salesforce and use Google cloud platform form storage) on time.

Second, TPA decision makers are advised to consider a platform exit or hybrid strategy at all times. This could be done through a thorough and continuous benchmarking of the primary platform with existing platform competitors and especially with new entrants. These benchmarking methods are commonly used in the software platform industry and are supported by several market analysts, such as Gartner and Forrester. From a cost effectiveness point of view, this could be done by integrating analysis practices internally and by utilizing own

51 resources, focusing on company needs and interests. This method has shown success as several analyses are based on facts, experience of TPAs, and end-users with the platforms.

Third, this study emphasises on the platform lock-in hurdles. Lock-in could have a huge impact on the decision making (depending on the amount of objects in an app). If a TPA is locked-in it is very hard to switch, even if wished. For some app developers rewriting the app could take between three to eight years to make the switch. Lock-in is very expensive and comes with several constraints as well. Being technologically fully dependent on one platform comes with big risks and limitations. This limitation could result in excluding an important amount of potential end-users that prefer to use a competitor platform.

Fourth, dual strategy is an effective method according to this research. Different TPAs have chosen a dual strategy, especially global TPAs. The goal is to attract as many global end-users as possible by using multiple platforms at the same time. Global end-end-users tend to reduce dependency risks that come with enslavement to one platform only.

The flip over effect of having a dual strategy is the relatively high costs involved in keeping up with resource knowledge and certification of different technologies at the same time.

Some even suggest that focusing on only one platform can increase loyalty and full engagement with the platform owner. Loyal TPAs will try at all times to help its primary platform to regain shine, even if lost. This, from a cost effectiveness point of view, is an attractive strategy too.

5.4 Limitations and future research

Like any research, this study suffers from several limitations, which could be seen as the beginning of new research areas and will be summarized in five suggestions

First, the collected data is generated within the software platform industry, focusing on software app developers only, which could limit the generalization to other platforms. Caution

52 should be taken when considering duplicating these findings to other platform industries such as social networks, e-commerce or payment.

Second, despite the depth achieved during the interview process, the amount of interviews in comparison to the number of TPAs worldwide could also be seen as a limitation.

This could be another area to nurture the TPA retention in a quantitative manner. For example by using secondary data and statically testing causality or by using a longitudinal study to make sense of innovation or growth variation during time and its effect on retention.

Third, although the effect of a competitor platform on the TPA choice has been investigated, other factors, such as end-user role, may influence the equation by having an effect on the relationship between platform performance and the TPA choice. One may suggest this area as a new direction for future research.

Fourth, this study has experienced more participants' willingness from the Salesforce community than for example the Microsoft community. This could be judged as a limitation because the collected data could lean more toward Salesforce than for example Microsoft (a direct competitor of Salesforce). Maybe because Microsoft is still young in the investigated platform area and is still struggling to establish a strong community. This is an area for new research.

Fifth, this study has examined platform performance as the main factor, without considering the aspects like ‘TPA exclusivity’ as a motivator to extend the use of a platform.

TPA exclusivity has been mentioned several times during the interview process, but did not have sufficient attention. Filling a platform gap could have a big impact on the relationship between TPA and platform owner and from that perspective, a platform owner can grant exclusivity to TPA, making retention very strong.