Limitations and Recommendations for Further Research

Several measures were taken to ensure reliability, validity, and generalizability of this study. Those measures were discussed in detail in chapter 4 alongside the methods. This chapter discusses the limitations of this study and the recommen-dations for further research are given.

To ensure reliability, neutral time and place for studying the subjects was chosen, anonymity was ensured for the interviewees, and the interview schedule was structured. In this research, the means for ensuring validity used were thick and rich data, debriefing and clarifying research bias.

The thick and rich data are ensured through the sample size and appro-priateness of the data. The sample size in this research has to represent the 29 currently operating hotel companies in Finland. It does so appropriately by in-cluding 7 companies, equalling about 24% of the hotel company population. Each of these seven companies was represented by between one and five decision makers, e.g. CEOs, general managers, and division directors, equalling a total of 15 industry experts. This enabled reproducibility among respondents of the same company, whose different position and thus different point of view could lead to complementing answers.

The regional responsibility of the 15 respondents covered all areas of Fin-land with strongly developed tourism, making the research generalizable across Finland. One limitation of this, however, is the sample representing only such hotel companies operating five or more hotels. Accordingly, some observations might differ in the context of smaller operators. For example; market expansion might not carry the same weight of importance for small operators. Yet, other

observations likely still hold true, like improving products/services; and devel-oping the business in general. In the context of generalization, this thesis found it necessary to distinguish between the hotel industry and other industries, as competitive dynamics and terms relating to competitive actions are found to dif-fer. Thus, findings stemming from research about other industries, like manufac-turing or the retail industry, have to be carefully examined for their transferabil-ity to the hotel industry and vice versa.

Debriefing was used to prevent the author’s bias, meaning a colleague, in this case the thesis supervisor, examined the transcripts, the methodology and the final thesis, and gave feedback. The author had worked in the field for several years and had some knowledge of how the industry operates. Taking this into consideration, it is apparent that the author had an impression of the competitive landscape. This could be used to ask questions that the related literature does not account for. During the interviews, the vocabulary used by the respondents was also used by the interviewer to get as close to the respondents as possible. This created the challenge of the interviewer becoming too “native” in the data collec-tion. To counteract this, an outsider was asked to read this thesis and pinpoint any naïve or biased interpretations. Nevertheless, this is a limitation that must be taken into account.

Hotel Company 1 operates two independent hotel brands and was accord-ingly allocated two competitive action profiles. Comparing these two profiles re-vealed significant differences, suggesting that the strategies used by hotel com-panies depend on the hotel brand, not on the operating company. However, this thesis only investigated one company’s multiple brands, therefore the generali-zability of this observation remains uncertain and could provide the basis for fur-ther studies.

There is a discrepancy between the barriers of entry literature and the qualitative data of this thesis. Conlin and Kadiyali (2006) wrote that companies with considerable market share can benefit of increasing capacity to the level of idle capacity as it can deter new ventures of entering the market. However, hotel experts interviewed in this thesis said that new entrants are not to be blocked.

Collaboration, clustering, and partnerships also have high relevance in the hotel industry. This discrepancy is explained through a lack of healthy competition in the history of Finland’s hotel industry and the desire to prevent its reoccurrence on the one hand, and shared benefits of an attractive destination among all local competitors on the other hand.

More research should be done on how the online travel agencies (OTAs), sharing platforms (e.g. Airbnb), and cruise ships are regulated in Finland. The interviewees explained their frustration with competition regulation perceived as unfair. It would be valuable to understand how the Competition Authority and Government justifies its decisions, regulations and legislation on these oper-ators. Currently, industry experts (hotel industry decision makers) feel that the situation is unfair and unjust, since companies offering similar products and ser-vices still operate under different regulations. This perception might be biased and caused by the interviewed industry experts conflict of interest, thusly more research on hearing all sides/perspectives on this matter is needed.

It is notable that the Finnish hotel industry operates differently compared to the industries related to the previous literature. Researchers in the competitive dynamics field should keep in mind the distinctiveness of the Finnish hotel in-dustry. Hence, one implication is to check if this perception of the hotel industry’s competition can be reproduced in other countries that don’t have the same his-tory as in Finland.

We know now that the Coronavirus has put the continuum of hotel and tourism business at risk. Thus, research on how hotel companies prepare for and survive during a global pandemic should be conducted. Meaning, how the use of competitive actions is different and how competition is experienced during a global crisis, should be studied.