Keywords

1 Introduction

Digital technologies have much potential for businesses but also many pitfalls. Business managers have never had as much data as they do now. Data allows, at least in theory, more informed decision-making in businesses. This should lead to competitive advantage and improved management [1]. However, adoption of digital technologies is always challenging. According to research conducted by Deloitte, around 70% of digital transformation projects fail [2].

The digital era challenges the tourism industry and destinations. Tourism is one of the biggest industries in the world, corresponding to around 10% of global GDP [20]. This means that the competition in the field is fierce, and novel approaches are needed for competitive advantage. Digital technologies might provide this edge, but only if correctly utilised.

Tourism organizations such as Destination Management Organizations (DMOs) have more and more data at their disposal. Big data analytics allow destinations to understand the marketplace and business environment better than before, at least in theory. These data sources should improve decision-making processes in organizations. We focus on one of the most important decision-making processes, namely how DMOs formulate their strategies and identify competitive advantage.

2 Research Problem

There is a lack of research regarding tourism data utilisation when developing strategies. Strategies can be considered the cornerstone of competitive advantage, e.g. [3, 4]. Destinations and tourism businesses need to have a clearly defined strategy on what kind of value they provide and for whom and understand how this strategy leads to competitive advantage. This strategy planning process requires many decisions to be made. Thus, data is needed to support managers and organisations in making the right decisions.

Numerous researchers have studied how tourism data can improve tourism destinations’ competitive advantage [5,6,7,8,9]. These studies typically examine the customer experience of a specific hotel or restaurant using big data from online sources such as social media. However, the crucial strategy development process has not been examined previously in tourism and destination management research. Tourism destinations should develop a knowledge-based approach using various data sources to support decision-making.

This research is based on strategic management and knowledge management theories. Strategy can be described as an insight into long-term goals with choices, actions and allocated resources to develop a competitive advantage in an organisation [10, 11]. Pechlaner and Sauerwein [12] defined the role of strategic management as interpreting essential knowledge provided by the environment into a form that supports future-oriented organisation structuring. Strategic management's primary goal is to ensure the strategy is accomplished effectively [13] by planning, organising, leading and coordinating the whole strategy process [10]. This process includes managing strategy planning, implementation, and analysing performance. [13]; [11] This research considers these three stages of strategy to understand strategic management as a process and how novel data sources are influencing it.

Knowledge management is about how an organisation transforms data into information and information into knowledge and how that knowledge is utilised in managing the organisation [14]. Big Data is crucial in knowledge management, mainly when producing new knowledge [9]. It has been defined in multiple ways, emphasising the difference from traditional data. Big data can be described as a considerable amount of data gathered from various sources [15]. From a business point of view, big data is a significant factor in improving operations and supporting decision-making processes [14]; [9]. However, the issue of using big data is not the availability of data anymore but how that data is used [16].

3 Methodology

The research method of this study is qualitative. Qualitative research enables one to find interpretations based on collected data by exploring social phenomena. It provides an in-depth understanding of the phenomenon and supports or argues for it and supports or argues with previous theories. [17]. This research and its structure are supported by earlier studies related to the phenomenon of this study.

This research was conducted in the context of Finnish DMOs. Qualitative research was conducted with nine semi-structured interviews in May 2023. The researchers contacted through telephone Finnish DMOs identified through Google search and the VisitFinland website. We used purposive sampling to interview different kinds of DMOs from all of the four major tourism regions (Lapland, Capital Region, Coast Archipelago, Lakeland). Interviews were conducted in Finnish online using Microsoft Teams. All interviews were recorded and transcribed.

The interview was divided into themes such as knowledge management and strategic management based on the literature. The core questions were structured beforehand to ensure that the interviews followed the same line and produced proper data related to the research topic. Even though there might come new perspectives or considerable issue issues to add to the interview, it remained the same and, thus, guaranteed the trustworthiness of the study as well [18]. The core of the interview is built based on previous studies and the research questions.

The data is analyzed using thematic analysis, widely used in semi-structured interviews. As the interview method of this study, thematical analysis can also be described as a flexible method as it provides also be described as flexible as providing rich and accurate data to analyze. Braun & Clarke [19] presented how to process thematic analysis within six stages, which are utilized in this research.

4 The Results

The findings show that the current position of knowledge management in DMOs in Finland is yet in the development stage. A lot of data is already available, but there is a lack of understanding of how to turn that data into knowledge that would lead to a competitive advantage. Utilizing tourism data effectively in tourism strategy requires enhanced knowledge management skills, resources and successful stakeholder collaboration. It is crucial to identify the relevant data and the purpose for its use. Additionally, further developing tourism data platforms would support DMOs and tourism companies as well as tourism strategies to collect data, analyze it and share it in the form of knowledge and interpretations.

The role of knowledge management could be divided into three themes: current strategy, updating strategies, and engaging stakeholders. DMOs were the hub for knowledge management in the destination, often responsible for using available data, procuring new data, and sharing the data to engage stakeholders.

DMOs acknowledge that big data from various sources can provide possibilities for competitive advantage and enable better strategies, but the current data use methods have not achieved that. This would suggest that there is a danger that big data-based strategy processes do not significantly improve destination strategies for competitive advantage.

5 Conclusions

This study elaborates on how destinations perceive the influence of big data and other novel data sources on destination strategies. Destinations are building capabilities in the field but are seeing limited results so far. There is little understanding of how big data can be turned into a competitive advantage through strategic decision-making processes. This study suggests that strategic management knowledge and expertise can enhance the possibilities to utilize data in DMOs. With novel data sources and possibilities to utilize data, destinations need to continuously evaluate current strategies and modify them if needed. Data enables better decision-making when comparing strategic possibilities. Thus, knowledge management and strategic management practices need to be implemented together [5]. Even though destinations are utilizing various novel data sources for benchmarking and customer understanding, they struggle with converting that data into knowledge that benefits the organization because they lack expertise in strategic management. More data does not automatically lead to better strategies, but efficient strategic management requires the implementation of knowledge management practices.