Facilitating innovation through lab projects: cases from experience-based tourism

ABSTRACT

Collaborative innovation approaches, such as innovation labs, have the potential to enhance innovation in experience-based sectors. However, they are rare and understudied. This study investigates the facilitation of innovation lab projects in experience-based sectors. The theory of transformational leadership and team learning is explored in the context of four idea-generating lab projects in Norway. This multi-case study involves two cases that focused on meal experiences and two on cultural experiences. The findings show that short-term team learning can be facilitated using the four transformational leadership dimensions. This study contributes to leadership theory by identifying 10 new sub-dimensions within three of the dimensions. These include three new sub-dimensions within the inspirational motivation dimension, two within the intellectual stimulation dimension, and five within the individualized consideration dimension. The findings have practical implications for the facilitation of learning and ideation in tourism innovation labs.

KEYWORDS:

• Facilitating innovation labs
• transformational leadership
• learning
• experience-based tourism
• multi-case method

Introduction

Open and collaborative innovation approaches are important for tourism firms to gain knowledge and learning for successful innovation (Marasco et al., 2018; Phi & Dredge, 2019), especially after the global Covid-19 pandemic. Collaborative innovation is the creation of innovations by sharing ideas, knowledge, expertise, and opportunities across firm boundaries (Ketchen et al., 2007). Examples of such approaches, or spaces, are innovation labs, which can serve as arenas to foster open innovation, co-creation, inter-organizational knowledge sharing and learning, and innovation formality in tourism firms (Bloom & Faulkner, 2015; Capdevila, 2013; Ketchen et al., 2007; Zach, 2016). However, despite their potential, the use of such labs as a learning device/arena for innovation is rarely studied (Capdevila, 2013; Tiesinga & Berkhout, 2014), particularly in experience-based tourism (Guimont & Lapointe, 2016; Jernsand, 2019; Zach, 2016). Consequently, there is limited knowledge about the facilitation of such labs in general (Lund & Tingström, 2011; Magadley & Birdi, 2009) and in the tourism context in particular (Thees et al., 2020).

Therefore, this study aims to investigate the facilitation of labs in experience-based tourism by answering the research question: Based on the participants’ perspectives, how do facilitators enable learning for innovation in experience-based tourism lab projects? To answer this question, this study examines four cases by employing the theory of transformational leadership and learning. These four cases consist of four innovation lab projects related to experience-based tourism in Norway. These labs involved owners and employees of tourism firms that focus on meal and cultural experiences (e.g. restaurants, hotels, and cultural tourism sites). Below, the terms used in this study, such as ‘experience-based tourism’, ‘facilitation’, ‘lab projects’, and ‘transformational leadership’, are defined.

The term ‘experience-based tourism’ is derived from the notion of ‘experience economy’ (Pine & Gilmore, 1998). Stamboulis and Skayannis (2003) view experience-based tourism as a novel type of tourism that uses ‘experience’ as a dematerialized commodity to generate income. Alsos et al. (2014, p. 16) define experience products as ‘mentally and/or bodily memorable experiences’. Such tourism firms innovate by creating new values, and unique, meaningful, and memorable experiences (Eide & Mossberg, 2013; Lapointe et al., 2015; Sternberg, 1997).

‘Facilitation’ in this study means ‘any meeting technique, procedure, or practice that makes it easier for groups to interact and/or accomplish their goals’ (Frey, 1994, as cited in Atasoy et al., 2013, p. 3). And ‘facilitator’ refers to a person responsible for the facilitation, sometimes also known as the leader (Atasoy et al., 2013; Kolb & Rothwell, 2002). This study focuses on exploring the actions or practices of the facilitators who enable learning for innovation in the labs.

Innovation labs (or labs) in this study are collaborative innovation spaces that can be defined as ‘physical or virtual spaces that enable and support the innovation (technological or otherwise) of those who participate in the space’ (Bloom & Faulkner, 2015, p. 8). However, as the cases in this study were temporary labs, they are referred to as ‘lab projects’.

‘Transformational leadership’ is a type of leadership style where the leaders ‘transform’ their followers by motivating and empowering them to achieve beyond expectations, instead of giving a reward for their compliance (i.e. transactional leadership) (Eagly et al., 2003; Raes et al., 2013; Seltzer & Bass, 1990). Such leaders gain trust and confidence from their followers by setting themselves up as role models (Eagly et al., 2003).

The following section presents the literature review of this study. Afterwards, the research design is presented, followed by the case descriptions. Next, the findings – which are organized according to the dimensions of the transformational leadership style – reveal some crucial aspects of facilitating learning for innovation in experience-based tourism. Then, the findings are discussed, followed by the conclusions. The paper ends with the limitations of the study and future research suggestions.

Literature review

This section presents the importance and relationship of different concepts and theories relevant to the aim of this study. It starts with the previous knowledge of the drivers of learning related to innovation, which leads to the importance of transformational leadership, and how the two are related in the tourism context. And lastly, previous studies on the facilitation of labs related to innovation are explored.

Learning and innovation

Tourism firms’ innovative capabilities depend on their ability to exploit knowledge from learning and external sources (Booyens & Rogerson, 2017). Innovation can be defined as ‘something new or significantly improved that is implemented (for example, commercialized or put into practice)’ (Eide & Mossberg, 2013, p. 250). Some studies show that learning in and across organizations has a positive relationship with innovation, as learning accelerates and facilitates innovation (García-Morales et al., 2012; Gil et al., 2018). Especially in experience-based tourism, learning is very central in staging the tourism experiences so that competitive advantage is achieved (Stamboulis & Skayannis, 2003). Therefore, it is crucial to understand what drives learning in organizations that foster innovation.

Team learning is the key driver for individual and organizational learning related to innovation in and across organizations (Decuyper et al., 2010). A team can be defined as a group of people with a shared goal, interdependent work, and joint responsibility for results, while team learning is the process through which team members acquire and share the unique knowledge, as well as examining what helps or hinders the improvement of the team (Druskat & Kayes, 2000; McDermott, 1999). On the other hand, leadership is one of the most important drivers of team learning (Nellen et al., 2020). Similarly, previous studies in tourism also highlight the importance of leadership in knowledge sharing, learning, and innovation (see e.g. Yang, 2007; Zach, 2016). Nevertheless, these studies also stress the need for further investigation of this topic related to collaborative innovation.

Transformational leadership

Although there are other leadership styles, the styles that are positive or constructive, such as transformational leadership, are beneficial for creativity and innovation (Hughes et al., 2018). This is because numerous studies show that the transformational leadership style has positive results on team learning and innovative behaviour in teams (e.g. García-Morales et al., 2012; Gil et al., 2018; Gundersen et al., 2012; Klaic et al., 2020; Raes et al., 2013), and even on the effectiveness of virtual teams (Purvanova & Bono, 2009). Moreover, Khan et al. (2020) suggest that the transformational leadership style enhances tourism firms’ innovativeness, while Hinkin and Tracey (1994) point out that it is appropriate for a dynamic and growing industry. Therefore, this study focuses on the transformational leadership style as it is relevant for the context of this study, i.e. experience-based tourism.

There are four dimensions of transformational leadership (Raes et al., 2013, p. 290). The first dimension, ‘idealized influence’, is when a leader demonstrates qualities that stimulate respect and pride from association with him or her. Secondly, ‘inspirational motivation’ means that the leader articulates or facilitates a vision that is appealing and inspiring to the team members. Thirdly, ‘intellectual stimulation’, means that the leader examines new perspectives for solving problems and completing tasks. And lastly, ‘individualized consideration’ is when the leader focuses on the development and mentoring of followers and attends to their individual needs.

Previous studies show that some dimensions might be more relevant than others in terms of innovation. For example, the inspirational motivation and intellectual stimulation dimensions are considered crucial for innovation (Elkins & Keller, 2003; Hughes et al., 2018). This is because the two dimensions encourage problem-solving and knowledge sharing among team members (Avolio et al., 1999; Srivastava et al., 2006). However, despite the growing interest in transformational leadership in the tourism literature (e.g. Jaiswal & Dhar, 2015; Khan et al., 2020; Liu & Huang, 2020; Mohamed, 2016), previous studies in tourism have not addressed the importance of each dimension related to innovation and creativity. Moreover, even though transformational leadership is needed to facilitate inter-organizational collaboration that can drive innovation in tourism firms (Hjalager, 2010; Zach, 2016), little is known about how the transformational leadership style works in collaborative innovation spaces, particularly in the experience-based tourism context.

Facilitation of labs

Labs can be viewed as short-term project teams that also serve as a learning device by providing a range of activities and events (Bloom & Faulkner, 2015; Druskat & Kayes, 2000; Tiesinga & Berkhout, 2014). These collaborative innovation spaces share some similar characteristics with short-term teams: they have a defined goal or focus shared by the members, the members are encouraged to share information and knowledge freely, and every member contributes and socially interacts with the others (Capdevila, 2013; McDermott, 1999; Quintane et al., 2013). Moreover, the participants of an innovation lab usually work in temporary teams (Fecher et al., 2020). Therefore, it is appropriate to look at what previous studies say about facilitating learning in short-term project teams and facilitating labs as a collaborative innovation approach.

According to Druskat and Kayes (2000), factors that facilitate learning in short-term project teams include interpersonal understanding and proactivity in problem-solving. Thus, activities that encourage team members to become familiar with each other, and engage in reflection and discussion, are beneficial. Also, Druskat and Kayes (2000) suggest that the learning goals should be explicitly encouraged. On the other hand, clearly mapped-out processes have a negative effect on team learning as they reduce mindfulness and spontaneous information sharing (Druskat & Kayes, 2000; Langer, 2000). However, it is still unknown whether these facilitating and hindering factors in short-term team learning are also applicable in the tourism context.

Next, regarding the facilitation of labs, Lund and Tingström (2011) suggest that a facilitator should have good communication skills, friendliness, the ability to mediate between individuals, as well as problem-solving ability. Additionally, Fecher et al. (2020) emphasize the importance of the space in addition to the facilitation itself and the labs’ resources. And in the tourism context, Jernsand (2019) stresses the importance of time management as one of the challenges in managing the labs. However, there is a need for further investigation on how to manage such collaborative innovation approaches in tourism (Phi & Dredge, 2019).

As the facilitators of the labs need to lead the activities in the labs, they can be assumed to be informal leaders (Fecher et al., 2020; Lund & Tingström, 2011). Therefore, leadership style is also important as one of the drivers of a successful lab (Holst et al., 2010; Lund & Tingström, 2011). Nevertheless, there are few studies regarding the facilitation of labs focusing on leadership styles and team learning. Most studies examine specific methods or tools for facilitation (e.g. Atasoy et al., 2013; Kasper et al., 2019), are rather practical, and are rarely well-anchored to more established theories.

Previous studies also point out other important factors that influence the facilitation of labs related to innovation. First, regarding the participants of the labs, it is crucial that a facilitator can manage their expectations and motivation from the very beginning, especially if the labs involve high levels of ambiguity (Fecher et al., 2020). Moreover, Hughes et al. (2018) reveal that the intrinsic motivation of the participants is one of the mediating variables between leadership and innovation, as intrinsic motivation is a key driver of innovation and creativity (Amabile, 1996). And lastly, Hakkarainen and Hyysalo (2016) argue that the role of facilitators in labs is not just about facilitating work, learning, and interaction, but also includes a broad range of intermediary activities such as brokering contacts before and after the lab project, and coordinating the resources. Therefore, the facilitators should possess ambidexterity, flexibility, and multi-tasking ability (Hakkarainen & Hyysalo, 2016; Nyström et al., 2014).

Research design

As this study has an exploratory nature, the qualitative case study approach is employed. Stake (1994) suggests that choosing multiple cases (collective case study) – and understanding them – will lead to a better understanding of the phenomenon in question.

Research setting and sampling

The research setting of this study is Norway, where labs are an unusual phenomenon in the tourism and/or experience sectors. Therefore, to acquire access to these rare arrangements, the university (with which the author is affiliated) cooperated with tourism-related organizations and networks across Norway. Therefore, the case selection strategy is purposive sampling, as the selected cases were related to innovation in experience-based tourism and located in Norway. The four cases include four innovation lab projects that have some different characteristics in comparison with each other. The differences include the background of the participants, the methods used in the activities, and the location/space. Therefore, each of them provides new, unique, and valuable contributions to the data (Tracy, 2010). The four cases were described after data analysis.

Data collection

The data gathering methods were observations (participant and non-participant) and individual semi-structured interviews. The interviews were conducted after the observations. The observation steps adopted the procedures from Creswell and Poth (2017). First, three researchers – including the author – decided who should participate in which case, who should be observed, and what type of observation should be conducted. Next, the researchers decided what should be observed (e.g. the activities, the duration of each activity, facilitators’ actions, and participants’ behaviour), and these were the themes of the observation guide. The observation guide followed the example from Creswell and Poth (2017), and thus included descriptive and reflective notes for explaining the observed themes.

In Cases 1 and 2, the researchers chose to be participant-as-observers to gain insider views. However, the researchers also understood that this type of observation might distract the note-taking process (Creswell & Poth, 2017). Thus, in Cases 3 and 4, the researchers acted as non-participant observers to record the observations in real time. Before the observations, the researchers introduced themselves to the participants. During the process, the observers took sequential notes following the lab activities. Finally, these notes were transferred to the observation guide and resulted in the observation reports. The observers also took photos of the lab processes, the participants’ actions, the rooms, and the tools used in the lab projects.

The interview protocol was developed by using previous knowledge of innovation and facilitation of labs, such as the literature on the motivations and expectations of the participants (Fecher et al., 2020). Thus, following the literature, the interview questions were divided into themes. The questions are, for example: ‘What motivates you to participate in the lab? What did you expect before participating?’ All interviewees were asked identical questions, but in each interview, additional questions emerged inductively following the responses of the interviewees (Guest et al., 2006).

A total of 16 in-depth interviews were conducted: 14 with the participants of the lab projects and two with the facilitators. This study focuses on the participants’ perspectives, as they were the ones experiencing the facilitation. Therefore, only two interviews were conducted with the facilitators as valuable supporting data. Moreover, in each case, three to five participants with different backgrounds were interviewed to ensure the data provided meaningful and significant claims (Tracy, 2010). The interviews were conducted either face to face at the interviewees’ workplaces, via phone calls, or digitally (via Zoom or Teams). Although mediated interviews (via phone or online) might lack non-verbal communication and ‘connection’, particularly with strangers (Easterby-Smith et al., 2021), the researchers had to resort to them for practical reasons, especially during Covid-19 restrictions. Moreover, the researchers were known to the interviewees as they had been introduced during the lab activities (before the interviews).

The interviews were conducted one-on-one by the three researchers, including the author. The average duration of each interview was around 60 minutes, with a few lasting up to one and a half hours. The list of interviewees and their roles in the lab projects are presented in Table 1. The interviewees are anonymized and identified with codes in this study. All interviews were recorded and transcribed.

Table 1. List of interviewees.

Cases	Interviewees’ codes	Interviewees’ roles
Case 1	C1A	Participant
	C1B	Participant
	C1C	Participant
	C1D	Participant
Case 2	C2A	Participant
	C2B	Participant
	C2C	Facilitator of Case 2
	C2D	Participant
	C2E	Participant
Case 3	C3A	Participant
	C3B	Participant
	C3C	Participant
	C3D	Facilitator of Cases 3 and 4
Case 4	C4A	Participant
	C4B	Participant
	C4C	Participant

Data analysis

The author analysed the observation reports – both descriptive and reflective notes – and interview transcriptions separately using qualitative content analysis. The coding process followed the steps suggested by Erlingsson and Brysiewicz (2017), starting with reading and re-reading the transcriptions and reports, dividing them into smaller parts (meaning units), and then condensing them to formulate codes. The codes were then grouped into categories and finally into themes.

The first-cycle coding loosely followed the structure of the interview, which was based on the broader concept of innovation and the facilitation of labs. Similarly, the first-cycle coding of the observation reports loosely followed the themes in the observation guide. The second-cycle coding was then matched and focused on the theory of transformational leadership dimensions (Easterby-Smith et al., 2021), following the abductive approach (Van Maanen et al., 2007).

First, the coding was categorized within the existing dimensions, but later the author discovered different meaning patterns that condensed into 10 new sub-dimensions within three of the main dimensions. Data saturation was reached when the author could not develop new themes from the data and thus no further coding was feasible (Fusch & Ness, 2015).

Finally, this study employed methodological triangulation to ensure validity (Denzin, 1989). The triangulation steps started with sorting out the data from the observations and interviews. Next, as mentioned previously, the interview transcripts and the observation reports were coded separately. Lastly, the themes from the interview transcripts were compared with the themes from the observation reports (Casey & Murphy, 2009). The comparison revealed similar findings. Thus, validity was established as the findings from the interviews and observations drew similar conclusions (Guion et al., 2011).

Case descriptions

This study examines four cases, and Table 2 presents the details. Each of these cases was part of a longer innovation labs’ process, with a series of temporary labs planned but delayed or cancelled due to the Covid-19 pandemic. Therefore, because of the short-term nature of the cases, it is appropriate to refer to them as ‘lab projects’.

Table 2. Case descriptions.

	Case 1	Case 2	Case 3	Case 4
Purpose of the lab project	To inspire participants to develop innovative meal experiences	To inspire participants to develop innovative meal experiences	To further develop a tourism guiding app	To further develop a tourism guiding app
Location	A hotel	A hotel	An office building	Digital platform (Zoom)
Number of participants	20	18	5	6
Background of participants	Mainly chefs; researchers	Mainly employees of hotels; researcher	Employees of cultural tourism sites; researchers	Employees of cultural tourism sites; researchers
Number of facilitator(s)	3	1	2	2
Background of facilitator(s)	Chefs	Professional advisor	Innovation (app) owner and a researcher	Innovation (app) owner and a researcher
Organizer(s)	Tourism network organizations	Tourism network organizations	Firm (innovation owner) and university	Firm (innovation owner) and university
Duration	8 hours	8 hours	4 hours	4 hours
Methods/activities and tools provided by the facilitators	Slide presentations, cooking demonstrations, discussions, testing of the food	Slide presentations, creativity exercises involving drawing and music, discussions	A preparation task before the lab project, slide presentations, IGP method, using pens, papers and post-it notes	A preparation task before the lab project, slide presentations, IGP method, using digital meeting platform (Zoom), and digital collaboration board with digital post-it notes (Miro)
Output of the lab project	Inspirations and potentially learning for the participants, to share and work with their own organizations	Inspirations and potentially learning for the participants, to share and work with their own organizations	Innovative ideas for further developing the app	Innovative ideas for further developing the app

The first two cases (Cases 1 and 2) aimed to inspire the participants to develop innovative meal experiences for their firms. Thus, the purpose of the lab projects was directly related to the learning of the participants. Conversely, Cases 3 and 4 aimed to further develop a cultural tourism mobile application (app) through a collaborative innovation process. Thus, the purpose of these lab projects was not primarily related to the learning of the participants, but to the innovation (app) owner. However, despite the different purposes of the lab projects, interviews with participants from all four cases revealed that they had learned something from them. More details about this can be found in the findings section.

In Cases 3 and 4, before the lab projects began, the participants (employees of cultural tourism sites) were requested to gather feedback from the end-users of the app, who were the participants’ customers or visitors. The activities were almost the same for Cases 3 and 4, and included presentations from the facilitators, followed by individual presentations, and then group and plenary discussions (IGP method (see Gausdal, 2015)). However, Case 3 was done physically in an office building and Case 4 through a digital platform (Zoom). And the participants of Case 3 were different from Case 4 (i.e. from different cultural tourism sites).

There were no concrete outputs from Cases 1 and 2, as the purpose was to give innovative inspirations to the participants. In contrast, Cases 3 and 4 resulted in many innovative ideas for further developing the app and also ideas that could be used in the innovation process in the participants’ home organizations. The contrasting purposes and outputs of these four cases influenced the findings, which are presented in Findings across cases.

Findings

This section answers the research question – Based on the participants’ perspectives, how do facilitators enable learning for innovation in experience-based tourism lab projects? – by presenting an array of facilitators’ actions that enabled learning in the lab projects, which are then structured following the transformational leadership dimensions and other significant factors. The findings are based on the subjective perceptions of the participants and the facilitators while participating in or facilitating the four cases. This section consists of three main parts: the findings within the transformational leadership dimensions, the other influencing factors, and the findings across cases.

Findings within the transformational leadership dimensions

Besides the four dimensions found in the literature, the categorization of the findings resulted in the formation of sub-dimensions within three of the main dimensions. In total, the findings generated 10 sub-dimensions. Only the findings under the idealized influence dimension yielded no sub-dimensions. The summary of the findings within the four dimensions is presented in Table 3.

Table 3. Summary of the findings within the transformational leadership dimensions.

Idealized Influence	Inspirational Motivation	Intellectual Stimulation	Individualized Consideration
Facilitators are inspiring, professional, and respectable Facilitators have a positive attitude, and are professional and effective	Communication-related: Clear goals/purposes Clear future plans/agenda Benefits of the lab projects Clear instructions Useful and relevant information Importance of language Interpersonal-related: Motivate to get to know each other Motivate to interact Encourage equal opportunity Get different perspectives to meet Actively engage the participants, lead and steer the activities Involve the right participants Follow up after the lab projects Develop trust Self-related: Be aware of his/her own expected role	Interaction-related: Balanced facilitator’s involvement/ interventions Create a positive climate Instil confidence in participants Motivate more interactions Technique-related: Balance between theory and practice Knowledgeable about creativity techniques Give something relevant to learn	Psychological needs: Aware of participants’ expectations Communicate individually with each participant Aware of participants’ difficulties Language consideration Welcome each participant Physical needs: Physical space should be comfortable Out of workplace/ outdoors Should be able to see everyone/ face to face Not sitting too much Physical space should be related to the theme of the lab project Should change rooms to stimulate creativity Refreshments during activities Time-related: Suits the participants’ timeframe Time to think individually Activities should not be too long, especially for virtual lab project Method-related: Focus on group work Activities should be easy to relate to one’s own organization Technical need: Explain how to use the digital tools

Idealized influence

Apart from Case 4, in this dimension the findings show that the leaders who encourage learning and innovation in the labs are inspiring, professional, effective, and have a positive attitude. To illustrate, the informants of Case 1 in particular emphasized that they learned a lot from the facilitators and were inspired by them as role models. They described the facilitators as inspiring, professional, and respectable. For example, during the interview, an informant remarked:

I think they are inspiring because they know so much, they are very confident in their own role of being a chef, and they are also sharing. So it’s [sic] good people for this kind of course. – C1B

However, none of the informants from Case 4 – which was the virtual lab project – mentioned leadership actions related to the idealized influence dimension. During the virtual lab, the author observed that one of the facilitators was more distant and less involved compared with the physical lab project (Case 3). Moreover, during the interviews, the informants of Case 4 were more eager to talk about their experiences using the digital tools, as this was the first virtual innovation lab experience for some of them.

Inspirational motivation

The findings related to the inspirational motivation dimension show an array of leadership actions that can be categorized into three sub-dimensions. These sub-dimensions are the communication-related, interpersonal-related, and self-related actions of the facilitators.

First, the “communication-related” actions are the most significant findings for this dimension. They include: communicating clear goals, clear future plans, clear benefits of the labs, giving clear instructions, imparting useful information, and using understandable language. For example, informants from all cases expressed the importance of clearly communicated purposes and benefits of the labs, and also future plans. However, in Case 2, these ideals were less fulfilled. The participants admitted that they were not sure if they had learned anything as they were unclear about the purposes and benefits of the activities. For instance, a participant said:

But it was perhaps missing exactly how you can, in a way, use such types of techniques then in your [own innovation-related work] … it was a little missing I think. – C2D

This shows that the participant did not understand how to relate the creativity exercises in the lab project to his own innovation-related work. Also, another participant stated that she did not learn anything concrete from the lab.

Next, the “interpersonal-related” actions consist of what the facilitator should ideally do in the labs in order to develop interpersonal relationships among the participants and with the facilitator him/herself. These actions include: motivating the participants to get to know each other and to interact, encouraging equal opportunity, getting different perspectives to meet, actively engaging and leading the activities, involving the right participants, developing trust, and following up with participants after the labs. An example of important action in this sub-dimension is that the facilitator needs to actively engage the participants while leading and steering the process. This was achieved in all cases, but less apparent in Case 2. According to the informants of Case 2 and the observation report, the facilitator appeared less engaged with the participants. This was probably due to the purpose of the method, i.e. to let the participants be creative without interference from the facilitator.

Lastly, the “self-related” action is about the facilitator’s awareness of what is expected from his/her role. This is also related to the degree of engagement with the participants. Similar to the previous sub-dimensions, only in Case 2 was this less accomplished, as the facilitator and the participants had different expectations. As mentioned previously, the participants expected the facilitator to be more involved. However, the facilitator explained that this might have been due to a misunderstanding between the facilitator and the lab orchestrators:

I felt afterward that … I should have gotten more … the whole picture of what my role is. – C2C

Therefore, the facilitator needs to understand what the participants and orchestrators expect from him/her.

Intellectual stimulation

The findings within the intellectual stimulation dimension consist of important actions that the facilitators should perform to stimulate creativity among the participants in the lab projects. These are categorized into two sub-dimensions: interaction-related and technique-related stimulations.

The “interaction-related” actions are: to balance the facilitator’s involvement/interventions, motivate more interactions, create a positive climate, and generate confidence in participants. For instance, regarding the facilitator’s interventions, participants in Cases 3 and 4 had different opinions. Some participants stated that they preferred the facilitator not to intervene during the group discussions, as that might limit their freedom to be creative. However, some supported more interventions to keep the activities ‘on track’. For instance, an informant from Case 3 articulated:

I think it's good to supervise when we are discussing. I think it was very good. Because without anyone, we could speak about anything. – C3A

In contrast, an informant of Case 4 said:

I do experience it's quite difficult on the end part, to be creative on demand when [name of the facilitator] facilitated, and sort of demanded we come to a conclusion. – C4A

Thus, the facilitators’ involvement in the group work and/or discussions should be balanced. This was also supported by the observation report of Case 4, which showed that one group was particularly quiet when the facilitator mainly stayed out of the digital discussion room (breakout room in Zoom).

Next, the “technique-related” stimulations include: a balance between theory and practice, having knowledge about creativity techniques, and imparting something relevant to learn. To illustrate, a balance between theory and practice was demanded by the participants in Cases 1 and 2. Particularly in Case 1, the participants – who were mostly chefs – argued that just sitting and watching would not stimulate creativity. For example, an informant explained:

I think it’s kind of important to do both of them. To have some balance in it. It depends, if it’s too theoretical you kind of get them lost on the way. After hours of seeing somebody on the screen talking about some numbers and things like that, usually, they only get half of it. There’s a reason they are chefs in the restaurant business. – C1A

And another informant reflected about the cooking demonstration:

But again, I’d like to participate more than we actually had the possibility to do. – C1B

Individualized consideration

The findings in this dimension are the participants’ individual needs that a facilitator has to attend to. These concerns are related to their psychological and physical needs, time, methods used in the lab projects, and technical issues. Thus, they are categorized into five sub-dimensions following the aforementioned concerns.

First, the “psychological needs” sub-dimension includes psychological-related considerations and actions, such as: awareness of participants’ expectations and difficulties, communicating individually with each participant, language consideration, and welcoming each participant. Some examples related to the participants’ difficulties were found in Cases 3 and 4. An informant of Case 4 expressed that representing the group after the group discussion was difficult:

But to be the one that comes to a conclusion on behalf of 3 or 2 other persons can be challenging … to make some concrete conclusions. It was not a conflict, but it wasn't smooth, I guess. – C4A

Also, some participants in Case 4 admitted that they had difficulties in performing the preparation task, which was interviewing the end-users of the app during the Covid-19 pandemic.

Next, the “physical needs” sub-dimension is mostly about considerations related to the physical space and location of the labs. These include: that the physical space should be comfortable, preferably out of the workplace or outdoors, participants should be able to sit face to face but not be seated too much, the space should be related to the theme of the lab, there is the possibility to change rooms to stimulate creativity, and refreshments such as fruits should be available. Even though the physical location was not always chosen by the facilitators, as in Cases 1 and 2, it strongly influenced the facilitation. For example, participants in Cases 1 and 2 admitted that the location of the labs, which was in a renowned hotel, was their main motivation to attend. An informant from Case 1 expressed:

Some of the people that I talked to, said we don’t really have time for this but it was [name of the hotel], they couldn’t say no. So places have more effect than others and the timing. – C1A

Thus, a facilitator needs to be aware of these considerations. Also – except for Case 4, which was a virtual lab project – all informants seemed to agree on what the physical space of the labs should be like.

The third sub-dimension is about “time-related” issues that the facilitator should take into consideration. These include the need to consider timing that suits the participants, the participants’ need for time to think individually, and that activities should not last too long, especially for virtual lab projects.

Next, the fourth sub-dimension consists of “method-related” issues. These include the need to focus on the group work (i.e. no individual work during the lab activities) and that the activities should be easy to relate to participants’ organizations.

Lastly, the fifth sub-dimension is the “technical-related” need. For the virtual lab (Case 4), it was crucial at the beginning to explain how to use the digital tools. The author observed that some of the participants initially had difficulties using the digital tools, which was also confirmed by one of the informants.

Other influencing factors

The findings also revealed two important factors outside of the four dimensions that influence team learning for collaborative innovation in the labs – participants’ self-motivation and backgrounds. First, to be well prepared, participants must have their own motivations. For instance, an informant from Case 2 expressed:

 … you must have a very clear entrance … when they come to that lab, they have in a way, a problem that is defined or have prepared then. – C2D

It was observed that some participants of Case 2 were less prepared; thus they were unclear about what they could learn from the lab. By contrast, participants of Case 3 could clearly express their motivations and goals for joining the lab project. For example, an informant said:

So my goal is both to learn more about the possibilities and to try to find out what we can do to make this a better project for us. – C3C

Therefore, these findings show that when the participants are self-motivated and prepared, they will learn more.

Lastly, participants’ backgrounds are crucial as they influence how they will learn. For example, the facilitator of Case 2 pointed out the challenge in facilitating the group innovation work, as the participants came from different firms with diverse experience-based products:

But then you wanted in the project here to work with your own things, and it becomes difficult when there are five in a group to work with their own things. Because then it will be, the others say … why should we work with their products? – C2C

Also, in Case 1, as previously described in the inspirational motivation dimension, the participants demanded more practical learning activities because they were mostly chefs. Thus, the facilitators need to know the background of the participants when preparing for the facilitation of the lab projects.

Findings across cases

Although there are no contradicting findings across the cases, there are findings within the transformational leadership dimensions that are emphasized in some of the cases but not mentioned in the others.

First, for the idealized influence dimension, only the participants in Case 1 emphasized that they were highly inspired and learned a lot from the facilitators. Although the interviewees of other cases acknowledged that their facilitators were professional and positive, none of them expressed the same admiration. Moreover, this was not even mentioned by the participants of the virtual lab project (Case 4). This might be because the facilitators in Case 1 were renowned chefs. Thus, the idealized influence dimension played little role in the cases unless the facilitators were well-known individuals.

Secondly, regarding the inspirational motivation dimension, participants in Case 2 were the most vocal about the vague goals and purpose of the lab project (communication-related sub-dimension). This might be due to the rather ambiguous method used in the activities, which was also related to the output of the lab project. In Cases 1 and 2, there was no concrete output, as the purpose of the lab projects was to inspire the participants and encourage learning. However, in Case 1, the cooking demonstration could be easily related to the participants’ own work and thus they felt that they learned a lot from the lab. Meanwhile, Cases 3 and 4 had a more concrete output, which was a collection of innovative ideas for developing the guiding app.

Thirdly, the need for a balance between theory and practice (technique-related sub-dimension) in the intellectual stimulation dimension was predominantly expressed by the participants of Case 1. This is because the participants in Case 1 were mostly chefs, who were used to being physically active in their workplaces. Thus, they expected to be involved in the cooking demonstration in the lab. This indicates that the background of the participants also plays a role in the intellectual stimulation dimension. However, in Cases 3 and 4, participants were most concerned about how the facilitator’s interventions should be balanced (interaction-related sub-dimension), especially during group discussions.

Fourth, for the individualized consideration dimension, the informants of Case 1 and Case 2 strongly emphasized how the physical space motivated their participation in the lab projects (physical needs sub-dimension). On the other hand, the participants of Cases 3 and 4 were more concerned about their psychological needs. And especially for Case 4, the informants were eager to talk about the technical issues.

Lastly, regarding the factors outside of the transformational leadership dimensions, the participants’ background had more influence in Case 1 and the participants’ motivation had significantly more effect on Case 2. For Case 1, the background of the participants – mostly chefs – also influenced the findings in the intellectual stimulation dimension (i.e. the importance of balance between theory and practice). And for Case 2, it might be that the participants were uncertain about the purpose and method of the lab, and thus they were less prepared. As for Cases 3 and 4, the importance of self-motivation was mentioned but not emphasized. However, the importance of the participants’ backgrounds was not brought up.

Discussion

This section consists of three parts. The first part focuses on the transformational leadership dimensions and other influencing factors. The second part highlights the importance of other intermediary roles in facilitating lab projects. The last part discusses how the findings are related to the broader topic of learning and innovation, and suggests a conceptual model.

Transformational leadership dimensions and other influencing factors

The findings generated 10 new sub-dimensions of transformational leadership within three of the four main dimensions from the existing literature. Some of the findings agree with the literature and others only partly. For example, the findings indicate that the idealized influence dimension is less important in facilitating lab projects, whereas the other three dimensions are more significant. This partly agrees with the existing literature regarding the importance of inspirational motivation and intellectual stimulation in innovation (Avolio et al., 1999; Elkins & Keller, 2003; Hughes et al., 2018; Srivastava et al., 2006). The findings show that the individualized consideration dimension is crucial, particularly regarding the physical space and location of the lab projects. This is because the physical space can be a motivation for the participants and can spark their creativity (Fecher et al., 2020). Moreover, time-related individualized consideration is also important, which is in line with the work of Jernsand (2019).

The findings also concur with the work of Druskat and Kayes (2000), in that interpersonal understanding and clearly communicated goals are important in facilitating short-term team learning. Equally, this study revealed the sub-dimensions of interpersonal and communication-related factors in the inspirational motivation dimension, which is also in accord with the work of Lund and Tingström (2011).

Additionally, the findings within the intellectual stimulation dimension indicate that the facilitators’ interventions should be limited and balanced. This echoes the existing literature and suggests that rigid procedures have a negative effect on short-term team learning as they hinder the team’s creativity and spontaneous information sharing (Druskat & Kayes, 2000; Langer, 2000).

There are also a few overlapping findings across the dimensions of transformational leadership. First, communicating useful information in the inspirational motivation dimension is similar to giving something relevant to learn in the intellectual stimulation dimension. Secondly, the need to motivate interactions can be found in both the inspirational motivation and intellectual stimulation dimensions. However, in the inspirational motivation dimension, interactions among participants aim to develop trust, whereas in the intellectual stimulation dimension the interactions stimulate new ideas or creativity. Lastly, language consideration is important in both the inspirational motivation dimension and the individualized consideration dimension.

Finally, the study revealed two influencing factors outside of the transformational leadership dimensions – the participants’ own motivations and their personal backgrounds. Similarly, Fecher et al. (2020) mention the importance of participants’ expectations and motivation in innovation labs. Also, Hughes et al. (2018) underline that intrinsic motivation is a crucial mediator between leadership and innovation. Nevertheless, the importance of the participants’ personal backgrounds, such as their occupations, is not mentioned in the literature.

Other intermediary roles

This study ties in well with previous studies which found the facilitators should have ambidexterity and flexibility, as the expected facilitator roles include a wide range of intermediary activities (Hakkarainen & Hyysalo, 2016; Nyström et al., 2014). These intermediary activities are highlighted in the findings related to the inspirational motivation and individualized consideration dimensions. These include the need to involve or invite the right participants, follow up with the participants after the lab projects, and be aware of the participants’ expectations and personal backgrounds. Thus, the facilitators’ roles should include contacting the participants before and after the lab projects, and also becoming familiar with them.

Lastly, the findings also emphasized the importance of the physical space and location of the lab project. Thus, choosing the appropriate location and physical space for the lab project should also be included in the intermediary activities. To summarize, based on the findings, the facilitation of lab projects should be viewed in a broader context and process.

The conceptual model

Based on the literature and the empirical findings, a conceptual model is suggested and presented in Figure 1. First, in line with the literature, the figure shows that transformational leadership dimensions facilitate team learning and team learning drives the collaborative innovation process in experience-based tourism lab projects (Decuyper et al., 2010; García-Morales et al., 2012; Gil et al., 2018; Hinkin & Tracey, 1994; Zach, 2016). This is supported by the fact that the lab projects resulted in new ideas based on the collaborative innovation process, especially in Cases 3 and 4. And even though there were no concrete innovative outputs in Cases 1 and 2, the participants were positive that they gained inspiration and some degree of learning (higher in Case 1) and would use both in the innovation processes of their own organizations.

However, the empirical study also shows that learning is influenced by the participants’ intrinsic motivations and personal backgrounds. This, at least to the author’s knowledge, has not been elaborated in earlier studies related to the facilitation of labs, particularly in experience-based tourism. Lastly, the conceptual model also includes other important leadership roles, i.e. intermediary activities.

Figure 1. A conceptual model based on the findings and literature.

Conclusions

By using the transformational leadership dimensions, this study shows how to facilitate learning – which is an essential part of the collaborative innovation process – in experience-based tourism lab projects. Thus, it contributes to the scarce literature on the facilitation of innovation in tourism labs, particularly in experience-based tourism. It also contributes to the transformational leadership theory by identifying 10 new sub-dimensions. Further, this study also points out additional important factors outside of the transformational leadership dimensions, i.e. intrinsic motivation and personal background. And one of them, the participants’ personal backgrounds, has not been mentioned in the general literature on the facilitation of innovation labs. Lastly, the practical contribution of this study lies in identifying the essential leadership practices that a facilitator should consider when planning and performing the facilitation of an innovation lab in experience-based tourism.

Limitations and future research suggestions

This study has some limitations, which suggest future research opportunities. First, the findings should be used with caution in different contexts, as the cases focused on meal and cultural experience-based tourism in Norway. Thus, future research involving different contexts might be of interest. Secondly, as the study used a qualitative multi-case design, which involved collecting and interpreting semi-structured interviews, there is always a risk of misinterpretation. However, the study also triangulated the data from observations and interviews, which increases its validity.

Next, some findings should be studied further. First, the importance of physical spaces related to learning, leadership, and collaborative innovation should be further investigated. Also, the comparisons of the physical and digital spaces can be a highly interesting research topic, as the use of virtual collaborative innovation spaces has become more common during the Covid-19 pandemic. There is also a need to study further the roles of methods or creativity techniques in tourism labs with different purposes, and the influence of participants’ personal backgrounds on collaborative innovation.

Lastly, as this study focuses on the facilitation during the lab projects’ activities, and not before and/or after them, another future research possibility is about the labs in a wider context or as a part of a complete innovation process, not just an isolated and temporary event. This is because all four lab projects in this study focused on ideation, while labs can have other purposes and be used in other innovation phases. Additionally, the orchestration of the labs is important as it has a strong influence on the outcome (e.g. in Case 2 there might have been miscommunication between the orchestrators and the facilitator, and in Cases 1 and 2 the orchestrators chose the physical space).

Acknowledgements

This study is funded by Nord University. The author would like to thank the informants, the cooperators, Professor Dorthe Eide, Professor Elisabet Ljunggren, and Associate Professor Hindertje Hoarau Heemstra.

Disclosure statement

The author reports there are no competing interests to declare.

Additional information

Notes on contributors

Yati Yati

Yati Yati is a PhD candidate at Nord University, Norway. Her research interests include labs for innovation, such as living labs and innovation labs, particularly in experience-based tourism. Her PhD project focuses on the innovation processes of labs in tourism. She graduated from UiT the Arctic University of Norway, with a Master of Science degree in Business Creation and Entrepreneurship.