Investigating Flow in Motorcycle Tourism: A Review of Previous Research and Identification of Opportunities

2.1 Flow

A flow state is the mental state in which a person performing an activity is fully immersed in a feeling of energized focus, full involvement, and enjoyment in the process of the activity. It is sometimes referred to as “being in the zone” (Kotler, 2021, p. 16). Flow is characterized by the complete absorption in what one does, and a resulting transformation in one’s sense of time (Csikszentmihalyi, 2008). Flow manifests as a state of seemingly effortless concentration in which a person is completely absorbed in what they are doing. It can arise during a wide range of daily activities, including work, physical and sport activities, technology use, and interactions with others (Lavoie et al., 2021, p. 38).

Figures 1 through 3, that follow, are graphic conceptualizations across the evolution of flow theory. Figure 1 stems from Csikszentmihalyi’s early research during the 1970s and his seminal flow questionnaire (Moneta, 2012). It basically juxtaposes the balance between an activity’s challenge versus one’s skill in completing the activity. If one’s ability is comensurate with the challenge, flow is achieved. If one’s skill level is lower than the challenge, anxiety is felt. If one’s skill level is higher than the challenge, boredom is felt (Csikszentmihalyi, 2008). It also implies that the cartesian space that flow occupies can happen at higher and lower intensities.

Figure 1:

Conceptualization of the flow state (1975).

Figure 2 represents the Experience Fluctuation Model (Moneta, 2012, p. 35) which was an evolution in flow theory, through an expansion of the range of possible outcomes between the balance of an activity’s challenge versus one’s skill set. It models experience sampling method (ESM) measures of flow (Moneta, 2012). Flow is still achieved when skill is comensurate with a relatively high-intensity challenge. However, unlike the first model, in Figure 1, when the balance between challenge and skill are both at a relatively low intensity, apathy sets in. More nuanced outcomes occur when challenge is greater than skill through, respectively, arousal, anxiety, or worry; conversely, when skill is greater than challenge, control, relaxation, or boredom arise, in turn (Engeser & Rheinberg, 2008).

Figure 2:

Conceptualization of the flow state (1985)

Figure 3 mirrors Csikszentmihalyi’s initial conceptualization but models multi-dimensional scale measures of flow that more clearly represents a linear cartesian flow space from high to low intensity. When flow occurs during relatively complex activities that are extreme and long in duration, flow is referred to as deepflow. However, when flow is elicited from shorter and less intense activities, it is called microflow (Lavoie et al., 2021).

Figure 3:

Conceptualization of the flow state (2012)

Csikszentmihalyi (2004) states that flow can come about haphazardly, but one has an improved chance of achieving it if three conditions are present. First, the activity must have clear goals to establish a reasonably finite direction. Second, the activity or task must provide unambiguous and immediate feedback to allow the individual to negotiate any changing demands and allow one to adjust performance to sustain flow. Third, as indicated in the figures above, good balance is required between perceived challenges of the activity, and one’s perceived skill. That is, one must have, at least, a perceived confidence in his or her ability to complete the task. Others (Engeser & Rheinberg, 2008) have suggested further conditions that might foster the ability to achieve flow. These include concentration and the absence of distractions, and that the activity is perceived to be inherently rewarding.

Csikszentmihalyi also hypothesized that people with certain personality traits may be better able to achieve flow. These traits include curiosity, persistence, low egotism, and a high propensity to perform activities for intrinsic reasons. These people are said to have an autotelic personality. The term “autotelic” derives from two Greek words, auto, meaning self, and telos meaning goal (Lopez et al., 2018).

As will be discussed in more detail below in the section on measurement, most flow scales address, at least, Csikszentmihalyi’s three core conditions. However, they do not investigate how flow conditions are manifest in the context of motorcycle riding. For example, road conditions (straight and flat versus twisty and hilly), and other factors, might impact whether the motorcyclist achieves flow. Also, sport-touring motorcycles handle better and provide more immediate feedback than, perhaps a cruiser (see Frash Jr. et al., 2018). A person with a full-face helmet could possibly be more isolated from distractions than a rider without helmet. Or, a person that rides more frequently would be expected to have a greater perceived confidence in his or her ability to complete a motorcycle journey.

2.2 Flow and Tourism

Tourism studies suggest that the relationship between a flow state and experiences is extremely pertinent (da Silva deMatos et al., 2021, pp. 1–2). This connection is often manifest with tourists’ desire to progress away from the pedestrian in favor of the remarkable – to be subjected to greatly satisfying and affirmative experiences (Huang et al., 2020). Tourists want to be exposed to, and live experiences that engage them in rewarding emotive states of mind (Aykol et al., 2017). Csikszentmihalyi (2008) and others (Engeser & Rheinberg, 2008) have found that the following rewards are associated with flow:

• Better emotional regulation: With increased flow, people experience more growth toward emotional complexity, which can help to develop skills that allow one to regulate emotions more effectively.

• Greater enjoyment and fulfillment: People in flow enjoy what they are doing more; and, because the task becomes more enjoyable, are more likely to find it rewarding and fulfilling.

• More happiness: Flow may be linked to increased levels of happiness, satisfaction, and even, self-actualization (Maslow, 1943).

• Greater intrinsic motivation: Because flow is a positive mental state, it can provide intrinsic motivation.

• Increased engagement: People in flow feel fully involved in the task at hand.

• Improved performance: Flow has been shown to enhance performance in a wide variety of areas including athletics, teaching, and creative endeavors.

• Enhanced skill development: Because the act of achieving flow indicates a substantial mastery of a certain skill, one typically keeps seeking new challenges and, and skills to achieve those challenges, in order to maintain the state.

Scholars indicate that flow is at the core of most recreational experiences (Kim & Thapa, 2018). The majority of these flow studies are centered on physical activities, such as playing a musical instrument, participating in sports (Sinnamon et al., 2012), or riding motorbikes (Frash Jr. et al., 2018). This is natural because Csikszentmihalyi’s (2008) seminal research in the 1970s and 1980s called upon such deeply engaging activities. However, some contemporary tourism scholars argue that the relationship between flow and broader tourism experiences need further analysis (da Silva deMatos et al., 2021). For example, there is a dearth of knowledge about the role of flow during tourists’ experience consumption. Huang et al. (2020, p. 1) indicate “… the way tourists assess their best experiences, and the underlying reasons of such experiences remain a pertinent but under-researched area in the tourism experience literature.”

A recent literature review by da Silva deMatos et al. (2021) offers an insightful narrative regarding the conceptualization of flow in the context of tourism. They convey that scholars’ concept of flow is closely related to positive psychology and optimal experience, which emphasizes the importance of self and positive dimensions of individual development. Flow-related studies (Freire et al., 2018; Freire et al., 2016) address topics that include self-esteem, self-concept, psychological well-being, happiness, and general satisfaction with life. Such findings are applicable to tourism, as most tourist experiences are expected to provide individuals with pleasure, as well as, increase their physical and psychological well-being (da Silva deMatos et al., 2021). As such, flow is thought to play a mediating role across tourism and leisure because it can provide experience enrichment and emotional satisfaction (Kim & Thapa, 2018).

Increasingly more studies have found that a person’s personality and intrinsic/extrinsic motivations to engage in tourist activities may be important drivers of one’s ability to achieve flow (Mills & Fullagar, 2008). An individual’s motivation can be pivotal to the development of skills that allow the person to respond to environmental cues and reach a state of flow activation (Ross & Keiser, 2014). Some suggest, that to attain flow in tourism, the tourist should display a level of “flow-proneness” (e. g. an autotelic personality) and be motivated to activate a flow state when provided with environmental cues (da Silva deMatos et al., 2021, p. 7). For MTs this could be made manifest through participation motorcycle skills training, or well-designed instructor-guided motorcycle tours. It could imply that those that seek to improve their riding skills, will by extension, be more motivated and more readily achieve flow. As Lee and Payne (2016, p. 163) put it, “what matters most to experiencing flow is not what we do, but how we do it.”

2.3 Flow and Motorcycle Tourism

There are approximately 8.7 million registered street-legal motorcycles in the United States of America (U.S.A.). Yet, this is quite modest when compared to the nearly 272.5 million registered cars in the U.S. (Federal Highway Administration, 2020). Retail motorcycle sales in the U.S., which is led by the Harley Davidson brand, fell for the 16^th straight quarter, resulting in an eight-percentage decline in Harley Davidson’s big cruiser motorcycle market share. Ironically, this decline came at a time when motorcycle sales went up globally in the wake of a demand for socially-distanced recreational outdoor activities (Singh & Ajmera, 2021). Overall, there has been a shift away from cruiser-type motorcycles to sport-touring and adventure-touring motorcycles, which arguably, are better suited to motorcycle touring and tourism. BMW Motorrad had its best annual sales ever in 2021, which was dominated by its adventure-touring and sport-touring models (Jitchotvisut, 2022). Most prominent motorcycle manufacturers (e. g. Harley Davidson, Honda, Suzuki, Kawasaki, Yamaha, Aprilia, Ducati, KTM, Moto Guzzi, Triumph, Royal Enfield, and others) now produce sport-touring and adventure-touring motorcycles.

With this backdrop, a literature review on motorcycle tourism was conducted. A systematic quantitative literature review (SQLR) method (Moher et al., 2015) was applied. The first step was to establish the research objective, which was to find scholarly articles dealing with facets of motorcycle tourism. Next, a review protocol was established. An academic expert, who had ridden motorcycles for over 40 years, and published peer-reviewed articles on motorcycle tourism, was consulted to select the search strings and criteria for inclusion and exclusion of articles. The Boolean operators were motorcycl* or motorbike or “motor bike” or motorbiking or moto* or “powered two-wheeler” and touris* or touring. The review was conducted in March 2022, in Web of Science (WOS) and EBSCO databases. The main selection conditions were peer-reviewed articles that were written in the English language, and pertaining to the subject areas of tourism, sociology, and psychology. The search output resulted in 226 articles, with eight duplicates. Only 24 articles met the intended subject criteria.

Most of the excluded articles dealt with motorcycles but not motorcycle-tourism issues, which included safety concerns (helmets, crashes, speeding, health, alcohol consumption, etc.), injuries, environmental issues, and mechanical matters (tire quality, maintenance, and kinematic handling). There were several articles on motorcycle events, but they were not included because they primarily deal with event management and not motorcycle travel and touring. Also, articles published in the International Journal of Motorcycle Studies were not included because it is an open-source journal that is not peer reviewed.

Though the included motorcycle tourism articles were limited in number, the research represented studies from the U.S.A., U.K., Europe, and Asia. Research topics largely discussed MT characteristics, preferences, and culture. The normative consensus is that most motorcycle riding is recreational and touristic in nature (Broughton & Stradling, 2005; Cater, 2017; Morris, 2009; Sykes & Kelly, 2016; Walker, 2010) and, year over year, there has been an increasing amount of interest in motorcycle tourism (Dorocki, 2021).

The literature largely debunks the stereotypical myth that MTs are outlaws, though some in the U.S.A. continue to cling to the facade (Austin & Gagne, 2008; Frash Jr. et al., 2018). In fact, most MTs are mainstream middle- and upper-class Boomers, Gen X, Millennials, and increasingly Gen Z. While most MTs are male, female MTs are growing at much faster rate (Romy & Dewan, 2021; Weddell, 2014). Curiously, while an MT’s personal income is not a probable root cause, their reported spending is modest when compared to more traditional types of tourism (Cater, 2017; Perez & Juaneda, 2000). In fact, MTs seem to feel that being parsimonious is a cultural badge of honor (Cater, 2017; Sykes & Kelly, 2016). However, Austin’s (2009) ethnographic case study of motorcycle rallies related paradoxical spending behavior. He reported that nearly all rally attendees ostensibly camped to save money and fit the rugged spendthrift image. Participants sat fireside swapping stories late into the night but would furtively leave to spend the night in a nearby hotel – implying that MTs’ reported spending may not reflect actual behavior. Moreover, MTs are typically highly involved and loyal consumers (Thompson, 2009; Walker, 2010), and particularly in rural areas that are not mainstream tourism destinations (Sykes & Kelly, 2016).

MTs have a strong sense of community and belonging within their peers (Walker, 2010). Walker writes (2010, p. 151) “when riding specifically with a group, the [motorcycle] rider is operating in the social group of the immediate riders, but also within the greater social group of all motorcyclists. This group riding, in some ways, is a paradox, as the actual riding of a bike is generally a solo activity with limited opportunity for communicating.” Although motorcycling is often done alone (i. e. one person on the motorcycle), some carry passengers on a pillion. This is sometimes referred to as riding two-up, and there is evidence that per-person travel spending is greater for those riding with a passenger (Cater, 2017; Frash Jr. et al., 2018).

MTs take out and back day trips (e. g. go to lunch), and multiday holiday trips, which are planned with a reasonable level of detail (Cater, 2017; Ramoa et al., 2021; Sykes & Kelly, 2016). Ramoa et al. (2021) noted MTs’ emerging motivation to engage in adventure touring. MTs indicated that they most preferred routes with landscaped views and with water in the forefront. Scenic routes with agricultural pastures or a backdrop of forests were also desirable (Merry et al., 2020). MTs are motivated to travel because of the lifestyle image and the need to escape from unpleasant daily deliriums – therefore push factors, more than pull factors (Colarič-Jakše & Ambrož, 2015).

In terms of Leiper’s (1979, p. 392) Whole Tourism System, the literature normatively supported the importance of the transit route, over the MTs’ destination region (Cater, 2017; Dorocki, 2021; Frash Jr. et al., 2018; Ramoa et al., 2021; Sykes & Kelly, 2016; Walker, 2010). Scuttari (2021, p. 1) conceptualizes this as a “journey experience”. This focus on the journey experience could be related to flow because MTs have been found to exhibit autotelic characteristics, including self-confidence, as well as, experiential desire and acceptance (Wu et al., 2021).

Csikszentmihalyi (2008, p. 71) states that a person “is much more likely that flow will result either from a structured activity, or from an individual’s ability to make flow occur, or both.” As noted above, motorcycle riding is a structured activity in which MTs exhibit autolectic characteristics – perhaps making them more inclined to achieve flow. Moreover, motorcycle tourism meets Csikszentmihalyi’s three requisite conditions. First, also noted above, MTs typically have clear goals and trip plans. Second, motorcycle riding provides unambiguous and immediate feedback. For example, if a rider pushes on one side of the handlebars, the motorcycle will turn immediately (Song et al., 2017; Walker, 2010). Third, motorcycle riding requires an enhanced skill set and can be not only challenging but, without a reasonable balance between skill and challenge, can be quite hazardous (Walker, 2010).

3.1 Flow Measurement

It is said that when studying the flow state, the most challenging task is to measure it, because when individuals are deeply involved in an activity (i. e. flow), they are arguably not fully conscious of their state, and not willing and/or available to comment on it (da Silva deMatos et al., 2021). Moneta (2012, pp. 23–24) writes that since Csikszentmihalyi’s original formulation of flow in 1975, there is still strong agreement among scholars regarding his seminal definition. However, scholars are less than congruent on how flow should be measured. Over the decades, researchers have developed and validated numerous measurement tools for flow, and/or modified and revalidated established scales. The apparent paradox between agreement on the concept and disagreement on how to measure it is not uncommon in psychology. This is because one must recognize that the path from theoretical definition, to the operationalization of a construct, goes through intermediate and context-specific processes of modeling. That is, what works in one research setting may not work in others. Before turning to suggestions for measuring flow in a motorcycle tourism specific context, some major milestones in flow measurement will be discussed.

A seminal flow measurement approach was the mixed-method Flow Questionnaire (FQ) [see Figure 1]. It was the outcome of interviews conducted with participants from a wide range of occupations, which produced a wealth of textual descriptions of the flow experience in various domains of human endeavor (Csikszentmihalyi & Graef, 1980). While the FQ was a good measurement method for studying the prevalence of flow, it is a limited measurement method for investigating the effects of challenges and skills on subjective experience, and it cannot measure the intensity of flow in specific endeavors (e. g. motorcycle tourism) (Moneta, 2012, p. 27).

Another major milestone was the Experience Sampling Method (ESM) (Massimini et al., 1987). It was among the first qualitative instruments created to assess flow. It consisted initially of contacting the study’s participants via pager or phone to report their experience. An alternative method was also developed, in which individuals used a diary, where, at different moments of the day (for several days, ranging from two to 14 days), they reported their activities, thoughts, and psychological states (Riva et al., 2017). The main strength of ESM stems from the rich and robust empirical findings it can generate. However, it has limitations. For example, the channel model [see Figure 2] is a qualitative classification system; therefore, it does not allow the researcher to test the implicit assumptions underlying the classifications. In particular, the superiority of the flow channel over the other channels is universally interpreted as being due to the equivalent ratio of perceived challenges from the activity to perceived skills in carrying out the activity. Yet, the balance of challenges and skills needed to explain the pattern of findings is not manifest in ESM (Moneta, 2012, p. 36). The ESM would not be practical in a motorcycle tourism research context because MTs are unlikely to interrupt their journey experience to intermittently phone in their feelings or, similarly, keep a diary.

While the aforementioned methods for measuring flow were reasonable in their time, and produced insightful and robust findings, they were far from being psychometrically sound. As such, researchers set out to construct and validate quantitative scales that would measure flow to the standards required by traditional test theory (Moneta, 2012). This period is what Moneta (2012, p. 40) paraphrases as the “componential approach” era, which includes an array of multidimensional quantitative scales (e. g. the Flow State Scale (FSS) and the Dispositional Flow Scale (DFS), which measured intensity of flow as a trait or a state (Jackson & Eklund, 2002)). A comprehensive description of these measures is beyond the scope of this paper, but they are consistent with Csikszentmihalyi’s (2008) componential view of flow.

The da Silva deMatos et al. (2021) review indicated that the majority of flow studies in tourism (77 %) used quantitative scales similar to the componential scales reported by Moneta (2012). Fourteen percent of the articles they reviewed used qualitative research methods (e. g. the ESM). While seven-percent of the reviewed studies used mixed methods (e. g. the FQ). Two-percent used relatively new physiological instruments, noninvasively, through wearable biosensors. While physiological instruments offer promise in measuring flow in motorcycle tourism because it might allow an, on the motorcycle, in-flow assessment, most MTs would likely find wearing biosensers to be untenable.

3.2 Measuring Flow in Motorcycle Tourism

Jackson and Eklund (2002) developed a “long” multi-item multi-factor flow scale they called the Flow State Scale (FSS) (Martin & Jackson, 2008, p. 142). The scale items were developed and first validated in physically active settings. The FSS is designed to assess the state, or situation-specific component of flow (e. g. motorcycle riding). In the FSS, nine key characteristics are assessed, following the nine-dimensional conceptual model of flow (Csikszentmihalyi, 2008; Jackson & Csikszentmihalyi, 1999). Each characteristic, or factor, comprises four items, so the FSS is a 36-item instrument. The dimensions or factors are challenge-skill balance, action-awareness merging, clear goals, unambiguous feedback, concentration on the task at hand, sense of control, loss of self-consciousness, time transformation, and autotelic experience. The FSS is frequently used in sports research (Martin & Jackson, 2008), which is suitable, because as noted above, MTs feel that their riding is a sport. The FSS yielded an acceptable factor structure and reliability with first order (involving the nine factors) models and higher-order (involving a global flow factor) models providing good fit to data (Jackson & Marsh, 1996). As such, the FSS could have utility in measuring flow in the context of motorcycle tourism.

However, it is important to anticipate and contextualize a possible motorcycle tourism study setting (i. e. how and where a survey might be disseminated) when assessing flow. Past studies (Frash Jr & Blose, 2019; Frash Jr. et al., 2018) used research panels, who completed online surveys, which proved to problematic because of recall issues. Flow is best measured as close to when the activity occurs as possible (Moneta, 2012). Therefore, it is suggested that the researcher disseminate the survey during, or at the end of, the motorcycle riding experience. For example, Scuttari (2019) conducted a short survey at a café at the end of a mountain pass, which was a haven for MTs. Also, motorcyclists tend to be time-sensitive when out riding. That is, it is not probable that MTs will be willing to complete a lengthy survey, especially while or at the end of a ride (Frash Jr. et al., 2018). Moreover, in research where flow is not the only construct of interest – which should be the case because innate motivations (e. g. flow) have been posited to be an antecedent of travel intentions (Jang & Cai, 2002) – a short form provides an opportunity to measure it without imposing restrictions on the other constructs (Martin & Jackson, 2008). Taken together, it is evident that a shorter flow scale is appropriate in a motorcycle tourism study context.

The literature revealed three disparate brief scale forms to measure flow (Lavoie et al., 2021; Martin & Jackson, 2008). While they all propose to assess whether the respondent achieved flow during an activity, each one has distinct features. Martin and Jackson (2008) developed and validated two brief, uni-dimensional flow scales, which they called the short flow scale (SFS) and the core flow scale (CFS). Lavoie et al. (2021) developed and validated a two-dimensional (fluency and absorption) flow short scale (FSS). The fluency factor was theorized to be an antecedent of absorption. However, they suggest the FSS is more robust when measuring microflow versus deepflow (see Figure 3). Given that motorcycle riding requires a more enhanced skill set and can be hazardous (Walker, 2010), motorcycle tourism is expected to be a deepflow activity. As such, the SFS and CFS are suggested in favour of the FSS.

The SFS was designed to be a succinct measure of flow. It has nine items, with each item representing one of the nine respective dimensions from the longer FSS. Martin and Jackson (2008) demonstrate that in a physically active domain, the SFS provides a valid and reliable global flow construct, as did the FSS. The CFS has ten items and is intended to capture the phenomenology of the experience itself – consistent with original conceptualizations of subjective optimal experience underpinning flow. Therefore, while the SFS summatively assesses the elements that comprise and/or lead to flow, the CFS captures the central subjective optimal experience (e. g. being “in the zone”, feeling like “everything clicks”, and being “totally focused” (Martin & Jackson, 2008, p. 143). Table 1, below, juxtaposes the SFS and CFS measurement items.

Given the nascent stage of flow in motorcycle tourism research, the SFS might be the preferred scale because an analysis could better determine the relative weights of the nine dimensions leading to flow. However, the singular focus of the CFS on flow absorption might have utility in subsequent studies. Also, adapting some of the item language to a more motorcycle-centric context could be advisable, so long beta tests do not reveal a loss of psychometric properties. For example, instead of saying “I feel I am competent enough to meet the high demands of the situation” the item might read, “I feel that I was fully capable of handling my motorcycle, even on challenging roadways.”

3.3 Intervening Variables

Looking at the SFS measurement items, one can see that it tests for Csikszentmihalyi and others’ (2008; Engeser, 2012) mainstream flow characteristics. However, as noted throughout this manuscript, there are motorcycle tourism related variables that are not addressed. For example, an MTs’ skill level would logically improve the more (or longer) he or she had ridden their motorcycle. Riding ability would also be augmented by motorcycle skills-based training sessions and/or through participation in instruction-centered commercial tours. An improved skill set would allow the MT to ride in increasingly more challenging settings; and therefore, perhaps achieve deeper flow. Roadway conditions should also be assessed because they can exemplify more challenging settings. Rider capability and challenging roadways are motorcycle-centric surrogates to assess an MT’s balance, which is needed to gain flow.

The type of motorcycle (e. g., cruisers, touring, sport-touring, dual-sport or adventure-touring, and sportbikes (Motorcycle Industry Council, 2015)), and/or weather might moderate the relationship between flow and an MT’s travel intentions. This is because even if flow is attained, its influence on future travel intentions might vary depending on the suitability of the motorcycle and/or the weather conditions. Figure 4, that follows, imagines a hypothetical path model in which flow positively influences MTs’ travel intentions with these antecedent and moderating intervening variables.

Figure 4:

Hypothetical path model for flow and travel intentions with intervening variables.