The effect of sensory experience on sport development: baseball simulation in Korea

ABSTRACT

Rationale:

A baseball simulation provides its participants a sporting environment in which programmed game mechanics mediate sensory stimuli. The current study aims to discover how simulation users’ interests in baseball, athletic identity, and intentions to participate in baseball differ by degree of stimuli. The results would reveal the dynamics of how baseball simulation users’ sensory experiences relate to their baseball development.

Design:

Data collection, taken at two Korean baseball simulation franchises, involved 136 simulation participants. On a self-administered survey, participants answered questions about their degree of perceiving visual, aural, and tactile stimuli as well as their baseball interest, athletic identity, and intentions to participate in baseball. The collected data were analyzed in MANOVA.

Findings:

The simulation users’ interests in baseball differed according to the degree of visual and aural stimuli. Regarding the degree of tactile stimuli, the simulation users differed in the degree to which they identified as an athlete and intended to participate in baseball. Playing a crucial role in their baseball development was their tactile sense.

Practical implications:

The study suggests managerial implications that sport practitioners implement toward developing a new participatory market.

Research contribution:

The study reveals how sport simulation users interact with the simulation's multi-dimensional environments.

KEYWORDS:

• Baseball simulation
• screen sports
• sensory experience
• sensory stimuli
• sport development

Introduction

At sporting complexes in America, it is common to see a parent and child working together in a batting cage. This is also fairly common in Korea, though with major contextual differences. The batting area resembles an air-conditioned entertainment center with people sitting around tables and chatting while surrounded by various amenities, such as food and music. Furthermore, there is no physical batting cage; people take their swings by interacting with a simulation and play a baseball game that is being projected onto a big screen. In Korea, this sort of enterprise is referred to as “screen baseball” (Min & Kim, 2018).

Referred to in computer science as human-in-the-loop (Narayanan et al., 1997), sport simulation is a special kind of simulation in which a particular system of sport is programmed, executed, and analyzed on a computer (Roberts et al., 2019). One example is a baseball batting simulation. Facing a computer-mediated baseball field that is being projected onto a screen, a participant bats and interacts with computer-operated game mechanics. Sport simulation's environment is two-fold, consisting of virtual and physical environments. The virtual one consists of computer-mediated features that simulate a baseball field on the screen while conveying game mechanics; the physical one consists of the simulation's surrounding environments and tangible objects related to a participant's kinetic movements, such as a baseball and bat. In the current study, sport simulation is interchangeably used with sport simulator. Also, sport simulation participants mean the users of sport simulation or simulator.

According to the “experience economy,” a concept put forward by Pine and Gilmore (1998, 1999), the live experience is a commercial offering for consumers. In this theory, the way consumers consume the experience shifts from being amused and entertained to engaging fully in the experience. An ideal example of the experience economy is baseball simulation. The simulation provides its users an immersive live experience that they actively experience, as they try swinging a bat and hitting a ball. In such dynamics, the key is simulator users’ sensory experience.

Consumers’ sensory experience refers to the subjective feeling derived by interacting with a surrounding environment (Krishna & Schwarz, 2014). In these interactions, consumers perceive diverse stimuli through each of the five senses (i.e. sight, sound, smell, taste, and touch). Mehrabian and Russell (1974) developed the Stimulus (S)-Organism (O)-Response (R) model to capture the effect of consumers’ sensory experience. By theorizing how consumers perceive an environment's stimuli, internally process them, and behave according to the process, the model highlights the importance of sensory experience in understanding consumers’ psychological and behavioral characteristics (Vieira, 2013). After all, baseball simulation's immediate environment is being mediated by technology and simulation users should take all of it in. In the current study, it is essential to know the baseball simulation users’ sensory experience so as to grasp what level of quality the experience holds for them.

According to Ahn (2020), the number of participants in Korean recreational baseball has increased to 383,000 spread across 12,500 teams. Those numbers notwithstanding, baseball does not even rank in the top 10 of Korean participatory sports and leisure activities (Korean Ministry of Culture, Sports and Tourism, 2021). Regarding baseball simulation, Korea's market size is estimated to be, as of 2020, approximately US$850 million (Kim, 2018). This incompatibility between the baseball simulation market and baseball participants suggests that researchers should develop systematic approaches to knowing how baseball simulations can play a role in furthering Koreans’ baseball participation. Baseball simulation's popularity is a phenomenon unique to Korea, so it provides a distinct opportunity to understand how baseball simulation users’ technology-mediated sensory experience can further their baseball participation.

Study purpose

The purpose of the study is to identify whether the sensory experience of baseball simulation users will motivate them to participate in actual baseball games. The study focuses on simulator users’ visual, aural, and tactile stimuli, all of which in simulation are prevalent. As for outcomes from perceiving the stimuli, the study focuses on simulation users’ interest in baseball, athletic identity, and intention to play baseball on the field. Specifically, the study aims to find how simulation users’ three outcomes differ by degree of each sensory stimulus. Guiding the study is the following research question:

RQ: How do three characteristics of baseball simulation participants – interest in baseball, athletic identity, and intention to play baseball on the field – differ by level of visual, aural, and tactile stimuli?

Researchers have applied the S-O-R model to various contexts, ranging from retailing (Liang & Lim, 2021) to virtual media consumption (Eroglu et al., 2003; Peng & Kim, 2014; Thomas & Mathew, 2018). What distinguishes the current study from these studies is a computer-mediated simulation's dual environments that urge its users to interact with a virtual environment as well as an immediate physical one. Applying the model to dual environments will reveal a new dimension of how sport consumers interact with different types of environments in their sensory experience.

Understanding users’ sensory experience helps baseball simulation franchises design and customize programs that can deliver quality experiences to in-shop users. Also, having knowledge of how simulation users intend to participate in baseball, baseball marketers are better able to develop various cross-promotions to expand its market size. By revealing the intersection between baseball simulation experience and baseball participation, the current study's practical implications will be implemented toward baseball simulation's promoting participation in baseball.

Literature review

S-O-R model

By including three factors, the Stimulus(S)-Organism(O)-Response(R) model theorizes how consumers interact with various stimuli in their immediate environment (Mehrabian & Russell, 1974). Specifically, the Stimulus conceptualizes the environment's various stimuli that stimulate consumers’ sensory organs. For example, it can be physical features of a retail environment, such as products display, store color, or particular scent. Also, marketing or promotional activities can generate the environment's stimuli. In being exposed to different types of stimuli (whether natural or technology-mediated), consumers’ stimuli sensitivity is an activation in which consumers’ sensory receptors (i.e. five senses) stimulate their neurons (Peck & Childers, 2008). This mechanism varies from person to person, resulting in inter-individual and – group variances in responding to external stimuli.

The Organism refers to how consumers psychologically treat their stimuli perception. Consumers’ two platforms – cognition and affect – are activated to treat stimuli internally. A prime indicator of the cognitive process is consumers’ satisfaction with the experience, particularly in retail and entertainment settings (Caro & García, 2007; Oliver, 1980; Yoshida & James, 2010). On the other hand, consumers’ arousal or pleasure reflects their affective status (Das & Varshneya, 2017; Kwak et al., 2011). As to how sport consumers process sensory stimuli, Chung et al. (2015) found that their perceptions of stimuli lead to satisfaction or arousal according to the stimuli's characteristics. This finding suggests that sport consumers’ perception of stimuli and their treatment of it internally is reflective of the stimuli's nature.

The S-O-R model's last factor is the Response. This factor indicates consumers’ behavioral outcomes caused by how they internally react to the magnitude and quality of their feeling. As for a behavioral outcome, a substantial body of consumer behavior studies (Chung et al., 2015; Kim et al., 2020; Kim & Lennon, 2013) adopts consumers’ intentions to purchase products and services. The intention is based on consumers’ current consumption experience, indicating how likely they are to buy or use products and services next time.

The S-O-R model possesses several theoretical merits for sport simulation users’ behavioral setting in which users work as acting agents to perceive and process sensory stimuli. First, by seizing on the stimuli in simulation users’ immediate environment, the model is able, after all, to conceptualize a variety of sensorial components. Thus, sport scholars can capture the effect of the surrounding environment on simulation users’ stimuli perception and their consequential outcomes Second, sport simulation users’ in-experience variables are inevitable and diverse because they should experience various sensory stimuli to proceed with a programmed game. The model's sequential process well captures those in-experience characteristics, such as psychological and behavioral variances.

Sport simulation users’ sensory experience

When simulation users are exposed to various stimuli in their immediate environment, their sensory organs (i.e. five senses) work as receptors. Simulation users thus become sensualized in a process called stimuli sensation (Foley & Bates, 2019). When simulation users are aware of the sensation, they identify the type and quality of the stimuli according to the sensation. This process is stimuli perception (Foley & Bates, 2019). Simulation users’ stimuli perception affects their cognitive and affective responses, influencing their behavioral outcomes (Foley & Bates, 2019). Simulation users’ stimuli perceptions vary according to the stimuli's evaluated quality and magnitude. Also, simulation users’ individual factors, such as prior sensory cues, affect their ability to interpret the stimuli (Chung et al., 2016).

A sport simulation provides its users with a technology-mediated environment in which a computer's program mediates all sensorial stimuli. While the mediated environment consists of diverse stimuli, simulation users are not always affected by all of it. Instead, to perceive the stimuli, simulation users tend to rely on only a few preferred senses. These perceived stimuli that are prevalent overshadow other minor stimuli. To explain this dynamic, Steuer (1992) suggested the concept of situational stimuli, which refers to the environment's certain stimuli that are dominantly loaded on simulation users’ sensory receptors. For example, baseball simulation users see a moving ball and various visual features projected on the screen. They hear various sounds originating with other participants or computer programs. Lastly, to play the programmed game, they grip and hold a bat to swing. While playing, their senses of smell and taste stay dormant. To better understand the characteristics of baseball simulation users’ experience, the current study focuses on the simulation's situational stimuli – visual, aural, and tactile.

Sport simulation users’ interest, athletic identity, and participation intention

Consumers’ interests in products and services reflect their motivation to actually consume. According to Hidi and Renninger (2006), a person's interest is a psychological and semi-stable construct in which two different statuses manifest a person's curiosity. One is a person's dispositional tendency to engage in the object of interests over time, which is called individual interest. The other is situational interest, a transient and temporal status evoked by contextual stimuli in the environment. This type of interest may be fleeting but specific to the context because it is aroused by perceiving situational stimuli in the simulation. For example, if baseball simulation users are excited and entertained by the stimuli, they would be interested in knowing more about the object of the stimuli, such as the history, news, and culture surrounding baseball. Therefore, the current study sets forth the following hypotheses:

H-1a/b/c: Does a group of baseball simulation users high in visual, aural, and tactile sensations have a greater interest in baseball than a group low in those qualities?

Athletic identity refers to one's tendency to identify oneself as an athlete (Brewer & Petitpas, 2017). Based on social identity theory (Tajfel & Turner, 1985), athletic identity concerns how an individual shapes a self-concept regarding a specific sport. People's athletic identity works as a social agent in which they interact with others and affiliate themselves with others. Also, athletic identity helps people interpret information and behave according to their role as an athlete. Some studies (Anderson, 2004; Anderson et al., 2009; Brewer & Petitpas, 2017; Lament-Mills & Christensen, 2006) have found that people's athletic identity impacts the likelihood of their participating in sport activities – the more developed their athletic identity, the more they tend to participate in sport activities.

Baseball simulation's surrounding environment mimics the stimuli that baseball participants can experience on the field. Also, baseball simulation provides its users with hands-on batting experience that facilitates their motivation to bat on the field. Baseball simulation's stimuli make its users play the role of a baseball player as if they were on the field. This role-play situation helps simulation users identify with baseball players. Therefore, it seems that baseball simulator users who experience quality sensory stimuli will identify with being a baseball player on the field. The current study tests the following hypotheses:

H-2a/b/c: Does a group of baseball simulation users high in visual, aural, and tactile sensations have a greater athletic identity than a group low in those qualities?

The S-O-R model (Mehrabian & Russell, 1974) suggests that the degree of consumers’ behavioral intention is a consequence of how aroused, pleased, or satisfied consumers are with their experience. In this vein, baseball simulator users who experience quality stimuli in the mediated environment may long for perceiving more genuine and authentic stimuli. Therefore, simulator users’ willingness to transit their quality simulation experience to their actual participation is specified as their intentions to participate in baseball on the field (cf. Potwarka et al., 2020). Simulation users’ intentions to participate in baseball specify future behaviors outside their existing behaviors. Lastly, the following hypotheses are suggested:

H-3a/b/c: Does a group of baseball simulation users high in visual, aural, and tactile sensations have a greater baseball participation intention than a group low in those qualities?

Method

Baseball simulation context

A typical retail setting for baseball simulation is an indoor space containing three or four batting rooms. Each room consists of two areas – one for batting and the other for waiting, where participants can sit, have refreshments, and cheer on other participants. For safety purposes, these areas are separated by fixed iron nets.

In the batting cage, the simulation screen is placed approximately 32 feet or 60 feet from a home plate. An actual baseball is launched through a hole in the screen, appearing to emerge from the throwing arm of a pitcher projected on the screen. A batter at the plate can then hit this ball. Prior to taking their position at the plate, the batter can, at a kiosk in the waiting area, choose the ball speed and pitch types; when ready for the pitch, the batter steps on a pedal.

The cage is equipped with sensors to analyze the spins, speed, and trajectory of a hit ball and then declares its relative success (i.e. home run, base hit, or foul ball). According to the simulated ball trajectories, the simulation tallies such data as hits, scores, and outs as well as positions of the infielders and outfielders.

In the baseball simulation, visual, aural, and tactile stimuli are situational. Various visual stimuli are generated – a ball launched from the screen, various features and artifacts projected on the screen, and decorations surrounding the simulation. The sense most heavily stimulated is the aural; other participants cheer and converse, a ball bounces off the wall, and computer-generated game sounds. To proceed with the simulation, simulation users should hold and grip a bat, swinging it to hit the ball. All these kinetic movements make simulation users perceive tactile stimuli in their upper limbs. All these stimuli are ineluctable parts of the simulation; simulator users’ perceptions of olfactory and gustatory stimuli depend on their selection to consume ancillary services, such as food and drinks.

Data collection and samples

For data collection, the researcher contacted a leading baseball simulation franchise in Korea. With the company's permission, the researcher randomly selected two locations in Seoul for on-site surveys. At each location, one investigator approached shop visitors as they checked in, asking them to participate in the survey. If they consented, the investigator provided paper surveys and asked them to begin the survey after their first at-bat. The participants were able to proceed with the survey as they waited for their next at-bat. In this way, the participants were able to instantly recall their in-the-moment feelings and experiences. The investigator stayed nearby to answer any questions during the survey. The data collection continued over three months.

Using a self-administered survey, 345 respondents responded to the items. Of them, 136 respondents (39.4%) played or were currently playing baseball in recreational leagues. The study excluded the group having prior baseball participation experience because the simulation's role would be evident for those users having no prior experience playing baseball. The rest (n = 209, 60.6%) had never played baseball on a field, consisting of 192 males (91.9%) and 17 females (8.1%). Their average age was 31.7 (SD = 5.75), ranging from 19 to 49 years old.

Measures

Regarding the in-the-moment perception of sensory stimuli during the experience, participants were queried about each stimulus in terms of the perceived sensualization of a specific item on a corresponding sensory organ. Previous studies regarding sport spectators’ sensory experience (Chung, 2020; Chung et al., 2015, 2016) were benchmarked. The items pertaining to athletic identity were developed based on the studies of Anderson (2004) and Brewer and Petitpas (2017). The items regarding interests in baseball were developed from the studies of Hidi and Renninger (2006) and Chung et al. (2019). Lastly, the items of baseball participation intention were adopted from Kim (2013).

All the questions were asked on a seven-point, Likert-type scale, ranging from 1 (not at all) to 7 (very much). Adopted English items were translated into Korean through the translation and back-translation technique to maintain the linguistic equivalence (Su & Parham, 2002). To accommodate the context of baseball simulation, the researchers slightly adjusted the wording of the adopted questions. Reviewing the items were one Korean sport management faculty member and one professional from the baseball simulation franchise, neither of whom was involved in the study. Table 1 explains the descriptive statistics and reliabilities of all the questions.

Table 1. Items’ descriptive statistics and reliabilities.

Construct (Cronbach's α)	Item “To what degree do (are) you” (Mean/Standard Deviation)	Item-total correlations	Inter-item correlations
Visual Stimuli (.82)	See athletes’ information? (3.69/1.78)	.68	.48
	See a pitcher's motion? (4.77/1.56)	.61
	See stadium background? (4.15/1.66)	.68
	See outfielders’ motion? (3.63/1.77)	.58
	See a ball launched? (5.26/1.55)	.54
Aural Stimuli (.83)	hear batting? (5.53/1.26)	.68	.52
	Hear ball bounced? (5.37/1.31)	.65
	Hear net hit by ball? (4.63/1.67)	.29
	Hear simulation's promotion? (4.83/1.47)	.40
	Hear people's cheering? (5.35/1.41)	.47
Tactile Stimuli (.77)	Feel a hit on arms? (5.59/1.34)	.55	.45
	Feel bat grip on hands? (5.46/1.33)	.64
	Feel glove on hands? (4.08/1.99)	.33
	Feel swing on arms? (5.25/1.35)	.64
Interest in Baseball (.93)	Interested in baseball information? (4.45/1.42)	.83	.78
	Interested in baseball knowledge? (4.42/1.48)	.87
	Interested in baseball culture? (4.48/1.43)	.85
	Interested in baseball news? (4.40/1.49)	.81
Athletic Identity (.93)	Identity yourself with a baseball player? (3.86/1.68)	.89	.82
	Identity yourself with a hitter? (4.07/1.65)	.88
	Identity yourself with a famous player? (3.46/1.66)	.79
Intention to Play Baseball (.93)	Intend to participate in baseball games? (3.96/1.49)	.82	.78
	Intend to participate in baseball practices? (4.17/1.47)	.89
	Intend to participate in baseball lessons? (4.14/1.56)	.85
	Intend to play baseball with others? (4.14/1.50)	.83

Data analysis

The researcher categorized each sensory perception into high and low groups, using each perception's mean. This group-splitting is quite logical, so the inferential statistics may not be powerful. Nonetheless, the split groups still represent the same group of populations: simulation users who lack experience playing baseball. The samples’ grouping by the mean split is inevitable to convert a continuous variable into a categorical variable.

On multivariate analysis of variance (MANOVA), the simulator users’ interest in baseball, athletic identity, and intention to play baseball on the field were compared with two groups of each sense. An analysis of variance (ANOVA) uses categorical predictors to explain the level of variability in continuous outcome variables, finding constructs’ linear relations (Christensen, 2016). Therefore, ANOVA was deemed appropriate for finding how the dependent variable changes in each sense, especially when MANOVA's results are significant. Interaction effects were also secured.

Results

In three-way MANOVAs, no significant difference was found in dependent variables on the group of visual stimuli, F(3, 199) = 2.11, p = .10, Wilk's Λ = 0.97. However, significant differences were found in dependent variables on the group of aural stimuli, F(3, 199) = 4.95, p < .01, Wilk's Λ = 0.93, partial η² = 0.07, and on the group of tactile stimuli, F(3, 199) = 6.30, p < .001, Wilk's Λ = 0.91, partial η² = 0.09.

In the following ANOVA on the group of visual stimuli, only participants’ interests in baseball were found to be different (H-1a accepted), F(1, 201) = 4.22, p < .05, partial η² = 0.02. The participants’ high perception of visual stimuli resulted in their high interest in baseball. Specifically concerning the mean score of the participants’ interest in baseball, the group of high visual stimuli was 0.4 higher than the low of low visual stimuli.

On the group of aural stimuli, participants’ interests in baseball were also found to be different (H-1b accepted), F(1, 201) = 13.53, p < .001, partial η² = 0.06. The participants’ high perception of aural stimuli related to their high interest in baseball. Concerning the participants’ interest in baseball in particular, the group with a high aural stimuli perception scored 0.72 higher than the group with a low aural stimuli perception.

On the group of tactile stimuli, the participants’ athletic identity and their intentions to play baseball on the field were found to be different (H-2c & H-3c accepted), F(1, 201) = 13.57, p < .001, partial η² = 0.06 and F(1, 201) = 13.26, p < .001, partial η² = 0.06, respectively. These results indicate that the participants’ high perception of tactile stimuli impacted their high degree of athletic identity and baseball participation intentions. The degree of athletic identity was .88 higher for the group with high tactile stimuli than that with low tactile stimuli. Also, the participation intention of the group with high tactile stimuli was .75 higher than the group with low tactile stimuli. Table 2 reports each group's sample size and their marginal mean differences.

Table 2. Groups’ marginal means and standard error.

	Visual Stimuli		Aural Stimuli		Tactile Stimuli
	High (n = 107)	Low (n = 102)	High (n = 108)	Low (n = 101)	High (n = 109)	Low (n = 100)
Interest in Baseball	4.62 (.14)	4.22 (.14)	4.78 (.14)	4.06 (.14)	4.57 (.14)	4.27 (.14)
Athletic Identity	3.72 (.17)	3.87 (.17)	3.85 (.17)	3.74 (.17)	4.24 (.17)	3.36 (.17)
Participation Intention	4.11 (.15)	3.88 (.15)	4.12 (.15)	3.87 (.15)	4.37 (.14)	3.62 (.15)

Note: Bold and italic cells suggest significant difference at .005 level.

Regarding interaction effects, the groups of aural stimuli and tactile stimuli significantly interacted on baseball participation intentions (p < .05).

Discussion

The current study examined the degree of perceiving visual, aural, and tactile stimuli among baseball simulation users and compared simulation users’ interest in baseball, athletic identity, and baseball participation intentions according to the degree of each stimuli perception. The results revealed that simulation users who perceived high stimuli on their visual and aural senses had a higher interest in baseball than those who perceived low stimuli on both senses (H-1a & H-1b accepted). Also, simulation users with a high perception of their tactile sense were found to possess a higher athletic identity and greater intention to play baseball than those who perceived low stimuli on the sense (H-2c & H-3c accepted).

In the current study, simulation users simultaneously interacted with dual environments – virtual and physical environments. Simulation users’ visual and aural stimuli primarily concern corresponding sensory components featured in the virtual environment. The current study's tactile stimuli, in contrast, featured the physical environment, consisting mainly of simulation users’ kinetic movements. As simulation users proceed with a game by gripping and swinging a bat, it seems that the stimuli's loading becomes prevalent in their tactile sense. Therefore, as found in H-2c and H-3c, simulation users’ perception of non-mediated stimuli originating from their physical environment tends to lead them to developing their athletic identity and increasing their intentions to participate in the sport. The current study reveals that one's tactile sense plays a crucial role in furthering a simulation users’ intention to play baseball.

A substantial body of studies (Arias et al., 2011; Dionisio et al., 1997; Gonçalves et al., 2019; Huisman, 2017) has attempted to find the role of tactile stimuli in creating quality virtual experiences. Most approaches aim to apply haptic technology to the user experience to know how users can feel the object's surface, force, and vibrations in the virtual environment (Sreelakshmi & Subash, 2017). Also, those studies have tried to identify how technology users’ haptic sense interacts with other senses in their virtual experience. The current study finds a significant interaction effect between tactile and aural stimuli on simulation users’ participation intentions. That is, baseball simulator users’ participation intentions reflect not only the quality of the simulator users’ tactile stimuli but also the dynamics of tactile and aural senses.

While simulation users’ tactile stimuli further their tendency to participate in baseball play, the visual and aural stimuli are effective only at arousing situational interest in baseball (H-1a & H-1b). Considering the nature of the two stimuli, the stimuli emanating from the virtual environment do not directly trigger an intention to play actual baseball. Chung et al. (2016) examined the dynamics of sport spectators’ five senses and their different reactions. In the study, while sport spectators’ visual and aural stimuli affected their cognitive aspect, their affective aspect was impacted by gustatory and tactile stimuli. Sport spectators’ olfactory stimuli influenced both areas. That is, sport consumers’ stimuli perceptions are irregular, depending on specific qualities and types of stimuli. In this vein, the current study's multi-dimensional context characterizes how technology-mediated and non-mediated stimuli work differently for sport simulation users’ experience.

Jacoby (2002) argued for reconceptualizing the S-O-R model, considering the shared areas among stimuli, organism, and response factors. In addition, Jacoby claimed that the S-O-R model should include the environment's multi-dimensionality to seize on consumers’ complexity. The current study tries to capture how sport simulation users selectively interact with their immediate but separate environment from the S-O-R model's perspective. As technology advances, people consume sports in diverse contexts and their sport-consuming experience becomes more dynamic. This claim is confirmed by the current study's findings that sport-simulation users react differently to a respective environment. The study's findings suggest a theoretical shift from a single view of processing sensory stimuli to the dimension of how sport consumers perceive and process stimuli in interacting with multiple environments.

The concept of Experience Economy (Pine & Gilmore, 1998, 1999) suggests that sport consumers seek out a quality experience. Playing an essential role in the design and delivery of sport consumers’ quality experiences is technology. As technology advances, sport consumers’ sensory experience is becoming more specific and diverse. Sport simulation is an emerging platform in which consumers enjoy a sporting experience mediated through technology. Given sport simulations’ various purpose-driven utilizations from casual visitors’ entertainment to elite athletes’ off-field practices, the current study endeavors to find how sport simulation users’ sensory experiences relate to their in-experience characteristics that indicate their tendency toward sport participation. Knowing this becomes so important, especially for the intersection between sport and technology, as sport consumers’ experience economy evolves with technology's driving force.

In business development, one market's increased needs create another market (Kim & Mauborgne, 1999). As sport simulations are being positioned, especially in Korea, into a new type of sport-and-leisure activity, the number of sport participants corresponds with the simulations’ growth. In Korea, for example, the growth in the number of golfers has been accelerating (approximately 5.15 million as of 2021; according to Seo, 2021); some attribute the growth to the country's lucrative golf simulation market (estimated to be US$882 million in 2017 according to Asian Golf Industry Federation, n.d.). Understanding this linkage between sport simulations and sport participants is crucial to facilitating sport participation, especially for young people. Several sport organizations face declining numbers of young participants at the grassroots level. Baseball is one of them (Aspen Institute, n.d.). Given the young people's pro-technology and experience-oriented characteristics, a more rigorous understanding of baseball simulation's sensory stimuli reveals one aspect of how to revert the decrease.

Practical implications

Sport simulation users should engage in kinetic movements (for example, swinging, kicking, or throwing) to proceed with simulated game mechanics, and inherent to those activities are tactile stimuli. Also, sport simulations are becoming equipped to specify more various haptic senses, such as heading a soccer ball and swinging with a stick. Therefore, sport practitioners should focus on enhancing the decisive role of simulation users’ haptic sense in their simulation experiences. For example, to enhance simulation users’ tactile stimuli perception, simulation program developers can specify gloves with sensors to strengthen the feeling of swinging a bat and the impact of hitting a ball (see Robertson, 2021).

Two significant utilities of sport simulations are their mobility and versatility. Sport practitioners can stage sport simulations in various forms, such as on-site activations or retailing shops. In doing so, sports practitioners could set up the simulation on and around sporting events to facilitate the connection between sport simulation users’ experience and their further commitment to the sport. In addition, several sport ventures organize simulation sport leagues not only for sporting competitions but for the attendant social benefits (see Cohen, 2020). Facing the influx of sport simulation industry, the current study's findings would be implemented toward various chances to connect simulation users’ experience with their actual sporting experience.

Limitations and future studies

At a certain point in their simulation, baseball simulation users were asked about their perception of stimuli and in-experience characteristics. However, the researcher could not control how long simulation users were exposed to the stimuli. In the on-site survey, this limitation was unavoidable if the simulation users’ leisure time was to be respected. Future studies should consider the stimuli's duration in data collection because stimuli that is prolonged can substantially change the way people perceive it (Jacoby, 2002). Data collection in a laboratory setting can include the stimuli's temporal factor. In such a controlled context, researchers could measure simulator users’ experience at intervals to reflect the effect of the stimuli's familiarity with the time as well as manipulate the stimuli's intensity for more diverse within-subject experiment designs.

It should be noted that simulation users’ in-experience characteristics might not be the outcomes of stimuli perception. Indeed, they may be the cause of perceiving different degrees of stimuli. The aim of excluding from data analysis simulation users who had played baseball was to neutralize study samples from any pre-held characteristics. In this way, the current study aligns with the stimuli's causal processing and its genuine effects. Future research could design an experimental study to manipulate stimuli in such a way to secure a one-way, causal effect of stimuli on simulation users’ in-experience characteristics.

Another limitation is that the study measured not simulation users’ actual behaviors but dispositional factors that may cause actual behaviors. Also, simulation users’ actual behaviors might be determined by several other influences excluded from the study. Therefore, the current results are, to some degree, restricted in their ability to predict how simulation users’ sensory experience is connected to their behavioral indicators that are toward sport development. Future studies should consider measuring indicators that explain actual sport behaviors, such as the degree of sport participation or the volume of sport consumption.

Conclusion

As technological advances convey diverse and high-quality sensory stimuli, sport simulation users can take in more diverse and authentic stimuli. The current study has attempted to determine whether baseball simulation users’ sensory experience motivates them to go out and play actual baseball. For this aim, the study tested how Korean baseball simulation users’ interests in baseball, athletic identity, intentions to participate in baseball differed by the degree of visual, aural, and tactile stimuli perceptions. The study found that baseball simulation users’ tactile sense affected their athletic identity and baseball participation intentions. This finding suggests the tactile sense can have a powerful impact on simulation users’ further commitment to baseball. Sport simulations’ multi-dimensional environments serve as a platform where simulation users can develop their characteristics toward sport development. This technology-driven sport platform projects the future aspect of sport participation.

Disclosure statement

No potential conflict of interest was reported by the author(s).