Exploring Intention & Reactance in Social Norm Interventions for Rail Business Travel

2.1 Theoretical explanations of business travel mode choice

Consumer behavior is one of the best-studied domains in the field of tourism (Cohen, Prayag, & Moital, 2014). There is a particular focus on decision-making behavior, as reflected in the large number of related publications (Sirakaya & Woodside, 2005). Examples include expected utility theory (Von Neumann & Morgenstern, 1947), satisficing behavioral theory (Simon, 1956), the influential theory of reasoned action (Ajzen & Fishbein, 1980), and the derived TPB (Ajzen, 1991). In this article, we draw on TPB because the model has been successfully tested in various contexts and disciplines, including the study of sustainable behaviors in the tourism and transportation sciences (Li, Nguyen, & Coca-Stefaniak, 2020; March & Woodside, 2005). A few examples include travelers’ general travel intentions (Park, Hsieh, & Lee, 2017; Quintal, Lee, & Soutar, 2010; Tsai, 2010; Yuzhanin & Fisher, 2016), predicting low-carbon tourism behavior (Kuo & Dai, 2012), transportation mode choice (Bamberg, Ajzen, & Schmidt, 2003; Bamberg & Möser, 2007; Chen & Chao, 2011), sustainable modal choices (Morten, Gatersleben, & Jessop, 2018), and specifically the impact of behavioral interventions on travel behavior (Parker, Stradling, & Manstead, 1996).

The TPB states that human actions are guided by three types of beliefs: behavioral beliefs (outcomes of the behavior), normative beliefs (others’ expectations), and control beliefs (factors that facilitate or impede the behavior). These beliefs shape individuals’ attitudes, perceived social pressure (subjective norm), and perceived behavioral control (PBC), which in turn affect behavioral intentions (Bamberg et al., 2003). Thus, Ajzen’s (1985, 1991) basic assumptions are that people engage in a behavior when they believe it will lead to a desirable outcome, their relevant peers value and approve of it, and they have the necessary skills, resources, and opportunities to engage in that behavior. Regarding the last point, a sufficient degree of autonomy or self-determination is a prerequisite for applying the theory in the case of business travelers (premise 3 is violated if low-carbon travel modes do not exist or cannot be chosen). Vis-à-vis continental business travel, a high degree of autonomy can be assumed in many cases (Higham, Hopkins, & Orchiston, 2019; Kesselring & Vogl, 2010; Wickham & Vecchi, 2010) so that the TPB can be applied similarly to mode choice in a leisure context.

2.2 Social norm interventions and low-carbon business travel mode choices

Business travel is often institutionalized and normalized (Gustafson, 2014; Hopkins et al., 2019; Unger, Uriely, & Fuchs, 2016) and, as occurs with leisure travel (Juvan & Dolnicar, 2014), Lassen (2010), describes the discrepancy between pro-environmental attitudes and (business) traveler behavior. Even though COVID-19 challenged business travel behaviors, voluntary sustainable behavioral change among business travelers is considered unlikely, highlighting the need for institutional-level measures (Cohen, Hanna, & Gössling, 2018; Lassen, 2010; Poggioli & Hoffman, 2022; Thaller et al., 2021). Therefore, organizational support for implementing low-carbon policies is crucial for persuading business travelers to switch to sustainable modes of transportation (Gössling et al., 2023). While the acceptance of restrictive policies for modifying travel mode choice is questionable (Douglas & Lubbe, 2010; Drews & Van den Bergh, 2016; Müller, 2023), low-coercive measures using persuasion or information provision (Bamberg et al., 2011; Fujii & Taniguchi, 2006) are a promising means of encouraging travelers to switch voluntarily from carbon-intensive air travel to low-carbon rail travel (European Environment Agency, 2021; Flügel, Fearnley, & Killi, 2019).

With regard to modal shift, travel time seems to be an especially important driver of (dis)satisfaction with business rail travel and may substantially impact employee acceptance and behavior (Chapuis et al., 2023; Jacobson, 2022; Robèrt, 2009). While some travelers prioritize minimizing travel time, others value the opportunity for productive work time (Dällenbach, 2020; Lyons, Holley, & Jain, 2008). Long travel times may discourage employees from using alternative modes of transportation, leading to low adoption rates and reducing the effectiveness of sustainable travel policies. Despite the importance of the topic, little is currently known about how companies can most effectively influence a modal switch in consideration of travel time. Understanding the behavioral interventions applicable to business travelers is an exciting avenue of research, and the latter may be a relevant approach in many organizations in opposition to coercive policies.

Bamberg et al. (2003) conclude that “choice of travel mode is largely a reasoned decision” (p. 175) – consequentially, “this decision can be affected by interventions that produce change in attitudes, subjective norms, and perceptions of behavioral control” (p. 175). Despite the long tradition of research on sustainable tourism, Demeter, Fechner, and Dolnicar (2023) were able to identify only a few intervention-based experiments in this area, which is surprising as Steinmetz et al. (2016) also emphasize the utility of TPB for designing interventions for numerous behaviors. A variety of behavioral interventions can be used to encourage the choice of low-carbon transportation for business travel. These can target all of the antecedents of the variables defined in the theory of planned behavior, namely behavioral beliefs, normative beliefs, and control beliefs (Ajzen, 2006, 2011; Fishbein & Ajzen, 2010).

Influencing social norms is a popular way to attempt to influence behavior (Yamin et al., 2019). Such interventions focus on changing normative beliefs, which are beliefs about what others think one should do (Ajzen, 2006). Demonstrating what others actually do (descriptive social norms) has been shown to have consistent effects on behavior (Farrow, Grolleau, & Ibanez, 2017; Grilli & Curtis, 2021; Kormos, Gifford, & Brown, 2015) and is more effective than informing about expectations (Ru et al., 2018). In a tourism context, various applications are conceivable (Dolnicar, 2020). Hotels have received the most attention, in relation to which behavioral changes concerning towel use (Goldstein, Cialdini, & Griskevicius, 2008), room cleaning (Dolnicar, Knezevic Cvelbar, & Grün, 2019), and buffets (Dolnicar, Juvan, & Grün, 2020) have been the focus of successful social norm interventions. Mode choice, too, has been the subject of intervention studies, particularly in the context of commuter mobility (Hunecke, Blöbaum, Matthies, & Höger, 2001; Klöckner & Matthies, 2004). Potential interventions might include highlighting the increasing trend to low-carbon mode choice or promoting the social status of sustainable travel.

In summary, targeting the normative beliefs of business travelers may increase the likelihood of adopting low-carbon transportation. This can help organizations support sustainable travel behavior. However, behavioral interventions may not always be successful. For example, social norms may have no effect if the target group is indifferent or opposed to them (Sunstein, 2017). Complex or confusing information conveyed through disclosure or educative nudges often has less impact than anticipated (Willis, 2011). For strongly habitual tourist behavior, information provision alone may be insufficient to prompt behavior change (MacInnes, Grün, & Dolnicar, 2022). Last, one particular concern for organizations is the risk that individuals may react adversely to attempts to modify behavioral interventions (Müller, 2023).

2.3 Reactance to behavioral interventions

The literature provides limited insight into the role and significance of reactance in business travel policies or interventions that aim to influence behavior. It also largely fails to address the effectiveness of such interventions. Regarding changing business travel practices, resistance is common (Poggioli & Hoffman, 2022). Although personal norms and a sense of responsibility support work policies that reduce flying (Whitmarsh et al., 2020), business travelers generally prefer low-coercive measures that leave their decision-making autonomy intact (Kreil & Stauffacher, 2021). Despite recent studies that have shown no direct link between business air travel and professional success (Schaer, Jacot, & Dahinden, 2020; Seuront, Nicastro, & Zardi, 2021; Wynes et al., 2019), and while the COVID-19 pandemic has permanently challenged the assumption that business travel is a necessity (Becken & Hughey, 2021; Parsons, 2022; Poggioli & Hoffman, 2022; Rowan Kelleher, 2022), companies may avoid implementing measures because they are concerned about negative employee responses (Müller, 2023).

Such feared adverse employee reactions may be explained by reactance theory. Reactance is a negative emotional response that is caused by a loss or threat to behavioral freedom (Brehm, 1966, 1972; Brehm & Brehm, 1981). Psychological reactance theory predicts that individuals value their perceived freedom of choice and react with an adverse state of arousal when this freedom is threatened or eliminated. They then focus on restoring their freedom (Brehm, 1966, 1972; Brehm & Brehm, 1981). Reactance is operationalized as a composite of anger and negative cognition (Dillard & Shen, 2005; Liang, Kee, & Henderson, 2018). It can even occur when individuals feel pressured by attempts at manipulation or persuasion (Heilman & Toffler, 1976). Addressing the phenomenon of reactance enhances the accuracy of predictions about behavior (Orbell & Hagger, 2006).

For corporate travel, the theory suggests that when the perceived threat to the freedom to travel for business increases, the intensity of reactance will increase and travelers will mobilize resources to restore their ‘right’ to travel (Font & Hindley, 2017). The existence or non-existence of reactance in the case of organizational influence on the business travel behavior of employees may substantially impact the willingness of companies to take measures, the design of the latter, and, ultimately, emissions reductions. Therefore, a better theoretical understanding of the impact and effects of business travel interventions is of major practical relevance and highlights the need for further research.

3.1 Study 1

3.2 Study 2

3.2.1 Hypotheses formulation

To answer our research questions, we formulated hypotheses and conceptual models (Figure 2). These are based on both the literature discussed in section 2 and the results from study 1, and were tested and evaluated using one-way ANOVA and additional univariate analysis of variance to test for interaction effects.

Hypothesis 1 (H1) is grounded in the premise that showcasing business rail travel as the norm – i. e. illustrating what fellow business travelers commonly do – is anticipated to exert a more significant influence on business travelers’ intentions to choose rail, compared to conveying expectations. This aligns with the established effectiveness of descriptive social norms, where peer behavior can wield considerable influence on individual choices (Farrow et al., 2017; Grilli & Curtis, 2021; Kormos et al., 2015). Drawing on the work of Ajzen (1985, 1991); Bamberg et al. (2003) we emphasize the impact of normative beliefs in the context of business travel mode choice, recognizing the nuanced dynamics of social influence among business travelers.

H1: Social norm treatments …

1. … strengthen normative beliefs about taking the train for business travel.

2. … strengthen subjective norms about taking the train for business travel.

3. … strengthen behavioral intentions about taking the train for business travel.

Hypothesis 2 (H2) builds on the premise that business travelers highly value reducing travel time, which they perceive more negatively as it increases. In the context of business travel, efficiency is crucial, and longer travel times, such as those resulting from substituting air travel with rail, are expected to amplify reactance. This expectation stems from reactance theory, which suggests that negative emotional responses intensify when perceived manipulations threaten valued aspects of behavior, such as minimizing travel time for business purposes (Brehm, 1972; Brehm & Brehm, 1981). Moreover, addressing reactance is found to enhance the accuracy of predictions about behavior (Orbell & Hagger, 2006). This renders reactance a crucial factor in understanding the potential resistance to social norm interventions, especially for longer rail journeys.

H2: Social norm treatments …

1. … increase the perceived threat to freedom.

2. … increase reactance.

Figure 2:

Hypothesized individual models for the effect of the treatment

Additionally, we formulated a set of hypotheses (H3) to investigate the influence of travel time on the effectiveness of social norm interventions. Hypothesis 3 (H3) leverages insights from Dällenbach (2020) and Gustafson (2012b), contextualized within the dynamics of business travel discussed with regards to H2. For longer business trips, we anticipate a weaker intention to choose rail, heightened perceived threat to freedom, increased reactance, and a smaller effect of social norm interventions on intention. This is again informed by the unique challenges and considerations associated with business travel, where time sensitivity and individual preferences play pivotal roles in mode choice.

H3: For longer business trips …

1. … the intention to travel by train is weaker

2. … the perceived threat to freedom is stronger

3. … reactance is stronger

4. … the effect of the social norm intervention on intention is smaller

4.1 Determinants of behavioral intention and reactance

First, we were interested in the general determinants of behavioral intention, perceived threat to freedom, and reactance in the overall sample. Participants had strong intentions to travel by train for business travel, with means of 5.69 and 5.09. On the other hand, they demonstrated low reactance to the social norm message we presented, with mean scores of 2.81 and 2.84, and perceived a minimal threat to their freedom, with means of 2.62 and 2.64. The error bars in the bar charts represent the standard error of the mean. The duration of the business train trip led to significant (p<0.001) differences in intention but not in reactance or perceived threat to freedom (Figures 3 and 4). Consequentially, we accept hypothesis H3a and reject H3b and c. Additionally, the analysis highlighted significant variation within the overall sample based on various controls.

Figure 3:

Means for 4h and 8h conditions

Figure 4:

Significant overall differences in intention by trip duration

Past behavior

After performing mean splits, variables related to past behavior (recency, frequency, and mode choice preference) significantly influenced both intention to travel by train and reactance to the social norm message (Figure 5). Individuals with more recent and frequent similar trips in the last six months showed stronger intention (p<0.001) and less reactance (p<0.001), though the perceived threat to freedom showed marginal significance (p=0.063). Mode choice history also impacted intention, notably with significant differences between those favoring trains for over 50 % of their continental trips versus others. Frequent train users exhibited lower levels of reactance and perceived threat to freedom (p<0.001). Frequency of continental business trips did not affect intention significantly (p=0.445), but those with lower frequency showed stronger reactance (p<0.001) and perceived greater threat to freedom (p=0.002) compared to frequent travelers. Notably, frequent business travelers intending to use trains, despite recent non-use, differed significantly in intention between four and eight-hour trip durations (p<0.001). The interaction term between these effects was marginally non-significant (p=0.066).

Figure 5:

Past behavior means

Personal socio-demographics

Several socio-demographic attributes influence business travel behavioral intention (Figure 6). Country of residence did not significantly affect intention but did impact perceived threat to freedom (p=0.022) and reactance (p=0.015), with higher levels observed in Switzerland. Age showed significant differences, with younger participants exhibiting stronger intentions (non-sig.), higher perceived threat to freedom (p<0.001), and greater reactance (p<0.001). Younger individuals also identified more strongly with work colleagues (p<0.001) and had stronger descriptive normative beliefs (p=0.043) and are therefore potentially more susceptible to social norm interventions. Presence of children in the household also led to significant differences. Travelers with children perceived the intervention as a stronger threat to freedom (p<0.001) and experienced greater reactance (p=0.003). They also identified more strongly with work colleagues as descriptive referents (p<0.001) and showed a stronger desire to comply with family expectations (4.74 vs. 3.30, p<0.001), although reported business trip numbers did not vary significantly. An interesting interaction effect emerged between age and presence of children. This interaction significantly affected intention (p=0.003, Figure 7, Table 3) but not reactance. The interaction effect illustrated in the graph shows how the presence of children influences intention differently across age groups. Older participants with and without children showed significant intention differences between four and eight-hour trip durations (p=0.002 and p=0.008, respectively), while this effect was not significant among younger participants with or without children. For younger participants (blue line), having children increases their intention, as seen by the upward slope. In contrast, for older participants (red line), the presence of children significantly decreases their intention, evident from the downward slope. This indicates that younger participants’ intentions are positively influenced by having children, whereas older participants’ intentions are negatively influenced when children are present. This differential pattern highlights the complexity of how age and family status interact to shape behavioral intentions. No significant gender differences were found.

Figure 6:

Socio-demographic means

Figure 7:

Interaction Effect Age x Children (Between Subjects ANOVA)

Table 3:

Test Results for Interaction Effect Age x Children (Between Subjects ANOVA)

Tests of Between-Subjects Effects
Dependent Variable: Intention
Source	Type III Sum of Squares	df	Mean Square	F	Sig.
Corrected Model	40.176a	3	13.392	3.494	0.015
Intercept	16204.461	1	16204.461	4227.793	0.000
Children	0.003	1	0.003	0.001	0.976
Age	7.419	1	7.419	1.936	0.165
Children* Age	34.418	1	34.418	8.980	0.003
Error	2418.523	631	3.833
Total	20889.000	635
Corrected Total	2458.699	634
a. R Squared = .016 (Adjusted R Squared = .012)
Children* Age
Dependent Variable: Intention
Children	Age	Mean	Std. Error	95 % Confidence Interval
				Lower Bound	Upper bound
no Children	Young	5.180	0.170	4.847	5.514
	Old	5.443	0.135	5.178	5.708
Children	Young	5.675	0.139	5.401	5.949
	Old	4.958	0.201	4.563	5.352

4.2 Effect of social norm interventions

The social norm interventions did not produce the expected effects. The one-way ANOVA results revealed no significant differences between groups for intention, normative beliefs, social norms, threat to freedom, and reactance (Tables 4 and 5). Despite expectations, the treatment group did not show higher intention levels, and unexpectedly, the control group reported higher perceived threat to freedom and reactance. Therefore, we conclude that the interventions did not achieve their intended outcomes, leading us to reject Hypotheses 1 and 2.

Regarding the potential interaction of trip duration and the social norm treatment, we performed univariate tests of between-subjects effects. As can be seen in Figures 8 & 9, the aforementioned difference in the intention to engage in business train travel is clearly significant between trips of four hours’ and eight hours’ duration. The direction of the effect of the treatment on intention is visible, as hypothesized in the four-hour condition but non-significant in both conditions. Therefore, we must reject Hypothesis 3d. With regard to the perceived threat to freedom associated with the social norm treatment, interestingly, the directions of the effects are inverse between the shorter and the longer trip. However, the differences between groups are also non-significant. The interaction effect was found to be non-significant for both measures.

Figure 8:

Interaction of experimental group and trip duration for intention

Figure 9:

Interaction of experimental group and trip duration for reactance

5.1 Discussion

Our main results did not meet expectations, which prompted us to deviate from our original research concept and refrain from the field experiment. However, we obtained meaningful results that we now discuss. This study examined determinants of behavioral intention, perceived threat to freedom, and reactance in business travel mode choice. Participants demonstrated strong intentions to choose trains, significantly influenced by trip duration. Past behavior, particularly mode choice preference and frequency, was crucial; frequent train travelers exhibited lower reactance and stronger intentions. Pro-environmental orientation also positively influenced train travel intentions. Contrary to expectations, social norm interventions did not significantly impact intention. The discussion analyzes these findings, their implications, and the dynamics of sustainable business travel choices.

First, participants reported unexpectedly strong behavioral intentions for business travel by train. While intentions varied by trip duration, consistent with Dällenbach (2020), they were still stronger than expected even for an eight-hour journey. Additionally, reactance to the social norm message was weaker than anticipated. These findings challenge existing literature, necessitating further analysis of possible causes and implications. One question is whether our sample differs from the broader population of business travelers. Compared with studies in German-speaking countries (FUR, 2023; Müller & Wittmer, 2023), our sociodemographic data align with key variables such as gender, age, and travel frequency. The slight leftward skew in pro-environmental attitudes among our sample also reflects industry trends, as recent studies show increasing environmental awareness (FUR, 2023; GBTA, 2022; Gustafson, 2006, 2012).

A strong reported willingness to engage in environmentally friendly travel behavior may be relativized by the existence of an attitude-behavior gap (Juvan & Dolnicar, 2014; Lassen, 2010). Although we do not have data on actual behavior, we can consider several reference points to assess the reliability of the behavioral intention statements. The only slightly stronger mean intention for train travel in our study compared to study 1 with a different sample suggests that the behavioral intentions reported by business travelers in our sample are consistent and not unexpected. Additionally, the noteworthy correlation between reported past behavior and intention indicates the lack of a significant attitude-behavior gap at a larger scale, given the presence of established travel habits. While some limitations remain and will be addressed later, we are confident that our study reveals that business travelers are more willing to travel by rail than is commonly thought.

Secondly, we highlight key factors influencing behavioral intentions toward rail travel and reactions to social norm messages. Of particular note is the impact of past business travel behavior, particularly the recency of past business rail travel. This is crucial as habits are known to influence decision-making among business travelers (Bamberg et al., 2003; Lyons, 2013; Poggioli & Hoffman, 2022; Roby, 2014) and can moderate the relationship between personal norms and behavior (Klöckner & Matthies, 2004). Our findings underscore the critical role of habits as drivers of sustainable business travel behavior, aligning with recent propositions (MacInnes et al., 2022). Given their significance, interventions and policies aimed at promoting train travel should address existing business travel habits. Our data indicate that the mere presence of any mode choice policy, even on recommendation basis, significantly enhances travelers’ intentions to use trains. Additionally, familiarity with train travel is pivotal for sustainable mode choices (Dällenbach, 2020; Walsh et al., 2021). Business travelers lacking recent experience with trains tend to exhibit lower intentions to choose rail, suggesting a need for policies that simplify usage and provide incentives for rail travel.

That we found no significant gender differences is somewhat surprising. Results from Gustafson (2006) suggest that men travel significantly more than women and that women are significantly inhibited from traveling by the presence of children. Although more men travel for business, among the travelers in our sample we could not confirm this effect of children for either past or intended behavior. Interestingly, our findings reveal that younger individuals exhibit a stronger intention to travel by train while also demonstrating higher levels of reactance, in line with previous research that suggests a decrease in reactance with age (Hong et al., 1994), as well as the notion that younger travelers are more inclined to choose train travel (Limtanakool, Dijst, & Schwanen, 2006; Shen, Chen, & Pan, 2016). Our data further support Dällenbach’s (2020) findings, highlighting that individuals who prefer working during business trips are more likely to opt for train travel. This indicates that for this group of employees, productivity compensates for the longer travel times. In general, it is confirmed that business travel decisions are always embedded in an organizational and private context, thus the corresponding contextual factors must be considered (Cohen et al., 2018; Gustafson, 2006; Lassen, 2010).

While our study did not find significant differences in business travel mode choice intention, perceived threat to freedom, or reactance between the treatment and control groups when considering trip duration and other contextual factors, it is crucial to consider the implications of these findings. Despite potential limitations to be discussed later, several significant considerations arise. One possible explanation is the strong existing preference for business rail travel, suggesting it is already widely accepted as the norm. This awareness aligns with the increasing use of rail for business travel in Europe (Magesh, 2023; Parsons, 2023), potentially limiting the impact of social norm interventions on normative beliefs. Therefore, the effectiveness of such interventions may be constrained in this context. Another explanation could be the perceived autonomy in decision-making regarding business trips. Unlike findings by Klöckner and Matthies (2004) suggesting people view work trips as beyond personal control, our participants indicated they have significant autonomy in deciding about their business travel.

Sunstein (2017) points out that social norm interventions can fail if individuals do not care about or want to defy social norms. Research generally states that social norms influence business travel more strongly than commuting (Lo et al., 2013). Concerning the normative referents, we discovered that family (injunctive referent) more strongly impacted social norms in our sample than coworkers (descriptive referent), which contradicts the findings of Ru et al. (2018) and Kormos et al. (2015). These authors suggested that informing individuals about others’ behavior is more effective than informing them about important others’ expectations. However, in business travel, family seems to be a more influential normative referent. A possible explanation for intention to defy norms could be respondents’ exposure to their company’s travel policies. Despite a relatively small number reporting mode choice policies, their existence significantly strengthened intention rather than prompting defiance.

Psychological reactance had minimal impact on the effectiveness of social norm interventions influencing business travel mode choice intention, leading us to omit reporting the SEM results in the final manuscript. Participants generally showed low levels of reactance to the presented social norm message, suggesting limited resistance to using the train for business travel. Several factors may explain the absence of participant reactance in our study. Most importantly, social norm messages may not induce reactance in the business travel context, potentially because rail travel is already widely accepted among participants. This aligns with the notion that reactance arises when individuals perceive a threat to their freedom or encounter restrictive measures. Our findings contrast with Heilman and Toffler’s (1976) assertion that reactance occurs in response to any attempt at manipulation.

Furthermore, it is worth noting that previous research has primarily examined the influence of reactance on variables such as attitude, persuasiveness, and motivation rather than specifically focusing on its relation to social norms (Dillard & Shen, 2005; Quick, 2012; Quick & Stephenson, 2007; Shen, 2015). Additionally, participants may not have had sufficient cognitive resources to connect the message with the potential implications for their actual business travel, as the cognitive load can impact the processing of and response to persuasive messages (Laurin et al., 2013). Last, our data also do not show a relevant ‘boomerang effect’ by which descriptive social norms are negatively related to behavioral intention (Kormos et al., 2015; Perkins, Haines, & Rice, 2005). Even in the combined models, we found only a marginally negative indirect effect of reactance on intention – as mentioned before, not enough to justify their inclusion in the paper. In sum, our results suggest that psychological reactance does not pose a major barrier to the effectiveness of social norm interventions in this context. Other factors, such as past behavior and socio-demographic attributes, were found to influence behavioral intention more strongly.

5.2 Limitations and further research

Based on our study findings, we propose recommendations for advancing research on social norm interventions for sustainable business travel. First, conducting field experiments in organizational settings can enhance findings’ applicability and overcome biases linked to hypothetical scenarios. Addressing concerns about negative employee reactions is crucial to ensure organizational participation. Including observations of actual behavior among business travelers alongside self-reported intentions would offer deeper insights into intervention effectiveness and mode choice alignment and help uncover a potential attitude-behavior gap. While our study focused solely on rail travel intentions, future research should broaden scope to include other modes like car or plane to increase realism. Using methods such as ACBC or CBC would further enhance the study’s generalizability by simulating comprehensive choice scenarios.

Second, further research is needed to conclusively evaluate social norm interventions’ efficacy in promoting pro-environmental behavior during business travel. This requires exploring diverse treatment types, formats, durations, and targeted referents beyond those in our study (Farrow et al., 2017; Grilli & Curtis, 2021). Investigating treatments targeting behavioral or control beliefs could elucidate effective strategies for encouraging sustainable travel choices.

Third, future studies should explore how TPB and reactance models interact under various conditions. Our integration attempt yielded inconclusive results, necessitating further exploration of reactance’s role in behavioral interventions and its impact on change outcomes. Additionally, our study’s results may have been influenced by potential methodological biases and challenges related to the operationalization of key constructs, as indicated by a failed CFA. Future research should address these limitations by refining measurement tools and ensuring more robust operationalization of constructs. By doing so, subsequent studies can provide a clearer understanding of the relationships between variables and offer stronger evidence for the efficacy of social norm interventions in promoting sustainable behaviors.

Lastly, given habits’ influence on travel behavior, future research should explore how habits interact with interventions. Understanding effective strategies to modify or overcome existing habits could offer insights into designing successful interventions for sustainable business travel.

5.3 Contribution to the literature

Our research represents a methodologically rigorous contribution to tourism studies, integrating behavioral interventions from the TPB, psychological reactance theory, and contextual factors influencing low-carbon business travel. Building on insights from scholars like Dillard and Shen (2005) and Orbell and Hagger (2006), who highlighted TPB’s predictive power enhanced by reactance considerations, our study offers a novel approach tailored to this domain.

Despite our findings that social norm interventions did not significantly influence business travelers’ intention to use trains, we consider it crucial to report these results comprehensively. This approach aligns with best practices advocated by Visentin, Cleary, and Hunt (2020), ensuring transparency in scientific discourse and guarding against publication bias. Our study contributes valuable insights into the effectiveness of these interventions, underscoring their limitations in the context of sustainable business travel behavior. This nuanced understanding not only enriches theoretical frameworks but also informs future research and practical strategies aimed at fostering more sustainable practices in the business travel sector.

While our study’s scope and methodology constrain broader claims, our findings offer a detailed exploration of factors shaping business travel decisions. Rooted in robust empirical data and integrating reactance with established theories, our study lays groundwork for future research in this field. It underscores the importance of ongoing investigations to deepen understanding of business travelers and accelerate sector decarbonization efforts.

In conclusion, our study not only advances knowledge on integrating behavioral theories and reactance in sustainable business travel but also guides future research directions. It highlights the imperative of effectively changing traveler behavior while ensuring long-term acceptance of measures. By elucidating the complexities of business travel behavior, our research informs ongoing efforts to achieve sustainability in the sector.

5.4 Practical implications

Scott and Gössling (2022) highlighted the sector’s unpreparedness for the climate disruptions expected to transform tourism in the coming decades, underscoring the urgency of our research contribution to decarbonization efforts.

Policy-makers and organizations can leverage the unexpectedly strong intentions toward train travel by tailoring policies to individual habits and preferences. Incentives and rewards for frequent train travelers can reinforce their positive behavior, while familiarization programs are essential for those with limited train experience, addressing concerns and reducing perceived complexities. Encouraging business travelers who haven’t recently taken the train is crucial due to the strong influence of recency on future travel intentions.

Concerns among organizations about implementing train travel policies appear unfounded to some extent, given the existing strong intentions for train travel among business travelers. This positive perception suggests that mandatory policies shifting continental business travel to rail can be confidently introduced, potentially minimizing backlash. Additionally, the mere presence of mode choice policies, even voluntary ones, has a lasting positive impact on encouraging train use. Involving employees in policy formulation enhances their sense of control, reduces reactance, and fosters acceptance of new travel norms. Inter-departmental initiatives promoting sustainable travel choices can create unity among employees and positively influence travel intentions. Continuous monitoring of mode choice policies through regular surveys and feedback mechanisms ensures their effectiveness.

To boost behavioral intention and reduce reactance, it’s crucial to tailor policies based on individual characteristics and preferences. This involves creating age-specific campaigns to resonate with young professionals’ strong intentions for train travel and implementing family-friendly policies to alleviate perceived threats to freedom, encouraging family-oriented individuals to opt for trains. Recognizing and promoting the travel preferences of managerial staff through customized incentives and support systems reinforces positive attitudes toward train travel. For employees prioritizing productivity during travel, interventions highlighting benefits like Wi-Fi availability and conducive work environments on trains may enhance their intention to choose rail for business purposes. Integrating personalized strategies into organizational policies fosters a positive and sustainable culture, addressing diverse needs and preferences while improving the overall travel experience for employees.

Lastly, on a broader scope, investing in efficient rail networks and improving travel times supports the transition to rail travel and enhances overall transportation sustainability. Policymakers must thus support the transition to rail travel and contribute to business travel decarbonization. Creating environments suitable not only for leisure but for business travelers is vital in this context.

In summary, these practical implications empower organizations and policymakers to effectively promote sustainable business travel by addressing concerns, tailoring interventions, incentivizing train travel, improving infrastructure, and engaging employees actively.