The Moderating Role of Generation on Residents’ Support for P2P Vacation Accommodations: Millennials versus Older Generations

Abstract

Massive-scale peer-to-peer vacation accommodation has become one of the most relevant recent trends in the tourism industry. The phenomenon coincides in time with the emergence of the millennial generation alleged to influence a distinctive behavior. Grounded in the Social Exchange Theory, the study presents a comparative analysis of millennial residents’ and previous generations’ support for P2P vacation accommodations. The article explores differences in support for the new activity, in the perception of its impacts, and on how the residents back their support. A quantitative survey was conducted with a sample of 1,285 residents from Tenerife (Spain), a major international tourist destination with a large number of P2P vacation accommodations. Results reveal that millennial residents display more support for P2P vacation accommodations. However, it is not based on structural differences in how they build their support, rather on a greater perception of positive economic, socio-cultural, and environmental impacts than previous generations. Relevant tourism destination and DMO implications are derived.

Keywords

millennials P2P vacation accommodations residents’ attitudes perception of impacts SET PLS

Introduction

The large-scale rental of accommodations between individuals is probably one of the most disruptive trends in the tourism industry (Bulchand-Gidumal et al., 2019; Guttentag, 2019). This practice, historically carried out informally, has experienced an impressive leap in scale boosted by the widespread use of the Internet and ICT (Russo & Quaglieri, 2014). The phenomenon has acquired such importance that already in 2015, the worldwide number of peer-to-peer (P2P) marketed beds exceeded those offered in traditional tourist accommodations (Reuters, 2015). Today, Airbnb alone hosts more than 2 million guests per night (ACER, 2020).

The success of platforms such as Airbnb, however, is not without controversy or obstacles (Gurran & Phibbs, 2017; Richards et al., 2019). There have been notorious examples of mobilization of mass protests (e.g., Barcelona, Berlin) that may hint toward a deficient interaction between tourists and residents and may seriously jeopardize the peaceful and successful development of the activity (Sharpley, 2014). Therefore, it is of vital importance that destination managers and regulators understand how residents’ support for P2P vacation rental accommodations is shaped and what variables may influence it.

Recently, some authors have started exploring the residents’ perception of impacts of Airbnb-like platforms (Guttentag, 2015; Heo, 2016; Mody et al., 2019), and preliminary explanatory models on how residents build their support for P2P vacation accommodations have been proposed (e.g., Garau-Vadell et al., 2019; Yeager et al., 2020). However, they do not take into account the fact that the age of the residents may sway their perception of the impacts and their support for a given tourism development (Harrill, 2004; Nugroho & Numata, 2022; Sinclair-Maragh, 2017).

Such a research gap is especially relevant as the hatching of P2P vacation rental coincides in time with the emergence of the millennial generation. This generation, formed by consumers born between 1980 and the early 2000s has already surpassed the baby-boomer generation in terms of numbers. Additionally, it has been proved that they show common and distinctive traits alleged to influence a distinctive behavior in various aspects, including their shopping motivations (Gupta et al., 2021; H. Kim et al., 2009), their decision-making processes and driving values (Boyd, 2010; D. Y. Kim & Park, 2020), and their travel attitudes and preferences (Ketter, 2021). Overall, the importance of millennials is such that some authors have made a specific call to explore, in the widest sense possible, how they are shaping tourism today and will continue to do so in the future (e.g., D. Y. Kim & Park, 2020). So far, research on millennials and P2P vacation rentals has mainly focused on their role as travel consumers (e.g., Amaro et al., 2019; Gardiner et al., 2014), leaving their role as residents unattended (Guttentag, 2019).

In this respect, this study, grounded in the Social Exchange Theory (SET), analyzes whether belonging to a certain generation may influence residents’ support for P2P vacation accommodations. It does so by (i) comparing millennial residents’ perceptions of the positive and negative impacts of P2P vacation accommodations and their support for the activity with the views of older generations, and (ii) by testing whether there are structural differences between generations in the formation of their support toward P2P vacation accommodations. The ultimate aim of this research is to broaden the comprehension of how residents’ support for P2P vacation rentals is shaped. By doing so, we may help destination managers to better focus, design, implement and evaluate policies and strategies to manage this new phenomenon in a way that would favor positive interactions between tourists and residents, which is claimed to be the basis for building successful, peaceful, and sustainable tourism destinations (Sharpley, 2014).

Literature Review and Hypothesis Development

One of the theories most referred to explain residents’ support toward tourism development is the Social Exchange Theory (SET) (Ap, 1992). This theory examines the process of interaction between individuals and groups of people; it proposes that visitors and residents undertake a process of negotiation or exchange, the final goal of which is to increase the benefits obtained from the encounter. The basic principle of the SET is that residents will take part in an exchange if they trust they will benefit from it (Sharpley, 2014). Building upon that, the vast majority of studies grounded in the SET suggest that residents’ support would be based on their perception of the impacts resulting from the activity (e.g., Garau-Vadell et al., 2019; Gursoy et al., 2019; Mody et al., 2019; Nunkoo et al., 2013; Vargas-Sánchez et al., 2011). One of the main strengths of the SET is that it can easily accommodate an explanation of both positive and negative perceptions at the individual or collective level (Ap, 1992).

The literature suggests a variety of impacts derived from tourism developments. More recently, with the emergence of P2P vacation accommodations, impacts have also been proposed that are specifically linked to this new activity. Impacts are usually grouped into economic, socio-cultural, and environmental dimensions.

In the economic dimension, tourism developments have mostly been associated with positive impacts such as more employment opportunities, increased income for local businesses, and higher living standards for residents (Brayley et al., 1990; Vargas-Sánchez et al., 2009). Besides, P2P vacation accommodations are considered to bring positive economic impacts as they may lead to additional income for families, a better distribution of income from tourism, revitalization of the destination, the fostering of entrepreneurship among residents, and additional and more loyal tourists (Airbnb, 2014; Dogru et al., 2020; Fang et al., 2016; Sperling, 2014). On the negative side, P2P vacation accommodations have been blamed for potentially causing a displacement of tourists from hotels and therefore reducing the number of available jobs in traditional lodgings (Fang et al., 2016; Zervas et al., 2014). Also, certain studies suggest the possibility of a decline in tax revenue due to the high levels of informality associated with P2P accommodations (Exceltur, 2015), and some research points to a rise in the cost of living derived from the increase in housing prices (e.g., Barron et al., 2018; Horn & Merante, 2017). On the whole, the majority of studies back the indication that there is a direct and positive relationship between the economic impacts and residents’ support (e.g., Garau-Vadell et al., 2019; Stylidis & Terzidou, 2014).

In the socio-cultural dimension, tourism developments are frequently linked to positive impacts such as improvements in public spaces, infrastructures, and public services (e.g., Lankford & Howard, 1994; Perdue et al., 1990; Tovar & Lockwood, 2008). In certain cases, they may also favor the conservation of local culture resulting from its enjoyment and appreciation by tourists (e.g., McCool & Martin, 1994; Weaver & Lawton, 2001). Additionally, it is suggested that P2P vacation accommodation may foster cultural exchange, empathy and tolerance, language learning, improved social distribution of the benefits of tourism, and improvements in the maintenance of buildings (Airbnb, 2014; Cheng et al., 2022). On the negative side, tourism developments are usually indicated to contribute to the loss of traditions, acculturation, and trivialization of cultural heritage (e.g., Osagie & Buzinde, 2011). Furthermore, P2P vacation accommodation developments are also blamed for deteriorations in the residents’ quality of life resulting from issues like having to compete for existing parking spaces and being subjected to higher noise levels (Sheppard & Udell, 2016), as well as the fact that they are driven away from their neighborhoods as they are unable to afford the housing prices (Barron et al., 2018; CEHAT, 2015; Cheng et al., 2022; Exceltur, 2015; Malhotra & Van Alstyne, 2014), and there may be a deterioration of the coexistence between neighbors and tourists (Gravari-Barbas & Jacquot, 2016). Despite such negative impacts, overall, the literature seems to suggest a direct and positive relationship between the socio-cultural impacts and residents’ support (Dyer et al., 2007; Garau-Vadell et al., 2019).

In the environmental dimension, tourism development impacts have normally been considered to be more negative than positive. They are frequently associated with the degradation of natural spaces, increased garbage, and the over-exploitation of natural resources (e.g., Andereck, 1995; Choi & Murray, 2010; Koenen et al., 1995). In addition P2P vacation accommodations have been specifically blamed for increases in noise pollution, traffic congestion, faster deterioration of infrastructures, and saturation of the spaces traditionally used by residents (CEHAT, 2015; Exceltur, 2015). On the other hand, positive environmental impacts are usually associated with improved awareness among residents of the value of environmental assets, and the impetus for conserving and recovering natural spaces (e.g., Perdue et al., 1990; Zhang & Lei, 2012). Additionally, in the particular case of P2P vacation rental developments, it can be added that they do not chomp away at new territorial resources, instead favoring a more efficient use of existing resources, and they result in a more sustainable and respectful form of travel (Airbnb, 2014; Fang et al., 2016). Despite these positive impacts, the common view is that there is a direct, negative relationship between the environmental impacts perceived by the residents and their support (e.g., Boley et.al, 2017; Garau-Vadell et al., 2019).

According to the SET, how residents perceive the impacts of a given tourism development will determine their support for the activity, with them granting their support if their perception of the positive impacts exceeds their perception of the negative ones (Sharpley, 2014). Such a perception has been proved to be influenced by several variables, including the demographics of the individuals (e.g., Bagri & Kala, 2016; Nunkoo & Ramkissoon, 2010; Sinclair-Maragh, 2017; Stylidis & Terzidou, 2014) and their values (e.g., Choi & Murray, 2010; Woosnam, 2012).

On the one hand, although sometimes contradictorily, the age of the residents is considered to be highly relevant in swaying residents’ perceptions (e.g., Bagri & Kala, 2016; Harrill, 2004; Sinclair-Maragh, 2017). In certain cases, the literature proposes that older residents will tend to display more negative perceptions than the younger ones, based on their fear of change (Bagri & Kala, 2016; Cavus & Tanrisevdi, 2002) or that younger residents may perceive tourism development more positively as they consider it as an opportunity for job creation and a business opportunity (Sinclair-Maragh, 2017). In other cases, older residents are anticipated to display more positive attitudes based on discourses arguing, for example, that older people will have more opportunities to benefit from better-paid positions in the tourism industry based on their experience (McGehee & Andereck, 2004), that they stand to gain more benefits from tourism than do younger residents (Rasoolimanesh et al., 2015) or that they show less concern about environmental issues (Tomljenovic & Faulkner, 2000).

On the other hand, personal values are also advocated to influence how residents perceive the impacts of tourism. For example, residents displaying emotional solidarity would perceive the positive impacts more than other residents and consequently give tourism developments more support (Woosnam, 2012). Overall, they are suggested to influence behavior and attitudes (H. Kim et al., 2009; Visit Scotland, 2017). Consequently, we may expect that the distinctive traits and values of millennials would influence how they perceive the impacts of peer-to-peer vacation accommodation developments and how they support the activity.

In this sense, relative to previous generations, millennials are less well off with lower earnings, fewer assets, and less wealth (Kurz et al., 2019). Growing up during times of economic difficulty has made them more cautious and sensitive than previous generations in economic matters, such as spending money or accumulating belongings and debts (Kurz et al., 2019). They are also more open to change and less attached to jobs for life (Arthursson, 2016). Furthermore, they tend to have a positive view of economic activities that imply an improved use of assets (Hamari et al., 2016). On these grounds, we can put forward the following hypotheses:

H1a: Relative to previous generations, millennial residents’ overestimate the positive economic impacts of P2P vacation accommodation and underestimate the negative ones.

H1b: The influence of the perception of the economic impacts on the support for P2P vacation accommodations is greater among millennials than previous generations.

Millennials are also considered to have a high level of social awareness (Sheahan, 2005), and to generally display a great commitment to their communities (Hira, 2007). Millennials care about thriving communities and “feel it’s important to preserve and conserve buildings, architecture, and neighborhoods” (American Express, 2019). They are considered to be open-minded and see interaction and cooperation with others as a prime living principle (CBI, 2019). On these grounds, we can put forward the following social-impact-related hypotheses:

H2a: Relative to previous generations, millennial residents’ overestimate the positive social impacts of P2P vacation accommodation and underestimate the negative ones.

H2b: The influence of the perception of the social impacts on the support for P2P vacation accommodations is greater among millennials than previous generations.

As far as cultural values are concerned, millennials are thought to be eager to explore, interact, and experience the world (Cavagnaro et al., 2018; CBI, 2019). The millennial generation is one that enjoys connecting with others, the community, and the world (OECD, 2018). They see travel as a major opportunity to discover the world and themselves (CBI, 2019). They appreciate true connections with local populations, the creation of authentic local experiences, and value for money (Ketter, 2021; Visit Scotland, 2017). Furthermore, millennials are claimed to be more willing to admit and understand diversity in lifestyles, cultures and ethnicity in society, and accept differences more readily than other generation cohorts (D. Y. Kim & Park, 2020). On these grounds, we can put forward the following hypotheses:

H3a: Relative to previous generations, millennial residents’ overestimate the positive cultural impacts of P2P vacation accommodation and underestimate the negative ones.

H3b: The influence of the perception of the cultural impacts on the support for P2P vacation accommodations is greater among millennials than previous generations.

Concerning the environmental dimension, millennials are considered to be in pursuit of a more sustainable society (Gansky, 2010; Kapferer & Michaut-Denizeau, 2020); they are also willing to pay more for brands that are committed to a positive social and environmental impact than previous generations (Nielsen, 2015). However, some studies suggest that millennials are more environmentally oriented in terms of attitude than behaviorally green (e.g., Grønhøj & Thøgersen, 2009). On these grounds, we can put forward the following hypotheses:

H4a: Relative to previous generations, millennial residents’ overestimate the positive environmental impacts of P2P vacation accommodation and underestimate the negative ones.

H4b: The influence of the perception of the environmental impacts on the resident’s support for P2P vacation accommodations is greater among millennials than previous generations.

Finally, many studies have pointed out that millennials display an outstanding positive attitude toward collaborative consumption (e.g., Botsman & Rogers, 2010; Činjarević et al., 2019; Gansky, 2010; Lamberton & Rose, 2012; Olson, 2013; Sacks, 2011). They usually argue that the sharing economy is very popular among this generation due to the many benefits it can provide to the world they live in, including connecting with local communities, creating authentic local experiences, and value for money (Ketter, 2021). Based on this and the previously discussed arguments, we can put forward our last hypothesis:

H5: Millennial residents show more support for P2P vacation accommodations than previous generations.

Figure 1 displays the conceptual framework and the hypotheses derived from the moderating effect of generation on the residents’ perception of the impacts of P2P vacation accommodations and on the influence of each of the perceptions on their support for the activity.

Figure 1.

Conceptual framework and hypotheses.

Methodology

Site Location

The fieldwork for this research was carried out in Tenerife (Canary Islands-Spain), a leading international mass tourism destination that hosts more than 5 million tourists a year (MoNE, 2019). Canary Islands archipelago is located around 2,000 km southwest of the Spanish mainland and 120 km west of the Saharan coast, with a total surface of 7,490 km², and consists of eight islands. Tenerife, the most populated island of the archipelago, depends largely on the tourism sector. The island has traditionally focused on the British market, which represents 50% of the total annual number of tourists to this destination. Tenerife specializes in sun-and-sea tourism (Santana-Jiménez & Hernández, 2011). On this island, P2P vacation rentals represent an important share of the total available tourism beds, which already exceeded 26.7% of the total available places in the destination in 2018 (Promotur, 2019).

Research Instrument

A structured questionnaire was designed to gage residents’ support and their perception of impacts. Residents’ support was operationalized with four statements based on previous scales (Garau-Vadell et al., 2014; Perdue et al., 1990). Their perception of the economic, cultural, social, and environmental impacts was piloted using constructs also based on pre-existing scales (Gursoy & Rutherford, 2004; Nunkoo & Ramkissoon, 2010; Vargas-Sánchez et al., 2011). The measurement scales were adapted to the specific case of P2P vacation accommodations. For classification purposes, the questionnaire included a set of socio-demographic variables, such as gender, age, education, relative family income, and area of residence. A Likert scale of five categories, ranging from “strongly disagree” (1) to “strongly agree” (5), was chosen as the most appropriate scaling. Before the fieldwork started, five experts in tourism (three academicians and two practitioners) confirmed the apparent validity of the questions. Also, a pretest was conducted with 50 residents to confirm that the statements were clearly understood.

Sample

The sample of this study was composed of permanent residents of Tenerife over 18 years of age. In January 2018, members of a major commercial marketing research panel in Tenerife were invited by email to participate in the survey and respond to a self-administered questionnaire in Spanish. This type of questionnaire is preferred since it delivers a higher response rate and the researcher’s interference is reduced to a minimum (Oppenheim, 1992). The total sample obtained consisted of 1,285 individuals. The sample error for a confidence level of 95% and p = q = 50% is ±2.8%.

Millennial residents (18–35 years old) made up 59.5% of the final sample (Table 1) and residents from previous generations (over 35 years old) made up the remaining 40.5%. By gender, 62% of the sample was female and 38% male. Both subsamples showed high levels of knowledge of P2P rental activity. Almost 68% of the millennials and just over 43% of the older generations have rented accommodations through P2P platforms. Moreover, around 18% of the millennials and 13% of the older generations have themselves or their family provided peer-to-peer vacation accommodations of their own. Finally, the self-perception of family income is very similar in both subsamples.

Table 1.

Sample Descriptives.

	Total	Millennials	Over 35s
Gender
Male	62.0%	62.7%	61.0%
Female	38.0%	37.3%	39.0%
Have you ever rented P2P vacation accommodation?
Yes	57.7%	67.7%	43.1%
No	42.3%	32.3%	56.9%
Have yourself, or your family, put accommodation of your own on a P2P rental platform?
Yes	16.0%	18.3%	12.7%
Don’t know	11.4%	9.7%	13.8%
No	72.6%	72.0%	73.5%
Education
None	2.5%	0.3%	5.8%
Elementary	15.6%	6.3%	29.2%
High school	35.8%	39.1%	31.0%
University	46.1%	54.4%	34.0%
Family income
Well below average	4.2%	4.1%	4.4%
Below average	21.1%	20.7%	21.7%
Average	57.5%	57.5%	57.5%
Above average	12.6%	12.7%	12.5%
Well above average	1.6%	1.4%	1.9%
Don’t know	3.0%	3.7%	1.9%
Total	1,285	765	520
	100%	59.5%	40.5%

The sufficiency of the sample size to perform the required hypothesis testing and analysis was confirmed under Reinartz et al.’s (2009) approach, which states that a minimum sample of 100 is required to ensure that PLS-SEM achieves the necessary power (0.8). Moreover, G*Power was used to calculate the minimum sample size required based on power analysis (Faul et al., 2009). Its results demonstrated that to test the proposed model (five predictors) a minimum sample of 146 individuals per group was required to achieve a statistical power of 0.95. Thus, it can be concluded that the sample size used in this research for both groups is statistically acceptable and surpasses the level required to run analyses in this study.

Data Analysis

To unveil whether significant differences existed between generations in the perception of the impacts and support for the activity, a means difference (t-test) analysis was conducted. Belonging to one generation or another was the independent variable, and the average perception of each of the positive and negative impacts were the dependent variables.

Subsequently, to analyze the moderating effect of generation on the relationships of the proposed structural model, a multi-group analysis (MGA) was performed using the Partial Least Squares technique (PLS-SEM) with Smart PLS v.3.3.9 software (Ringle et al., 2009). PLS-SEM was chosen to be used in this study because nonparametric SEM techniques are considered to be the most appropriate when conducting MGA (Hair et al., 2014; Henseler et al., 2016; Sarstedt et al., 2011).

Results

Differences in Impact Perception and Support for P2P Accommodations

Table 2 displays the millennial residents’ and over-35 residents’ average perception of the impacts of P2P vacation accommodations, their levels of support for the activity, the corresponding t-test of differences, and whether there is support for the formulated hypotheses. To ensure the validity of the t-test, independently of the equality of the variances, we have conducted the Games Howell procedure (Shingala & Rajyaguru, 2015).

Table 2.

Perception of Impacts, Support for P2P Vacation Accommodations, and t-tests.

	Constructs	Millennials	Over 35s	Dif.	Sig.		Hypothesis supported
	Economic impacts
	Positive economic impacts
PEI1	Generates a considerable number of jobs	3.39	3.13	0.26	.000	***
PEI2	Helps many families economically	3.79	3.46	0.33	.000	***	H1a-Partially
PEI3	Revitalizes the area where the accommodation is located	3.53	3.27	0.26	.000	***
	Negative economic impacts
NEI1	Produces precarious, low-quality jobs	3.08	3.11	−0.02	.915	ns
NEI2	Destroys existing jobs in hotels	3.06	3.19	−0.14	.094	*
	Social impacts
	Positive social impacts
PSI1	The benefits of tourism are more evenly distributed among society	3.24	3.10	0.13	.095	*
PSI2	Encourages better maintenance of dwellings and neighborhoods	3.34	3.23	0.11	.178	ns	H2a-Partially
	Negative social impacts
NSI1	This type of tourism causes a deterioration in citizen coexistence	2.96	3.06	−0.10	.258	ns
NSI2	This type of tourism causes residents to move away	2.96	3.07	−0.12	.218	ns
NSI3	Where this tourism is practiced, tranquility and quality of life declines	2.92	3.07	−0.15	.054	*
	Cultural impacts
	Positive cultural impacts
PCI1	Favors the exchange and understanding of different cultures	3.73	3.46	0.26	.000	***	H3a-Yes
PCI2	Is an opportunity to meet and interact with people from other places	3.83	3.53	0.31	.000	***
	Negative cultural impacts
NCI1	This type of tourism makes the residents feel like strangers on their own island	2.60	2.76	−0.16	.039	**
NCI2	This type of tourist does not bring anything of interest to the residents	2.50	2.82	−0.31	.000	***
	Environmental impacts
	Positive environmental impacts
PENI1	This type of tourism values natural protected spaces more	3.14	3.04	0.10	.098	*	H4a-Partially
PENI2	In general, this type of tourism is more respectful toward the environment	3.19	3.03	0.16	.019	**
	Negative environmental impacts
NENI1	Causes more pollution (noise, trash, etc.)	2.95	2.97	−0.02	.954	ns
NENI2	Makes the neighborhood infrastructure deteriorate faster	2.70	2.77	−0.06	.529	ns
NENI3	Saturates the spaces normally used by residents	2.92	2.93	−0.01	.981	ns
	Support for P2P vacation accommodations
SU1	Generally, this type of accommodation is good for the island	3.49	3.17	0.32	.000	***
SU2	This type of accommodation should be promoted further	3.37	3.13	0.24	.001	***	H5a-Yes
SU3	I support this type of accommodation	3.65	3.31	0.34	.000	***
SU4	I like that this type of activity can be carried out	3.65	3.34	0.31	.000	***

Note. Significance level according to Games-Howel post hoc procedure for unequal variances: *** <.01;** <.05;* <.1.

Concerning economic impacts, the results point out that millennials perceive the positive economic impacts derived from P2P vacation rental significantly more than previous generations, including its capacity to generate jobs, the economic help provided to many families, and the revitalization of the areas where it is on the increase. Regarding negative economic impacts, there are no significant differences between generations in the perception that P2P rental may produce precarious, low-quality jobs. However, millennials display a significantly lower perception that P2P vacation accommodations may destroy existing jobs in hotels. Consequently, H1a stating that, relative to previous generations, millennial residents’ overestimate the positive economic impacts of P2P vacation accommodation and underestimate the negative ones, is partially supported. This is because, although millennials have a greater perception of all the positive economic impacts, their perception of the negative impacts is not significantly lesser in all the items considered.

In the case of social impacts, millennials perceive the positive social impacts significantly more than previous generations, including the fact that the activity generates a large number of jobs and helps many families financially, and that the benefits of tourism are more evenly distributed among society. As for the perception of the negative impacts, millennials display a significantly lesser perception that the activity leads to a decline in living standards and causes residents to move away, whereas no differences arise in the perception that the activity causes a deterioration of coexistence. Thus, H2a is partially supported since millennials have a greater perception of all the positive social impacts considered, but not all the negative social impacts considered get a significantly lesser perception.

Regarding cultural impacts, millennials perceive all the examined positive impacts significantly more than previous generations, including the fact that P2P vacation accommodations favor the exchange with and the understanding of different cultures, and that they enable them to meet and interact with people from other places. As for the negative cultural impacts, millennials perceive significantly less than the older generations that P2P vacation accommodations may cause residents to feel like strangers in their own home, and that this type of tourism does not bring anything of interest to residents. Therefore, H3a stating that millennials perceive the positive cultural impacts more and the negative impacts less than previous generations, is fully supported.

As far as environmental impacts are concerned, millennials perceive the positive impacts analyzed significantly more than previous generations, including the fact that tourists staying in P2P vacation accommodations value natural protected areas more than tourists in hotels and are more respectful toward the environment. No significant differences between generations appear when evaluating the perception of the negative impacts. The results indicate that both groups display similar levels of perception of the pollution, deterioration of infrastructures, and saturation of public spaces caused by the activity. Consequently, H4a stating that relative to previous generations, millennial residents’ overestimate the positive environmental impacts of P2P vacation accommodation and underestimate the negative ones, grants partial support. This is because millennials have a greater perception of all the positive environmental impacts than their older counterparts but not a significantly lesser perception of all the negative impacts.

Finally, concerning support for P2P vacation accommodations, the support shown by millennials is greater than that of previous generations in each of the four statements measuring it and is statistically significant. Consequently, H5 is corroborated.

Differences in the Influence of the Perception of Impacts on Residents’ Support for P2P Vacation Accommodations

To analyze the moderating effect of generation on the influence of the perception of impacts on support for P2P vacation accommodations, first of all, a structural model that links residents’ support with their perception of the impacts of the activity was tested (see Figure 2). Then, a multi-group analysis (MGA) was performed using the Partial Least Squares technique (PLS-SEM).

Figure 2.

Structural model for each group.

Evaluation of the Model Fit

The model fit was calculated using the standardized root mean square residual values (SRMR) recommended as an adequate approximation (Henseler et al., 2016). The SRMR results revealed values of 0.058 for the millennials and 0.047 for the over 35s. Both values are below the recommended maximum values of 0.08 (Henseler et al., 2016). Hence, the model fit can be considered acceptable.

The existence of common method bias (CMB) was also examined using Harman’s single-factor approach (Podsakoff & Organ, 1986). This procedure evaluates CMB by including all constructs in a principal component analysis (PCA) and concludes that CMB is present if a single or general factor appears to represent the majority of the variance. In our case, a non-rotational factor analysis using the greater-than-one criterion revealed three different factors for the millennial sample and two factors for the over-35 generations, which represented 60.1% and 66.0% respectively of the total variance. The first factor identified in each sample represented 41.7% and 53.7% of the variance. Therefore, as no single factor emerged and the first factor did not account for most of the variance, the CMB is not a concern. Furthermore, there is no evidence of multicollinearity between the background variables of each of the endogenous constructs, since all the VIF (Variance Inflation Factor) values are less than 5 (Table 3) (Hair et al., 2011).

Table 3.

Inner VIF Values.

	Support for P2P vacation rental
Cultural impacts	2,811
Economic impacts	2,673
Environmental impacts	3,026
Social impacts	3,859

Assessment of the Measurement Model

In the second stage of testing, the measurement model was evaluated. This evaluation was to assess the reliability and validity, convergent and discriminant, of the model’s latent variables (Hair et al., 2014).

To confirm the reliability, the loading of each item on its latent variable should be higher than 0.7 to be considered acceptable (Hair et al 2011). A loading of less than 0.4 indicates that the item should be considered for removal, items with a loading between 0.4 and 0.7 are acceptable if their composite reliability (CR) and average variance extracted (AVE) meet the recommended thresholds of CR > 0.7 and AVE > 0.5 (Vinzi, 2010; Hair et al., 2011). Table 4 shows that no items loaded less than 0.4, and the ones loading between 0.4 and 0.7 met the CR and AVE thresholds, therefore, no items had to be removed.

Table 4.

Assessment of the Measurement Model.

	Loading		Cronbach’s alpha		Composite reliability		AVE
Constructs/items	Millennials	Over 35s	Millennials	Over 35s	Millennials	Over 35s	Millennials	Over 35s
Support for P2P vacation accommodations (SU)			0.900	0.948	0.930	0.963	0.768	0.865
SU1	0.868	0.926
SU2	0.882	0.923
SU3	0.877	0.935
SU4	0.879	0.937
Economic impacts (EI)			0.774	0.848	0.869	0.908	0.689	0.767
PEI1	0.784	0.838
PEI2	0.774	0.794
PEI3	0.813	0.863
NEI1ª	0.563	0.680
NEI2ª	0.544	0.666
Social impacts (SI)			0.741	0.826	0.852	0.658	0.896	0.741
PSI1	0.737	0.722
PSI2	0.730	0.798
NSI1ª	0.688	0.797
NSI2ª	0.717	0.754
NSI3ª	0.731	0.816
Cultural impacts (CI)			0.788	0.862	0.877	0.703	0.917	0.786
PCI1	0.808	0.865
PCI2	0.839	0.886
NCI1ª	0.607	0.700
NCI2ª	0.692	0.741
Environmental impacts (ENI)			0.803	0.870	0.883	0.716	0.920	0.794
PENI1	0.709	0.809
PENI2	0.724	0.802
NENI1ª	0.738	0.747
NENI2ª	0.670	0.774
NENI3ª	0.682	0.769

The items marked have been recoded to avoid direct and inverse items in the same analysis. That is: 1 was changed to 5, 2 to 4, 4 to 2, and 5 to 1.

Reliability was also checked using Cronbach’s alpha (CA) and composite reliability (CR) tests, using as recommended thresholds CA > 0.7 and CR > 0.7 (Vinzi, 2010; Hair et al., 2011). The results of these tests (see Table 4) show that both indicators score higher than 0.7 in both groups, which indicates adequate levels of reliability.

Finally, the convergent validity of the measurement model was accepted as the AVE of the constructs was higher than 0.5 (Vinzi, 2010; Hair et al., 2011). The discriminant validity was also accepted as all the correlations (see Table 5) were lower than the square of the AVEs (Fornell & Larcker, 1981).

Table 5.

Discriminant Validity Assessment.

	Millennials					Over 35s
Constructs	CI	EI	ENI	SI	SU	CI	EI	ENI	SI	SU
CI	0.839					0.886
EI	0.697	0.830				0.786	0.876
ENI	–0.326	–0.305	0.846			–0.410	–0.403	0.891
SI	0.687	0.667	–0.375	0.811		0.805	0.782	–0.457	0.861
SU	0.674	0.798	–0.398	0.689	0.877	0.758	0.840	–0.520	0.757	0.930

Note. Fornell-Larcker Criterion. The square roots of the AVEs are shown diagonally in bold.

The Structural Model

Figure 2 shows the structural model relating the residents’ perception of economic, social, cultural, and environmental impacts with their support for P2P vacation accommodations. The model was tested for (i) millennial residents and for (ii) residents over 35. The path coefficient analysis shows that in both groups there is a statistically significant influence of the perception of the economic, social, cultural, and environmental impacts on their support for P2P vacation accommodations. In both groups, the greatest influence on the formation of support corresponds to the perceived economic impacts.

To complete the evaluation of the structural model, the explanatory power (R ²) of the endogenous construct was calculated (support for P2P vacation accommodation activity). The obtained R ² values of 0.69 for millennials and 0.76 for the over 35s, both very close to 0.7, indicate a sufficiently high and acceptable explanatory power, under behavioral research standards (Hair et al., 2014).

Multigroup Analysis

Finally, a multi-group analysis was performed. The goal of this analysis was to unveil whether the sense and intensity of the influence of the perception of impacts on the residents’ support for P2P vacation accommodations vary between generations. Following Henseler et al. (2016) recommendations for algorithms such as PLS-SEM, the measurement invariance was established before proceeding (see Table 6), using the measurement invariance of composites (MICOM) approach.

Table 6.

Invariance Measurement Testing.

		Compositional invariance (Correlations = 1)			Equal mean assessment			Equal variance assessment
Constructs	Configural invariance (Same algorithms for both groups)	C = 1	Confidence interval	Partial measurement invariance established	Differences	Confidence interval	Equal	Differences	Confidence interval	Equal	Full measurement invariance established
SU	Yes	1.000	[1, 1.000]	Yes	0.300	[–0.089, 0.095]	No	–0.291	[–0.122, 0.126]	No	No
EI	Yes	0.999	[0.999, 1.000]	Yes	0.268	[–0.094, 0.095]	No	–0.275	[–0.137, 0.14]	No	No
SI	Yes	0.999	[0.998, 1.000]	Yes	0.145	[–0.091, 0.095]	No	–0.270	[–0.131, 0.127]	No	No
CI	Yes	1.000	[0.998, 1.000]	Yes	0.324	[–0.09, 0.096]	No	–0.342	[–0.148, 0.147]	No	No
EnI	Yes	0.999	[0.997, 1.000]	Yes	–0.104	[–0.094, 0.09]	No	–0.295	[–0.128, 0.134]	No	No

The multigroup analysis was conducted using two nonparametric tests: the Henseler test (Henseler et al., 2009) and the permutation test (Chin & Dibbern, 2009). Both of them compare path coefficients between groups. Henseler’s MGA test directly compares group-specific bootstrap estimates from each bootstrap sample. According to this method, a p-value lower than .05 or higher than .95 indicates a significant difference of 5% between the trajectory-specific coefficients of the two groups (Henseler et al., 2009; Sarstedt et al., 2011). Similarly, the permutation test also compares the path coefficients, and differences are at the 5% level of significance only if the p-value is less than 0.05.

The results of both tests (see Table 7), contrary to what was hypothesized, indicate that no statistically significant differences could be confirmed in the sense and intensity of the relationships between the models. There is no confirmed evidence, so to speak, that the influence of the perception of economic, social, cultural, and environmental impacts on the support for P2P vacation accommodations significantly differs between generations. Hence, H1b, H2b, H3b, and H4b could not be backed.

Table 7.

Structural Relationships and Multi-Group Analysis.

		Path coefficients				Confidence interval (95%)		Path coefficient difference	p-value difference (one-tailed)
Hypotheses	Relationships	Millennials		Over 35s		Millennials	Over 35s	Path coefficient difference	Henseler’s MGA		Permutation test		Supported
H1c	EI –> SU	0.547	***	0.556	***	[0.504, 0.647]	[0.534, 0.634]	–0.008	0.478	ns	0.472	ns	No/No
H2c	SI –> SU	0.198	***	0.115	**	[0.091, 0.272]	[0.166, 0.298]	0.083	0.208	ns	0.203	ns	No/No
H3c	CI –> SU	0.118	***	0.154	***	[0.051, 0.185]	[0.034, 0.159]	–0.037	0.648	ns	0.355	ns	No/No
H4c	EnI –> SU	–0.118	***	–0.180	***	[–0.134, 0.025]	[–0.045, 0.07]	0.062	0.137	ns	0.129	ns	No/No

Note. In Henseler’s MGA method, a p-value lower than .05 or higher than .95 indicates significant differences between specific path coefficients across two groups at the 5% level.

Significance level: ***p < .001. **p < .01. *p < .05; ns no significance.

Conclusion and Discussion

This study responds to the call launched by D. Y. Kim & Park (2020) to explore, in the widest sense possible, how millennials are shaping tourism today. It analyzes how belonging to one or another generation moderates residents’ support for P2P vacation accommodations, their perception of the impacts derived from the activity, and the influence of those perceptions on their levels of support. This research contributes to expanding the understanding of how residents’ support for peer-to-peer vacation accommodations is backed. Such knowledge is crucial to helping destination managers to implement and evaluate policies that aim to foster peaceful, successful, and sustainable developments (Sharpley, 2014).

In this respect, our research reveals that millennials, as a generation, display a distinctive, greater than their older counterparts, support for P2P vacation accommodations. This finding would be in line with a general view that the millennial generation shows a more positive attitude toward collaborative consumption (Činjarević et al., 2019; Lamberton & Rose, 2012; Olson, 2013; Sacks, 2011). It also clarifies a sometimes contradictory view of the influence of generation on residents’ attitudes toward tourism, supporting, in the specific case of P2P vacation accommodations, the theory that the older the residents, the less positive their attitudes toward tourism development are (Bagri & Kala, 2016; Cavus & Tanrisevdi, 2002; Sinclair-Maragh, 2017), and not backing that older residents tend to be more willing to lend support to tourism developments (Deng et al., 2011; McGehee & Andereck, 2004; Nugroho & Numata, 2022; Rasoolimanesh et al., 2015; Tomljenovic & Faulkner, 2000).

Surprisingly, differences in support amongst generations do not come from a diverse decision-making process, as sometimes has been suggested (Boyd, 2010; Gardiner et al., 2014). Instead, they originate from a different intensity in the perception of the impacts. In our case, the millennials’ alleged special sensitivity to economic, cultural, social, and environmental dimensions (Botsman & Rogers, 2010; Gansky, 2010; Lamberton & Rose, 2012; Sacks, 2011) would boost their perception of the positive impacts but does not originate significant differences on the structural influence that each of the dimensions has on the residents’ support. In fact, the millennials and the older generations coincide in that the dimension with the greatest influence is the economic one, followed by the social, cultural, and environmental impacts. These findings reinforce the view that the millennials, younger, more open-minded, and less scared of change than their previous generations (Arthursson, 2016), do not build support for p2p vacation accommodation developments differently, but have a greater than their previous generations ability to perceive the numerous positive impacts. It overcomes the traditional view stating that older generations, because of their experience, perceive more the benefits of tourism development (McGehee & Andereck, 2004), and highlights the stability, among generations, of the explicative model of residents’ support for P2P vacation accommodations used to back this research (Garau-Vadell et al., 2019).

For tourism destinations, the results provide useful indications regarding what they should focus on if they want to promote support for the new activity. Overall, the results unveiled that all residents are especially sensitive to the economic impacts. Therefore, to gain their support, tourism destination management policies should prioritize that as many residents as possible economically benefit from the new activity. In this respect, restrictive regulations of P2P vacation accommodation developments, which limit residents’ access to the economic benefits, may not be the most appropriate approach to gain their support. Instead, flexible regulation allowing a broad participation of residents but addressing the negative impacts (e.g., involving platforms in tax collection, facilitating tax regulation, reserving parking spaces for residents, launching campaigns to promote good behavior among guests, etc.), would probably be more effective.

Specifically, the knowledge gained from this study can help destination managers to effectively forecast how specific policies will affect residents’ support for P2P vacation rentals, indicating how support will vary across generations in the face of changes in perceptions of impacts. In this respect, the results of the study have shown that there exist significant differences in how residents perceive the impacts of the new activity, thus facilitating the launching of targeted generational campaigns (e.g., undertake specific campaigns addressed to older residents to help increase their perception of the positive impacts of the activity) to efficiently gain more support for the activity, if this is the goal of the destination managers.

Finally, despite the relevance of the results obtained, the authors acknowledge that they would benefit from a longitudinal and cross-national extension of the research to further sustain or reject them. Additionally, the current covid-19 pandemic situation may have expanded the dimensions of impacts that residents take into account when evaluating their support for a tourism activity and modified their structural influence. Probably health and safety issues will have to be considered now as key residents’ support influencing variable, in addition to the traditional economic, social, cultural, and environmental dimensions. Consequently, the moderating role of generation belonging on support to p2p vacation accommodation developments will have to be reviewed under this new premise. Exploring these topics would probably be a logical progression from this research, and this should be undertaken sooner rather than later.

Footnotes

Declaration of Conflicting Interests

The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Funding

The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the Spanish Ministry of Science and Innovation under grant PID2020-114788RB-I00.

ORCID iDs

Joan B. Garau-Vadell

Desiderio Gutiérrez-Taño

Ricardo J. Díaz-Armas

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