What to Do After Visiting a Museum? From Post-consumption Evaluation to Intensification and Online Content Generation

Abstract

In the context of museums, this article analyses to what extent visitor evaluation of the experience (attainment, emotion, and satisfaction) drives their short-term online behavior: consumption of further online content (intensification) and posting content in online sites (content generation). On the basis of the optimal stimulation level theory and on the balance theory, it proposes that the evaluation of the experience has an inverted U-effect on visit intensification intention while a U-effect on the intention to generate content after the visit. Findings indicate that satisfaction fosters the intention to intensify or consume further content, while the perception of having gained the maximum attainment and emotional value limits it. On the other hand, while satisfaction and the perception of a profitable visit motivate visitors to post online comments, poor experiences in museums have no impact on the generation of online content.

Keywords

tourist experience museums intensification user-generated content

Introduction

Understanding how tourists’ experiences impact on their behaviors is essential vis-à-vis evaluating the performance and success of a tourist service or destination, such that it has become a common topic in tourism literature. A large body of work is exploring which factors determine tourists’ intentions to return to a destination in the future (Bigné, Sánchez, and Sánchez 2001; Chi and Qu 2008; Prebensen, Woo, and Uysal 2014; Sohn, Lee, and Yoon 2016; Yoon and Uysal 2005; Yuksel, Yuksel, and Bilim 2009). However, loyalty and revisiting imply long-term behaviors, which are difficult to predict on the basis of current postconsumption evaluation (Jang and Feng 2007). As an alternative, short-term behaviors, which involve immediate actions, can be better anticipated by evaluating the current experience (Bigné, Mattila, and Andreu 2008). A positive evaluation of the tourist experience also stimulates short-term intentions, such as participating in eWOM and searching for further information or activities, which may have an immediate impact on a destination’s success. Tourism websites, blogs, and social networks allow tourists to share their experiences with many potential visitors. Public dissemination of other tourists’ experiences (with comments and images) provides relevant and credible sources of information for many tourists and can have a great influence on their decision process, even more than travel brochures, catalogs, or official sites (Parra-López et al. 2011; Xiang and Gretzel 2010). Moreover, consuming further information about the destination keeps the tourist in touch with it, thus possibly maintaining or increasing the desire to return in the future.

In the current research, we analyze the influence of postconsumption evaluation of an experience on short-term behavior intentions in the context of museums. After the visit, the visitor’s evaluation of the experience is reflected in perceived value (Prebensen, Woo, and Uysal 2014) and satisfaction (Assaker, Vinzi, and O’Connor 2011; Chi and Qu 2008; Yoon and Uysal 2005). This postconsumption evaluation can lead tourists to maintain their activity, intensifying the experience by consuming additional online content and sharing their experiences and memories. To this aim, museum websites (informational content, virtual visits, or online shops) and social networks are new spaces for visitor participation and interaction with museums. Thus, we ask to what extent visitor evaluation of the experience drives these short-term online behaviors. Specifically, we propose that the effect of postconsumption evaluation (attainment, emotion, and satisfaction) on postconsumption short-term behavior intention (intensification and online content generation) is not lineal. Based on the optimal stimulation level theory, we posit an inverted U-effect on visit intensification. When the experience is full and intense, visitors reach the optimal level of stimulation and the intention to further consume decreases. On the other hand, based on the balance theory, we propose that the evaluation of the experience has a U-effect on the intention to generate content after the visit: both the most positive and most negative experiences drive visitors to share them in order to achieve emotional equilibrium.

Overall, our research makes two major contributions. First, we demonstrate that post-purchase short-term behavior in online sites is conditioned by the onsite experience, but that the effect in not always lineal. The outcomes of our results suggest that satisfaction with the visit has a positive effect on the intention to intensify the experience with further content, but that the perception of having achieved the maximum attainment and emotion reduces the intention to consume additional online content. Second, our findings indicate that museum visitors are more predisposed to share what they have seen than what they have felt. The best experiences in terms of satisfaction and attainment, that is, that the visit has been full and profitable, motivate the generation of online content, while the emotional value (which may be more intimate and personal) has no impact on participation in online content.

Literature Review

Postconsumption Evaluation: Attainment, Emotions, and Satisfaction

The tourist experience can be evaluated through two dimensions: the quantitative dimension and the qualitative dimension. While the quantitative dimension reflects aspects related to the amount consumed at the destination, the qualitative dimension principally refers to the emotional aspects which the tourist attributes to the activities undertaken (Antón, Camarero, and Laguna-García 2017a). In this line, in the current study we consider three aspects to evaluate visitor experience in a museum: the attainment (the quantitative aspect), the emotion (the qualitative aspect), and the satisfaction with the visit (as both a quantitative and qualitative evaluation).

Attainment

Attainment is seen as the perception that the investment made has been capitalized on and rewarded (Antón, Camarero, and Laguna-García 2017a). It is the consequence of the consumer’s conscious and rational search for an outcome and is therefore mainly a cognitive evaluation of the experience in terms of effectiveness based on the belief that the activity has proven both full and beneficial. Attainment is related with a knowledge-seeking experience, a way of experiencing tourism described by Gnoth and Matteucci (2014) as the acquisition of new knowledge, the memory of having been to certain places, actually seen certain things, and learned from them. Gnoth and Matteucci (2014) explain that museum tourism may be included in this pattern of behavior, as it focuses on satisfying socially formed norms and expectations. In the context of museums, attainment would refer to exploiting the visit, that is, visitors’ perception that they have made good use of their time and have had an efficient visit in terms of the route taken and the content visited.

Emotions

Emotions are a mental state of readiness that arises from cognitive appraisals of events or thoughts (Bagozzi, Gopinath, and Nyer 1999) and represent critical aspects when describing a tourist’s experiences (Li, Scott, and Walters 2015). The dimensional approach of emotions developed by Mehrabian and Russell (1974) proposed three dimensions (pleasure, arousal, and dominance) that differentiate speciﬁc emotions from one another. However, there is widespread consensus in considering pleasure and arousal as the main dimensions of the emotions (Bigné, Andreu, and Gnoth 2005). Pleasure refers to the pleasantness of an experience and arousal to an activation of the individual’s internal state. In the context of a museum visit, emotions therefore reflect the affective perception of the consumer experience (Holbrook 1999). It involves the pleasure brought about by the visit and the feelings it has aroused. Moreover, recent studies analyze additional aspects of emotions, such as enjoyment or playfulness (Wu and Holsapple 2014). Mathwick, Malhotra, and Rigdon (2001) define playfulness as “the intrinsic enjoyment that comes from the engagement in activities that are absorbing, to the point of an escape from the demands of the day-to-day world.” Padilla-Meléndez, Aguila-Obra, and Garrido-Moreno (2013) argue that when individuals are in the playfulness state, they ﬁnd the interaction intrinsically interesting, as they are involved in the activity for pleasure and enjoyment.

Satisfaction

Consumer satisfaction is defined as a cognitive and affective judgment that derives from the consumer’s experience with the product or service (Bigné, Andreu, and Gnoth 2005; Oliver 1997). Satisfaction emerges from comparing the experience with previous expectations. Put differently, satisfaction refers to the feelings generated by cognitive and emotional aspects of the goods and services, as well as an accumulated evaluation of various components and features. Therefore, in the current context, satisfaction is understood as the cognitive and emotional reaction derived from visiting a museum. Although the literature has established a causal relationship between the perceived experience (perceived value, emotions, etc.) and satisfaction (Bigné, Mattila, and Andreu 2008; Cronin, Brady, and Hult 2000; Parasuraman and Grewal 2000; Sánchez et al. 2006), the current work does not delve deeply into this relationship but rather considers the effect of the three evaluation aspects (attainment, emotions, and satisfaction) on visitor behavior.

In the area of tourism, numerous studies support the relationship between tourists’ experiences and their behavioral intentions (Chen and Chen 2010, 2013; Hosany and Witham 2010; Oh, Fiore, and Jeoung 2007; Prebensen, Woo, and Uysal 2014; Williams and Soutar 2009; among others). Said future behavior has often been measured as the intention to revisit the destination and to recommend the visit to others (Baker and Crompton 2000; Oppermann 2000). Several studies have confirmed the positive effect of emotions on loyalty to a destination and the intention to recommend it (Bigné, Mattila, and Andreu 2008; Hosany and Prayag 2013; Lee et al. 2008). Likewise, satisfaction is one of the main antecedents of future consumer behavior (loyalty, repurchase intentions, WOM, etc.) (Bigné, Sánchez, and Sánchez 2001; Chi and Qu 2008; Kozak and Rimmington 2000; Yoon and Uysal 2005; Yuksel, Yuksel, and Bilim 2009). In the tourism domain, numerous studies have reported the positive effect of satisfaction on the intention to return to a destination (Chen and Chen 2013; Chi and Qu 2008; Prayag et al. 2017; Severt et al. 2007; Sohn, Lee, and Yoon 2016; Yoon and Uysal 2005), although some authors urge caution when establishing a direct relation between the two variables (Antón, Camarero, and Laguna-García 2017b; Jang and Feng 2007).

However, in the context of museums, revisiting does not reflect immediate tourist behavior. Many of the museum’s visitors (except for local visitors) will not visit it again in the short term. Short-term behaviors are, basically, intensification and content generation. These behaviors are, obviously, determined by the evaluation of the experience. In the following subsections, we explain the kind of relationship that may emerge between visitor experience and short-term behaviors.

Intensification and the Optimal Stimulation Level Theory

One type of short-term tourist behavior is visit intensification. Intensification refers to visitor intention to extend the experience (Holbrook and Gardner 1993, 1998) by searching for further information about the destination (the museum, the content, etc.) or by making the experience more tangible through purchasing souvenirs, gifts, and photos (Bigné, Mattila, and Andreu 2008; Dong and Siu 2013). It reflects the interest and motivation that individuals maintain after the visit (De Rojas and Camarero 2008). In the context of museums, visitors may seek to intensify the visit with subsequent action such as participating in other activities promoted by the museum, searching for further information in the website, or following the museum’s social networks.

The effect of the evaluation of the experience on visit intensification can be explained on the theoretical bases of the optimal stimulation level theory. According to this theory “the relationship between stimulation obtained from the environment or through internal means and a person’s affective reaction to stimulation follows an inverted U-shaped function, with intermediate levels of stimulation perceived as the most satisfying” (Steenkamp and Baumgartner 1992). An individual’s optimum stimulation level has been related with exploratory consumer behavior (curiosity, information seeking, variety-seeking behavior, or innovative behavior). Based on this theory, we maintain that the effect of visitor experience evaluation on visit intensification follows an inverted U-shape. The evaluation of the experience (in terms of attainment, emotion, and satisfaction) has a positive effect on intensification, yet becomes negative when the visitor has reached a stimulation threshold.

Consumers’ short-term behavioral intentions are expected to be consistent with their level of satisfaction (Bolton 1998) as well as the attainment and emotional value of their experience. Dong and Siu (2013) indicate that a more favorable service experience should lead to a greater tendency to intensify it. The positive experience will lead visitors to become consumers of other contents of the museum. Having experienced a profitable and pleasing visit may encourage visitors to intensify the experience by seeking further information about the museum on the webpage and social networks or by participating in other activities promoted by the museum. When the visit generates interest but there are other aspects to discover, the visitor will likely search for additional content on other sources. However, when visitors have exploited the visit, have engaged in most of the activities proposed by the museum, and so perceive that they have acquired the maximum degree of knowledge about the museum content, they will have reached the optimal level of stimulation and will not have any motivation to search for further information. At the other end of the scale, visitors who perceive that the visit has not proven in the least useful or valuable, that they have failed to gain anything at all out of the museum, and that the emotional value has been low, will lose interest in the museum and will display no intention to intensify the visit. Therefore,

Hypothesis 1: Satisfaction with the visit (hypothesis 1a), the attainment (hypothesis 1b), and the emotional value (hypothesis 1c) of the visit have an inverted U-effect on the intensification of the visit.

Content Generation and the Balance Theory

Content generation implies sharing the positive or negative experience with others. Tourists like to talk about what they have learnt and felt during their visit (Carballo et al. 2015) and to evoke pleasant (or unpleasant) memories of their stay (Ali, Ryu, and Hussain 2016). Moreover, because of the expansion of social networks and travel websites, tourists can share their experiences and recommend, or not, a museum to thousands of people. Therefore, by actively participating in these sites, tourists and visitors generate content about the destinations (in our case, the museums) and contribute toward building a shared knowledge. Visitors can publish different content in websites specialized in tourism or travel (such as TripAdvisor), in blogs or in social networks. The impact of user-generated content is particularly important for the tourism and hospitality industry because it influences travelers’ information searches (Dey and Sarma 2010; Gretzel and Yoo 2008) and travel planning behaviors (Ayeh, Au, and Law 2013; Fotis, Buhalis, and Rossides 2012). Moreover, user-generated content becomes a relevant source of information for service providers (Presi, Saridakis, and Hartmans 2013): tourists’ information is more credible, is widely disseminated, and remains over time, in addition to which eWOM allows interaction between tourists.

The literature has also explored the antecedents of user-generated content in the context of tourism (Parra-López et al. 2011; Wang and Fesenmaier 2004; Yoo and Gretzel 2011). These studies have focused on tourists’ benefits and incentives, positively relating tourist intention to generate online content with functional, social, psychological, and hedonic benefits, as well as with altruism, trust, or personal skills. However, the intention to create online content is negatively related with the costs of use (effort, difficulty of use, and loss of privacy). Similarly, in the context of museums, it is expected that, after the visit, individuals may be willing to share their experiences with other potential visitors in social networks and other online communities.

Whatever the expected benefits and costs determining visitor intention to generate content, the main driver of this behavior is the perceived experience. Consumer satisfaction as well as their emotions are determinant factors in user generated content (Zeelenberg and Pieters 2004). In this sense, the effect of visitor evaluation of the experience on the intention to generate content can be explained on the basis of the balance theory. According to Hennig-Thurau et al. (2004), individuals try to restore equilibrium when it has become unbalanced because of a strong positive or negative consumption experience. One way to restore the equilibrium is “expressing positive emotions and venting negative feelings” (Hennig-Thurau et al. 2004). In the context of visiting a museum, we propose that, after the visit, individuals are able to form their own view of the museum (positive or negative) and may be willing to share their learning or emotional experience with other potential visitors in social networks and other online communities.

As for the positive experience, when visitors perceive that they have seen and learnt (high attainment), have felt intense emotions, and rate the visit as having been fully satisfactory, they will want to appreciate and recognize the museum’s value and to help other visitors by sharing their positive feelings and expressing their emotions. A pleasant experience may therefore play a decisive role in their intention to share and recommend the trip to those around them (Chen and Tsai 2007; Um, Chon, and Ro 2006).

On the other hand, a dissatisfying experience, scant attainment or a perceived lack of hedonic value, will lead to negative feelings being vented through the publication of online comments. These seek to offset the discontent and dissonance associated with negative emotions and can serve to lessen the frustration, reduce anxiety, and let off steam (Engel, Blackwell, and Miniard 1993; Hennig-Thurau et al. 2004). Negative WOM is frequently motivated by a desire to punish organizations that have not promoted a memorable experience to consumers through incompetent, inefficient, or irresponsible attitudes; behaviors; tactics; strategies; or products (Hennig-Thurau et al. 2004). Several authors have concluded that negative WOM is driven by a desire for anxiety reduction, vengeance, as well as advice seeking (Sundaram, Mitra, and Webster 1998) and the wish to help other consumers (Zeelenberg and Pieters 2004). Literature on tourism also show that tourists tend to post online reviews of negative experiences in social networks (Pantano and Di Pietro 2013; Presi, Saridakis, and Hartmans 2013).

Therefore, in the case of museums, visitors may be willing to share their experiences and opinions in the museum’s social networks and other online opinion communities both when they have experienced tremendous satisfaction, have perceived high emotional value, and have exploited the visit and when they have not been satisfied and have failed to perceive any value in the museum. On the contrary, medium levels of satisfaction, attainment, and emotion will not represent an unbalanced emotion and will lead to more indifference and less intention to generate content. Therefore,

Hypothesis 2: Satisfaction with the visit (hypothesis 2a), the attainment (hypothesis 2b), and the emotional value (hypothesis 2c) of the visit have a U effect on the intention to generate content after the visit.

Methodology

Sample and Data Collection

Data were collected through a survey conducted at five Spanish museums: the Reina Sofía National Museum Centre of Art in Madrid (MNCARS, a contemporary art museum with 84,000 m² of exhibition space), the Guggenheim Museum of Bilbao (a 24,000-m² contemporary art museum), the National Archaeological Museum of Madrid (MAN, a 23,000-m² archaeological museum), the Principe Felipe Science Museum in Valencia (MCPF, a 42,000-m² science museum), and the Granada Science Museum (a 70,000-m² science museum).

Museums were selected from among the most important and visited in Spain and taking into account their location so as to cover as wide an area of the country as possible. Moreover, given that experiences and behavior depend to a large extent on the kind of exhibition being visited, museums housing different types of exhibitions were chosen (contemporary art, archaeology, and science). The aim was to make sure that the range of surveyed visitor experiences and behaviors was as wide as possible and to ensure diversity of the sample.

A questionnaire was designed to measure the variables in the model. The questionnaire was revised by the managers of two museums, and some questions were adapted to the specificities of each museum. A pilot test was conducted to estimate the interview time and to improve the structure and layout of the questions.

A group of professional surveyors were in charge of data collection. In each museum, an interviewer had to choose 35 tourists randomly (not local visitors), on different days of the week and at different times of the day (morning and afternoon). The surveyors were indicated to fulfill established gender and age quotas, that is, a sample proportional to the Spanish population (www.ine.es). Visitors were contacted at the hall at the end of the visit. Data were collected in July 2015.

A total of 175 valid questionnaires were collected. Table 1 summarizes the distribution of the sample by age, gender, origin of the visitor, and the day of the week in which the questionnaires were collected. Overall, 80.8% of the sample were Spanish nonlocal visitors (with a distribution by gender and age proportional to the Spanish population), while 19.2% were international visitors.

Table 1.

Sample Characteristics.

Day of the Week		Age		Origin		Gender
Monday	13.7%	Up to 25	22.9%	Spanish visitors	80.8%	Men	48.0%
Tuesday	10.3%	From 26 to 35	14.2%	Foreign visitors	19.2%	Women	52.0%
Wednesday	33.1%	From 36 to 45	20.0%
Thursday	10.2%	From 46 to 55	16.6%
Saturday	22.3%	From 56 to 65	9.2%
Sunday	10.3%	Over 65	17.1%

Measurement of Variables

Most of the measurement scales of the variables in this study were adapted from previous studies to the context of visiting a museum and others were created ad hoc. Five-point Likert-type scales were used.

An ad hoc scale was created to measure intensification on the basis of the previous works of De Rojas and Camarero (2008) and Bigné, Mattila, and Andreu (2008), with three items dealing with visitor intention to participate in future activities and search for information about the museum on the website and in social networks. The scale to measure visitors’ content generation was also created ad hoc for this study, adapting items related to participation and content generation in social networks (Shin, Song, and Biswas 2014; Szymanski 2001). Specifically, we used three items indicating the visitor’s desire to share the experience through social networks or other travel websites.

Satisfaction was measured by a three-item scale based on Oliver’s (1980) scale and adapted to the case of museums by Camarero and Garrido (2011). In order to reflect emotional value, we measure pleasure and arousal (the most common dimensions of the Mehrabian and Russell-PAD model; Russell 1980) and playfulness (Wu and Holsapple 2014). On the basis of the self-assessment manikin (Bradley and Lang 1994), each dimension was measured with a differential semantic item and emoticons that illustrated the scale points. Finally, attainment was measured by a three-item scale reflecting to what degree it was felt that the most had been made of the visit (Antón, Camarero, and Laguna-García 2017a).

As control variables, we introduced age, previous knowledge, and previous expectations about the museum content. Falk and Dierking (2000, p. 87) state that “visitors to museums do not come as blank slates. They come with a wealth of previously acquired knowledge, interests, skills, beliefs, attitudes and experiences.” Prior knowledge endows the museum’s proposal with value and shape visitor experience. On the other hand, satisfaction and perceived value emerge from comparing the experience with previous expectations (Oliver 1980). Thus, previous knowledge and previous expectations about the museum content may influence short-term behavior intentions. According to several studies (Christofides, Muise, and Desmarais 2012), younger people are more prone to self-disclosure on social media. In the context of tourism, Bronner and De Hoog (2011) found that younger vacationers have a greater tendency to generate eWOM. We therefore introduced visitor age as a control variable. Age was measured as a numerical scale. Age distribution was 22.9% up to 25 years, 14.2% from 26 to 35 years; 20% from 36 to 45 years; 16.6% from 46 to 55 years; 9.2% from 56 to 65 years; and 17.1% over 65 years. Previous knowledge and previous expectations were measured as dichotomous variables. It was found that 95.4% had some previous knowledge about the museum and 4.6% had not. We measure if the visitor had entertainment or learning expectations. The distribution of entertainment expectations was 57.5% yes and 42.5% no; the distribution of learning expectations was 78.7% yes and 21.3% no.

Table 2 shows the variables used in the study and the measurement indicators together with the corresponding descriptive statistics (mean and standard deviation). In order to validate the measurement scales, a CFA was performed. The goodness of fit index (χ²(78)=189.24, p=0.000; GFI=0.879, comparative fit index = 0.890, root mean square error of approximation=0.09) and the loading factors confirm the reliability and convergent validity (Table 2). Table 3 shows the correlation matrix and the Fornell–Larcker criterion of discriminant validity.

Table 2.

Descriptive Statistics and CFA Results.

	Mean	SD	Loading Factors
Intensification (intention) (α = 0.77, CR = 0.86, AVE = 0.66)
I would be happy to participate in future museum activities.	3.44	1.45	0.837
I intend to seek out more information about the museum on its web or social networks.	2.35	1.44	0.804
I intend to follow the museum on its social networks.	1.98	1.28	0.806
Content generation (intention) (α = 0.73, CR = 0.85, AVE = 0.65)
I intend to talk about my experience in social networks or other websites (e.g., blogs)	2.02	1.36	0.798
I would make suggestions to the museum if asked to or if given the chance by them.	2.85	1.26	0.762
I would be willing to give my opinion of the museum on travel websites such as TripAdvisor	2.25	1.49	0.859
Emotion (α = 0.77, CR = 0.86, AVE = 0.68)
Pleasure	4.27	0.68	0.843
Arousal	4.29	0.69	0.721
Playfulness	4.09	0.83	0.892
Attainment (α = 0.60, CR = 0.78, AVE = 0.54)
I have had time to see everything	3.08	1.24	0.674
I have made the most of the time during the visit	3.89	0.96	0.706
I have seen everything I wanted to	3.26	1.37	0.827
Satisfaction (α = 0.76, CR = 0.86, AVE = 0.68)
It is one of the best cultural activities I have ever had	3.10	1.03	0.727
I have no regrets about having visited the museum	4.12	1.00	0.848
I feel satisfied with the decision to visit the museum	4.24	0.90	0.892

Table 3.

Correlation Matrix.

	Satisfaction	Emotion	Attainment	Intensification	Content Generation
Satisfaction	0.825
Emotion	0.305**	0.822
Attainment	0.122	0.071	0.738
Intensification	0.476**	0.165*	0.276**	0.816
Content generation	0.466**	0.231**	0.253**	0.686**	0.808

Note: The main diagonal shows the square root of the extracted variance for the reflective variables (Fornell–Larcker criterion of discriminant validity).

Significance levels: *p < 0.05; **p < 0.01.

Analysis and Results

A hierarchical regression analysis was performed to test the proposed hypotheses. The measurement scales were reduced to a single factor in order to measure each variable. The analysis was carried out in three steps. First, the control variables were introduced; second, the direct effects of satisfaction, attainment, and emotion; and third, the quadratic effects of satisfaction, attainment, and emotion. Results are shown in Tables 4 and 5. The collinearity diagnosis indicates that multicollinearity is not a problem in the analysis and with regard to interpreting results.

Table 4.

Hierarchical Regression Analysis (Dependent Variable: Intensification).

	Dependent Variable: Intensification			Collinearity Diagnosis
	Step 1	Step 2	Step 3	Tolerance	VIF
(Constant)	0.794***	0.610**	0.850***
Age	−0.016***	−0.013***	−0.014***	.935	1.069
Lack of knowledge (0=no; 1=yes)	−0.253	0.096	−0.022	.781	1.280
Entertainment expectation (0=no; 1=yes)	−0.469**	−0.253^†	−0.264^†	.846	1.182
Learning expectation (0=no; 1=yes)	0.449*	0.370*	0.389*	.935	1.070
Satisfaction		0.411***	0.423***	.631	1.584
Attainment		0.167*	0.123⁺	.869	1.151
Emotion		−0.004	−0.034	.749	1.334
Satisfaction²			0.003	.573	1.744
Attainment²			−0.115*	.871	1.148
Emotion²			−0.108*	.830	1.205
Adjusted R-squared	0.149	0.333	0.362
F	7.993***	12.389***	10.059***
Change in F (sign.)	7.993***	15.317***	3.313*

Note: VIF = variance inflation factor.

Significance levels: †p < 0.10; *p < 0.05; **p < 0.01; ***p < 0.001.

Table 5.

Hierarchical Regression Analysis (Dependent Variable: Content Generation).

	Dependent Variable: Content Generation			Collinearity Diagnosis
	Step 1	Step 2	Step 3	Tolerance	VIF
(Constant)	0.774***	0.591**	0.487*
Age	−0.013**	−0.011**	−0.010**	.935	1.069
Lack of knowledge (0 = no; 1 = yes)	−0.627^†	−0.329	−0.595^†	.781	1.280
Entertainment expectation (0 = no; 1 = yes)	−0.504**	−0.288*	−0.365*	.846	1.182
Learning expectation (0 = no; 1 = yes)	0.125	0.035	0.064	.935	1.070
Satisfaction		0.365***	0.447***	.631	1.584
Attainment		0.166*	0.142*	.869	1.151
Emotion		0.086	0.111	.749	1.334
Satisfaction²			0.138*	.573	1.744
Attainment²			−0.033	.871	1.148
Emotion²			0.024	.830	1.205
Adjusted R-squared	0.113	0.290	0.297
F	6.171***	10.435***	7.855***
Change in F (sign.)	6.171***	14.079***	1.568^a

Note: VIF = variance inflation factor.

Significance levels: †p < 0.10; *p < 0.05; **p < 0.01; ***p < 0.001.

Since the change in F between steps 2 and 3 shows no significant improvement, we estimated the model again without including the variables that did not prove significant (“learning expectation,” “emotion,” “attainment²,” and “emotion²”) to obtain a more parsimonious model. After eliminating the nonsignificant effects, we observed that the variable added in model/step 3 (the quadratic effect of satisfaction) substantially improved the explanation of content generation.

As shown in Table 4, satisfaction has a positive effect on intensification, although the inverted U-effect is not confirmed (hypothesis 1a is rejected). The positive evaluation of the museum in terms of satisfaction does not diminish visitor intention to consume additional museum content.

Hypothesis 1b is partially supported. In the relationship between attainment and intensification, both the linear and the quadratic effects prove significant, although we did find a decreasing marginal effect (Figure 1A). In this case, because the quadratic effect is negative and the linear effect positive, the ratio of the linear and the quadratic term represent the point where the downward effect of the quadratic term cancels out the upward effect of the linear term. From this point on, the maximum level admitted by the visitor has been reached and the perception of having undertaken a comprehensive visit to the museum has no impact on the intention to consume anything else.

Figure 1.

Estimated quadratic effects: (a) Attainment-intensification; (b) Emotion-intensification; and (c) Satisfaction-content generation.

However, hypothesis 1c is supported. Emotion has an inverted U-effect on the intention to intensify the visit by consuming online content. In the relationship between emotion and intensification, only the quadratic effect is significant (Figure 1B), such that increased emotions foster intensification. Yet for values of emotion around 0 (mean of the variable), the intention to intensify the consumption of content decreases. As for the control variables, younger visitors display a greater intent to intensify the visit as do those who had no entertainment expectations and those who had learning expectations.

Table 5 shows the results for the dependent variable content generation. In this case, the change in F between step 2 and 3 shows no significant improvement. In order to be more conclusive about the nonlinear effects (step 3), we estimated more parsimonious models without including the effects that did not prove significant (learning expectation, emotion, and the quadratic effects of attainment and emotion). After eliminating these nonsignificant effects, we observed that the variable added in step 3 (the quadratic effect of satisfaction) significantly improved the explanation of content generation. Therefore, satisfaction has a linear and a quadratic effect on the intention to participate in creating online content about the experience. Nevertheless, as can be observed in Figure 1C, the relationship between satisfaction and content generation is not U-shaped, but J-shaped. The most satisfied visitors are those most willing to share their experience, while for low and medium levels of satisfaction, the intention to share the experience remains scant. Therefore, hypothesis 2a can be considered partially supported. The proposed U-effect of attainment and emotion on the generation of content is not supported (hypotheses 2b and 2c are rejected). Attainment, that is, the perception of having enjoyed a comprehensive visit, has a positive effect on the intention to share it in online sites, while in contrast the perceived emotion has no effect. As for the control variables, younger people, those with previous knowledge and those who had no entertainment expectations exhibit greater intention to generate online content.

Table 6 summarizes the results obtained in relation with each hypothesis.

Table 6.

Results of the Proposed Hypotheses.

Hypotheses	Proposed Effect	Estimated Effect	Result
Hypothesis 1a. Satisfaction → Intensification	Inverted U-effect	Positive	Rejected
Hypothesis 1b. Attainment → Intensification	Inverted U-effect	Decreasing marginal effect	Partially accepted
Hypothesis 1c. Emotion → Intensification	Inverted U-effect	Inverted U-effect	Accepted
Hypothesis 2a. Satisfaction → Content generation	U-effect	Increasing marginal effect	Partially accepted
Hypothesis 2b. Attainment → Content generation	U-effect	Positive	Rejected
Hypothesis 2c. Emotion → Content generation	U-effect	Not significant	Rejected

Discussion and Conclusions

In the current research, we draw on the optimal stimulus theory and the balance theory to explore the effect of evaluating onsite experience in museums and short-term behavior intentions in the online milieu. Results show that the intention to intensify the experience by consuming online content and the intention to share the experience and generate content depend on the onsite experience, although the effect is not linear.

Satisfaction with the visit fosters the intention to intensify the experience by participating in other activities organized by the museum, to follow the museum on social networks and to search for further information, while the perception of having gained the maximum value from the visit limits the intention to consume additional online content. When visitors perceive full value, that is, when they feel emotionally satiated and that they have been given everything they expected, they will not need to look for anything else. If satiated, the tourist will feel that the experience is complete and, therefore, that there is no continuity or further consumption. In contrast to previous works, which propose that the effect of perceived value on tourist behavior is linear and mediated by satisfaction (Prebensen, Woo, and Uysal 2014; Williams and Soutar 2009), our results demonstrate that the effect of attainment and emotion on future consumption behaviors is not linear.

As regards the intention to generate online content, the best experiences in terms of satisfaction and the attainment, that is, the perception of a profitable visit and having taken advantage of the time, motivate visitors to post comments on social networks or to rate the museum positively on opinion pages, while unsatisfactory experiences have no impact on participation in online content. Despite the literature that points to the high impact of negative experiences on negative eWOM (Sundaram, Mitra, and Webster 1998), even in the context of tourism (Pantano and Di Pietro 2013; Presi, Saridakis, and Hartmans 2013), our results show that visitors to museums are not willing to share negative evaluations. This result may indicate that museum visitors are reluctant to reveal their opinions when these run contrary to the socially accepted opinion. In other words, individuals might prefer not to publish a bad evaluation about a top museum. In addition, visitors may not dare to disclose their opinions because of a lack of self-confidence or the perception of their own low level of expertise. A similar behavior, contrary to reveal a negative opinion, could arise in the evaluation of other cultural products, such as literary masterpieces or theater performances.

Emotional value is also seen to have no impact on participation in online content. This unexpected finding indicates that museum visitors are more willing to share the side of the experience that proves easier to communicate (satisfaction and exploitation of the visit). However, the experienced emotion in museums seems to be perceived as a more intimate and personal aspect that does not deserve to be shared with other visitors or that is more difficult to express and convey in words or pictures.

Considering the findings, we propose certain managerial implications and recommendations that might prove useful for museum curators and managers. First, a museum visitor seeks to exploit the visit, see everything, make the most of the time spent there and ultimately experience positive emotions. Logic would suggest that when museums are able to provide these positive experiences, they are forging links with visitors and, as a result, the latter will be willing to participate in future activities and to consume online content (websites or social networks). However, since this idea might drive managers to offer exceptional experiences, a satiated tourist who has experienced a full and comprehensive physical visit will have no intention to further consume online content. Therefore, managers should seek to strike a balance between the content consumed during the visit and the unique content available online (for instance, additional didactic material, online games, videos, movies, etc.). The visit, although satisfactory, should not be satiating to encourage visitors to consume supplementary content.

Second, the perceived exploitation as well as satisfaction after the visit are the requirements for posting comments in social networks or rating the museum positively on opinion webpages. Since these comments, recommendations, and eWOM are essential to attract new visitors (at least, for the first time), museum managers should, of course, design visits that offer tourists maximum satisfaction in terms of content visited and learning but should also provide visits that are adapted to the time available to tourists and to their expectations. These results can be extended to other cultural attractions. The visits and tours designed should adapt to the tourists’ capacity to absorb the visit and to their expectations of the activities provided at a destination and the time devoted to each. As is widely known (Hosany and Witham 2010; Hosany et al. 2017), satisfied tourists and visitors draw other potential tourists through recommendations and determine a destination’s reputation and image. In fact, leisure and tourist attractions are activities that particularly stimulate eWOM communication (Bronner and De Hoog 2011).

But, what happens with not satisfied tourists? Since museum visitors are not willing to share negative evaluations, maybe because they are afraid that their opinions reveal a lack of knowledge, museum managers should also make an effort to collect these opinions, for instance with anonymous questionnaires when the visit has finished. In this way, negative evaluations and unfulfilled expectations might serve as information for adapting the tours and for providing different content to different kinds of visitor.

Another challenge for museums is to find mechanisms to encourage museum tourists to disclose their feelings and emotions. Curiously, the experienced emotion is not a motivation to comment the experience. As if museums were functional services, tourists neglect their emotions when they convey their impressions to others. Therefore, managers are required to be creative and offer stimulus to visitors who express these feelings, maybe not by means of written comments, but by means of photos or emoticons, or inviting them to choose the best memory of the visit, the most pleasurable situation, or the most amusing and captivating moment.

Although these findings make a contribution to the literature, there are some limitations that require further examination and demand additional research. First, measuring visitor intention to generate online content may be conditioned by their general predisposition toward using social networks to share online content and their expertise in arts, science, or other cultural subjects. In addition to satisfaction and the experience value, future research should take into account other factors that affect eWOM, such as visitor motivation and self-confidence in cultural matters. Second, although the study takes into account the visitor’s age as well as the effects of a lack of knowledge and expectations, future research might include specific museum characteristics and other individual traits. The kind of collection, the length of the route, or visitor personality may affect the functional forms for the relationship between satisfaction and value, and behavioral intentions. Finally, measures of actual online behavior, as opposed to behavioral intentions, might also enhance the validity of the study. Unfortunately, such data are often difficult and costly to gather.

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: The present study forms part of the research project “Innovating European Museums. Analyzing Activities, Determinants, and Efficiency Indicators” (ref. ECO2012-38552) funded by the Ministry of Economy and Competitiveness (National R&D Plan 2008-2011).

Author Biographies

Carmen Antón, PhD in Business Administration, is Associate Professor at the University of Valladolid (Spain). Her research focuses on consumer behaviour, adoption of innovations and non-profit marketing. She has published in several international refereed journals (Psychology & Marketing, Public Management Review, European Journal of Marketing, Current Issues in Tourism, Journal of Consumer Behaviour, International Journal Human Resource Management).

Carmen Camarero, PhD in Business Administration, is Associate Professor at the University of Valladolid (Spain). Her research focuses on relationship marketing, online consumer behaviour and marketing in cultural organizations. She has published in several international refereed journals (Psychology & Marketing, Journal of Service Research, Tourism Management, Electronic Commerce and Research Applications, European Journal of Marketing.

María-José Garrido, PhD in Business Administration, is Associate Professor at the University of Valladolid (Spain). Her current research focuses on non-profit marketing, new technologies and e-marketing and internal marketing. She has published different articles in journals in her field of research, including Journal of Business & Industrial Marketing, International Journal Human Resource Management, Journal of Cultural Economics, Tourism Management, Journal of Cultural Heritage.

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