Information Sources and the Tourism Decision-making Process: An Examination of Generation X and Generation Y Consumers

Abstract

Generation Y (Gen Y) is becoming more important to marketers as its members continue to enter the workforce. Members of this generational cohort are essential to the tourism industry as they engage in planning vacations themselves. This study accesses the information search behaviour of Gen Y and makes comparisons to the previous generation, Generation X (Gen X). A demographic profile, including information sources, is compiled. Additionally, several proposals were developed based upon the literature regarding tourism information searches and decision-making for Gen X and Y. Key constructs were identified as part of the purchase decision process. They were analysed using primary research study data. Specifically, independent-samples t-tests were used to test the propositions. The analyses revealed that there were significant differences between generational cohorts regarding technology-based information sources, risk aversion and use of information sources. As a result, this study offers a synthesis of contingency factors affecting tourist decision-making. It provides both theoretical and managerial implications.

Keywords

Generation X generation Y tourism decision-making information search

Introduction

Generational Cohorts

A generational cohort is a group of consumers with common birth years and shared experiences, attitudes and behaviours. These groups are thought to be more viable for target marketing than a uniform, yet more arbitrary, designation of age groups. Each cohort is estimated to last approximately 20 years before the next generation arises (Pendergast, 2010).

The profile of the US travel market is characterized by multiple generations, known as the Silent Generation, Baby Boomers, Generation X (Gen X) and Generation Y (Gen Y) (Glover, 2010). According to generational theory, each generation is distinctive in terms of its traits, values/beliefs and interests/expectations (Strauss & Howe, 1997). In essence, a generation can be identified with some core values, which provide cues for behaviour patterns (Schewe & Meredith, 2004).

Gen X is defined as consumers born between 1965 and 1976 (Alch, 2000; Norum, 2003; Phillips, 2005), consisting of about 49.3 million members, approximately 17 per cent of the US population. The most commonly cited birth years for Gen Y are from 1977 to 1994 (Broadbridge, Maxwell, & Ogden, 2007; Buksa & Mitsis, 2011; Bush, Martin, & Bush, 2004; Cui, Trent, Sullivan, & Matiru, 2003; Kim, Knight, & Crutsinger, 2009; Loroz & Helgeson, 2013; Wolburg & Pokrywczynski, 2001), so for purposes of this study, Gen Y is defined as those born between 1977 and 1994, including about 60 million US consumers, which is about 41 per cent of the population (Pendergast, 2010). According to Nielsen (2015), Gen Y is the largest segment of the population and is more educated and more culturally diverse than any other generation. In essence, members of Gen X and Gen Y came out of a different history and with a different set of coping skills and expectations.

Recent research suggested that tourism growth might be dependent upon how service providers understand the social and demographic trends that influence travellers’ behaviour (Horneman, Carter, Wei, & Ruys, 2002). As such, generational theory provides a theoretical framework to pinpoint the consumption patterns and offers implications on travel attitudes, preferences and behaviours among various generations (Li, Li, & Hudson, 2013). As a result, insights gained through the lens of generational theory provide important practical and theoretical implications for a variety of behavioural phenomena (Chen & Hsu, 2000).

According to De Lollis (2005), Gen Xers have been entering their peak earning years and are categorized as both business and leisure travellers. Evidence shows that Gen X is the most free spending of travellers and outspent Baby Boomers on trips involving a hotel stay (De Lollis, 2005). In 2004, Gen X spent roughly US$1,297 per trip per person (McMahon, 2005) and the spending power of such a generation has continued to increase. In addition, Gen X runs 45 per cent of households with children (‘American generations …’, 2010) and is more likely to travel with children than other generations (‘Travel across …’, 2006). Although Gen X outspends Baby Boomers (1946–1964) on trips involving hotel stays, Gen Y consumers are the biggest potential spenders, with US$200 billion in annual buying power (Schawbel, 2015). For example, by 2020, the Gen Y market will be travelling internationally 47 per cent more than it did in 2013 (Fuggle, 2015). Trip planning involves information search.

The study generates a demographic profile as well as an information source profile for Gen X and Gen Y respondents. Proposals are developed regarding the vacation decision-making process, and several key constructs in the information search will be used to compare and contrast Gen X and Gen Y. The discussion offers theoretical and practical contributions. It should be noted that the secondary data research revealed many gaps in the literature. There was a considerable dearth of Gen-X literature, and in several cases, a general review of the tourism literature was provided.

Literature Review

Consumer Purchase Decision Process

Although there are slightly different ways of presenting it, the consumer purchase decision process is more often depicted in a five-step or five-stage model, beginning with problem recognition and ending with post-purchase behaviour (see Figure 1). The entire model is used to accommodate high-involvement purchase decisions, whereas the elimination of steps or stages two and three is appropriate for low-involvement (routinized) decision-making. In nearly all cases, the travel decision is a high-involvement purchase decision, which would involve all stages of the model. The topics in the literature review will be prefaced with their relevance/importance to the consumer purchase decision process.

Figure 1

Source: Kerin, Hartley, and Rudelius (2011).

Source Preferences

Consumers begin seeking information during the second stage of the consumer decision-making process, information search. Information available to individuals has a significant impact on travellers’ decision-making, especially when choosing a destination (Bieger & Laesser, 2004). Information technology (IT) has transformed travel and tourism (Werthner & Klein, 1999) and continues to impact the way travellers gain access to, and use, travel-related information.

Technology empowers travellers to control their travelling experience and the Internet has become the primary information source for travel planning (Xiang, Magnini, & Fesenmaier, 2015). Tools, such as search engines, have become a dominant force that influence travellers’ access to tourism products (Xiang, Woeber, & Fesenmaier, 2008). Social media is another platform that has changed the dynamics of online communication, and mobile apps have created new locales for information search, facilitating information search in guiding travel decisions (Wang & Xiang, 2012). Additionally, travel portals, virtual communities and websites of destination marketing organizations (DMOs) serve as different sources for travel planning (Xiang et al., 2015). As the use of the Internet for travel planning becomes more prevalent, decision-making processes are expected to be increasingly influenced by electronic word of mouth (eWOM). This phenomenon may be due to the high-involvement nature of purchasing traveling packages (Yoo & Gretzel, 2011).

Furthermore, research shows that traditional media, such as TV, radio, and even movies, still remain relevant to travellers’ information search and decision-making (Xiang et al., 2015). Moreover, there is an emerging trend that travellers who search for information through social media and mobile devices also engage in offline communication for travel needs (Xiang et al., 2015). Additionally, Benckendorff and Moscardo (2010) suggest that Internet usage may be overstated. However, information needs and search strategies can vary for different stages in the travel decision-making process (Gretzel, Fesenmaier, Formica, & O’Leary, 2006). Travel planning involves a multitude of facets for which decisions need to be made (Yoo & Gretzel, 2011). Yet, little is known about how generational cohorts make travel decisions based upon different communication channels at various stages of decision-making.

Gen X is the first generation exposed to computer technology (Losyk, 1997). Studies show that Gen X is able to work with a variety of software programmes and is willing to face cyberspace challenges (e.g., Losyk, 1997). Generally, members of this generation are technology savvy and they leverage technology to personalize/humanize many aspects of their lives (Reisenwitz & Iyer, 2009). However, Gen-Y consumers tend to place an emphasis on the integration of technology with many aspects of their lives, such as leisure (Leask, Fyall, & Barron, 2014). For instance, 65 per cent of this generation made online travel arrangements in 2008 (Jones & Fox, 2009). The use of technology is considered as an important tool for meeting their needs and expectations while travelling (Leask et al., 2014). Furthermore, many Gen Yers have used travel-related social media to share their travel experiences (Chatchaidamrong & Leelapanyalert, 2009; Moscardo & Benckendorff, 2010).

Jones and Fox (2009) found that Gen Yers are more likely to read other peoples’ blogs and write their own than other generations. Online social interaction is perceived as entertaining, customizable and exciting (Nusair, Bilgihan, & Okumus, 2013), although females tend to receive greater benefits from using online reviews than males (Gretzel & Yoo, 2011). eWOM has become a determining factor to influence travel-related decision-making (Gretzel & Yoo, 2001). For example, eMarketer (2007) reported that among travellers who use peer reviewers for their hotel bookings, 25 per cent of infrequent leisure travellers and 33 per cent of frequent travellers reported having changed their hotel stay based upon reviews by other consumers.

In essence, Gen Y is a challenging generation to connect with, as many of the traditional methods of advertising have proven to be ineffective communication (Schawbel, 2015). Like Gen Xers, Gen Y is tech savvy and is the first generation to use e-mail, instant messaging and cell phones since childhood (Tyler, 2007, 2008). But, more than previous generations, Gen Y is more comfortable with technology (Auby, 2008) and knows how to solve problems and shorten the learning curve using collaboration tools, such as cell phones, bluetooth, windows CE handhelds, laptops, e-mail and text messaging (Bradley, 2007). Barnikel (2005) notes that Gen Y is the first generation in which Internet consumption has exceeded television consumption. Based upon the previous discussion, it is proposed that Gen-Y consumers use more technology-based information sources than Gen-X consumers for their vacation planning.

Risk Aversion

Perceived risk begins early in the decision-making process during the information search stage and continues throughout the remainder of the process, including post-purchase behaviour. Consumers wish to minimize this risk, especially with high-involvement decisions. A major way of reducing this risk is accomplished by acquiring information.

In their adolescent life stage, Gen-Y consumers were described as risk averse (Morton, 2002), struggling with independent thinking and decision-making, due to the fear of making mistakes (Howe & Strauss, 2003). More recently, however, Gen-Y consumers have been described as risk-takers (Sharma, 2013). On the other hand, Gen Xers have been characterized as more cynical, more pessimistic and less idealistic than Gen Yers (Reisenwitz & Iyer, 2009). Hence, they tend to be sceptical of the status quo (Jurkiewicz, 2000), which may be due to their pessimistic nature. In fact, research shows that this generation is a reactive generation and has a low capacity for risk (Reisenwitz & Iyer, 2009).

Users of social networking websites are more likely to engage in risky behaviours than non-users (Fogel & Nehmad, 2009). Zhu, Dholakia, Chen, and Algesheimer (2012) found that online-community engagement leads individuals to make riskier financial decisions because they rationalize that, if a mistake was made, they will get help from the community, even if consisting of relative strangers. Bolton et al. (2013) note whether, and to what extent, Gen Y’s use of social media increases its risk proneness; this requires further study, especially since its risk-taking behaviours are important to firms and policymakers. Based upon this discussion and the earlier discussion of information search preferences, it is proposed that Gen-X consumers are more risk averse than Gen-Y consumers.

Source Credibility

As mentioned, information search usually follows problem recognition as the second step in the purchase decision process. Providing information to potential tourists is a major marketing activity for a typical DMO and in many cases may make up a significant portion of a DMO’s operating budget (Cai, Feng, & Breiter, 2004). In terms of consumer behaviour, environmental influences and individual differences are antecedents during the consumption process, including information search (Cai et al., 2004). Studies have shown that personal experience from past vacation travel and information from family members and friends are the most utilized information sources, whereas mass media sources, especially advertising and editorial messages (publicity), are rated as less important in the vacation decision-making process (Loda, 2003). The role of the credibility of information sources in tourists’ information search behaviour, along with the role of prior knowledge and information needs, was examined by Cho (2001). Results showed that credibility of the source was the most important criterion when deciding upon an information source, compared to prior knowledge and need for information. However, there was no distinction between advertising messages and editorial messages (publicity) in the rating process.

In contrast, more recent research found that publicity created significantly higher scores than advertising for credibility, message strength and purchase intent (Loda, Norman, & Backman, 2005, 2007). These findings confirm that publicity is an important element in the tourism marketing mix, suggesting that a publicity-then-advertising strategy is most effective in persuading prospective tourists to visit a particular destination.

More recently, Li et al. (2013) found that paid advertising has little influence as an information source for all four generational cohorts (The Silent Generation, Baby Boomers, Gen X and Gen Y), supporting the contention that the effectiveness of traditional advertising is weakening in today’s digital world (Carey, Kang, & Zea, 2012). Based on the previous discussions, the following proposals are presented: (a) Gen-X consumers have a higher attitude towards traditional vacation advertising than Gen-Y consumers and (b) Gen-Y consumers have a higher attitude towards online vacation advertising than Gen-X consumers.

Satisfaction

A satisfactory or unsatisfactory experience is an important variable in the last stage of the purchase decision process, post-purchase behaviour. Based on the disconfirmation paradigm, satisfaction is a comparison between performance and expectations (Moliner, Sanchez, Rodriguez, & Callarisa, 2007). Restated, consumer satisfaction is a function of expectations related to important attributes and judgements of attribute performance (Meng, Tepanon, & Uysal, 2006). It is regarded as one of the key judgements that consumers make in regard to a tourism service (Bowen & Clarke, 2002) and is a crucial element to sustain a competitive business in the tourism industry (Meng et al., 2006).‘Successful service providers are able to meet and, whenever possible, exceed consumers’ expectations. If tourism agencies fail to meet the expectations of tourists, they become dissatisfied. Dissatisfied tourists will not come back to such travelling agencies, for their next tour’ (Bhat, 2012, p. 328). Although satisfaction has both a cognitive and an emotional component, it is generally thought to be more affective or emotional than quality (Huang & Chiu, 2006), with the consumer addressing the question ‘Did you like it?’ versus the cognitive question ‘Was the experience high in quality?’

According to Bowen and Clarke (2002), the literature more broadly discusses a variety of elements that comprise tourism satisfaction: expectation, performance (of management, service personnel, the tourists themselves, whether in groups or as individuals, the host population), expectancy disconfirmation (the difference between expectation and performance), attribution (a consideration of the locus), stability over time, management control and importance of causal inferences (blame) made by the tourist(s), emotion (e.g., fear, surprise) and equity. These elements may act independently or in combination. An element(s) could also be suppressed or heightened in a particular tourist situation. Ko and Lui (2010) also note that tourism attraction is a significant influence on tourist satisfaction. Additionally, Neal and Gursoy (2008) found that level of satisfaction or dissatisfaction varies during different stages of travel and can affect the overall level of satisfaction with travel and tourism services.

Moreover, reviews on satisfaction in the marketing literature have emphasized the need for a context-dependent approach (Fournier & Mick, 1999). Tourist satisfaction is responsive to the service climate. Tourists deal with a product that is characteristic of most services: intangible, inseparable, heterogeneous and perishable, as well as high risk, high involvement and interdependent. Judgements are usually confined to a shorter timeframe than other purchases, with similar financial requirements or degree of involvement in decision-making (Bowen & Clarke, 2002).

Meng et al. (2006) note that tourist satisfaction is important to gain a better destination image, increase consumption of the product and services mix, increase loyalty and generate repeat business. Furthermore, Ibrahim and Gill (2005) proposed that the measurement of the customer’s perception of a destination’s services can result in the identification of attributes that can be used to lead to informed decisions of the destination’s positioning strategy. They believe that customer perception and satisfaction can be used in tandem for positioning and promotion purposes. The measurement of customer perception and satisfaction, when combined, can result in the identification of specific niche markets, which can be integral components in developing and promoting an effective positioning strategy for a destination. It is proposed that the generational cohort that utilizes more information sources is more satisfied with the vacation destination.

Self-concept

It has been suggested that some purchase decisions may be affected by the consumer’s self-image or self-concept (Sirgy, 1982). Self-concept, the sum total of an individual’s ideas, thoughts and feelings about himself or herself relative to other objects, is a multidimensional concept which includes actual self-concept, how individuals perceive themselves to be, and ideal self-concept, how an individual would like to be perceived (Sirgy, 1982). Consumers generally have favourable attitudes towards products and brands that are consistent with their self-image and less favourable attitudes towards products and brands perceived to be inconsistent with their self-image (Graeff, 1996). Subsequently, consumers may be influenced to direct their purchase behaviour towards products and services that will protect or enhance their self-concept (Litvin & Kar, 2003).

Chon (1992) is credited with first applying the self-concept congruity theory to tourism via a study of post-visit satisfaction. Satisfaction was significantly correlated with ‘self-image/destination image congruity’. Specifically, he found that tourists who perceived a low discrepancy between a destination’s user-image and their actual or ideal self-image were most satisfied with the destination, while those with high discrepancies were found to be least satisfied. Litvin and Kar (2003) affirmed the applicability of self-image in tourism research and extended their research to encompass the concept in conjunction with the cultural moderating variable of individualism/collectivism. Their message for tourism marketers is that a product reflective of the target market’s self-image has the potential to result in higher satisfaction levels when sold in individualistic markets, such as those found in Australia, versus more collectivist markets, such as those found in Japan. In sum, while applicable across cultures, self-concept may work better in some markets than in others. Although they did not employ a multicultural focus, Murphy, Benckendorff, and Moscardo (2007) found that if tourists can associate a destination with a destination brand personality and the association is consistent with their desired experience, then a high correlation between the tourists’ self-image and perception of the destination results. In contrast, Curtin (2010) focused on characteristics of the tourist, versus the destination, and found that wildlife tourism consists of individuals who ‘differentiate themselves from other tourists in terms of dress, behaviour, development of skills, equipment and intellectual capital’ (p. 17) as shown by their interest in scoping, identifying and photographing wildlife.

Gen X was labelled as ‘lacking ego strength’ and having ‘low self-esteem’ (Howe & Strauss, 1993), while Gen Yers were characterized as having inflated self-esteem issues, due to overprotection by their parents (Princeton One, 2016). In addition, Giovannini, Xu, and Thomas (2015) found that marketing strategies positioning luxury fashion brands as status symbols that support or encourage a specific lifestyle or personal value would be useful when targeting Gen-Y consumers. This type of strategy is also supported by the research of Sirgy (1985) who determined that consumers who are driven to feel a connection with the products they purchase are likely to seek out brands that reflect their self-image. Based on the previous discussion, it is proposed that the generational cohort with a higher self-image towards the vacation was also more satisfied with the vacation.

Objectives

Information search on vacation packages accompanies high-involvement decision-making. Therefore, the main objective of this study is to compare and contrast Gen X and Gen Y regarding the information search stage of the vacation decision-making process. The second objective of this study is to investigate how Gen X and Gen Y use various communication channels to make travel decisions and suggest the effective method(s) to promote tourist destinations to them.

Methodology

The study sample was a regional sample. The respondents consisted of individuals who were recently contacted by upper-level undergraduate marketing students trained in data collection procedures and used as interviewers. This approach has been successfully used in previous research (e.g., Arnold & Reynolds, 2003; Bitner, Booms, & Tetreault, 1990; Jones & Reynolds, 2006). Interviewers administered questionnaires and were instructed to screen potential respondents with three qualifying questions on the cover page of the instrument: (a) an age range that categorized the respondent as a member of Gen X or Gen Y, (b) an acknowledgement that the respondent had taken a vacation within the past year to allow retrieval of information from short-term memory and (c) confirmation that the respondent had been employed full-time for a majority of the past year, so the likelihood of the respondent planning the vacation would be greater. The questionnaires for Gen X and Gen Y were identical except for the age-qualifying question on the cover page. An introduction to the questionnaire was just below the three questions on the cover page, including an assurance to respondents that their responses would be kept confidential.

The first section of the questionnaire included demographics questions (see Table 1).

Another section of the instrument asked respondents to report their Internet usage in a series of dichotomous questions and frequency-level questions. The remainder of the questionnaire focused on the vacation destination itself and began with a series of frequency questions, including an exhaustive list of information sources used to plan the recent vacation (see Table 1).

Table 1.

Descriptive Information of Sample

Items		Generation X	Generation Y
		Per cent (n)	Per cent (n)
		100 (219)	100 (247)
Gender	Male	44 (96)	49 (122)
	Female	56 (122)	50 (124)
Age	(50, 22)	17 (38)	38 (93)
Income	0–10,000	3 (7)	35 (86)
	10,001–30,000	9 (19)	29 (72)
	30,001–50,000	18 (39)	15 (37)
	50,001–70,000	24 (52)	10 (24)
	Above 70,000	45 (98)	8 (19)
Martial	Married	64 (140)	17 (41)
	Single	17 (38)	69 (170)
	Living with another	7 (16)	9 (23)
	Widowed	1 (2)	<1 (1)
	Separated	1 (2)	-0-
	Divorced	9 (19)	1 (2)
	Rather not say	<1 (1)	3 (7)
Race	White (Caucasian)	59 (129)	49 (122)
	African American	30 (65)	31 (77)
	Hispanic American	3 (6)	2 (6)
	Asian American	<1 (1)	2 (4)
	Native American	3 (6)	1 (2)
	Other	5 (11)	12 (29)
Education	GED	2 (5)	2 (4)
Completed	High school	23 (50)	36 (89)
	Undergraduate	24 (53)	41 (102)
	Graduate	31 (68)	13 (32)
	Professional degree	8 (4)	3 (7)
	Technical	4 (8)	3 (8)
	Other	3 (7)	1 (3)
Occupation	Homemaker/not employed	3 (7)	5 (12)
	Self-employed	11 (25)	9 (23)
	Educator	15 (32)	5 (12)
	Professional	13 (29)	8 (20)
	Work for a firm/business	49 (107)	57 (142)
	Other	8 (17)	14 (34)
INTERNET CHARACTERISTICS
Use the Internet		99 (216)	99 (245)
Use the Internet for purchasing products/services		85 (185)	96 (237)
Use the Internet for browsing products/services		91 (200)	97 (240)
Frequency of Internet access
	Never	2 (4)	1 (2)
	Daily	81 (178)	95 (234)
	Weekly	14 (30)	4 (9)
	Monthly	2 (4)	-0-
	Less than once a month	1 (3)	<1 (1)
Time using the Internet
	Never	1 (3)	<1 (1)
	Less than 6 months	<1 (1)	<1 (1)
	6–11 months	1 (2)	1 (2)
	12–23 months	-0-	-0-
	2–5 years	15 (33)	4 (11)
	Over 5 years	82 (179)	93 (230)
Frequency of Internet purchases
	Never	13 (29)	2 (5)
	Once a year	8 (18)	7 (18)
	Once every few months	36 (78)	44 (108)
	Once a month	30 (66)	34 (83)
	Once a week	10 (21)	0 (25)
	More than once a week	3 (7)	3 (7)
Internet purchases in the past 12 months
	Never	13 (29)	3 (8)
	1–5 times	33 (73)	41 (101)
	6–10 times	18 (40)	20 (50)
	11–15 times	12 (26)	12 (29)
	16–20 times	9 (20)	6 (16)
	Over 20 times	14 (31)	17 (41)
VACATION CHARACTERISTICS
Vacation destination	Instate	8 (18)	10 (26)
	Out of state	74 (162)	68 (167)
	International	17 (38)	21 (52)
Length of stay
	1 day	2 (4)	5 (12)
	2 days	8 (18)	12 (29)
	3 days	28 (62)	22 (54)
	4 days	15 (33)	17 (42)
	5 days	15 (34)	18 (45)
	6 days	8 (18)	9 (22)
	7 days or more	23 (50)	17 (41)
Travel time (days to and from destination)
	1 day	53 (117)	58 (143)
	2 days	32 (70)	24 (59)
	3 days	2 (4)	4 (11)
	4 days	3 (6)	4 (10)
	5 days	2 (5)	4 (9)
	6 days	2 (5)	1 (3)
	7 days	5 (12)	4 (11)
Principal means of travel
	Personal car	61 (133)	63 (156)
	Rental car	5 (12)	4 (11)
	Plane	26 (57)	20 (50)
	Train	-0-	2 (4)
	Bus	3 (6)	2 (4)
	Other	5 (10)	8 (21)
Number in party (including self)
	One	5 (10)	10 (25)
	Two	28 (62)	27 (68)
	Three	14 (30)	17 (42)
	Four	24 (53)	19 (46)
	Five	13 (28)	9 (22)
	Six or more	16 (35)	17 (41)
Accompanying party members
	Immediate family	56 (123)	29 (71)
	Relatives	12 (26)	8 (20)
	Friends	17 (38)	47 (115)
	Other	11 (25)	13 (31)
Approximate total cost of vacation
	US$0–100	3 (6)	8 (21)
	101–500	15 (32)	36 (89)
	501–1,000	32 (69)	27 (67)
	1,001–2,000	26 (58)	11 (28)
	Over 2,000	23 (51)	16 (40)
Number of prior times visiting the destination
	Never	24 (52)	39 (97)
	1	13 (29)	15 (36)
	2	14 (31)	11 (28)
	3	12 (27)	7 (17)
	4	4 (9)	6 (14)
	5	6 (14)	6 (16)
	7	1 (3)	1 (1)
	7 or more	25 (54)	14 (35)
Time spent planning the vacation
	None, it was spontaneous	9 (19)	14 (35)
	None, already travelled there	31 (67)	22 (55)
	Less than 1 month	27 (60)	25 (62)
	About 1 month	12 (27)	17 (42)
	Over 1 month	21 (46)	21 (52)
Who paid for the vacation expenses (circle all that apply)
	Self	52 (114)	64 (158)
	Self and spouse	39 (86)	17 (41)
	Parents	3 (7)	24 (60)
	Spouse’s parents	2 (5)	2 (4)
	Other	10 (21)	9 (22)
Attraction to the vacation destination	(circle all that apply)
	Price	10 (23)	14 (34)
	Exotic/unique location	16 (35)	17 (41)
	Popular destination	31 (69)	36 (90)
	Have visited before	53 (117)	39 (97)
	Recommended by friends/relatives	23 (50)	32 (78)
	Privacy	9 (20)	6 (16)
Travel websites used for vacation planning (circle all that apply)
	Booking	6 (13)	4 (9)
	TripAdvisor	18 (40)	14 (35)
	Yahoo! Travel	3 (6)	3 (7)
	Expedia	20 (43)	15 (37)
	Priceline	8 (18)	10 (25)
	Hotels	14 (30)	13 (33)
	Travelocity	13 (28)	7 (18)
	Kayak	5 (10)	6 (15)
	Orbitz	4 (9)	4 (10)
	Hotwire	3 (7)	4 (10)
	Other	8 (18)	11 (27)
Travel websites comparisons before making the decision
		41 (90)	36 (89)
If booked through a travel website, travel website used
	Booking	2 (5)	2 (4)
	TripAdvisor	4 (8)	2 (4)
	Yahoo! Travel	<1 (1)	-0-
	Expedia	8 (18)	7 (17)
	Priceline	1 (3)	2 (6)
	Hotels	4 (9)	3 (8)
	Travelocity	3 (6)	2 (5)
	Kayak	1 (2)	2 (5)
	Orbitz	1 (3)	1 (2)
	Hotwire	<1 (1)	1 (2)
	Other	5 (11)	6 (16)

Source: The authors.

All multi-item scales were established scales, some of which were revised for use in the study. The risk-aversion scale was a four-item, seven-point, Likert scale (Donthu & Gilliland, 1996). The measures for attitude towards online advertising and the attitude towards traditional advertising of the vacation destination were identical four-item, seven-point, semantic differential scales. These items were drawn from the inventory of 64 bipolar adjective scale items from Bruner and Hensel (1998), who noted that past generated scales ‘have relied heavily on researcher judgment with respect to which specific adjective pairs are appropriate for a given situation’ (p. 818). A similar five-item, seven-point, semantic differential scale was generated for measuring attitude towards the vacation destination. A five-item, seven-point, satisfaction scale (Oliver, 1980) was adapted to assess satisfaction of the travel destination. Finally, a six-item, seven-point, self-congruency, self-image or self-concept scale was also slightly modified for use in the study regarding the vacation destination (Sirgy et al., 1997).

Two pretests were conducted to test the questionnaire. The first pretest (n = 32) was conducted with an undergraduate marketing class of traditional students (Gen Y). Some basic formatting issues were addressed as a result of the pretest. A second pretest (n = 34) was conducted with another undergraduate marketing class of traditional students (Gen Y). Modifications, including a frequency issue in one question, were made as a result of this second pretest.

The data for the main study were collected, coded and entered into the SPSS (Statistical Product and Service Solutions) program. A frequencies analysis was run to check for any outlier values. In the Gen-X dataset, multiple respondents were removed who were outside of the 40–51 years of age range. Additionally, outlier values for five other variables were checked and corrected, and one questionnaire with a blank page was deleted, resulting in a final sample size of 219 for Gen X. In the Gen-Y dataset, only age outlier values were an issue. These respondents were also deleted, resulting in a final sample size of 246 for Gen Y.

Reliabilities (Cronbach’s alpha) were run for multiple-item scales. All values were above the minimum acceptable value of 0.70 (Nunnally & Bernstein, 1994), except for the Gen-X risk aversion value of 0.61 (see Table 2).

Table 2.

Reliability Coefficients

Scale/Statements		Coefficient Alpha
Scale/Statements		Gen X	Gen Y
Risk aversion		0.61	0.71
I would rather be safe than sorry.
I want to be sure before I purchase anything.
I avoid risky things.
I like to take chances.*
Attitude towards traditional advertising (semantic differential scale)		0.98	0.95
Good:	: Bad
Like:	: Dislike
Pleasant:	: Unpleasant
Enjoyable:	: Not enjoyable
Attitude towards online advertising (semantic differential scale)		0.97	0.95
Good:	: Bad
Like:	: Dislike
Pleasant:	: Unpleasant
Enjoyable:	: Not enjoyable
Satisfaction		0.96	0.97
My experience at my travel destination was good.
I am happy that I decided to go to my travel destination.
My travel destination worked out as well as I thought it would.
I am sure it was the right thing to go to my travel destination.
I am overall satisfied with my travel destination.
Self-image		0.93	0.93
The image of this destination is consistent with how I see myself.
This destination reflects who I am.
People similar to me visit this vacation destination.
The kind of person who visits this destination is very much like me.
This destination is a mirror image of me.
I am very much like the typical person who visits this destination.

Source: The authors.

Note: *Reverse-scored item.

Analysis

The demographic data revealed that nearly all Gen-X and Gen-Y consumers use the Internet and about 10 per cent more Gen-Y consumers than Gen-X consumers use the Internet to purchase products and services. Both generational cohorts use the Internet daily and have used it for over 5 years, making purchases once every few months. In terms of vacation behaviour, both generational cohorts spent about 3 days at the vacation destination, generally using a personal car for travel with two immediate family members in the party. Expectedly, Gen X spent more on the vacation (US$501–1,000) versus Gen Y (US$101–500). The majority in both cohorts was attracted to the destination because they had visited there previously. Please see Table 1 for the demographic profiles of both cohorts.

Independent-samples t-tests were used to test the propositions or proposals; the results are summarized in Table 3. The first proposition, that Gen-Y consumers use more technology-based information sources than Gen-X consumers for their vacation planning, was supported (p < 0.00). The second proposal, that Gen-X consumers are more risk averse than Gen-Y consumers, was also supported (p < 0.00). However, the third proposal, that Gen-X consumers have a higher attitude towards traditional vacation advertising than Gen-Y consumers and Gen-Y consumers have a higher attitude towards online vacation advertising than Gen-X consumers, was not supported. Furthermore, the fourth proposition, that the generational cohort that utilizes more information sources is more satisfied with the vacation destination, was not supported. It was significant (p < 0.05) that Gen Y used more information sources than Gen X; however, the satisfaction with the vacation destination was not significantly greater. For the fifth proposition, that the generational cohort with a higher self-image towards vacation was also more satisfied with the vacation, there were no significant differences between generational cohorts in terms of self-image.

In sum, three propositions were supported: (a) Gen-Y consumers use more technology-based information sources for their vacation planning, (b) Gen-Y consumers use more information sources overall for their vacation planning and (c) Gen-X consumers are generally more risk averse than Gen-Y consumers. The first finding is reasonable, given that Gen-Y consumers have been exposed to more technology for a greater part of their lives than Gen-X consumers. The second finding makes sense as well, since Gen Y is most likely dealing with more limited discretionary funds than the more-established, Gen-X, counterpart. Gen-Y consumers must use care when considering spending their more limited funds. However, the third finding, that Gen-X consumers are more generally risk averse, seems to contradict the previous finding, since risk reduction is usually associated with a greater use of information sources.

Table 3.

Differences Between Gen X and Gen Y

Variable	Gen X Mean (SD)	Gen Y Mean (SD)	t-Value	Significance (p-value)
Technology-based information sources	1.81 (0.83)	2.18 (1.17)	−2.86	0.00*
Risk aversion	5.18 (1.03)	4.72 (1.18)	4.43	0.00*
Attitude towards traditional vacation advertising	3.31 (1.65)	3.46 (1.61)	−0.78	0.44
Attitude towards online vacation advertising	2.61 (1.47)	2.66 (1.49)	−0.28	0.78
Use of information sources	2.28 (0.67)	2.51 (0.93)	−2.15	0.03**
Self-image	4.98 (1.36)	5.00 (1.56)	−0.11	0.91
Satisfaction	6.40 (0.99)	6.42 (1.13)	−0.14	0.89

Source: The authors.

Note: *p < 0.00 **p < 0.05.

Conclusion

The purpose of the research was to examine the differences between Gen X and Gen Y in terms of their information search behaviour in a tourism context. The proposed framework addresses the research gap by incorporating major factors, such as source credibility, satisfaction, risk aversion and self-concept or self-image. A series of propositions suggested by the previous literature is offered, which was tested with survey data. As a result, this study expands the discussion of tourist information search behaviour from a generational perspective. It offers a synthesis of contingency factors (e.g., risk aversion, self-concept, satisfaction) affecting vacation decision-making and information research. In addition, the research expands the literature on how Gen X and Gen Y use technology in tourist decision-making.

From a theoretical perspective, this research confirmed the notion that tourist profile and travel behaviour variables are critical to investigate the decision-making process (i.e., Ozdemir et al., 2012). As the findings indicated, Gen Y tends to use technology (non-traditional media) to search information for vacation planning. This finding is consistent with previous literature that Gen-Y consumers place an emphasis on online social interaction (Nusair et al., 2013). Additionally, our study found that Gen X is more risk averse than Gen Y. The tendency may be due to technology exposure. As Zhu et al. (2012) posited, online community engagement or frequent technology usage leads individuals to make riskier decisions.

Contrary to the previous literature (e.g., Carey et al., 2012) that traditional advertising (e.g., TV) is weakening in a digital world, our study revealed that Gen Y and Gen X share similar attitudes towards vacation advertising in both traditional and non-traditional media. Although Gen Y tends to use online media to search information, the attitude towards advertising is not affected by such behaviour. This finding may reflect the scepticism towards advertising claims (Obermiller & Spangenberg, 1998). We speculate that the usage of various media types does not have impact on trustworthiness in advertising.

Managerial Implications

‘As the tourism and hotel industry continue to prosper in the global economy, competition becomes fiercer. Possessing competitive advantages could be the key to success for those members’ (Roy, 2011, p. 51). From a practical perspective, the findings help practitioners develop a framework for segmentation, vacation package positioning and promotional strategies that relate to tourist information search behaviour. In order to target Gen Y, advertisers may put emphasis on online promotion with images and copies that attract this generation. For instance, online websites may show models below the age of 35 to draw more attention from this generation. The images may focus on more adventurous activities, such as surfing or sky diving, as Gen Y is more risk seeking than the previous generations. If the ads target Gen Y, marketers may place the ads in traditional media, such as TV or travel magazines, to increase ad exposure. However, marketers need to be aware that the exposure to various media/ads may not directly impact attitude towards advertising. The attitude towards ads may be determined by other factors, such as brand equity or travellers’ previous vacation experience. Marketers should further assess the content of the advertising and the media types, as well as other factors, such as service quality and brand awareness.

Limitations and Future Research

There are some limitations to this study that future research can address. For example, future research needs to determine if these results can be replicated with a national random sample. Also, as with most primary research studies, only a limited number of psychographic variables were assessed. Future studies could explore other variables that may also attempt to capture buyer behaviour during the information search stage of the tourism destination decision-making process. Given the growth and financial power of the Internet as well as the Gen-Y market, this topic is vital for marketers to continue to study and hopefully this article encourages additional research and discussion on these topics.

Moreover, additional research on tourist information search is needed in many areas. For example, future research could incorporate variables such as advertising scepticism. This variable may explain why there is no difference in terms of attitude towards vacation ads in various media between Gen X and Gen Y. In addition, research may focus upon the discrepancy between perception and attitude towards vacation advertising and post-vacation evaluation. This discrepancy may provide marketers further insights on how to improve customer loyalty programmes. Furthermore, tourist satisfaction should be taken into account when assessing the strengths and weaknesses of a tourist destination. Such an assessment can be useful to help form strategic and operational planning for the tourist industry.

In conclusion, this study contributes to the literature by showing the relationship between Gen X and Gen Y concerning several variables that have implications for the tourism organization and marketer. This study emphasizes that members of Gen Y are becoming an increasingly more viable segment for organizations and marketers. Those organizations and marketers that finely tune their strategies to address the needs of this emerging segment will increase their likelihood of success.

Footnotes

Acknowledgement

The authors are grateful to the anonymous referees of the journal for their extremely useful suggestions to improve the quality of the article. Usual disclaimers apply.

Declaration of Conflicting Interests

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

Funding

The research was supported by a Rea and Lillian Steele Grant.

References

Alch

M. L.

(2000). The echo-boom generation: A growing force in American society. The Futurist , 34(5), 42–46.

American generations: Who they are and how they live. (2010). Ithaca, NY: New Strategist Publications, Inc.

Arnold

M. J.

Reynolds

K. E.

(2003). Hedonic shopping motivations. Journal of Retailing , 108(2), 1–20.

Auby

(2008, August 25). A boomer’s guide to communicating with Gen X and Gen Y. Business Week , (4097), p. 63. Retrieved from https://www.bloomberg.com/news/articles/2008-08-13/a-boomers-guide-to-communicating-with-gen-x-and-gen-y

Barnikel

(2005, May 20). Gen Y media habits show tide is turning in favour of internet. Media , p. 12. Retrieved from http://connection.ebscohost.com/c/articles/17237352/gen-y-media-habits-show-tide-turning-favour-internet

Benckendorff

Moscardo

(2010). Understanding Generation-Y tourists: Managing the risk and change associated with a new emerging market. In Benckendorff

Moscardo

Pendergast

(Eds.), Tourism and Generation Y (pp. 38–46). Cambridge, MA: CAB International.

Bhat

M. A.

(2012). Tourism service quality: A dimension-specific assessment of SERVQUAL. Global Business Review , 13(2), 327–337.

Bieger

Laesser

(2004). Information sources for travel decisions: Toward a source process model. Journal of Travel Research , 42(4), 357–371.

Bitner

M. J.

Booms

B. H.

Tetreault

M. S.

(1990). The service encounter: Diagnosing favorable and unfavorable incidents. Journal of Marketing , 54(1), 71–84.

10.

Bolton

R. N.

Parsuraman

Hoefnagles

Migchels

Kabadayi

Gruber

… Solnet

(2013). Understanding Generation Y and their use of social media: A review and research agenda. Journal of Service Management , 24(3), 245–267.

11.

Bowen

Clarke

(2002). Reflections on tourist satisfaction research: Past, present, and future. Journal of Vacation Marketing , 8(4), 297–309.

12.

Bradley

(2007). Training the next generation. Systems Contractor News , 14(12), 48–50.

13.

Broadbridge

A. M.

Maxwell

G. A.

Ogden

S. M.

(2007). Experiences, perceptions, and expectations of retail employment for Generation Y. Career Development International , 12(6), 523–544.

14.

Bruner

G. C.

Hensel

P. J.

(1998). Marketing scales handbook: A compilation of multi-item measures: Volume II . Chicago, IL: American Marketing Association.

15.

Buksa

Mitsis

(2011). Generation Y’s athlete role model perceptions on PWOM behavior. Young Consumers , 12(4), 337–347.

16.

Bush

A. J.

Martin

C. A.

Bush

V. D.

(2004). Sports celebrity influence on the behavioural intentions of Generation Y. Journal of Advertising Research , 44(1), 108–118.

17.

Cai

L. A.

Feng

Breiter

(2004). Tourist purchase decision involvement and information preferences. Journal of Vacation Marketing , 10(2), 138–149.

18.

Carey

Kang

Zea

(2012, February). The trouble with travel distribution. McKinsey Quarterly . Retrieved from https://www.mckinsey.com/industries/travel-transport-and-logistics/our-insights/the-trouble-with-travel-distribution

19.

Chatchaidamrong

Leelapanyalert

(2009). The influence of marketing communication mix on 18–34 years-old international tourists travelling to Thailand . Paper presented at the 3rd International Colloquium on Tourism and Leisure, Bangkok, Thailand.

20.

Chen

J. S.

Hsu

C. H. C.

(2000). Measurement of Korean tourists’ perceived images of overseas destinations. Journal of Travel Research , 38(4), 411–416.

21.

Cho

M.-H.

(2001). The role of prior knowledge, need for information and credibility of information sources in tourists’ information search behavior (Unpublished doctoral dissertation). Pennsylvania State University, University Park, PA.

22.

Chon

K.-S.

(1992). Self-image/destination linage congruity. Annals of Tourism Research , 19(2), 360–363.

23.

Cui

Trent

E. S.

Sullivan

P. M.

Matiru

G. N.

(2003). Cause-related marketing: How Generation Y responds. International Journal of Retail and Distribution Management , 31(6), 310–320.

24.

Curtin

(2010). The self-presentation and self-development of serious wildlife tourists. The International Journal of Tourism Research , 12(1), 17.

25.

De Lollis

(2005). Hotels loosen their ties for a younger crowd. USA Today , p. 1b. Retrieved from https://www.hospitalitynet.org/news/4022291.html

26.

Donthu

Gilliland

(1996). Observations: The infomercial shopper. Journal of Advertising Research , 36(2), 69–77.

27.

eMarketer. (2007). UGC users outnumber creators. Retrieved from http://www.eMarketer.com

28.

Fogel

Nehmad

(2009). Internet social network communities: Risk-taking, trust and privacy concerns. Computers in Human Behavior , 25(1), 153–160.

29.

Fournier

Mick

D.G.

(1999). Rediscovering satisfaction. Journal of Marketing , 63(4), 5–23.

30.

Fuggle

(2015). Eight ways to adapt your tours for Millennials. Retrieved from https://www.trekksoft.com/en/blog/travel-industry-trends-2016

31.

Giovannini

Thomas

(2015). Luxury fashion consumption and Generation Y consumers: Self, brand consciousness, and consumption motivations. Journal of Fashion Marketing and Management , 19(1), 40–22.

32.

Glover

(2010). 14 Generation Y’s future tourism demand: Some opportunities and challenges. In Benckendorff

Moscardo

Pendergast

(Eds.), Tourism and Generation Y (pp. 155–164). Cambridge, MA: CAB International.

33.

Graeff

T. R.

(1996). Using promotional messages to manage the effects of brand and self-image on brand evaluations. Journal of Consumer Marketing , 13(3), 4–18.

34.

Gretzel

Yoo

K. H.

(2011). Influence of personality on travel-related consumer-generated media creation. Computers in Human Behavior , 27(2), 609–621.

35.

Gretzel

Fesenmaier

D. R.

Formica

O’Leary

J. T.

(2006). Searching for the future: Challenges faced by destination marketing organizations. Journal of Travel Research , 45(2), 116–126.

36.

Horneman

Carter

R. W.

Wei

Ruys

(2002). Profiling the senior traveler: An Australian perspective. Journal of Travel Research , 41(1), 23–37.

37.

Howe

Strauss

(1993). 13th Gen: Abort, retry, ignore, fail? New York, NY: Vintage.

38.

Howe

Strauss

(2003). Millennials go to college: Strategies for a new generation on campus: Recruiting and admissions, campus life, and the classroom . Washington, DC: American Association of Collegiate Registrars and Admissions Officers.

39.

Huang

H.-H.

Chiu

C.-K.

(2006). Exploring customer satisfaction, trust and destination loyalty in tourism. Journal of American Academy of Business , 10, 156–159.

40.

Ibrahim

E. E.

Gill

(2005). A positioning strategy for a tourist destination, based on analysis of customers’ perceptions and satisfactions. Marketing Intelligence & Planning , 23(2/3), 172–189.

41.

Jones

Fox

(2009). Generations online . Retrieved from http://www.pewinternet.org/PPF/r/275/report_display.asp

42.

Jones

M. A.

Reynolds

K. E.

(2006). The role of retailer interest on shopping behavior. Journal of Retailing , 82(2), 115–26.

43.

Jurkiewicz

C. L.

(2000). Generation X and the public employee. Public Personal Management , 29(1), 55–74.

44.

Kerin

R. A.

Hartley

S. W.

Rudelius

(2011). Marketing (10th ed.). New York, NY: McGraw-Hill Irwin.

45.

Kim

Knight

D. K.

Crutsinger

(2009). Generation Y employees’ retail work experience: The mediating effect of job characteristics. Journal of Business Research , 62(5), 548–556.

46.

P.-F.

Lui

Y.-L.

(2010). Factor and correlation analyses of tourism attraction, tourist satisfaction and willingness to revisit: Evidence from mainland Chinese tourists to Taiwan. The Business Review , 16(2), 255–261.

47.

Leask

Fyall

Barron

(2014). Generation Y: An agenda for future visitor attraction research. International Journal of Tourism Research , 16(5), 462–471.

48.

Hudson

(2013). The application of generational theory to tourism consumer behavior: An American perspective. Tourism Management , 37(3), 147–164.

49.

Litvin

S. W.

Kar

G. H.

(2003). Individualism/collectivism as a moderating factor to the self-image congruity concept. Journal of Vacation Marketing , 10(1), 23–33.

50.

Loda

M. D.

(2003). The communicative effect of message presentation and sequencing on tourist destination selection (Published doctoral dissertation). Clemson University, Clemson, SC.

51.

Loda

M. D.

Norman

Backman

(2005). How potential tourists react to mass media marketing: Advertising versus publicity. Journal of Travel & Tourism Marketing , 18(3), 63–73.

52.

Loda

M. D.

Norman

Backman

(2007). Advertising and publicity: Suggested new applications for tourism marketers. Journal of Travel Research , 45(3), 245–269.

53.

Loroz

P. S.

Helgeson

J. G.

(2013). Boomers and their babies: An exploratory study comparing psychological profiles and advertising appeal effectiveness across two generations. Journal of Marketing Theory and Practice , 21(3), 289–306.

54.

Losyk

(1997). Generation X: What they think and what they plan to do. The Futurist , 31(2), 39–42.

55.

McMahon

(2005). Going the X-tramile. Retrieved from www.singonsandiego.com

56.

Meng

Tepanon

Uysal

(2006). Measuring tourist satisfaction by attribute and motivation: The case of a nature-based resort. Journal of Vacation Marketing , 14(1), 41–56.

57.

Moliner

M. A.

Sanchez

Rodriguez

R. M.

Callarisa

(2007). Relationship quality with a travel agency: The influence of the post-purchase perceived value of a tourism package. Tourism and Hospitality Research , 7(3–4), 194–211.

58.

Morton

L. P.

(2002). Targeting Generation Y. Public Relations Quarterly , 47(2), 46–48.

59.

Moscardo

Benckendorff

(2010). Mythbusting: Generation Y and travel. In Benckendorff

Moscardo

Pendergast

(Eds.), Tourism and Generation Y (pp. 16–26). Cambridge, MA: CAB International.

60.

Murphy

Benckendorff

Moscardo

(2007). Linking travel motivation, tourist self-image and destination brand personality. Journal of Travel & Tourism Marketing , 22(2), 45.

61.

Neal

J. D.

Gursoy

(2008). A multifaceted analysis of tourism satisfaction. Journal of Travel Research , 47(1), 53–62.

62.

Nielsen

E. M.

(2015). Understanding Generation Y and their buying power. Retrieved from https://www-linkedin-com-s.web.bisu.edu.cn/pulse/understanding-generation-y-buying-power-egil-moller-nielsen

63.

Norum

P. S.

(2003). Examination of generational differences in household apparel expenditures. Family and Consumer Sciences Research Journal , 32(1), 52–75.

64.

Nunnally

J. C.

Bernstein

I. H.

(1994). Psychometric theory (3rd ed.). New York, NY: McGraw-Hill.

65.

Nusair

K. K.

Bilgihan

Okumus

(2013). The role of online social network travel websites in creating social interaction for Gen Y travelers. International Journal of Tourism Research , 15(5), 458–472.

66.

Obermiller

Spangenberg

E. R.

(1998). Development of a scale to measure consumer skepticism toward advertising. Journal of Consumer Psychology , 7(2), 159–186.

67.

Oliver

R. L.

(1980). A cognitive model of the antecedents and consequences of satisfaction. Journal of Marketing Research , 17(4), 460–469.

68.

Ozdemir

Aksu

Ehtiyar

Cizel

R. B.

(2012). Relationships among tourist profile, satisfaction and destination loyalty: Examining empirical evidences in Antalya region of Turkey. Journal of Hospitality Marketing & Management , 21(5), 506–531.

69.

Pendergast

(2010). Getting to know the Y Generation, from tourism and Generation Y. In Benckendorff

Moscardo

Pendergast

(Eds.), Tourism and Generation Y (pp. 1–15). Cambridge, MA: CAB International.

70.

Phillips

J. C.

(2005). Generation X: Americans born 1965 to 1976. Choice , 42(6), 1005.

71.

Princeton One. (2016). Understanding Generation Y: What you need to know about the Millennials. Retrieved from http://www.princetonone.com/news/PrincetonOne%20White%20Paper2.pdf

72.

Reisenwitz

T. H.

Iyer

(2009). Differences in Generation X and Generation Y: Implications for the organization and marketers. Marketing Management Journal , 19(2), 91–103.

73.

Roy

(2011). Competitiveness in service sector: A case of hotel industry in India. Global Business Review , 12(1), 51–69.

74.

Schawbel

(2015). Ten new findings about the Millennial consumer. Forbes/Entrepreneurs . Retrieved from http://www.forbes.com/sites/danschawbel/2015/01/20/10-new-findings-about-the-millennial-consumer/#764133d228a8

75.

Schewe

C. D.

Meredith

(2004). Segmenting global markets by generational cohorts: Determining motivations by age. Journal of Consumer Behavior , 4(1), 51–63.

76.

Sharma

(2013). How cool brands stay hot. International Journal of Retailing & Rural Business Perspectives , 2(1), 324–325.

77.

Sirgy

M. J.

(1982). Self-concept in consumer behavior: A critical review. Journal of Consumer Research , 9(3), 287–300.

78.

Sirgy

M. J.

(1985). Using self-congruity and ideal congruity to predict purchase motivation. Journal of Business Research , 13(3), 195–206.

79.

Sirgy

M. J.

Grewal

Mangleburg

T. F.

Park

J.-O.

Chon

K.-S.

Claiborne

C. B.

… Berkman

(1997). Assessing the predictive validity of two methods of measuring self-image congruence. Academy of Marketing Science Journal , 25(3), 229–241.

80.

Strauss

Howe

(1997). The fourth turning: What the cycles of history tell us about America’s next rendezvous with destiny . New York, NY: Broadway Books.

81.

Travel across the generations . (2006). Washington, DC: Travel Industry Association.

82.

Tyler

(2007). The tethered generation. HRMagazine , 52(5), 40–47.

83.

Tyler

(2008). Generation gaps. HRMagazine , 53(1), 69–73.

84.

Wang

Xiang

(2012). The new landscape of travel: A comprehensive analysis of smartphone apps. In Fuchs

Ricci

Cantoni

(Eds.), Information and communication technologies in tourism (pp. 308–319). New York: Springer.

85.

Werthner

Klein

(1999). Information technology and tourism: A challenging relationship . New York, NY: Springer.

86.

Wolburg

J. M.

Pokrywczynski

(2001). A psychographic analysis of Generation Y college students. Journal of Advertising Research , 41(5), 33–52.

87.

Xiang

Magnini

V. P.

Fesenmaier

D. R.

(2015). Information technology and consumer behavior in travel and tourism: Insights from travel planning using the Internet. Journal of Retailing and Consumer Services , 22, 244–249.

88.

Xiang

Woeber

Fesenmaier

D. R.

(2008). Representation of the online tourism domain in search engines. Journal of Travel Research , 47(2), 137–150.

89.

Yoo

K.-H.

Gretzel

(2011). Influence of personality on travel-related consumer-generated media creation. Computers in Human Behavior , 27(2), 609–621.

90.

Zhu

Dholakia

U. M.

Chen

Algesheimer

(2012). Does online community participation foster risky financial behaviour? Journal of Marketing Research , 49(3), 394–407.