Evaluation of Segment Attractiveness by Risk-Adjusted Market Potential

Abstract

Numerous studies on destination marketing assume that repeat visitors are a more attractive market segment than first-time visitors. The current study questions this assertion, by focusing separately on the balance between economic potential, as determined by tourists’ spending, and risk. Specifically, the methodology adopted here integrates assessment of risks involved with targeting the two separate market segments. Consequently, it is possible to calculate a more comprehensive and accurate assessment of the relative attractiveness of different market segments. The study relies on a survey conducted in Kissimmee, Florida, a mature destination attempting to avoid decline by attracting more tourists. Analysis of the tourist data reveals that the commonly suggested attractiveness of the repeat visitors segment should be reconsidered. The economic potential of both segments varies across spending categories as well as according to whether per-trip or per-day expenditures are considered. Conclusions and implications for both research and practice are provided.

Keywords

repeat visitors segment attractiveness expenditure risk size risk

Introduction

Competition among businesses aiming at profit maximization coupled with the diversity of consumers’ needs and wants have led to the widely used practice of market segmentation (Dickson and Ginter 1987; Kotler, Bowen, and Makens 2003). This provides organizations with two main capabilities: (1) developing suitable products/services and other marketing functions for each segment and (2) targeting the most attractive segment (or several segments), thus sparing redundant marketing costs and gaining a competitive edge (Dolnicar 2002; Kotler, Bowen, and Makens 2003). As noted by Hu and Yu (2007), a variety of assessment criteria has been proposed, both in the general and tourism marketing literature, in order to assess the attractiveness of market segments and select optimal market mixes. Yet profitability, which typically refers to the segment’s purchasing power, has remained a paramount factor or indicator for measuring segment attractiveness (Kotler et al. 2005; McQueen and Miller 1985; Loker and Perdue 1992).

Although a plethora of factors (e.g., price sensitivity; marketing operations and service costs) affect profitability, in tourism marketing studies profitability is typically assessed by using tourist expenditures as a proxy (e.g., Mok and Iverson 2000; Moufakkir et al. 2004; Perez and Sampol 2000; Pizam and Reichel 1979). Yet this approach has been criticized for neglecting risk issues associated with tourist expenditures (Cardozo and Wind 1985; Jang and Chen 2008). The marketing and consumer behavior literature contains numerous definitions of risk, most referring to organizational situations as well as to consumer risk perceptions associated with the purchase of products or services (Grönroos 2007). For example, Emblemsvåg and Kjølstad (2002) consider organizational strategic risk as a choice apparent whenever there are alternative possible actions faced by the organization. The stream of research dealing with consumer behavior clearly focuses on the individual consumer and often views risk as a consumer’s perception about an unpleasant event associated with the purchase or consumption of a product, service, or tourist experience (Fuchs and Reichel 2010). For the purpose of understanding and analyzing the different patterns of expenditures of tourists, the current study adopts Cardozo and Wind’s (1985) definition that considers risk as unpredictable variations in level of return, either among sets of environmental conditions or through time periods. Along these lines, Jang and Chen (2008) refer to risk in tourism in terms of instability in tourist influx and expenditures, specifying the similarities between financial portfolio theories and managing optimal market mix. The authors further distinguished between two types of risk: expenditure risk and segment size risk. Both risks are calculated in terms of standard deviation (SD), as will be demonstrated later in the article.

Focusing on the market profitability proxy of tourist expenditure, Jang, Morrison, and O’Leary (2004a) consider risk as the level of uncertainty associated with reaching a certain level of travel expenditures, as measured by the two aforementioned dimensions of expenditure risk and segment size risk. With regard to the former, a specific segment might be characterized by high overall spending, yet considerable variations between various segment members may be evident. In terms of the latter, seasonality might significantly affect demand and market potential (Baum and Hagen 1999; Jang 2004). For example, despite a particular segment’s seemingly large size, instability of tourism demand over seasons may negatively affect the segment’s attractiveness (Jang, Morrison, and O’Leary 2002, 2004b). In sum, high “risk” or uncertainty associated with reaching a certain level of travel expenditures or segment size—as measured by the two dimensions of risk—moderates the profitability potential of a segment and should be taken into account when assessing segment attractiveness.

The tourism literature has assessed segment attractiveness from various angles, including serviceability, costs, market potential, and segment structural attractiveness (Jang, Morrison, and O’Leary 2004a). Similarly, as noted above, diverse studies attempted to rank the attractiveness of market segments from the perspective of a particular organization or destination. One classification that has attracted considerable attention in the tourism marketing literature is based on the visitor’s previous visitation history (i.e., first-time vs. repeat visitors). Repeat visitation is an important phenomenon with significant implications for tourism destination marketing. Repeat visitors were found to constitute the majority of all tourists at many destinations (e.g., Darnell and Johnson 2001; Niininen, Szivas, and Riley 2004; Wang 2004). Moreover, the assumption that repeat visitors (and loyal visitors, in general) are a preferable market segment is prevalent in tourism and hospitality sectors, as is evident in the abundance of loyalty programs and incentives offered for repeat patronage (Bai et al. 2006; Mattila 2006). However, the relationship between repeat visitation levels and tourist expenditure has not been the focus of significant empirical research (Alegre and Juaneda 2006). Moreover, the few existing empirical studies that revealed mixed results regarding the segments’ expenditure patterns relied on partial measures of evaluation, without focusing on risk considerations (e.g., Oppermann 1997; So and Morrison 2004; Wang 2004).

The current study analyzes first-time versus repeat visitors segment attractiveness by adding a risk factor related to tourist expenditures and visitation patterns. This analysis applies the Risk-adjusted Market Potential Index (RMPI) model suggested by Jang, Morrison, and O’Leary (2004a, 2004b). The model integrates mean expenditures, expenditure risk, segment size, and segment size risk as the evaluation criteria for assessing and comparing market segments. Three risk-adjusted indexes are calculated in order to simultaneously consider expenditure level, market segment size, market potential, and risk in the process of segment attractiveness evaluation.

Using such a precise and comprehensive empirical approach to ranking the attractiveness of first-time versus repeat visitors can shed further light on our understanding of segment attractiveness measurement and generate marketing implications for destination promoters as well as for particular sites and attractions within a destination.

Background Literature

Throughout the years, the scientific literature has suggested an abundance of segmentation criteria, including those based on consumers’ sociodemographics, psychographics, geographical origin, and behavior (Shoemaker, Lewis, and Yesawich 2007). As a discipline that relies heavily on marketing concepts, hospitality research pays special attention to the value of segmentation (e.g., Pennington-Gray, Fridgen, and Stynes 2003; Reid and Reid 1997; Schewe and Calantone 1978). For example, one of the most popular behavioral techniques in this discipline involves the differentiation of travelers based on their usage rate: light versus heavy users of products or services (Holloway 2004). This segmentation base is heavily supported by studies that indicate that a relatively small fraction of the population is responsible for the lion’s share of the overall purchase and consumption of a wide range of products (Twedt 1964; Wasnik and Park 2000). User-based segmentation has been widely applied in tourism and hospitality research (e.g., Goldsmith and d’Hauteville 1998; Goldsmith and Litvin 1998; Litvin 2000; Woodside, Cook, and Mindak 1987). A more advanced type of segmentation relates to the nature of customer demand in case of increased consumption: quantity versus quality. The former refers to a segment that increases the number of vacation days, while the latter tends to increase the quality of the service, usually in terms of willingness to pay more for higher-quality services (Fleischer and Rivlin 2009). One of the leading user-based segmentation approaches refers to customer loyalty to a specific brand. This phenomenon is often referred to in the marketing literature as the repeat purchase criterion (Fader and Schmittlein 1993; Yim and Kannan 1999). Repeat brand purchase is considered to be a more efficient segmentation criterion than overall usage rate (heavy vs. light) of products or services. Given that companies generally retain their customers’ personal details as well as buying routines and history, customer loyalty or repeat purchase can serve as a powerful marketing tool. Specifically, systems like customer relationship management (CRM) facilitate accurate segmentation analysis and accessibility for direct marketing (Lovelock and Wirtz 2007). This way, organizations can cut customer communication costs and simultaneously develop relationship marketing. In the tourism and hospitality literature, the repeat purchase concept and its advantages are usually manifested in terms of first-time versus repeat visitors (e.g., Chen and Gursoy 2000; Fakeye and Crompton 1991; Milman and Pizam 1995).

Since repeat visitation seems contradictory to the novelty-seeking characteristic often attributed to tourists, exploring the reasons that bring visitors back to a familiar destination has been the focus of attention of abundant tourism studies. Gitelson and Crompton (1984) found that desire to reduce risks associated with unfamiliar destinations, intent to ensure a quality vacation, emotional attachment to the destination, and a desire to share with friends and relatives past, satisfying experiences were significant motivational factors for repeat visitation. Li et al. (2008) concluded that “a need for stability and continuity may spur a number of individuals to become repeat tourists who enjoy familiarity with the destination for either (or both) aesthetic reasons (sentimentality, memory, a sense of belonging) or utilitarian reasons (better knowledge of geographic areas for selected tourism activities)” (p. 278). Other studies revealed association of repeat visitation with a quest for authenticity and deeper meaning to their trip, especially when visitors return to the destination with the purpose of strengthening their relationships with either local residents or fellow tourists (e.g., Kim and Jamal 2007; Levy and Hassay 2005).

As noted earlier, the differentiation between first-time and repeat visitors has proven to be an effective basis for consumer market segmentation. The two segments were found to vary in terms of their motivations and activities at the destination. In comparison to repeat visitors, first-timers tend to be more explorative and adventurous in nature (i.e., involved in more activities and visit more iconic attractions), have greater interest in sightseeing and geographically dispersed vacations, and spend more time at the destination. Repeat visitors, on the other hand, concentrate most of their activities in a more limited area than first-timers, tend to engage in more recreational activities, and tend to assign higher value to shopping and dining (Lau and McKercher 2004; Oppermann 1996, 1997; Tiefenbacher, Day, and Walton 2000). Fuchs and Reichel (2010) found significant differences between first and repeat visitors in terms of destination risk perception, risk reduction strategies, and motivation for the visit. McKercher and Chan (2005) concluded that visitation history is a powerful predictor of visitors’ trip-related characteristics. Similarly, Li et al. (2008) noted this segmentation base as an antecedent of planning behavior and posttrip evaluations. Finally, repeat customers/visitors are commonly perceived as an attractive market segment that is more profitable and less costly than first-time visitors, and thus, they should receive high priority in terms of targeted marketing efforts.

The high profitability value attributed to repeat customers has been enthusiastically adopted in tourism and hospitality, resulting in an abundance of loyalty programs and other incentives offered to encourage and reward repeat visitation, such as service guarantees and complaints management programs (Dowling and Uncles 1997; Klophaus 2005; Shoemaker and Lewis 1999). Lehto, O’Leary, and Morrison (2004) observed that generating behavioral loyalty among visitors has become an important goal of destination marketers, as “many destinations adopt a business strategy focused on attracting tourists to visit more than once” (p. 801). In some cases, formal loyal visitors programs were established to offer incentives to revisit destinations (Fyall, Callod, and Edwards 2003).

Oppermann (1998) explains the growing appeal of encouraging repeat visitation by the prevalent (albeit, not proven) marketing perception that “it is five or six times more effective to attract previous customers than it is to gain new ones” (p. 131). Bowen and Shoemaker (1998) considered the loyalty trend to be a central element of the transaction from traditional marketing, which focuses on short-term goals and single sales, to relationship marketing, which focuses on ongoing contact with customers. They also mentioned other benefits of customer loyalty such as reduced marketing costs and customers’ lower price sensitivity. Loyal customers are also claimed to generate more positive word-of-mouth advertising and express more intention to repurchase (Reichheld and Sasser 1990). In addition, mature or saturated destinations rely heavily on attracting repeat visitors, assuming that their loyalty would compensate for the expected declining demand (Ioannides 1992; Oppermann 1998).

Nevertheless, the high value attributed to repeat customers has not been unanimously accepted in the marketing literature (Oppermann 1998; Henry 2000). Empirical studies designed to examine the profitability of loyal versus nonloyal customers have revealed inconclusive and contradicting results (e.g., Helgessen 2006; Ranaweera 2007; Loveman 1998), which at the least constitute an indication that the value of the former might be overestimated. Tourism studies on the characteristics of first-time versus repeat visitors have often used travel expenditure as a proxy for assessing segment attractiveness, and their results frequently contribute to the lack of clarity on the issue. In some studies, first-timers were found to spend more (Li et al. 2008; Jang et al. 2004; Petrick 2004), while in Wang’s (2004) study on Chinese tourists to Hong Kong, repeaters were actually the big spenders. In other cases, nationality was found to be a significant moderating variable in the relationships between visitation patterns and expenditures (Oppermann 1997; So and Morrison 2004).

This lack of clarity regarding the value of repeat visitors might pose problematic consequences for the marketing efforts of destinations as well as for specific tourism and hospitality ventures, especially from a strategic-choice perspective. This challenge becomes more complicated when adding the aforementioned risk dimension. Specifically, the need to alleviate the fluctuations in tourist demand expressed in either number of visits or expenditures in order to minimize the volatility or instability of the tourism industry. The instability in the tourism industry has been criticized as a drawback, leading to adverse effects on the local economy. For example, in a country like Israel, there are clear patterns of high- and low-demand cycles, often determined by geopolitical events (Collins-Kreiner et al. 2006). These fluctuations highly increase the risk of investing in the hospitality industry and often result in lack of additional investment or failure to upgrade. These risks, generating fluctuations, are powerful regardless of the particular nature of the tourist segments (Mansfeld and Winckler 2008). In sum, considering not only a segment’s expenditure level but also variation in spending can contribute to better stability of the tourism industry. The current study aims to bridge these gaps in the literature, taking the tourism destination of Kissimmee as a case study.

Study Objective

The current study focuses on the contribution of first-time and repeat visitor segments to tourist destinations as well as to various local ventures by analyzing their attractiveness in terms of expenditures as proxy for profitability. In addition, the analysis integrates variability among segment members as well as fluctuations in tourist arrivals. As such, the study proposes a behavioral-economic analysis, incorporating Jang, Morrison, and O’Leary’s (2004a, 2004b) methodology into the study of first-time versus repeat visitors. Applying this risk-adjusted attractiveness assessment is intended to assist in targeting the segment with the most economic market potential. As noted earlier, using a more precise and comprehensive empirical approach to ranking the attractiveness of first-time versus repeat visitors can shed further light on our understanding of segment attractiveness measurement and generate marketing implications for destination promoters as well as for particular sites and attractions within a destination.

Method

Study Destination

The destination chosen for the present study is Osceola County in the State of Florida, a region marketed internationally as Kissimmee. As can be seen in Figure 1, during the decade between 1998 and 2007 approximately 5 to 6 million tourists visited Osceola County yearly (Kissimmee Convention and Visitors Bureau 2009). Situated at the periphery of Orlando, Kissimmee’s main attractor is its geographic proximity and accessibility to central Florida theme parks and attractions. However, Kissimmee has several attractions of its own, encompassing the entire spectrum of tourism and hospitality sectors, such as restaurants, museums, historic sites, shopping facilities, and sport activities. Kissimmee tourists account for nearly $3 billion in revenues, making travel and tourism a most important industry. In addition, Croes and Severt (2007) demonstrated that tourist expenditures in Kissimmee have a significant multiplier effect on the local economy. However, a careful examination of annual tourist visits to Kissimmee between the years 1998 and 2008 (see: Osceola County 2008) indicate a relatively unstable, or stagnated, destination in terms of Butler’s (1980) destination life-cycle model.

Figure 1.

Yearly Overnight Visitation to Kissimmee, Florida

Research Instrument and Sample

The instrument used for data collection is an annual standard tourist study questionnaire issued by Kissimmee Convention and Visitor Bureau (KCVB). The purpose of the questionnaire was to collect reliable data about tourist behavioral patterns, mainly in terms of accommodation, dining, and other hospitality and leisure activities such as shopping and visiting attractions. The questionnaire also included specific and explicit questions about expenditures on each item consumed while visiting Kissimmee. For the purpose of the current study, three major parts of the 2006 KCVB survey were used: (1) sociodemographic variables such as country of origin, age, and annual income; (2) trip-related characteristics such as number of previous visits, length of stay, party size, and accommodation type; and (3) travel expenditures, including lodging, food and restaurant meals, car rental, gasoline, activities and entertainment, and shopping. Again, the expenditures used for the current analysis refer to the Kissimmee area only. It should be noted that from the viewpoint of the DMO, gasoline or car rental expenditures, spending that might be used to travel out of the destination, are still part of the economic gains from tourism.

The study uses data collected by the KCVB, which conducts regular intercept surveys among overnight visitors to the destination. The survey was conducted in 2006 over a 12-month period, on both weekdays and weekends, resulting in approximately 10,600 participants. The data set used for the current study included 4,305 respondents who reported their travel expenditures and number of prior visits to the destination. Respondents with data showing excessive and disproportional travel expenditures were excluded from the analysis, under the assumption of erroneous data processing. This exclusion left a sample of 4,289 for the analysis. All the participants were recruited by trained interviewers from lodging facilities in Kissimmee–St. Cloud, including hotels, motels, and timeshare properties, immediately subsequent to checkout. Excluded from the survey were the segments of business and convention participants, campground visitors, theme park hotel guests, and visiting friends and relatives (VFR) and day visitors.

Of the 4,289 survey participants, 3,072 (71.6%) were domestic U.S. visitors and 1,217 (28.4%) were international visitors. Most of the participants ranged in age from 30 to 49.9 (61.5%), and more than half (55.7%) earned an annual salary of $60,000 or more. Regarding accommodation type, the vast majority stayed in a hotel/motel (78.2%) and the rest in timeshare establishments (21.8%). In addition, the average length of stay was 5.02 days (SD = 3.10) and average party size was 3.01 (SD = 1.55). Of the current study sample, 1,872 (43.6%) were first-time visitors (i.e., those with no previous overnight visits) versus 2,417 (56.4%) repeat visitors (i.e., those with one or more previous overnight visits to Kissimmee).

Analysis Procedure

As noted earlier, the main statistical analysis to distinguish between the segment attractiveness of first-time versus repeat visitor is based on the RMPI model for evaluation of tourist segment attractiveness, as suggested by Jang, Morrison, and O’Leary (2004a, 2004b). The analysis comprises five components (see Figure 2). First, each segment’s mean expenditures were used as proxy for business profitability potential. Second, two risk types were considered for each segment: expenditure risk and segment size risk. The expenditure risk refers to the disparity of the segment’s expenditures relative to a segment’s expenditure mean, and it is calculated in terms of standard deviation. This measure indicates the amount of variation from the segment’s mean. A large standard deviation in the expenditures within a segment implies that there is less likelihood of obtaining the mean expenditure, and vice versa. A large standard deviation therefore means that the segment is riskier. The segment size risk is calculated as the standard deviation in monthly frequency distribution of tourists for each segment. Clearly, in the occurrence of high seasonality effect, there is more uncertainty in obtaining the monthly mean frequency of the segment.

Figure 2.

Illustration of the Analysis Procedure

Third, segment mean expenditures and its corresponding expenditure risk are simultaneously considered in computing the Risk-adjusted Expenditure Index (REI). The REI indicates the relative expenditure level per unit of risk for a segment and is calculated by dividing the mean expenditure by the expenditure risk, multiplied by 100. The segment with the higher REI is considered the best from an expenditure level standpoint.

Fourth, the Risk-adjusted Segment Size Index (RSSI) is computed by dividing the segment size by the segment size risk, multiplied by 100. The RSSI represents the relative seasonal risk-adjusted frequency of each segment. The segment with the higher RSSI is considered to have a better market size after adjusting for the effect of seasonality. Lastly, the overall attractiveness of each segment is determined by the Risk-adjusted Market Potential Index (RMPI). It is calculated by multiplying REI with RSSI, and then dividing it by 100. The RMPI takes into account the segment’s market profitability potential and segment size risks at the same time; this constitutes a more comprehensive estimation with regard to each segment’s attractiveness than exclusively considering expenditures. Higher RMPI points to superior market attractiveness, and vice versa.

The assessment procedures for the evaluation of the first-time versus repeat visitor segments, including the RMPI, were conducted for both total tourist expenditures at the destination and expenditures for each hospitality sector separately (e.g., lodging, food and restaurant meals, shopping). This computation was performed to capture visitors’ spending pattern variability across hospitality sectors. Consequently, each hospitality sector might have its own most attractive tourist segment. In addition, all measures, including RMPI, were calculated for both per-trip and per-day expenditures, as the attractiveness of the segment might be determined by spending for the entire trip, or based on per-day expenditures. This distinction depends on marketing considerations and priorities of different businesses within the destination, as well as the destination as a whole.

Findings

Profiles of First-Time vs. Repeat Visitor Segments

Both segments (first-time and repeat visitors) were compared in terms of their sociodemographics and trip-related characteristics by using chi-square test of association and independent sample t-tests (see Table 1). Statistically significant differences were found between the segments with regard to all sociodemographic characteristics: age, country of origin, and annual income. Generally, in both segments the percentage of domestic tourists exceeds that of international tourists. Yet as depicted in Table 1, the first-time visitor segment was characterized with a statistically significantly higher rate of international visitors, in comparison to the repeat visitors. Repeat visitors, on the other hand, had a higher proportion of high-income respondents as well as a higher rate of older age groups.

Table 1.

Sociodemographic and Trip-Related Characteristics of Segments

Variable	First-Time Visitors	Repeat Visitors	χ² or t Value
Country of origin			χ² = 486.070^***
United States	54.4	85.0
International	45.6	15.0
Age			χ² = 277.354^***
18-29	22.0	11.3
30-39	40.5	29.5
40-49	24.6	29.2
50-59	9.5	16.1
60-69	3.0	11.8
≥70	0.5	2.1
Annual income			χ² = 409.284^***
≤$20K	4.3	1.0
$20,001-$29,999	8.8	3.4
$30,000-$39,999	18.3	8.8
$40,000-$49,999	16.8	10.2
$50,000-$59,999	11.8	8.8
$60,000-$69,999	9.3	9.8
$70,000-$79,999	6.1	9.7
$80,000-$89,999	5.7	8.5
$90,000-$99,999	3.7	8.4
≥$100K	6.0	17.0
Refused	9.2	14.4
Length of stay	5.17 (2.99)	4.89 (3.18)	t = −2.915^**
Party size	3.01 (1.57)	3.01 (1.52)	t = 0.130
Lodging			χ² = 3.955^*
Hotel/motel	79.6	77.1
Timeshare	20.4	22.9

Note: Values are % or M (SD).

p < .05. **p < .01. ***p < .001.

With respect to trip-related characteristics, a statistically significant difference was found in regard to the segments’ average length of stay, with first-time visitors showing a higher average length of stay than repeat visitors. Another small difference, albeit statistically significant, was revealed in the chosen lodging type. Although the vast majority of members of both segments chose hotel/motel as their type of accommodation, a slightly higher rate of repeat visitors than first-timers chose to lodge in timeshares. No significant difference was found between the segments with regards to party size.

Risk-Adjusted Expenditure Index

As noted earlier, the mean expenditure of each segment is considered as a proxy for their profitability potential. As can be seen in Table 2, first-time visitors were characterized with higher total mean expenditures than the repeat visitors. This pattern was found both in terms of per-trip expenditures as well as per-day expenditures. However, a closer examination of the various spending categories indicates a more complex picture, with first-time visitors spending, on average, more on food and restaurant meals, lodging (only per-trip), and car rental, while repeat visitors spent more on gasoline, activities and entertainment, as well as on shopping, both per trip and per day.

Table 2.

Attractiveness Assessment of First-Time vs. Repeat Visitors

	First-Time Visitors				Repeat Visitors
	Expenditure	Expenditure Risk	REI	RMPI	Expenditure	Expenditure Risk	REI	RMPI
Total per trip	$968.03	741.67	131	595	$822.31	655.60	125	536
Total per day	$186.37	115.19	162	738	$169.42	91.14	186	794
Food and restaurant meals per trip	$278.47	248.01	112	512	$239.31	212.51	113	481
Food and restaurant meals per day	$55.67	41.91	133	606	$51.33	37.59	137	583
Lodging per trip	$569.75	477.05	119	545	$424.55	388.61	109	466
Lodging per day	$110.58	86.55	128	583	$87.45	52.82	166	707
Car rental per trip	$17.25	88.41	20	89	$5.18	36.79	14	60
Car rental per day	$3.65	21.25	17	78	$1.14	9.41	12	52
Gasoline per trip	$13.74	29.79	46	210	$24.84	35.45	70	299
Gasoline per day	$2.27	5.52	41	188	$5.17	7.69	67	287
Activities and entertainment per trip	$21.36	75.85	28	128	$39.33	91.90	43	183
Activities and entertainment per day	$2.89	10.21	28	129	$7.06	17.33	41	174
Shopping per trip	$67.46	161.31	42	191	$89.10	160.85	55	237
Shopping per day	$11.33	28.54	40	181	$17.27	31.98	54	231

Note: Bolded figures present the higher RMPI scores. Expenditure risk = SD of expenditure; Risk-adjusted Expenditure Index (REI) = (expenditure mean/SD) × 100; Risk-adjusted Market Potential Index (RMPI) = (REI × RSSI)/100.

As can be seen in Table 2, when a particular segment has shown higher mean expenditure in certain spending categories, it was also associated with higher expenditure risk (measured as the SD of expenditures) within the same category. As noted earlier, in assessing the most preferable segment from an expenditure-risk perspective, the Risk-adjusted Expenditure Index (REI) was calculated. Reviewing Table 2 indicates that the first-time segment had higher REI in terms of total per-trip expenditure, while the repeat visitor segment had higher REI in terms of total per-day expenditure. The same pattern was found in the lodging category, where first-time tourists had higher REI in per-trip expenditure, while repeat visitors are characterized with higher REI in per-day expenditure. In addition, repeat tourists were associated with higher REI in food and restaurant meals, activities and entertainment, and shopping, while the opposite was found in regard to gasoline expenses.

Risk-Adjusted Segment Size Index

Although the REI provides useful indication with regard to the attractiveness of the segments from the expenditure level standpoint, there is still a need to consider the effects of the segment size, as it is an important factor in determining the economic viability of the segment. The monthly mean distribution of the segment was used as an estimation of its size. As can be seen in Table 3, on average, repeat tourists have a larger market size (201.42 tourists per month) compared to first-time visitors (156.00 tourists per month). Next, segment size risk was calculated, using the SD of the monthly mean frequency distribution of segment as a proxy. Table 3 shows that despite its larger size during most of the months, the repeat visitor segment is characterized as a riskier market segment in comparison to the first-time segment (47.15 vs. 34.25, respectively). In other words, this would make the variability of the smaller first-time visitor segment more attractive than the larger repeat visitor segment. Finally, the segment size and segment size risk were simultaneously evaluated by measuring the Risk-adjusted Segment Size Index (RSSI). Accordingly, again, first-time tourists (RSSI = 456) emerged as a more preferable market segment than repeat tourists (RSSI = 427), in terms of segment size adjusted for seasonality.

Table 3.

Frequency Distribution of Segments and Size Risk

	First-Time Visitors	Repeat Visitors	Total Sample
Monthly frequency
January	116	255	371
February	133	246	379
March	131	243	374
April	127	246	373
May	152	215	367
June	185	254	439
July	195	182	377
August	226	164	390
September	136	172	308
October	186	176	362
November	156	133	289
December	129	131	260
Segment size	156.00	201.42	N = 4,289
Segment size risk	34.25	47.15
RSSI	456	427

Note: Segment size = monthly mean frequency of segment; segment size risk = SD of monthly mean frequency distribution of segment; Risk-adjusted Segment Size Index (RSSI) = (segment size/segment size risk) × 100.

Risk-Adjusted Market Potential Index

The Risk-adjusted Market Potential Index (RMPI), which simultaneously considers the REI and RSSI, was calculated for overall travel expenditures at the destination, as well as for expenditures in the variety of tourism and hospitality sectors examined in the survey. RMPI was also calculated for both per-trip and per-day expenditures and is used as the major measure for segment attractiveness comparisons.

Reviewing Table 2 reveals that with regard to total per-trip expenditures, first-time tourists seem to be the more attractive segment, with higher risk-adjusted market potential (RMPI = 595), when compared to repeat tourists (RMPI = 536). The picture is reversed when examining the case of total per-day expenditures, in which repeat tourists are revealed as a more attractive segment than first-time tourists (RMPI = 794 and 738, respectively). Taking into consideration the various tourism and hospitality sectors, first-time tourists appear as the more attractive segment, with regard to food and restaurant meals and car rental, while repeat tourists have higher RMPI scores for gasoline, activities and entertainment, as well as shopping. In the case of lodging, the situation was more complex. First-time tourists had higher RMPI in per-trip expenditures than their counterparts, while the latter had higher RMPI in per-day expenditures.

Conclusions and Implications

The findings of the current study raise interesting conclusions with significant implications for both research and practice. First, the reliance of many tourism development and finance studies exclusively on expenditures as an attractiveness indicator of segments seems to provide only a partial view of their economic potential. The current study suggests a more sophisticated and comprehensive evaluation criterion, integrating risk factors that refer to the uncertainty involved with the segments’ variability in expenditures throughout the year. Specifically, the segments’ market potential was adjusted for expenditure risk, which refers to the probability of obtaining the mean expenditure, as well as for segment size risk, which relates to the probability of obtaining the mean frequency distribution of the segments. The role of the RMPI analysis is especially important for mature destinations, where the dilemma about identifying the most attractive segments for further marketing investment is particularly crucial (Ioannides 1992; Oppermann 1998).

Second, the study’s findings illustrate the importance of considering segment attractiveness by both per-trip and per-day expenditures. In some cases, marketers might prefer to focus on a particular market segment with regard to overall spending at the destination, regardless of per-day spending. Such a focus may be advisable when the marginal costs of a day of visit are relatively low (e.g., in terms of additional service and operational costs). On the other hand, when the marginal costs of visitors staying another day are fairly high, marketers may favor focusing on the most attractive segment in terms of per-day expenditures. In the case of Kissimmee, first-time visitors were found to be the more attractive target market when overall spending was considered, and repeat visitors were revealed as more preferable when per-day spending is considered. When confronted with a dilemma as to which segment marketing efforts should be directed to, the destination marketing organization (DMO) should consider additional factors, such as operation, service costs, market structure, and demand elasticity. Specifically, when the operational and service marginal daily costs are relatively high, it is reasonable to predict DMOs to prefer concentrating on the most attractive segment from a per-day expenditure perspective. Clearly, in our case that would be the repeat visitor segment. On the other hand, when the daily operational and service marginal costs are relatively low, it is logical to concentrate marketing resources toward the most attractive segment in terms of overall spending. This procedure facilitates the design of an optimal combination of segment mix.

Third, the suggested model enables DMOs to assess the attractiveness of market segments not only for the destination as a whole but also in terms of subsectors within the tourism and hospitality industry. In other words, it is recommended that different sectors employ different marketing strategies regarding repeat visitation or first-time visitors along the RMPI attractiveness index. For example, in the current study, first-time visitors were found to have the most economic potential for food and restaurant meal consumption and car rental, whereas repeat visitors were a more attractive segment in terms of gasoline consumption, leisure activities and entertainment, and shopping. As noted earlier, from a lodging perspective, first-time visitors are the more attractive segment when overall spending is considered and repeat visitors have more economic potential with regard to per-day spending. Again, the decision on lodging establishments’ target market, in view of this finding, will also rely on marginal cost considerations of visitor’s additional day at the hotel/motel or timeshare establishment.

Finally, the results provide further support for the recommendation to exert caution with regard to the assumed high profitability associated with repeat customers/visitors (Henry 2000; Reinartz and Kumar 2002; Petrick 2004; Oppermann 1998). The current study indicates that the viability of repeat visitors, when compared to first-time visitors, relies heavily on the unit of analysis (i.e., the entire destination or individual hospitality and tourism subsectors) as well as to the aforementioned considerations of per-trip versus per-day expenditures. The findings demonstrate that first-time visitors are an attractive or a preferred market segment for Kissimmee, when overall spending is considered. Again, the prevailing premise asserting that repeat visitors are always the preferable segment (Reichheld and Sasser Jr. 1990) should be replaced with a more cautious approach that relies on empirical market intelligence. In this particular study, both segments seem to be well differentiated with regard to their sociodemographics, which can easily facilitate tailoring specific marketing campaigns to target the two. The first-time visitors to Kissimmee are younger, with lower incomes and a higher proportion of international visitors, and tend to have longer lengths of stay than repeat visitors do. Clearly, the RMPI analysis and application can be relatively easily facilitated when market segments are distinct. The analysis does not relieve the DMOs’ leadership or local destination business executives from making a choice between various segments based on their attractiveness.

Limitations and Future Research

The current investigation has its limitations. First, the research relies on the participants’ accounts regarding their travel expenditures at the destination, which involves the risk of recall bias. Nevertheless, the participants were asked to complete the questionnaire at the end of their vacations (at checkout); thus the accuracy of their reported expenditures is expected to be high.

Second, caution should be exerted in generalizing the study’s results and conclusions, as Kissimmee is a somewhat unique destination, with high proximity and accessibility to the mega theme parks and attractions of central Florida. However, the study illustrates the usefulness of the procedure for target market selection in assessing the attractiveness of first-time versus repeat visitors, especially in a maturing market.

Third, the current analysis is based exclusively on a 12-month period. Clearly, a longer time period would have enabled identifying possible external events that might not necessarily be related to seasonality. It should be noted, however, that obtaining data from DMOs that encompasses longer time periods is often a most challenging task.

Fourth, despite the comprehensive approach to assess segment attractiveness adopted in the current analysis, future studies should integrate additional indicators to derive more definite conclusions. For example, information on the marketing, sales promotion, and operational and service costs for each segment is vital in determining the most attractive target market. Obtaining such information would help to further develop the study’s model.

Fifth, the issue of timesharing passed a challenge for future study. An attempt to fully integrate this segment in the analysis revealed numerous models of ownership and commitment to timesharing, and the ability to subdivide them into workable segments (e.g., owners vs. renters) was doomed to failure. Consequently, the current study included them all in the category of “timesharing” visitors. Clearly, more in-depth investigations should be aimed at this often controversial mean of vacationing.

Sixth, the risk measures introduced in this article represent the assumption that equal weights are assigned to the risks of both “underachieving” and “overachieving” in terms of number of tourists and/or tourists’ expenditures. Evidently, most prediction models reflect attempts at smoothing the demand curve in order to avoid problems of fluctuations, seasonality, cases of overdemand, and problems of exceeding carrying capacity. Future research should further study this assumption in reference to the model presented here, especially in terms of fluctuations in tourist expenditures.

Lastly, the current study did not investigate the information sources used by the interviewers prior to the trip, which is essential for accessibility purposes. Specifically, it is not clear how the respondents gained their information about Kissimmee as a vacation destination. Access to such data would enable the KCVB to reach its target market in a precise way. In addition, further studies should also focus on explaining the different spending patterns and behaviors of first-time versus repeat visitors that were found in this and other studies. It seems that with regard to these pressing issues, the tourism literature has only touched the tip of the iceberg.

Footnotes

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

The author(s) received no financial support for the research and/or authorship of this article.

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