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2025 BMW R 1300 GS Adventure to Quail MotoFest: A Travel Story

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In what is becoming a frequent pilgrimage for me, I attended this year’s The Quail MotoFest—formerly The Quail Motorcycle Gathering—now in its 15th year in Central California’s scenic Carmel Valley. It’s a Concours d’Élégance with motorcycles of every type vying for recognition in segments such as British, Italian, American, and Japanese. This year’s MotoFest featured classes including the 45th anniversary of the BMW GS, Italian Innovation by Bimota, and Yoshimura. There were some crazy customs, too, with about 200 bikes on display all over a lovely grass field near the golf course. Bucket list this if you’ve never been here.


BMW Motorrad invited me, along with a few other moto writers, to ride almost 300 miles from Hollywood over some great back roads on the new R 1300 GS Adventure to Paso Robles for an overnight stay. The next morning, it was on to Carmel Valley for The Quail MotoFest. I was eager to explore the improvements in this new model and the ever-evolving tech integrated by the manufacturer. A new motor, new transmission, new chassis, and familiar user interfaces compelled my interest.

The 2025 BMW R 1300 GS Adventure delivered in every way possible during this on-road trip. There wasn’t much dirt involved outside of a few gravel, side-of-the-road stops, and maneuvers, and that’s okay with this New York City-born rider who never saw a patch of dirt until moving out west.

The GSA for 2025 has been completely redesigned and is svelte but for the look that is dominated by the 7.9-gallon fuel tank. Given the equipment it possesses, the motorcycle weighs in at a claimed 593 pounds unladen, fully fueled, and ready to go. It has been the better part of a year since we had our detailed First Look at the R 1300 GS Adventure, so I won’t go over all the details. Rather than a traditional test, this is a travel story that incorporates some of the features and performance observations I found essential.

Our journey started on U.S. Route 101 from Hollywood to Santa Barbara. On that 85-mile stretch, I was able to get a feeling for the bike in traffic, and I explored the speeds one can ride when unhindered by pesky vehicles. The adaptive cruise control (ACC) helped make this easier—more on ACC later.

The Author.

The GSA simply wants to run at any speed your driver’s license can support. It’s smooth, with a tremendous ability to add velocity quickly with just a twist of the wrist, even in top gear. There does not seem to be a limit to the boxer’s comfort zone. If you need to add 30 mph for a quick pass in a tight spot, just blink, and you’re there with calm precision. Thanks to 110 ft-lbs of torque at 6500 rpm, it’s no surprise, and the 145 horsepower at 7750 rpm doesn’t hurt.

Approaching Montecito, south of Santa Barbara, we exit the 101 and climb to the top of the Santa Ynez Mountains. There, East Camino Cielo is paved but rough and follows the ridgeline west until it meets California State Route 154. A right turn sends us northwest toward Los Olivos in the Sanya Ynez Valley wine country.

While I have ridden up on the east end to visit Big Caliente Hot Springs, I haven’t traversed the westerly route we took. Looking south is a breathtaking, panoramic view of greater Santa Barbara and the Pacific Ocean—a magnificent sight.

East Camino Cielo includes every kind of undulation known to man. From rare 70 mph straights and sweepers to miles of switchbacks and low gear, tight corners. It’s a perfect place to test the GSA’s mountain goat-like abilities, albeit on pavement. It simply soaked up the rough road sections.


I selected Road mode (versus Eco, Rain, Dynamic, and Dynamic Pro) because it provided softer suspension settings, allowing for the smoothest ride possible under these conditions. Later, I learned that I can independently adjust damping within the Settings menu to further dial in the ride.

SR 154 is about 15 miles of two-lane, with occasional passing lanes. The GSA gobbled them up just as we would consume lunch in nearby Solvang, a Danish-themed tourist town offering various food types and high-calorie baked goods. It’s picturesque, yet I couldn’t wait to get back in the saddle for the final segment of day one to our Paso Robles overnight stop.

This last leg is one familiar to me and many SoCal locals and a Top 10 favorite. Foxen Canyon Road heads north out of Los Olivos past countless vineyards and wineries, including Fess Parker Winery & Vineyard and Zaca Mesa Winery.

A right turn after Riverbench Vineyard & Winery onto Tepusquet Road—it’s pronounced like it’s spelled—which basically parallels the 101 to the east. This route serves up another dose of the twisty bits popular with sport-tourer and adventure bike riders. Much of it is narrow with no painted center strip—Heaven, I’d say. This road ends at Cuyama Highway (aka California State Route 166). A left turn and 15 miles put us on El Camino Real (the original name for U.S. 101).


We head north on the 101 through Pismo Beach and San Luis Obispo. After avoiding the temptation to turn right at the famed California State Route 58 for another go at the twisties, we slog 20 more miles to our lodging for the evening.

Dating back to 1857, Paso Robles Inn sits on the edge of Downtown City Park. Paso Robles is a lovely town. The region is renowned for its world-class Zinfandel, Pinot Noir, and other Bordeaux-style blends. I will admit to savoring several over dinner.

The next morning, we have 135 miles to go before we arrive at The Quail Lodge & Golf Club. Much to my surprise and joy, Jimmy Faria, BMW’s ride-leading ex-CHP officer—I rode with him for the 2014 R 1200 RT launch out of Sedona—takes us on a route I’ve never explored.

Ten miles north of Paso Robles, we exited El Camino Real in sleepy San Miguel. From there, we continued north on Indian Valley Road and Peach Tree Road—two more rustic routes with no centerline. Peach Tree Road ends at the intersection of California State Routes 25 and 198. We took 90-year-old Airline Highway (SR 25) 10 miles north to the hamlet of Lonoak. A left turn and 14 miles brought us to King City and back to the 101.

We’re now back on the northbound 101, and 12 miles later, we’re off on old El Camino Real at Greenfield. Instead of going through town, we turn left on Elm Avenue, which points us back toward the coast. Elm ends at Arroyo Seco Road, where we make another left after crossing the Arroyo Seco River on what is locally known as the Green Bridge, which features a now-off-limits steep cement staircase.

After seven miles on Arroyo Seco Road, we turn right on Carmel Valley Road, which takes us 37 scenic miles to The Quail Lodge. Carmel Valley Road is an excellent alternative to the freeway. It’s a bit rough—I drove it last summer and hit a pothole hidden in the shade—and you have to be careful as, again, there is no center line for much of the east end. Of course, I enjoyed it far more on the 2025 BMW R 1300 GS Adventure than I did on four wheels.

As I was the first at Ultimate Motorcycling to get aboard the new boxer GSA, I was anxious to learn everything I could about this sophisticated machine.

Of most interest to me was the new and optional Automated Shift Assistant (ASA), which I chose over the standard manual transmission version. Essentially, ASA is an automatic transmission that can be operated in two modes: M (no clutch, requiring manual shifting with the foot shifter) and D (fully automatic, linked to the ride mode, with manual shift override).


I could wait until further down the screen, but I’ll say it now—I love the ASA transmission and the R 1300 GS Adventure. Now, hear me out before you hate me.

During my decades of riding, I thought that at least two elements were required on a motorcycle—two wheels and a clutch lever. Now, I find out that I can live without that lever. Diehard riders will likely dissent‚ at least until they try it.

Likely, all experienced riders can agree that shifting gears is easy and relatively automatic within our brains. It really doesn’t take any thought to make that happen. Yet, when I removed the need to shift and use the fully automatic transmission, I found that that small slice of bandwidth used to change gears allowed me to focus on the trip, giving me a greater sense of my surroundings and the experience. Never did I feel any loss in the soul of the ride.

From the outset, I was determined to ride in D for most of the trip. I knew I was riding the bike home and keeping it for a while so I could do more extensive testing. For now, I wanted to know what 700 miles was like with ASA doing all the work.


Acceleration through the gears is mostly smooth. As with any automatic transmission you’ve ever driven, various factors—speed, load, throttle position, and rev count among them—determine when the gearbox will upshift to the next cog. First-to-second upshifts can be a bit clunky, especially when powered by a motor delivering this kind of power. Low-speed acceleration, naturally, is smoothest. Yet, when you twist hard, there is a bit of a jolt during low-gear upshifts, but this is to be expected and does not interfere with the quality of the ride.

ASA lacks the finesse of human feathering the clutch when starting from a stop, especially if navigating out of a tight parking lot or other place where there is limited room. It can be slightly grabby, so slow throttle application is required to avoid any lurching until the bike gets going. This is not a big deal once you become familiar with the system.

BMW did not design a new transmission. Per our technical introduction to the bike, we were told that their engineers had adapted the new six-speed manual gearbox to make it automatic. When asked what was done, we were told it was “too complicated to explain.” My guess is that the transmission was fitted with some solenoids, servos, and logic boards to make this a reality. The foot shifter, while it appears to be a traditional mechanical lever, is an electronic switch. So, it does not have the granular feel of the manual transmission mechanism. However, it does the job of shifting gears.

The result is that the ASA simply works, and for a first-year effort, I give it high marks. I did not have to rely upon overriding the ASA’s gear choice even when rounding some 10 mph uphill switchbacks that I’d do in first gear with a manual. With ASA, when I entered a turn in third gear, it would sometimes shift to second and other times remain in third. No matter what the situation, a simple twist of the throttle sent me sailing through the turn and uphill.

The ASA likes to downshift when applying the brakes, and the shifts are perfectly rev-matched. Often, the transmission is a bit slow to downshift when I enter a corner, letting the boxer’s compression slow me down rather than using the brakes. So, when I am strafing some canyons, I often find the transmission in third or fourth gear at the apex when I would rather be in second. This is a perfect time to use the foot shifter to drop down one or two cogs. Still, even if I don’t override the selected gear, there is always enough grunt to yank me through the corner and launch me toward the next one.

I have found similar action with other manufacturers’ automatic transmissions, so this is not a challenge only to BMW. Twisting the throttle will not always cause the transmission to downshift as it might in some automobiles.

The road manners of the suspension are excellent. The Evo Telelever has been improved with a new flex element under the handlebar and a central dual-speed adjustable (DSA) shock. The Evo Paralever out back rocks a central DSA spring strut and electronic load compensation. Riders can dial in damping through the dashboard setup to further customize the stock settings associated with Road, Rain, Eco, Dynamic, and Dynamic Pro modes.

The 2025 BMW R 1300 GS Adventure rails in the twisties better than one might imagine. At high speeds on straight roads, it is solid and smooth, perfect for all-day enjoyment. As for comfort, I’m six-foot-even, and the stock seat height and reach to the bars are just about perfect. Other seating choices can lower the seat to 31.1 inches or as high as 36 inches.

BMW’s Adaptive Vehicle Height Control lowers the bike three-quarters of an inch when coming to a stop, then rises when moving. I never experienced this, but it’s possible it did. I will experiment more on my next ride. The same goes for the Comfort Prop-Up Aid, which is designed to make centerstand usage easier when the bike is in the lowered position.

I enjoyed using the cruise control, which came with the optional Riding Assistant featuring radar sensors for adaptive cruise control, front collision warning, and lane change warning. I never felt the need for active cruise control until I was stuck behind slow-moving traffic that I couldn’t pass safely. When you’re stuck behind traffic or following a riding group, it is a joy to let ACC keep you at the right pace and distance from the vehicle ahead. Riders can adjust the spacing distance in the dash settings. It will also apply the brakes and flash a red warning on the dash when approaching other vehicles too quickly.

There is so much tech now that it would be impossible to have dedicated buttons for items like grip and seat heaters or windshield height adjustment. BMW has added a “hamburger” menu button on the left grip that allows you to control many functions. You can choose a prime function so that the up-down arrow button becomes dedicated to a function of your choice. It takes a bit to get accustomed to it, but once done, it works a treat.

I’ve now passed 1200 miles riding the 2025 BMW R 1300 GS Adventure, and I am completely impressed. I’ll likely add another 600-700 miles this weekend before my editor steals it away from me for his technical review—such is the life of a motojournalist. I must reiterate that even after all these miles, I still adore the ASA. After testing fully manual shifting in M, I was quick to switch back to D. It just works, and I like the extra headspace provided by not needing to think about shifting.

The 2025 BMW R 1300 GS Adventure is a fabulous bike and a significant upgrade from the last few years’ R 1250 GS, which was already a great moto.

Action photography by Kevin Wing
Still photography by Jonathan Handler and Kevin Wing

RIDING STYLE

2025 BMW R 1300 GS Adventure Specs 

ENGINE

  • Type: Horizontally opposed twin
  • Displacement: 1301cc
  • Bore x stroke: 106.5 x 73mm
  • Maximum power: 145 horsepower @ 7750 rpm
  • Maximum torque: 105 ft-lbs @ 6500 rpm
  • Top speed: 124+ mph
  • Compression ratio: 13.3:1
  • Fueling: EFI w/ 52mm throttle body
  • Valvetrain: DOHC w/ dual profile cams; 4vpc
  • Cooling: Liquid and air
  • Transmission: 6-speed
  • Clutch: Hydraulically actuated wet multiplate w/ slipper function (optional $850 automatic clutch and shifting option tested)
  • Final drive: Shaft

CHASSIS

  • Frame: Two-section steel sheet metal w/ bolt-on subframe
  • Front suspension; travel: BMW Evo Telelever 37mm fork w/ shock; 8.3 inches
  • Rear suspension; travel: BMW Evo Paralever and shock; 8.7 inches
  • Wheels: Wire-spoke
  • Front wheel: 19 x 3.00
  • Rear wheel: 17 x 4.50
  • Tires: Michelin Anakee Adventure (Metzeler Karoo 4 tires optional)
  • Front tire: 120/70 x 19
  • Rear tire: 170/60 x 17
  • Front brakes: 310mm discs w/ radially mounted 4-piston calipers
  • Rear brake: 285mm disc w/ dual-piston floating caliper
  • ABS: BMW Motorrad ABS Pro

DIMENSIONS and CAPACITIES

  • Wheelbase: 60.4 inches
  • Rake: 26.2 degrees
  • Trail: 4.7 inches
  • Seat height: 34.3 or 35.0 inches (optional 31.0 to 36.0 inches)
  • Fuel capacity: 7.9 gallons
  • Curb weight: 593 pounds

COLORS

  • Racing Red
  • Style GS Trophy (+$845)
  • Triple Black Package (+$895)
  • Style Option 719 (+$2495)

2025 BMW R 1300 GS Adventure Price: from $23,400 MSRP

2025 BMW R 1300 GS Adventure to Quail MotoFest Photo Gallery

 

 



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Budget & Luxury Travel

Perfect Stay Guide: Must-Have Tips for Effortless Travel Style

Discover how the perfect stay guide can help you choose accommodations that match your travel style, whether you’re seeking luxury indulgence or budget-friendly comfort for an unforgettable trip.

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How to Choose the Perfect Stay for Your Travel Style

Choosing the perfect stay for your travel style can make or break your entire trip experience. Whether you’re planning a relaxing retreat or an adventurous getaway, where you choose to stay sets the tone for your journey. The decision often hinges on several factors, including preferences like luxury vs budget accommodations, whether you’re traveling solo vs group, or if your destination is more urban or rural—city vs countryside. Navigating these choices can be overwhelming, but with the right guidance, you can tailor your accommodation to perfectly align with your travel style. Here’s how to approach this important aspect of travel planning.

Understanding Your Travel Priorities

Before diving into specific options, it’s crucial to identify what kind of travel experience you want. Are you aiming for rest and rejuvenation, cultural immersion, or social interaction? Your answers will reveal a lot about the kind of stay that will best suit you.

Luxury vs Budget: Finding the Right Balance

One of the most common dilemmas travelers face is choosing between luxury vs budget accommodations. Both have distinct advantages depending on your needs and style:

The Appeal of Luxury Stays

Luxury accommodations offer comfort, top-notch amenities, exclusive services, and often prime locations. These stays are perfect if relaxation and indulgence are top priorities. You’ll find five-star hotels, boutique resorts, or lavish villas equipped with spa services, gourmet dining, and concierge assistance. For travelers who value impeccable service and extra pampering—often a solo traveler looking to recharge or couples on romantic retreats—luxury stays can turn an ordinary trip into an extraordinary experience.

Why Budget Stays Are Sometimes Better

Budget options like hostels, guesthouses, or budget hotels appeal to those prioritizing cost savings without compromising on cleanliness and basic comforts. Backpackers, students, and group travelers often prefer budget stays to maximize their travel duration or spend more on experiences rather than lodging. Interestingly, budget accommodations can also foster community and social interaction, especially in dorm-style hostels that encourage mingling among solo travelers.

Bargain Your Way to the Best Hotel Stays

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Striking the Balance

Sometimes, a mid-range option with boutique hotels or higher-end Airbnb units can combine comfort with affordability. Think about how much time you plan to spend in your room versus exploring the destination—this can help you decide how much to invest in your stay.

Solo vs Group: Tailoring Your Stay to Company

Your choice of accommodation should reflect whether you’re traveling solo vs group, as this can significantly influence comfort, privacy, and convenience.

Solo Travel: Emphasis on Security and Connection

Solo travelers often look for safe, comfortable places that also offer opportunities to meet others if desired. Hostels with social areas, small bed-and-breakfasts, or co-living spaces are great for creating connections. On the other hand, solo travelers seeking solitude might prefer boutique hotels or private rentals where they can enjoy peace and quiet. Importantly, solo stays require accommodations that are easy to navigate alone and offer good customer support in case of emergencies.

Group Travel: Focus on Space and Shared Experiences

Groups, whether friends or family, demand ample space and cost-effective options. Vacation rentals or serviced apartments with multiple bedrooms and communal areas work wonderfully for groups. These options often allow you to cook your meals and enjoy quality time together, enhancing the group dynamic. Hotels offering suites or adjoining rooms can also be convenient, providing individual privacy alongside shared space.

City vs Countryside: The Setting Matters

Your destination’s environment—whether city vs countryside—plays a key role in shaping your lodging preferences.

City Stays: Convenience and Connectivity

Urban destinations are typically bustling with activity, so accommodations here often prioritize proximity to transportation, nightlife, museums, and dining hotspots. Hotels or apartments in the city center or near major transit hubs make it easier for you to explore without wasting time commuting. For solo or group travelers alike, the city offers plenty of social opportunities and amenities.

Countryside Stays: Nature and Tranquility

If your aim is to disconnect and recharge, rural stays provide a serene atmosphere surrounded by nature. Farmhouses, cabins, or countryside inns often embody the essence of peace and offer authentic local experiences. These types of accommodations encourage relaxation and allow travelers to engage in outdoor activities like hiking or stargazing. However, keep in mind the potential trade-off in terms of fewer dining and entertainment options nearby.

Additional Tips for Choosing the Perfect Stay

  • Read Reviews Thoroughly: Past guest experiences can offer invaluable insights into what to expect.
  • Consider Amenities: Free Wi-Fi, kitchen facilities, and laundry services can significantly affect comfort.
  • Check Accessibility: Make sure the accommodation suits your mobility needs and proximity to points of interest.
  • Book Early: Especially in popular destinations or during peak seasons, early booking ensures availability and better rates.

Finding the ideal accommodation depends on a clear understanding of your travel style and priorities. Balancing luxury vs budget needs, choosing based on solo vs group dynamics, and factoring in the environment—city vs countryside—will guide you toward the perfect stay. Remember, your lodging isn’t just a place to sleep; it’s part of your travel adventure. Choose wisely, and your stay will enhance your journey, creating memories you’ll cherish forever.

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Ways to Travel

Pursuit of entertainment or self-expression? Research on adventure tourism

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Data collection

The study focused on domestic and foreign tourists aged 18 and above participating in rafting at Antalya Köprülü Canyon. The questionnaires were applied immediately after rafting in-person, and it was thought that the tourists’ experiences were reflected. In order to accurately measure tourist motivations, the literature was reviewed and scales were selected from the literature. In the process of selecting the scales, previously experienced ready-made scales were used, however, the scales were preferred from ready-made scales with high values in terms of validity and reliability. The aim here is to measure the constructs measured in the study in the most reliable way and in a way that can be distinguished from other constructs. For this purpose, scales with high Cronbach α or composite reliability values and AVE (average variance extracted) values were preferred. Then the convenience sampling method was used as the sampling method because there was no random selection. It is a statistical fact that the convenience sampling method does not represent the whole population because it is not random. However, it is easier to apply than random sampling in terms of reaching individuals with new experiences. In addition, as a result of studies that can be carried out in other countries or regions, although it is not a random sample, new literature becomes more debatable and converges to a scientific reality with the literature obtained with the convenience sampling method together with the developing literature.

Participants voluntarily participated in the survey after the rafting experience. Thus, it can be stated that the participants’ responses to the questionnaire were not influenced by any incentives. This situation causes the participants’ views on the subject to be more sincere. The questionnaires were collected in 2021. From 327 questionnaires, 31 were excluded for incomplete data, leaving 296 for analysis. The demographics included 68.1% Russian, 21.5% EU citizens, 9.5% Turkish, and 1% from other nationalities, reflecting general tourism trends in Turkey as reported by the World Travel and Tourism Council (2021). According to the World Travel and Tourism Council (2021) report, 12% of those who came to Turkey in 2019 were Russian, and 8% were German tourists, while in 2020, this rate was 13% for Russians and 7% for Bulgaria, Germany and Ukraine. In this case, it is predicted that the data and results obtained from the target audience will provide correct inferences. Therefore, bias in the study poses as much risk as bias that can occur in real life.

Although 50% of the participants have visited Antalya before, the rate of those who have visited Köprülü Canyon before is 24.3%. In this case, it can be said that individuals who have visited before have returned home without rafting in Köprülü Canyon. The rate of those who have rafted before is 29.7%. The fact that the rates of those who have visited Köprülü Canyon and those who have rafted are close may indicate that individuals tend to do it again after the first experience. While 62.4% of the participants were female, 37.6% were male. In this case, it can be stated that women are more oriented towards adventure tourism. 12.2% of the participants are high school graduates, 21.3% are associate degree graduates, 57.4% are bachelor’s degree graduates, and 9.1% are master’s and doctorate graduates. The average age of the participants was 33.36, while the median was 33.

Measures

Five-point Likert-type scales assessed all constructs. The scales covered “experiencing nature” (Perić et al., 2019), “escape” (Carvache-Franco et al., 2019), and “joy” (Pestana et al., 2020). The “WOM” influence (Sirakaya-Turk et al., 2015) and “self-image congruence” (Sirgy et al., 1997) were also measured, along with “revisit intention” (Zhang et al., 2018).

Data analysis and results

The data analysis validated the measurement model and evaluated relationships between the constructs.

Measurement model

The confirmatory factor analysis (CFA) indicated a satisfactory fit, with chi-square/df at 2.81, CFI at 0.92, SRMR at 0.059, and RMSEA at 0.078 (Hu and Bentler, 1999), as detailed in Table 1.

Table 1 Confirmatory factor analysis results.

Construct validity was confirmed, with convergent and discriminant validity assessed and meeting established thresholds (Hair et al., 2014) as shown in Table 2.

Table 2 The results of the inter-construct correlations and AVE value.

According to Tables 1 and 2, the AVE values are greater than 0.50 and the correlation between the variables. Therefore, convergent and discriminant validity is provided. After this stage of the analysis, common method bias (CMB) or common method variance (CMV) was examined. According to Podsakoff et al. (2003), CMB analysis refers to the bias that emerges from external factors on the data set and occurs when the majority of the variance is explained by a single factor (Podsakoff et al., 2003; Gaskin and Lim, 2016). To measure whether the majority of the variance was gathered under a single factor, the single factor Harman test was performed, and the explained variance rate was calculated as 43%. Since the single factor Harman test is a weak analysis, CMB was re-examined using the Controlling for the effects of an unmeasured latent methods factor analysis suggested by Podsakoff et al. (2003), and each regression path was calculated as 0.64, and the explained variance rate was found to be 41%. Since CMB does not exceed 50% (Eichhorn, 2014: p. 8), it can be said that CMB does not exist or is insignificant (Büyükdağ and Kitapci, 2021).

Structural model

The structural model’s evaluation produced the following results: chi-square/df value at 2.81, CFI value at 0.92, SRMR value at 0.059, and RMSEA value at 0.078. These indices satisfy the criteria set by Hu and Bentler (1999), indicating a good fit between the theoretical model and the observed data.

Table 3 shows that push factors significantly and positively influence self-image congruence (β = 0.66), WOM (β = 0.55), and revisit intention (β = 0.32). Self-image congruity also significantly enhances WOM (β = 0.35) and revisit intention (β = 0.30), while WOM positively impacts revisit intention (β = 0.28). The model explains 44% of the variance in self-image congruity, 68% in WOM, and 66% in revisit intention (Fig. 2).

Table 3 Result of the SEM.
Fig. 2: Structural model with standardized path coefficients.

This figure shows the tested structural model with standardized regression weights, reflecting direct and indirect effects among variables. This figure illustrates the structural model with standardized path coefficients, examining the relationships between push factors, self-image congruity, revisit intention, and word-of-mouth. The push factors are measured through three dimensions: experience nature, escape, and joy. The arrows represent the hypothesized paths, and the numerical values indicate the standardized regression weights. The model shows that push factors significantly influence self-image congruity, revisit intention, and word-of-mouth, both directly and indirectly.

Multi-group structural equation modeling (SEM) and analysis results

Multi-group structural equation modeling (SEM) was employed to compare the regression paths between two variables based on socio-demographic and field-specific characteristics. Various studies have utilized this approach: Yada et al. (2018) to understand teachers’ attitudes and self-efficacy, Al-Swidi and Al Yahya (2017) to examine educational intention and work behavior differences by gender, and Babin et al. (2016), Huang and Ge (2019), Murray et al. (2017), and Aka and Buyukdag (2021) to analyze factors such as culture, household characteristics, store design, and marital status. In this study, multi-group SEM was applied to explore the effects of rafting experience (first-time vs. repeated) and gender (female vs. male model).

According to the multi-group SEM related to rafting experience, the model showed good fit indices with a chi-square/df value of 2.19, a CFI of 0.90, an RMSEA of 0.064, a GFI of 0.79, and an AGFI of 0.73. The comparative analysis between unconstrained and constrained models revealed a chi-square difference of 35.06 and a df difference of 25, indicating no significant variation between the effects of rafting experiences (p = 0.087). Consequently, the research model is applicable to both first-time and repeated rafters. The significance of each path’s rafting experience was further analyzed and is detailed in Table 4.

Table 4 Multi-group SEM results.

According to the multi-group structural equation modeling focused on gender, the model demonstrated good fit indices with a chi-square/df value of 2.17, a CFI of 0.90, an RMSEA of 0.063, a GFI of 0.79, and an AGFI of 0.73. This suggests that the multi-group SEM adequately represents the gender-based differences in the data. Comparative analysis between unconstrained and constrained models showed a chi-square difference of 24.83 and a df difference of 25, indicating no significant variance in gender effects (p = 0.472). Therefore, the research model is equally applicable to both female and male categories. Further analysis was conducted to determine if significant differences exist in local paths based on gender, with detailed results presented in Table 4.

Table 4 shows that push factors affect self-congruence differently for first-time versus repeated rafters. Rafting experience moderates how these factors influence self-image congruence, with a more pronounced effect on first-timers. While push factors significantly impact WOM for both groups, the effect is stronger for newcomers, but rafting experience doesn’t moderate this relationship. Similarly, push factors notably influence revisit intention for first-time rafters, but less so for experienced rafters, where experience doesn’t act as a moderator (Fig. 3).

Fig. 3: Multi-group comparison by visit frequency and gender.

This figure illustrates differences in structural paths across first-time and repeat visitors, as well as male and female participants, using varying line styles. This figure presents the multi-group analysis results based on visit frequency (first-time vs. repeated) and gender (female vs. male). The structural paths between push factors, self-image congruity, revisit intention, and word-of-mouth are illustrated with different line styles. Solid lines represent first-time visitors, dotted lines indicate repeat visitors, dash-dot lines show female participants, and dashed lines represent male participants. Path coefficients are shown along each arrow. The figure highlights how these variables interact differently across groups, revealing variations in motivational and behavioral responses based on experience and gender.

The influence of self-congruence on WOM is significant for both novice and seasoned rafters, more so for the latter. This suggests that rafters with prior experience, and with higher self-image congruity, are likelier to share their experiences. Self-congruence significantly affects intention to revisit among experienced rafters, but not for newcomers. However, rafting experience does not moderate these relationships in either case.

The impact of WOM on revisit intention was significant for first-time rafters but not for repeat rafters, with rafting experience not moderating this relationship. Table 4 shows variance differences between these groups. For first-timers, the explained variance is 51%, while only 26.9% for repeat rafters. For WOM, the variance is 70.5% for first-time users and 66.5% for repeat rafters. Regarding revisit intention, the variance is 65.3% for novices and slightly higher at 66.1% for experienced rafters.

The model showed no significant gender-based moderating effects, but coefficients highlight important relationship nuances. Both genders experience a positive, significant effect of push factors on self-image congruence, with males showing a higher coefficient. The impact of push factors on WOM is significant for both, yet stronger for males. Females, however, demonstrate a greater influence of push factors on revisit intention. The effects of self-congruence on WOM are similar across genders. Males exhibit a more substantial influence of self-image congruence on revisit intention. WOM’s impact on revisit intention is marginally higher in males. While gender doesn’t significantly moderate these paths, the data suggest males typically have higher values in consumer experiences involving adventure and risk-taking.

Self-congruence significantly influences WOM for both first-time and repeat rafters, more so for the latter. This suggests experienced rafters, likely with higher self-image congruity, are more prone to sharing their experiences. Self-congruence also impacts revisit intention significantly among experienced rafters, but less for novices. In both cases, rafting experience does not moderate these relationships.

The study shows gender differences in variance rates for self-image congruity, WOM, and revisit intention. Self-image congruity explains 49.3% of the variance in males and 38% in females. For WOM, the variance is 81.6% in males and 57.7% in females. Regarding revisit intention, males have a variance rate of 68.1% compared to 65.7% in females. These results imply that self-image congruence is more prominent in male first-time rafters, who also tend to discuss their adventurous experiences more, indicating higher communication about risk-taking and adventure among males.

Study 2

A multiple correspondence analysis examined relationships between push factors, self-image congruence, and demographics in adventure tourism for greater insight into consumer behavior dynamics.

Multiple correspondence analysis

Multiple Correspondence Analysis (MCA) is a robust multivariate technique used to examine relationships among nominal data. This method allows researchers to analyze data, interpret findings, and develop perceptual maps, facilitating a deeper understanding of the data structure (Hair et al., 2010; Hair et al., 2014). In this study, MCA was employed to analyze the relationships between individuals’ perceptions of push factors, self-image congruence, WOM, and revisit intentions, alongside demographic or social factors such as gender, nationality, rafting experience, and visiting status. The objective was to conduct in-depth research and derive meaningful inferences. The graphical representation from the Multiple Correspondence Analysis is provided in Fig. 4.

Fig. 4: Joint plot of category points from correspondence analysis.

This plot visualizes the associations between categorical variables, such as nationality, gender, experience, loyalty, and satisfaction. Spatial proximity indicates stronger relationships. This joint plot of category points illustrates the relationships among categorical variables based on their positions along two dimensions extracted through correspondence analysis. The plot visualizes associations between destination-related experiences (e.g., visit status, experiential satisfaction, loyalty), demographic variables (e.g., nationality, gender), and motivational/behavioral outcomes (e.g., push/pull factors, revisit intention, WOM). For example, high revisit intention, high congruity, and high WOM cluster on the right side of Dimension 1, while variables like low satisfaction and low loyalty appear on the left. The spatial proximity between categories indicates stronger associations.

According to the multiple correspondence analysis (MCA) results, repeat visitors to Köprülü Canyon are predominantly Turkish, male, and have prior visits to Antalya and rafting experience. These individuals are notably influenced by push and pull factors and demonstrate high self-image congruity, WOM, loyalty, and satisfaction, indicating a strong intention to revisit. Conversely, first-time visitors to Antalya and Köprülü Canyon are primarily Russian and female tourists, characterized by their pursuit of excitement, unique experiences, and experiential pleasure in adventure and risk-taking activities. Despite showing a high intention to revisit, the likelihood of Russian and female tourists returning is relatively low. This pattern suggests that while tourists enjoy adventure tourism as part of their sea, sun, and sand vacation, it is not the primary purpose of their visit. The findings imply that although tourists have significant rafting experiences and entertainment, they are more inclined to explore different geographical regions rather than revisit the same location. Consequently, it is expected that these tourists will likely choose alternative destinations for their next vacation.

Therefore, emphasizing promotions targeting first-time visitors in rafting or adventure tourism is anticipated to yield significant benefits. Consequently, catering to the preferences of Russian and female tourists with diverse adventure and risk-taking tourism options is projected to create a vital market segment. However, the analysis indicates that European tourists exhibit lower levels of self-image congruity, WOM, revisit intention, and satisfaction with push and pull factors related to rafting. As such, understanding the specific expectations of tourists from the European Union and offering varied tourism alternatives could become a significant source of revenue. Addressing these preferences may lead to enhanced tourist experiences and increased revisit rates.



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