Assessing Hualien’s Agrotourism Destination Image and Revisit Intention: A Secondary Analysis Using Importance-Performance Analysis

Abstract

This study re-examines an archived survey of agrotourism visitors in Hualien, Taiwan region, and reframes the evidence as a descriptive Importance-Performance Analysis (IPA) study rather than a causal test. The dataset contains 141 valid on-site questionnaires collected from visitors at multiple Hualien agrotourism venues. Destination image was measured through four adopted dimensions—product, quality, service, and price image—together with two behavioral-intention items on revisit and recommendation. The archived report provides aggregate reliability evidence (Cronbach’s alpha > 0.80; KMO = 0.867; Bartlett’s test p < 0.001), but dimension-level validation statistics were not preserved; therefore, the four-dimension structure is treated here as an adopted measurement framework rather than a newly reconfirmed factor model. The overall importance mean was 5.8434 and the overall performance mean was 5.805. High-performing strengths were food quality, distinctive cuisine, relaxation, dining comfort, positive service attitude, empathy, problem solving, creative activity design, and favorable revisit and recommendation intention. The archived IPA output also flagged scenic beauty and staff appearance as managerial watch points. Because these two items sit close to the grand means in the reproduced descriptive tables, they should be interpreted cautiously as expectation-sensitive attributes rather than unequivocal failures. The study concludes that Hualien’s agrotourism operators should prioritize visible place aesthetics, frontline presentation, and place-based experiential design while maintaining their strong food and hospitality advantages.

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Lin, C.-N. and Yang. T.-H. (2026) Assessing Hualien’s Agrotourism Destination Image and Revisit Intention: A Secondary Analysis Using Importance-Performance Analysis. Open Access Library Journal, 13, 1-12. doi: 10.4236/oalib.1115174.

1. Introduction

In recent years, tourism demand has shifted from simple sightseeing toward deeper experiences involving local culture, rural life, food, and well-being. Agrotourism is therefore increasingly important because it links agricultural production, landscape resources, environmental education, and leisure consumption within the same destination setting. In this context, destination image matters not only as a marketing concept but also as a practical lens through which operators can understand what visitors value and where service improvement should be prioritized.

Hualien possesses mountains, coastlines, rural scenery, multicultural heritage, and distinctive agricultural products, all of which give it considerable agrotourism potential. However, the competitiveness of an agrotourism destination depends on more than attractive scenery alone. Visitors evaluate the destination as an integrated experience that includes local products, service encounters, environmental quality, and price perceptions. Previous tourism research has consistently shown that destination image is associated with satisfaction, loyalty, recommendation, and revisit intention [1]-[3].

The original archived study on Hualien agrotourism framed the topic as an “influence” relationship between destination image and revisit intention. However, the preserved outputs available for the present manuscript are primarily descriptive tables and IPA results rather than a complete inferential model. To align the article with the evidence actually available, the present paper repositions the study as a descriptive secondary analysis of destination-image evaluations and behavioral-intention items. The purpose is not to claim a confirmed causal effect, but to identify which destination attributes visitors consider important, how well those attributes perform, and which areas deserve managerial attention.

Accordingly, this paper has three objectives: (1) to describe the adopted destination-image dimensions used to evaluate Hualien agrotourism; (2) to report tourists’ perceived importance and performance for individual attributes, including revisit and recommendation intention; and (3) to use IPA to distinguish strengths, watch points, and improvement priorities for local operators.

2. Literature Review

2.1. Destination Image in Agrotourism

Destination image refers to the set of perceptions, impressions, and evaluations that tourists form toward a place before, during, and after a visit [4]. Gunn treated destination image as a central component of tourism-region design [4], while Baloglu and McCleary emphasized that image formation reflects the joint influence of personal factors and stimulus factors [1]. Recent studies further suggest that emotional responses to destination imagery [5], social media affordances [6], and user-generated visual content [7] also shape how tourism destinations are perceived. In agrotourism, destination image typically includes not only natural scenery but also food, agricultural experience, service encounters, environmental cleanliness, and value-for-money perceptions.

Prior work in tourism and agritourism has treated destination image as a multidimensional concept. In the literature in Taiwan region, destination image has been organized into such dimensions as landscape, activities, quality, facilities, service, and price [8] [9]. Later work adapted these into more operational groupings such as product, quality, service, and price image [10]. This four-part structure is particularly useful for agrotourism management because it translates a broad destination-image concept into concrete service domains that can be monitored and improved.

2.2. Revisit Intention as a Behavioral Outcome

Revisit intention is usually defined as a visitor’s willingness to return to a destination or to recommend it to others after the visit [11]. Gitelson and Crompton described repeat visitation as a core manifestation of tourism loyalty [11], and Kozak argued that revisit behavior is shaped by satisfaction, prior experience, and travel-related constraints [12]. In empirical studies, revisit and recommendation intention are often used as concise behavioral indicators of favorable post-visit evaluation [2] [13] [14]. Recent reviews also confirm that revisit intention remains a central loyalty indicator in tourism and hospitality research [15]. In the present article, these two items are treated as behavioral-intention attributes within the descriptive IPA framework rather than as dependent variables in a causal model.

2.3. Importance-Performance Analysis

Importance-Performance Analysis (IPA) was introduced by Martilla and James as a simple but powerful managerial tool for diagnosing service strengths and weaknesses [16]. By plotting the perceived importance of each attribute against its perceived performance, IPA helps identify attributes that should be maintained, monitored, or improved. In tourism research, IPA has been widely used because it turns diffuse visitor evaluations into a clear resource-allocation logic. For agrotourism destinations, the main value of IPA lies in showing where managers should concentrate limited attention and investment to improve the overall visitor experience.

3. Method

3.1. Study Design, Provenance, and Sample

This article is a manuscript redevelopment and secondary analysis of an archived survey study originally conducted by the authors on Hualien agrotourism. The archived Chinese report indicates that questionnaires were administered on site at multiple farms, agricultural sightseeing areas, and agricultural-experience venues in Hualien. The target population comprised visitors who had participated in agrotourism activities in Hualien and were willing to complete the questionnaire. A total of 141 valid questionnaires were retained for analysis.

Several procedural details requested by reviewers cannot be fully reconstructed from the archived report alone. Specifically, the exact survey period, the exact number of participating sites, and the step-by-step recruitment log were not preserved in the manuscript file available for redevelopment. For this reason, the present article describes the sample conservatively as an on-site convenience sample and does not claim statistical representativeness. These archival limitations are acknowledged explicitly so that the empirical scope of the study remains transparent.

Transparency statement. This article is an English-language manuscript redevelopment and secondary analysis of an archived survey study prepared by the same authors. The present version reorganizes the preserved tables and analytical outputs for journal submission and does not involve additional data collection.

3.2. Measures and Item Framework

The questionnaire contained three parts. First, tourist characteristics were measured through seven background variables: gender, age, education, occupation, income, place of residence, and prior travel experience in Hualien. These background variables were adapted from domestic tourism studies on visitor socioeconomic attributes [17] [18]. Second, destination image was assessed through 24 adopted items organized into four dimensions: product image (7 items), quality image (5 items), service image (8 items), and price image (4 items). These items were adapted from earlier destination-image studies [8]-[10]. Third, behavioral intention was measured with two items—revisit intention and recommendation intention—adapted from [2] [13] [14].

All substantive items were evaluated on a 7-point Likert scale twice: once for perceived importance and once for perceived performance (reported in the original study as satisfaction). To improve traceability across Methods and Results, the present article labels the 24 destination-image items as DI1 - DI24 and the two behavioral-intention items as BI1 - BI2. Because the archived report preserved the analytical outputs but not the original raw dataset, the wording and item grouping reported here follow the archived instrument rather than a newly reconstructed questionnaire.

Notably, the archived report states that destination image contained 23 items, but the reproduced descriptive tables enumerate 24 destination-image items (DI1 - DI24) plus two behavioral-intention items (BI1 - BI2). Because the item-level tables and IPA output are internally consistent with 26 total attributes, the present article follows the 24-item destination-image count. Table 1 summarizes the construct definitions, item codes, and adopted sources.

Table 1. Construct definitions, item codes, and adopted sources.

Construct

Codes

Definition/representative items

Adopted from

Tourist characteristics

BG1 - BG7

Gender, age, education, occupation, income, place of residence, prior travel experience in Hualien

[17] [18]

Product image

DI1 - DI7

Scenic beauty, transportation convenience, folk-cultural attraction, agrotourism activity attraction, distinctiveness of local specialty products, food deliciousness, and distinctive cuisine

[8]-[10]

Quality image

DI8 - DI12

Relaxation, learning new knowledge, dining comfort, cleanliness, and public-facility quality

[8]-[10]

Service image

DI13 - DI20

Interpretive ability, attitude, dress/appearance, problem solving, empathy, information access, creative activity planning, and clear circulation/signage

[8]-[10]

Price image

DI21 - DI24

Ticket prices, dining prices, agricultural-product prices, and activity-fee reasonableness

[8]-[10]

Behavioral intention

BI1 - BI2

Revisit intention and recommendation intention

[2] [13] [14]

3.3. Reliability, Validity, and IPA Procedure

The archived report preserved only aggregate measurement diagnostics: Cronbach’s alpha values above 0.80 for the full scales, KMO = 0.867, and Bartlett’s test of sphericity with chi-square = 16316.575, df = 1326, p < 0.001. These results indicate acceptable internal consistency and factorability at the overall scale level. However, dimension-specific alpha coefficients, factor loadings, and other validity statistics were not preserved. Accordingly, the four-dimension structure is treated in this article as an adopted framework derived from the original instrument rather than a factor structure independently reconfirmed in the current manuscript.

For the IPA, the archived report used an overall importance mean of 5.8434 and an overall performance mean of 5.805 as reference values. Items were then grouped into four conventional categories: keep up the good work, possible overkill, low priority, and concentrate here. The archived graphical output appears to have been generated from a standardized spreadsheet rather than from the reproduced raw means alone. Because that spreadsheet is not available, the present manuscript reports the archived quadrant assignment, while also disclosing the raw item means for the two archived priority items so that readers can judge their placement more carefully.

The archived descriptive paragraph also reports an overall performance mean of 5.22, whereas the IPA section reports 5.805. Because the reproduced item-level means range from 5.53 to 6.00 and are therefore consistent with the higher value, the present article uses the archived IPA crosshair value of 5.805 while flagging the discrepancy as an archival inconsistency. The archived reliability and validity information reported in this study is summarized in Table 2.

Table 2. Archived reliability and validity information.

Indicator

Archived result

Interpretation for the present article

Cronbach’s alpha

Overall scale, importance scale, and performance scale > 0.80

Acceptable internal consistency at the aggregate scale level

KMO

0.867

Adequate overall sampling adequacy/factorability in the archived study

Bartlett’s test

chi-square = 16316.575, df = 1326, p < 0.001

Sufficient inter-item correlation for factor-analytic treatment

Dimension-level statistics

Not preserved

The four-dimension structure is treated as adopted, not newly reconfirmed

4. Results

4.1. Sample Profile

The sample was dominated by male respondents (55.3%). The largest age group was 21 - 30 years (45.4%). Most respondents had a university or junior-college education (64.5%), and the largest occupational group was the service sector (27.0%). Monthly income most commonly fell between NT$30,000 and NT$50,000 (40.4%). Respondents from eastern Taiwan region and the outlying islands accounted for the largest residential group (41.4%). Overall, the sample mainly represents relatively young adult visitors with moderate spending capacity and a substantial regional connection to eastern Taiwan region. The sample profile is summarized in Table 3.

Table 3. Summary of sample characteristics.

Indicator

Main distribution

Gender

Male: 55.3%

Age

21 - 30 years: 45.4%

Education

University/junior college: 64.5%

Occupation

Service sector: 27.0%

Monthly income

NT$30,000 - 50,000: 40.4%

Residence

Eastern Taiwan region and outlying islands: 41.4%

4.2. Scale Diagnostics

At the overall scale level, the archived report indicated Cronbach’s alpha values above 0.80 for the combined importance and performance instruments, suggesting good internal consistency. The KMO value of 0.867 and Bartlett’s test result (chi-square = 16316.575, df = 1326, p < 0.001) further indicated that the item set had sufficient intercorrelation for factor-analytic treatment in the original study design. Nevertheless, because the archived material does not preserve dimension-level diagnostics, the present article does not claim new confirmation of the four-dimensional structure.

4.3. Item-Level Importance and Performance

The overall importance mean was 5.84, indicating that respondents generally regarded Hualien’s agrotourism attributes as important. The highest importance scores were DI8 (“helps me feel physically and mentally relaxed”) and BI1 (“I am willing to plan time to revisit this destination”), both at 6.02. BI2 (“I would recommend Hualien to others”) followed closely at 6.01. These results suggest that relaxation and favorable future behavioral intention are central to visitors’ evaluation framework.

Most performance means fell between 5.53 and 6.00, indicating moderate to high satisfaction overall. The highest performance scores were DI1 (“the scenery is beautiful”) and BI2 (“I would recommend Hualien to others”), both at 6.00, followed by DI8 (“helps me feel physically and mentally relaxed”) and BI1 (“I am willing to revisit”), both at 5.99. The lower-performing items were DI2 (“transportation is convenient,” 5.53) and DI24 (“fees for experience activities are reasonable,” 5.69). Thus, Hualien’s agrotourism appears strongest in scenery, relaxation, and positive word of mouth, while accessibility and perceptions of activity pricing remain comparatively weaker. The complete item-level importance and performance means, together with the archived IPA category assigned to each attribute, are reported in Table 4.

Table 4. Item-level importance and performance means with archived IPA classification.

Code

Attribute

Importance

Performance

Archived IPA category

DI1

The scenery is beautiful

5.81

6.00

Concentrate here (archived)

DI2

Transportation is convenient

5.73

5.53

Low priority

DI3

Folk-cultural activities are attractive

5.57

5.56

Low priority

DI4

Agrotourism experience activities are attractive

5.64

5.65

Low priority

DI5

Agricultural specialty products are distinctive

5.67

5.75

Low priority

DI6

Food is delicious

5.90

5.88

Keep up the good work

DI7

Food has distinctive characteristics

5.88

5.85

Keep up the good work

DI8

Helps me feel physically and mentally relaxed

6.02

5.99

Keep up the good work

DI9

Helps me learn new knowledge

5.65

5.77

Low priority

DI10

Dining environment is comfortable

5.87

5.80

Keep up the good work

DI11

Dining environment is clean and tidy

5.94

5.79

Possible overkill

DI12

Public facilities are of good quality

5.92

5.77

Possible overkill

DI13

Staff have professional interpretive ability

5.68

5.74

Low priority

DI14

Staff have a good attitude

5.94

5.82

Keep up the good work

DI15

Staff are neatly dressed

5.73

5.84

Concentrate here (archived)

DI16

Staff can solve problems quickly

5.85

5.85

Keep up the good work

DI17

Staff show empathy

5.88

5.83

Keep up the good work

DI18

Tourism information is easy to obtain

5.87

5.80

Possible overkill

DI19

Experience activities are creatively designed

5.88

5.89

Keep up the good work

DI20

Circulation and explanatory signage are clear

5.95

5.84

#not listed/likely near keep or overkill

DI21

Ticket prices are reasonable

5.84

5.78

Low priority

DI22

Dining prices are reasonable

5.89

5.76

Possible overkill

DI23

Agricultural specialty-product prices are reasonable

5.90

5.76

Possible overkill

DI24

Experience-activity fees are reasonable

5.89

5.69

Possible overkill

BI1

I am willing to plan time to revisit

6.02

5.99

Keep up the good work

BI2

I would recommend Hualien to others

6.01

6.00

Keep up the good work

Note. DI20 was not explicitly assigned to a quadrant in the archived narrative even though its mean values place it close to the overall crosshair. The two archived “concentrate here” items (DI1 and DI15) are retained for transparency, but their placement should be interpreted cautiously.

4.4. Archived IPA Interpretation

Using the archived IPA classification, ten attributes were placed in the “keep up the good work” quadrant: delicious food (DI6), distinctive food characteristics (DI7), relaxation (DI8), comfortable dining environment (DI10), positive staff attitude (DI14), rapid problem solving (DI16), staff empathy (DI17), creative activity design (DI19), revisit intention (BI1), and recommendation intention (BI2). Six items fell into “possible overkill”: clean dining environment (DI11), quality public facilities (DI12), ease of obtaining tourism information (DI18), reasonable dining prices (DI22), reasonable agricultural-product prices (DI23), and reasonable activity fees (DI24). Seven items were classified as “low priority”: convenient transportation (DI2), attractive folk-cultural activities (DI3), attractive agrotourism experiences (DI4), distinctive agricultural specialty products (DI5), learning new knowledge (DI9), professional interpretive ability (DI13), and reasonable ticket prices (DI21).

The archived graphical output identified two “concentrate here” items: scenic beauty (DI1) and staff appearance/clean dress (DI15). To make this placement transparent, Table 5 reports their reproduced raw means. DI1 had an importance mean of 5.81 and a performance mean of 6.00, while DI15 had an importance mean of 5.73 and a performance mean of 5.84. Because both items lie close to the overall reference values and because the archived plot was based on a standardized spreadsheet that is no longer available, these two attributes are best interpreted as expectation-sensitive managerial watch points rather than as straightforward low-performing failures. This interpretation is especially important for scenic beauty, whose absolute performance mean was high even though the archived IPA figure still marked it as a priority area.

Table 5. Item-level means for the two archived “concentrate here” attributes.

Code

Attribute

Importance

Performance

Compared with crosshair

Interpretive note

DI1

The scenery is beautiful

5.81

6.00

Importance slightly below; performance above

Archived priority/ watch-point item despite high absolute performance

DI15

Staff are neatly dressed

5.73

5.84

Importance below; performance near overall mean

Archived priority/watch-point item located close to the crosshair

Note. The overall IPA crosshair values were importance = 5.8434 and performance = 5.805. Both archived priority items are located close to these reference values, so their quadrant placement should be interpreted cautiously.

5. Discussion

The first substantive implication is that Hualien’s agrotourism strengths are concentrated in emotionally salient and experience-rich attributes: food quality, distinctive cuisine, relaxation, interpersonal warmth, and activity creativity. These are the elements most likely to generate memorable experiences and support favorable revisit and recommendation intention. The finding is broadly consistent with prior agrotourism studies showing that destination image and affective experience are closely tied to loyalty-related outcomes [19] [20].

Second, the archived priority items suggest that visible presentation still matters. Even when absolute satisfaction is not low, visitors in scenic rural destinations may hold unusually high expectations for landscape beauty and for the professional appearance of frontline staff. In that sense, image management in agrotourism is not limited to service attitude; it also includes the visual coherence of the site, the impression conveyed by staff presentation, and the shareable aesthetic quality of the environment. For Hualien operators, this means that visible place quality remains strategically important even when other aspects of the experience are already well received.

Third, the low-priority placement of transportation convenience, interpretation, and learning content should not be read as meaning that these attributes are unimportant in all contexts. Rather, within this sample they were less decisive than food, relaxation, and interpersonal service. If Hualien seeks to strengthen deeper place attachment and educational value, however, these attributes deserve long-term improvement because they can help convert a pleasant rural outing into a more distinctive and meaning-rich destination experience.

The sample composition also helps explain the pattern of findings. Nearly half of respondents were 21 - 30 years old, and the largest residential segment came from eastern Taiwan region and the outlying islands. A younger and regionally closer sample may place relatively greater value on relaxation, social recommendation, and immediately appreciable experience attributes, while long-haul visitors, family groups, or older cohorts might evaluate accessibility, interpretive depth, and facility design differently. The managerial implications should therefore be applied most confidently to visitor segments resembling the present sample.

6. Managerial Implications

(1) Managers should first strengthen visible place aesthetics and frontline presentation. Landscape maintenance, photo-spot design, site tidiness, signage consistency, uniforms or dress guidelines, and reception etiquette all contribute to the first impression that visitors form and share with others.

(2) Second, operators should maintain their strongest competitive assets—food quality, distinctive cuisine, relaxation, and hospitable interaction—because these are the attributes most clearly positioned in the high-importance/high-performance area of the archived IPA output.

(3) Third, local culture and agricultural learning should be deepened through better interpretation and activity scripting. Even if these attributes were not the immediate priorities in the archived IPA chart, they remain central to what differentiates agrotourism from generic sightseeing.

(4) Finally, resource allocation should be selective rather than uniform. Basic service quality in facilities, information access, and price fairness should be maintained, but additional investment is likely to have greater strategic value when directed toward the visible and memorable components of the destination experience.

7. Conclusions

This study repositions the Hualien agrotourism survey as a descriptive IPA-based assessment rather than a direct causal test of influence. The evidence shows that visitors evaluated Hualien positively overall, especially with regard to food, relaxation, service attitude, activity creativity, and favorable revisit and recommendation intention. At the same time, the archived IPA output indicates that visible destination presentation—especially scenic aesthetics and staff appearance—deserves managerial attention, although those two items should be interpreted cautiously because their reproduced raw means lie close to the overall crosshair values.

Overall, the findings suggest that Hualien’s agrotourism competitiveness depends on maintaining strong experiential and hospitality assets while refining the visible and place-based aspects of destination image. The study therefore offers practical guidance for operators seeking to allocate resources more effectively in rural tourism settings.

8. Limitations and Future Research

Several limitations should be acknowledged. First, the study is based on 141 valid questionnaires from one destination and should not be generalized mechanically to other agrotourism regions. Second, the present manuscript is a secondary analysis of an archived survey report; the exact survey period, exact number of participating sites, and detailed recruitment protocol were not preserved in the file available for redevelopment. Third, the raw dataset and original spreadsheet calculations were unavailable, so direct inferential tests linking destination image dimensions to revisit intention could not be re-estimated and the archived IPA plotting logic could not be fully reproduced. Fourth, dimension-level reliability and validity statistics were not retained in the archive, which means the four-dimension structure should be understood as adopted rather than newly validated in this article.

Future research should collect a fresh multi-site dataset, report sampling procedures more fully, test the measurement structure at the dimension level, and use inferential methods such as regression or structural equation modeling to examine whether and how destination image dimensions shape revisit intention in Hualien and other agrotourism destinations.

Conflicts of Interest

The authors declare no conflicts of interest.

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