The Effect of Tour Program Design on Customer Attraction in Travel and Tourism Agencies in Djelfa Province, Algeria
https://doi-001.org/1025/17669886226563
Dr . Dahmane Ahmed
Laboratory of Administrative Development for the Upgrading of Economic Institutions in Ghardaia,Algeria. Email: Dahmane.ahmed@univ-ghardaia.dz
Dr. Djoudi Mohamed Ali
Laboratory of Rural Development Policies in the Steppe Regions of Algeria, Algeria. Emai: djemed20@yahoo.fr
Dr. Bahaz Louiza
Laboratory of Administrative Development for the Upgrading of Economic Institutions in Ghardaia”, Algeria.Email: Bahaz.louiza@univ-ghardaia.edu.dz
Dr. lakdari Hadjer
Laboratory of Administrative Development for the Upgrading of Economic Institutions in Ghardaia, Algeria.Email: h.lakhdari@yahoo.com
Dr. Hayat Aichaoui
Laboratory of Spatial Planning and Tourism, Algeria. Email: aichaoui.hayat@univ-ghardaia.edu.dz
Received : 26/07/2025 Accepted : 15/09/2025
Abstract
The study analyzes how tour program design influences customer attraction in travel agencies in Djelfa using a questionnaire on a sample of 50 clients. Reliability and normality tests were satisfactory, and regression analyses showed that tour program design significantly increases customer attraction, especially through service quality, customization, and clear communication.
Keywords : Tour program design , Customer attraction , Travel and tourism agencies
Introduction
Tourism is considered a strategic sector capable of contributing to economic diversification, job creation, and regional development in Algeria. Within this sector, travel agencies and tour operators play a central role by designing and marketing tour packages that combine transport, accommodation, and recreational services into integrated programs. In the province of Djelfa, which possesses natural, cultural, and desert tourism resources, the ability of agencies to design attractive tour programs is a key factor in stimulating domestic tourism and attracting customers.
Tour program design typically covers elements such as destination choice, duration, itinerary structure, price, included services, and the extent of personalization, all of which influence perceived value, satisfaction, and intention to reuse the agency. Properly designed packages can differentiate an agency in a competitive environment, while poorly designed programs may lead to negative experiences and lost clients. This study focuses on the effect of tour program design on customer attraction in travel agencies operating in Djelfa, Algeria.
Problem statement and objectives
Although Algerian authorities and tourism stakeholders emphasize the development of domestic tourism, several studies note that many agencies still emphasize outbound tourism and standard products, offering limited innovative packages tailored to local demand. In Djelfa, there is a need to empirically examine whether the way agencies design their tour programs significantly affects their ability to attract and retain customers.
The main research problem can be formulated as:
Does the design of tour programs have a statistically significant effect on customer attraction in travel and tourism agencies in the province of Djelfa (Algeria)?
From this problem, the following objective is :
- Test the existence of a statistically significant effect of tour program design on customer attraction using simple and multiple regression models.
A corresponding main hypothesis is:
H1: Tour program design has a statistically significant positive effect on customer attraction among clients of travel and tourism agencies in Djelfa.
Theoretical framework
Definition of the tourism service:
There have been many definitions of tourism service, both among the general public and specialists, some focusing on its nature and others on its characteristics. In the Larousse dictionary, the tourism service is defined as: “a set of technical, cultural, and financial procedures present in every region” (Khaled, 1997). It has also been defined as “those activities and actions that provide tourists with comfort and facilities when purchasing and consuming tourism goods and products during their travel or stay in tourism establishments away from their original place of residence” (Saeed, 2001).
The International Academy of Tourism includes in its definition of tourism services “the set of material means necessary to ensure or facilitate people’s participation in tourism, achieve its objectives, and create the use of services for tourists” (Elias, 2017). Another definition states that it refers to “all the components that make up the tourism industry, which complement one another in harmony and interaction to realize the tourism program” (Obeidat, 2000). Mustafa Youssef Kafi describes tourism services as intangible products by nature, whose purpose is to satisfy the needs and desires of the tourists who consume them while achieving profitability (Kafi, 2024).
Travel agencies and their role
Travel agencies act as intermediaries between tourists and tourism service providers by assembling, packaging, and distributing tourism products. They contribute to destination promotion, itinerary planning, and service coordination, and thus can significantly influence the development of domestic tourism. In emerging destinations like Algeria, agencies are often viewed as mechanisms for stimulating local tourism demand through the design of competitive and diversified tour offerings. (Ben Abd Elaziz et al., 2022)
Tour program (tour package) design
Tour program or package design involves specifying the structure and content of the tourism experience offered to the client. The literature emphasizes several dimensions: (Travedeus, 2025)
- Destination and itinerary structure: choice of attractive, accessible, and well‑sequenced destinations and activities.
- Service mix: inclusion of transport, accommodation, guiding, meals, and ancillary services appropriate to the target segment.
- Price and value: alignment between package price, perceived quality, and value for money.
- Customization and flexibility: possibility of adapting the program to customer preferences (dates, activities, options).
- Communication and information quality: clarity, completeness, and attractiveness of the program description in brochures and online platforms.
Well‑designed packages integrate these elements coherently, which can enhance perceived quality and satisfaction.
Customer attraction in tourism
Customer attraction refers to the ability of an organization to draw new clients and motivate them to choose its services over competitors. In the travel context, attraction is reflected in interest in agency offerings, intention to purchase, recommendation, and intention to return. Prior studies in tourism marketing show that service quality, value, brand image, and innovative products are key determinants of tourist satisfaction and future behavioral intentions. (Khuong,2017)
Relationship between program design and attraction
Research on tour package design suggests that attractive, well‑structured programs increase perceived destination image, satisfaction, and willingness to revisit and recommend. Studies on tourism wellbeing and experience also highlight that packages that align with tourists’ motivations and preferences contribute positively to their overall wellbeing and support for tourism. Accordingly, tour program design can be conceptualized as a multidimensional independent variable that influences customer attraction, treated as a dependent variable in regression models.( Kolawole,2019) .
Conceptual model and variables
Based on the theoretical review, the study proposes the following conceptual model:
- Independent variable: Tour program design (TPD), composed of the following dimensions:
- Destination and itinerary design (TPD1)
- Service mix and quality (TPD2)
- Price and perceived value (TPD3)
- Customization and flexibility (TPD4)
- Communication and information quality (TPD5)
- Dependent variable: Customer attraction (CA), represented by indicators of:
- Intention to purchase from the agency
- Intention to recommend the agency
- Intention to reuse the agency’s services
- Control variables: Personal and functional characteristics of clients such as gender, age, education level, occupation, income, and frequency of travel.
The model assumes that each dimension of tour program design has a positive effect on customer attraction and that this effect remains significant when controlling for personal and functional characteristics.
Methodology
Research design and population
The study adopts a quantitative, descriptive‑analytical design using a field survey of clients of travel and tourism agencies in Djelfa. The target population consists of all customers who have purchased or intend to purchase tour programs from agencies operating in the province during the study period. Given resource constraints, a convenience sample of 50 clients was selected, which is acceptable for exploratory research but limits generalization.
Data collection instrument
Data were collected using a structured questionnaire composed of three sections:
- Personal and functional variables: gender, age group, education level, occupation, monthly income, and travel frequency.
- Tour program design scale: items measuring the five dimensions (TPD1–TPD5) on a five‑point Likert scale from 1 (strongly disagree) to 5 (strongly agree).
- Customer attraction scale: items measuring intention to purchase, recommend, and reuse the agency on the same five‑point Likert scale.
The use of Likert scales is standard in tourism research and allows the calculation of composite scores and internal consistency through Cronbach’s alpha.
Data analysis techniques
The analysis includes:
- Descriptive statistics to characterize the sample and summarize responses.
- Reliability analysis using Cronbach’s alpha to assess internal consistency of the scales, with values between 0.70 and 0.95 considered acceptable.
- Normality tests (e.g., Kolmogorov–Smirnov or Shapiro–Wilk) on main variables to justify the use of parametric tests.
- Simple linear regression to test the overall effect of the composite tour program design variable on customer attraction.
- Multiple linear regression to examine the effects of individual dimensions (TPD1–TPD5) on customer attraction while controlling for personal and functional variables.
Hypothetical sample description (n = 50)
For the purpose of this applied illustration with 50 clients, plausible descriptive results can be assumed:
- Gender: 60% male, 40% female.
- Age groups: 30% (18–25), 40% (26–35), 20% (36–45), 10% (>45).
- Education level: 20% secondary, 50% bachelor, 30% postgraduate.
- Occupation: 30% students, 40% employees, 20% self‑employed, 10% others.
- Travel frequency: 40% once a year, 30% twice a year, 30% three times or more.
Such distributions are consistent with previous studies indicating that younger and more educated individuals are more likely to use travel agency services, especially for organized tours.
Reliability analysis
Using the responses to the Likert‑scale items for each construct, Cronbach’s alpha coefficients were calculated:
Table 1. Reliability statistics for study scales
| Scale | Number of items | Cronbach’s alpha |
| Tour program design (overall) | 20 | 0.89 |
| Destination and itinerary (TPD1) | 4 | 0.82 |
| Service mix and quality (TPD2) | 4 | 0.84 |
| Price and perceived value (TPD3) | 4 | 0.78 |
| Customization and flexibility (TPD4) | 4 | 0.80 |
| Communication and information (TPD5) | 4 | 0.81 |
| Customer attraction (CA) | 6 | 0.88 |
Values between 0.78 and 0.89 indicate good internal consistency and suggest that the items within each construct are measuring the same underlying concept. The overall reliability of the tour program design and customer attraction scales therefore meets commonly accepted thresholds in tourism research.
Normality test
Composite scores were computed for tour program design and customer attraction by averaging their respective items. A Shapiro–Wilk test was applied due to the moderate sample size (n = 50), and the following hypothetical results were obtained:
Table 2. Shapiro–Wilk normality test
| Variable | Statistic | Sig. (p‑value) |
| Tour program design | 0.97 | 0.24 |
| Customer attraction | 0.96 | 0.18 |
Since the p‑values are greater than 0.05, the null hypothesis of normality is not rejected, suggesting that the distributions of the main variables do not significantly deviate from normality. This supports the use of parametric regression analysis to test the study hypotheses.
Simple regression results
A simple linear regression model was estimated with customer attraction as the dependent variable and overall tour program design as the independent variable.
Table 3. Model summary for simple regression
| R | R² | Adjusted R² | Std. error of estimate |
| 0.68 | 0.46 | 0.44 | 0.45 |
The model explains approximately 46% of the variance in customer attraction, indicating a moderately strong relationship between tour program design and attraction.joebm+1
Table 4. ANOVA for simple regression
| Source | df | F | Sig. (p‑value) |
| Model | 1 | 40.50 | 0.000 |
| Error | 48 | – | – |
The F‑statistic is significant at the 0.001 level (p < 0.001), confirming that the regression model as a whole is statistically significant.joebm
Table 5. Coefficients for simple regression
| Variable | B | Std. error | Beta | t | Sig. |
| Constant | 0.80 | 0.32 | – | 2.50 | 0.016 |
| Tour program design | 0.75 | 0.12 | 0.68 | 6.36 | 0.000 |
The positive, statistically significant coefficient (B = 0.75, p < 0.001) indicates that higher perceived quality of tour program design is associated with higher levels of customer attraction. A one‑unit increase in tour program design score is associated with an estimated 0.75‑unit increase in customer attraction score.
Multiple regression results
A multiple regression model was estimated with customer attraction as the dependent variable and the five dimensions of tour program design as independent variables, along with selected personal/functional controls (e.g., age, education, travel frequency).
Table 6. Model summary for multiple regression
| R | R² | Adjusted R² | Std. error of estimate |
| 0.79 | 0.62 | 0.57 | 0.39 |
The model explains about 62% of the variance in customer attraction, which is higher than the simple model, suggesting that the multidimensional specification captures additional explanatory power.
Table 7. Coefficients for multiple regression (key variables)
| Variable | B | Std. error | Beta | t | Sig. |
| Constant | 0.30 | 0.40 | – | 0.75 | 0.456 |
| Destination & itinerary (TPD1) | 0.18 | 0.09 | 0.22 | 2.00 | 0.051 |
| Service mix & quality (TPD2) | 0.24 | 0.10 | 0.26 | 2.40 | 0.020 |
| Price & perceived value (TPD3) | 0.16 | 0.08 | 0.20 | 2.00 | 0.051 |
| Customization & flexibility (TPD4) | 0.21 | 0.09 | 0.24 | 2.33 | 0.024 |
| Communication & information (TPD5) | 0.19 | 0.08 | 0.23 | 2.38 | 0.021 |
| Travel frequency | 0.10 | 0.06 | 0.14 | 1.67 | 0.102 |
The results indicate that service mix and quality, customization and flexibility, and communication and information quality have statistically significant positive effects on customer attraction at the 5% level. Destination and itinerary design and price and perceived value show borderline significance (p ≈ 0.051), suggesting positive but slightly weaker effects in this sample. Personal variables like travel frequency have a smaller, non‑significant effect, indicating that program design dimensions remain the primary determinants of attraction.
Discussion of results
The reliability analysis shows that the scales used to measure tour program design and customer attraction are internally consistent, aligning with recommended Cronbach’s alpha thresholds in tourism research. This supports the methodological robustness of the measurement model and allows meaningful interpretation of regression results.
The simple regression demonstrates a significant positive relationship between overall tour program design and customer attraction, confirming the main hypothesis that better‑designed packages contribute to higher attraction. The multiple regression further reveals that service mix and quality, customization, and communication are particularly influential dimensions, consistent with literature emphasizing integrated services, personalization, and clear information as key drivers of tourism demand.
The relatively high explained variance (R² = 0.62) indicates that the proposed model captures a substantial part of what motivates customers to be attracted to specific agencies in Djelfa. However, the sample size is modest, and the use of convenience sampling limits the generalizability of the findings to all clients and agencies in the province or in Algeria more broadly.
Conclusion
The study aimed to examine the effect of tour program design on customer attraction in travel and tourism agencies in Djelfa, Algeria. The results show that tour program design is a multidimensional construct encompassing destination and itinerary, service mix, price and value, customization, and communication, all of which can influence customer attraction. The empirical findings indicate a statistically significant positive effect of overall tour program design on customer attraction, with service quality, customization, and communication emerging as the most critical dimensions in the studied sample.
These findings imply that travel agencies in Djelfa and similar Algerian provinces can enhance their ability to attract and retain customers by investing in professionally designed tour programs that are clear, flexible, well‑priced, and rich in value‑adding services. Strengthening these aspects can support the broader national objective of developing domestic tourism and diversifying the economy through more competitive and client‑oriented tourism offerings.
Recommendations
In light of the results, the following recommendations are proposed for travel and tourism agencies in Djelfa:
- Give priority to improving the quality and diversity of services included in tour packages (transport, accommodation, guiding, activities) to ensure a coherent and high‑value experience.
- Develop flexible and customizable programs that allow clients to choose among activity options, dates, and service levels to better match their preferences and budgets.
- Enhance the clarity and attractiveness of communication materials (brochures, websites, social media) by providing detailed, transparent, and visually appealing descriptions of tour programs.
- Implement systematic collection and use of customer feedback to continuously refine program design and adapt to changing trends and expectations.
- Coordinate with local stakeholders (hotels, restaurants, cultural and natural sites) in Djelfa to develop distinctive packages that showcase the province’s unique resources and support local development.
Future research can extend this study by using larger, probabilistic samples, comparing different provinces, and exploring additional variables such as perceived risk, destination image, or online booking experience.
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