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Abstract
The success of tourism destinations in world markets is influenced by their relative competitiveness. The aim of this study was to establish determinants of enhancing the extent of tourism destination competitiveness. Primary data was collected through self-administered structure questionnaires. A convenience sampling strategy was used in this study, with a sample size of 250 respondents having been selected. The obtained information was analyzed through descriptive statistics. The results showed that improving the attractiveness of the tourist destination is one of the factors that help in improving its competitiveness. Support resources were, however, not found to have any effect on the tourists’ destination competitiveness. It is therefore critical to recognize that performance enhancement and the introduction of a proper positioning strategy in the tourism market are dependent not only on a destination’s ability to attract new visitors but also on the destination’s ability to introduce appropriate product differentiation techniques with the help of a sustainable framework for natural and cultural resources management.
Introduction
Competitiveness is a wide concept that may be seen from several perspectives, such as goods, economic sectors, or national economies, in the short or long run. Competitiveness is defined in both micro and macro terms. From a macro viewpoint, Streimikiene et al. (2021) define competitiveness as a major national issue, which suggests that the ultimate goal is to increase the community’s actual income. It is viewed as a phenomenon occurring on a corporate level from a micro viewpoint. To remain competitive, every firm must produce products and services that fulfill the modern consumer’s never-ending needs.
Previously, tourism destinations felt that having merely tourists, destination resources, inexpensive wages, and favorable exchange rates was enough to compete and succeed in the international tourism sector. This strategy resulted in the development and execution of strategies and policies geared primarily at increasing visitor flows. In most cases, the results were not as predicted, calling this technique into doubt. Empirical research on destination competitiveness continues to differ across authors and, consequently, between destinations, demonstrating that competitive criteria for destinations cannot be the same for all locations (Streimikiene et al., 2021). For example, research by Alseiari et al. (2019), on the competitiveness of Hong Kong as a South-East Asian international conference location. According to Alseiari et al. (2019), housing, as well as the related notions, including conventional facilities, were viewed as essential tourist choices. Similarly, the presence of accessibility, the consistent focus on safety, and the development of a robust infrastructural system represented crucial aspects of the tourism industry. In their examination of Seoul as an important aspect of the tourism infrastructure, Cronjé and du Plessis (2020) identified service quality, the infrastructure and vehicles within the transportation system, amenities provided, such as meeting rooms, and destination appeal as important factors to consider when selecting a location. Long-term profitability and ongoing patronage are critical in gaining a competitive edge.
China’s tourism competitiveness is based on five fundamental dimensions: destination management, tourist resources, tourism superstructure, infrastructure, and destination-supporting variables. According to Hanafiah and Zulkifly (2019), South Africa has a variety of characteristics that make it a potentially lucrative tourist attraction. Specifically, the extent of political and economic stability, massive opportunities for building marketing strategies, focus on quality, and the extent of food diversity should be mentioned. United Nations World Tourism Organizations’s strategy (UNTWO) posits that destination competitiveness is one of the primary topics linked with the development of the target venue since it makes destinations especially lucrative and sustainable in the long term (Hanafiah & Zulkifly, 2019). Additionally, the available evidence indicates that elements influencing the profitability of the target venue include investment opportunities, its brand image, options associated with innovation and branding, and the associated issues.
The worldwide market has become more competitive, offering a challenge to the tourist sector as well as other businesses. This rise has fueled fierce rivalry among destinations to enhance their market share. Over the past couple of years, Asia has gained major traction in the global economy as a source of tourism destinations, threatening Europe’s and North America’s historic supremacy, with variety and distinction playing an important role in the competition (Hanafiah & Zulkifly, 2019). Due to heavy rivalry among global tourist destinations, Africa has had a reduced proportion of worldwide tourism distribution. The research utilizes the framework of Ritchie and Crouch’s destination competitiveness model (Kovačević et al., 2018). The level of competitiveness observed in a destination can be interpreted as being inherently dependent on the robustness of core resources, the variety of attractors, as well as the related resources, and the efficacy of the management framework.
Literature Review
This chapter evaluated the literature on the following topics: theoretical framework, tourist destination concepts, the competitiveness of tourist destinations, approaches to managing and maintaining a tourism destination, the efficacy of destination attractors’ performance, the robustness of support resources, and the framework for destination management.
Research by Boivin and Tanguay (2019) details that the combination of competitiveness and attractiveness allows for enhancing the extent of the appeal of tourist destinations. Specifically, the application of the conceptual model developed by the authors helps determine the connection between the two variables. The authors go on to say that the more a place represents the thoughts and opinions of its guests, the more appealing it is seen to be and likely to be picked. Reisinger et al. (2019) agreed that the appeal of a tourist area motivates visitors to visit and spend time there. As a result, the primary value of destination attractiveness is the enticing influence it has on travelers, without which tourism could not exist. Seyfi et al. (2020) discovered that cultural factors are one of the factors that attract international conferences to European locations. Castillo-Manzano et al. (2021) all contributed to the idea that towns with venues that serve as crucial historic sites attracting the attention of tourists are more appealing to both conference attendees and visitors in general.
Bakker (2019) classified inherited, developed, and support resources as having diverse features that make a location appealing to visitors. Furthermore, Bakker (2019) divided inherited resources into two categories, namely, natural and cultural ones. He considered encouraging active development of aspects and resources, namely, the infrastructure, the efficacy of performance, the extent of service accessibility, and the level of hospitality) as the cornerstone for a successful tourist sector. According to Dos Anjos and Da Rosa (2021), natural and sociocultural roots represent the main selling point of Slovenian tourism. In his study, Sekhniashvili (2020) proves that cultural legacy, as well as the robustness of resources, are crucial factors causing an increase in destination competitiveness. According to Tien et al. (2021), tourist managers value the specified resource type more than developed resources and the efficacy of their management.
Location resources, according to Bakker (2019), are assets that are linked to the concept of a destination. These are characterized as strategic assets that define how active a place may be. They also claim to be the primary resources on which a destination’s tourism is built. Luštický and Štumpf (2021) assert the overwhelming significance of developing destination service infrastructure as an instrumental part of enhancing tourist experience. Reisinger et al., (2019) stressed the importance of individual visitor well-being and the importance of considering destination attractiveness as a significant predictor of TDC. Castillo-Manzano et al. (2021) developed a quantitative model of four TDC determinants: tourist resource endowment, as well as the characteristics such as tourism reception capacity, the level of its industrial strength, and the extent of support provided within the respective services. It is also critical to recognize that the beauty of a place is the key motivator for establishing a successful tourist sector.
Research Aims and Objectives
Main Aim and Objective
This study seeks to locate core determinants of improving tourism destination competitiveness.
Specific Objectives
- To investigate the connection between tourism destination attractors and destination competitiveness rates.
- To determine the effects that resources have on tourism-related entrepreneurship.
- To study the impact of destination management and the associated strategies for managing destination on the extent of competitiveness of the tourism destination.
- To investigate the effects of safety and security on the possible correlation and causation between tourism destination competitiveness and the essential determinants thereof.
Research Hypotheses
H01: Attractiveness of a destination does not chive a cause-and-effect connection to tourism destination competitiveness.
H02: Support resources in a destination do not create a cause-and-effect connection to tourism destination competitiveness.
Methodology
Research Design and Data Collection procedures
This section considers the most effective research methodology, design, and data collection techniques for this study.
Research Design
An explanatory research design was used in the study. According to Sovacool et al. (2018), the approach is suitable for obtaining data on people’s views, attitudes, opinions, and sentiments about a variety of social concerns. However, Abutabenjeh and Jaradat (2018) define its goal as describing the current condition of circumstances. It was also great for gaining a better grasp of the key aspects of improving tourist destination competitiveness.
Target Population
The study targeted population was mainly people on social media. Questionnaires were sent to targeted populations via specific social media handles. Respondents were given a period of two days to fill up the forms and sent them back. The target population included primarily freelance participants and hence was not quantifiable.
Sample Size
The sample size consisted of 250 respondents who were tourists visiting the destinations under study.
Sampling Procedure
Convenience sampling creates a sample by locating persons who are suitable or available. A sample size of 250 visitors visiting the destinations was chosen using convenience sampling. This approach was great since it made it simple to recruit respondents and collect data in a short amount of time.
Research Instrument
Research instruments refer to the methods used in collecting data and they can either be qualitative or quantitative. Unlike qualitative data gathering techniques, where data is gathered by interviewing and observing, quantitative data gathering involves measuring and counting to get data. Furthermore, in quantitative, data is analyzed by use of statistical analysis tools, while in qualitative, data is analyzed by grouping.
Data was gathered via questionnaires. A questionnaire is a set of questions that is written and delivered in order to elicit replies (Abutabenjeh and Jaradat, 2018). Closed-ended questionnaires were also incorporated to collect the data relevant to the study. Due to the opportunity to maintain the reliability of the obtained information high, the specified framework was exceptionally useful. The selected research instrument simply had one component that included questions about study variables. Short sentences were offered on a Likert scale containing five key points, allowing respondents to express their opinions, ranging from strong agreement to strong disagreement.
Data Analysis
Eviews (Web), a statistical tool was employed for the analysis. The independent variable, namely, the strategic determinants considered for this research, and the dependent variable, specifically, the destination competitiveness of specific tourist locations, were analyzed using inferential analysis. With the help of a multiple regression analysis, a conceptual model was developed to examine the variables under analysis and the correlation between them. Due to the number of variables, the specified conceptual model was regarded as the most suitable one.
Hypothesis Testing
The study utilized the Z-test as the means of examining the possible correlation between the extent of destination competitiveness and the relevant factors. Specifically, the principles of Z-statistics were applied.
Discussion
Overview
This chapter demonstrates the key findings of the study. The demographic variables studied as part of the descriptive statistics were respondents’ age, as well as their visits frequency. The findings were structured in accordance with the goals. The study’s goal was to identify the primary variables for boosting tourist destination competitiveness. As a result, strategic determinants were the independent variable, whereas destination competitiveness was the dependent variable.
Response Rate
Only 250 (83%) of the 300 copies of the study questionnaires supplied were returned. Sovacool et al. (2018) details that the response rate was sufficient since it approached 60%.
Correlation Results
The study tried to determine if there is a link between the factors under consideration. Destination attractors, as well as resources for supporting the business and destination management, were the independent factors. Destination competitiveness represented the main moderating variable, whereas the dependent variable was the extent of tourists’ safety and the level of their security. According to the core findings, safety and security are positively correlated with both of the dependent variables, namely, attractors and resources. The findings agree with Hanafiah and Zulkifly (2019) assertion tourists’ choices regarding the attractiveness of a certain venue are defined by factors such as safety. Streimikiene et al. (2021) identified transportation safety records, corruption of police as the related authorities, including the administration, sanitation quality, illness outbreak prevalence, quality/reliability of medical services and medicines as significant qualifying variables of the extent of destination competitiveness.
Resources and management strategies are likewise positively and strongly associated, indicating their equally robust contribution to a destination’s success. This supports Hanafiah and Zulkifly’s (2019) conclusions that it is crucial for a destination to demonstrate an acceptable level of progress in order to compete with similar alternative locations. The findings agreed with Sekhniashvili (2020) who discovered that the cornerstone for developing a lucrative destination is closely connected to the issues associated with the infrastructure, which offers access to critical resources. Luštický and Štumpf (2021), on the other hand, argued that competitive forces varied in determinacies and relevance and are country-dependent.
Destination management was also shown to be positively and substantially connected with core attractors. This demonstrates that appropriate management of attractors contributes to a destination’s successful growth and development. Luštický and Štumpf (2021) found similar results, stating that the management process should incorporate the actions that enhance the appeal of core resources. Tien et al. (2021) agreed that in order to gain a competitive edge, management should be able to maintain the multidimensional elements of the tourism framework in balance. Positive correlation was also located between support resources and attractors, which aligned with the findings by Boivin and Tanguay (2019). Bakker (2019), who offered a classification of core resources needed to increase the appeal of a tourist destination, supports the specified claim.
Hypothesis Testing
To test the hypothesis, an analytical comparison of the independent and dependent factors involving the regression analysis was performed. The generalized Linear Model was applied to both models. The Z-statistic was used to evaluate if the null hypothesis should be rejected, and the likelihood ratio test, also known as the LR test, was utilized to evaluate the quality of fit for the specified frameworks. The two models’ LR statistics were significant (8.066; p-value=0.0450.05 and 20.546; p-value=0.005 0.05), indicating a regression link observed in the relationships between the variables.
The findings indicate that there is a clear correlation between the variables under analysis. Specifically, the Generalized Linear Model shows that the coefficient, standard error, z-statistics, and probability for the destination attractions are -0.812, 0.318, 2.550, and 0.011, respectively. For destination management, these are -0.523, 0.342, -1.530, and 0.126; whereas for support resources, these estimate -0.443, 0.259, -1.711, and 0.087 correspondingly. Finally, for the constant, the specified variables are 4.589, 1.038, 4.423, and 0.000. In turn, Regression Model 2 demonstrates the following rates for destination management: -4.133, 1.620, -2.552, 0.011; the support resources: 2.276, 1.421, 1.602, 0.109l; safety and security: 2.497, 1.375, 1.816, 0.069; safety and security in regard to destination management: -1.155, 0.365, -3.165, 0.002; safety and security in regard to support services: -0.628, 0.328, -1.910, 0.056; and safety and security as it pertains to destination attractions: 1.231, 0.385, 3.195, 0.001.
The Effect of Attractors on Competitiveness of a Tourist Venue
The idea that there was no positive correlation between destination attractors as the essential component of the tourism business and the level of destination competitiveness was rejected since the data proved that attractors for specific destinations had a substantial positive influence on the competitiveness level of the venue. The observed trend means that the beauty of a destination is the key motivator for a visitor to choose a certain trip. The data support Vengesayi’s (2017) claim that beauty increases the popularity of a tourist site. Bakker (2019) concurs that destination attractors are significant in influencing tourist destination competitiveness. To gain a competitive advantage, a location must guarantee that its total appeal as far as its landscapes, culture, and overall experience are concerned is greater than that of other alternative locations.
Support Resources: Impact on the Extent of Destination Competitiveness
The null hypothesis for the specified aspect of the analysis was not rejected. Consequently, support resources have little impact on a destination’s competitiveness in the Western tourism circuit. Luštický and Štumpf (2021), on the other hand, believe that supporting variables and resources, including infrastructure, accessibility, and opportunities for entrepreneurship, create the essential basis for developing a successful tourist destination. Reisinger et al. (2019) also suggested that a destination must have a robust framework of offerings in regard to the range of destinations, as well as the quality and diversity of services.
Conclusion
The hypothesis regarding the extent of attractiveness for a specific destination, as well as its competitive advantage, tried to determine whether or not there was a link between the variables. The study has returned results that showed that destination attractiveness has a substantial influence on destination competitiveness (=0.812; p=0.0110.05). The second hypothesis tried to determine whether or not there was a link between resources and the competitive rates of a destination. As the data (=-0.443; p=0.0870.05) illustrates, the level of impact that support resources have on the dependent variable can be regarded as insignificant enough to be dismissed.
According to the research, the attractiveness of a tourist destination influences and hence enhances its competitiveness. As a result, it is critical to recognize that a sufficiently positive rise in the opportunities for promoting the services in the tourism market are dependent not only on the extent to which a specific venue attracts visitors but also on the extent to which the provided services and products are differentiated. In turn, the specified movement can be achieved by allocating the respective resources, including natural and cultural ones. The destination’s marketing strategy should be extended to include diversity. The poor attendance of visitors within the range of the service attractions should cause the relevant stakeholders involved to increase their promotional efforts.
Reference List
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Abutabenjeh, S. and Jaradat, R. (2018) ‘Clarification of research design, research methods, and research methodology: A guide for public administration researchers and practitioners’, Teaching Public Administration, 36(3), pp.237-258.
Boivin, M. and Tanguay, G.A. (2019) ‘Analysis of the determinants of urban tourism attractiveness: The case of Québec City and Bordeaux’, Journal of destination marketing & management, 11, pp.67-79.
Bakker, M. (2019) ‘A conceptual framework for identifying the binding constraints to tourism-driven inclusive growth’, Tourism Planning & Development, 16(5), pp.575-590.
Cronjé, D.F. and du Plessis, E. (2020) ‘A review on tourism destination competitiveness’, Journal of Hospitality and Tourism Management, 45, pp.256-265.
Castillo-Manzano, J. et al. (2021) ‘Assessing the tourism attractiveness of World Heritage Sites: The case of Spain’, Journal of Cultural Heritage, 48, pp.305-311.
Dos Anjos, F.A. and Da Rosa, S. (2021) ‘Measurement of competitiveness of nature-based tourist destinations: Application to national parks in brazil’, Journal of Environmental Management & Tourism, 12(5), pp.1204-1219.
Hanafiah, M.H., and Zulkifly, M.I. (2019) ‘Tourism destination competitiveness and tourism performance: A secondary data approach’, Competitiveness Review: An International Business Journal.
Kovačević, N. et al. (2018) ‘Applying destination competitiveness model to strategic tourism development of small destinations: The case of South Banat district’, Journal of destination marketing & management, 8, pp.114-124.
Luštický, M. and Štumpf, P. (2021) ‘Leverage points of tourism destination competitiveness dynamics’, Tourism Management Perspectives, 38, p.100792.
Reisinger, Y. et al. (2019) ‘Destination competitiveness from a tourist perspective: A case of the United Arab Emirates’, International Journal of Tourism, 21(2), 259-279.
Seyfi, S. et al. (2020) ‘Exploring memorable cultural tourism experiences’, Journal of Heritage Tourism, 15(3), pp. 341-357.
Streimikiene, D. et al. (2021) ‘Sustainable tourism development and competitiveness: The systematic literature review’, Sustainable Development, 29(1), pp. 259-271.
Sekhniashvili, G. (2020) ‘Wine tourism destination competitiveness: The case of Georgia’, Ecocycles, 6(1), pp.39-51.
Sovacool, B. et al. (2018) ‘Promoting novelty, rigor, and style in energy social science: Towards codes of practice for appropriate methods and research design’, Energy Research & Social Science, 45, pp.12-42.
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