To carry out the current study, a total of 509 self-administered questionnaires were distributed among the tourists to collect the data which was analysed by using SPSS and Partial Least Square (PLS). PLS-SEM was applied to find out the relationship between variables and test the strength of model.
Findings:The key findings are consistent with other studies while price mix and promotion mix are in contrast from others showing insignificant relationship in tourism development. There is evidence from the results that tourists are not concerned about the expenses which include mountaineering royalty fee, trekking royalty fee and other expenses while they tour to mountain areas. Therefore, it can be argued that price becomes less important for tourists to be considered, so, the relationship of price mix with the tourism development is insignificant. Another argument may come up regarding promotion mix that traditional advertisements have become obsolete now and majority of tourists use social media as it is also evidenced in the study that majority of tourists get information from social media sources, therefore, traditional promotion mix has no influence on attracting tourist towards the destinations. Practical Implication: In addition to the contribution to existing body of knowledge, this study helps policy makers and managers of tourism sector to formulate proper plans by considering tourism marketing strategies for the development of tourism in mountain areas of Pakistan. Originality/Values: This study contributes to find out the relationship of 4Ps-marketing mix with tourism development in the mountain areas of northern Pakistan.
To carry out the current study, a total of 509 selfadministered questionnaires were distributed among the tourists to collect the data which was analysed by using SPSS and Partial Least Square (PLS). PLS-SEM was applied to find out the relationship between variables and test the strength of the proposed model. Findings: The study concludes that two variables have significant impact on tourism development while other two identified with insignificant impact on tourism development in the Central Karakoram National Park, Gilgit-Baltistan Pakistan. Practical implications: Tourism development is linked with increasing the accommodation, facilities, and advertisement whereas the current study includes all the required components which helps in developing tourism at destination. Originality/value: The importance of infrastructure development as the basis for the tourism development whereas current research further strengthens this idea by exploring and including more components in it.
The large number of merchants that make sponsorship held by the Bank reaches thousands, data mining is used to classifying thousands of data. Naïve Bayes algorithm and C 4.5 are classification algorithms in data mining. The classification results are used as determinant where the merchant deserves to receive the sponsorship program, which potentially provides the source of funds and increase the brand awareness of the company by looking at the performance, transaction amount, total nominal, average daily transaction, average transaction nominal. Comparison results show that The C 4.5 algorithm is the best model for handling case of Merchant eligibility in the Sponsorship Program. This can be proved by looking at the level of accuracy generated on the testing and validation process of the model. Both models have the same AUC value but the C 4.5 algorithm produces a superior accuracy value with a difference of 0.45% compared to Naïve Bayes.
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