Investigating the Role of Geo-marketing and its Value Creation in the Urban Tourism Infrastructure Development in Mashhad

Document Type : Article extracted From phd dissertation


1 PhD Student in Business Management - Marketing Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran

2 Assistant Professor, Department of Business Management, Central Tehran Branch, Islamic Azad University, Tehran, Iran


Extended Abstract
Today, the tourism industry is considered as one of the largest and most diverse industries in the world as the main source of foreign exchange earnings, employment, social justice, cultural growth, increasing welfare and grounds for private growth and a tool for infrastructure development. In this regard, to realize the vision of the tourism industry and growth in this field, the use of GIS approach is inevitable and the capabilities and resources that exist in this field should be used to the fullest. Geo-marketing (location based) is a tool to identify and predict the needs of tourists and provide facilities to meet their needs and motivate them to visit, which will ensure the satisfaction of tourists and the realization of organizational goals (sustainable income, job creation, etc.). One of the important tourist cities is the holy city of Mashhad, which is considered as the largest religious and pilgrimage city in Iran. The city welcomes countless pilgrims and tourists every year with its many hotels and tourist accommodations, pilgrimage and tourism routes, scenic and natural attractions. Existence of busy routes and high volume of tourists and the number of attractions and accommodations has caused tourists to face many problems in choosing the appropriate route and accommodation, etc., so it is necessary to take measures to facilitate routing as well as infrastructure development. One of the effective solutions is to use new geo-marketing parameters. According to the above, this research is trying to find a suitable answer to the following question:
- What is the role and impact of geo-marketing on the development of urban tourism?
This research is applied-developmental in terms of purpose and descriptive-survey in terms of method. The statistical population of the research, in the qualitative part, includes experts and managers of the public sector of the tourism industry, the statistical population of the research, in the qualitative part, included experts and managers of the public sector of the tourism industry, which 26 people (the criterion for selecting this number is theoretical saturation) were familiar with the discussion of geo-marketing and urban tourism factors, were chosen as sample. In the quantitative part, the statistical population includes all managers of the tourism industry which 86 people were selected by available methods. Data collection tools were interviews and questionnaires. The method of data analysis in the qualitative section was based on the Grounded Theory and using coding and categorization. In order to investigate the type of data distribution, Kolmogorov-Smirnov test was used by spss24 software. Structural equation modeling (SEM) with partial least squares (PLS) approach was also exerted to test the hypotheses.
Results and discussion
Using the opinions of the interviewers, the main and sub-categories were calculated as follows: For the main category of causal conditions (geo-marketing identification, launching geo-marketing campaigns, upgrading geographic information system (spatial)), contextual conditions (appropriate tourism education from place-based systems, urban branding, structural cohesion of tourism), intervening conditions (characteristics of tourists, environmental factors, infrastructure factors), central category (standardization, promotion of urban tourism, tourists' expectations), strategy (promotion of positioning, promotion of communication channels, value creation), outcome (competitive advantage, welfare and quality of life, sustainable tourism) can be seen that 87 questionnaire indices were identified into six structures. The PLS method was also found to be positive for all variables in the study and the total average of this index is 0.578 which indicates the desired and high quality of the measurement model. The value of the fit index (GOF) is equal to 0.662 and is greater than the value of 0.4 and indicates a suitable fit of the model. And the path coefficient of all hypotheses was confirmed.
The results of the qualitative part of the research, which was conducted through a coding interview, showed that the causal conditions include geo-marketing identification, launching geo-marketing campaigns, upgrading the geographic information system (spatial) and the underlying conditions include appropriate tourism education from spatial systems. Urban branding is based on the structural cohesion of tourism and the intervening conditions include tourist characteristics, environmental factors, investment / financing. The central category includes standardization, promotion of urban tourism, and tourists' expectations. Strategies include positioning, communication channels, value creation, and outcomes include competitive advantage, welfare and quality of life, and sustainable tourism.
The results obtained from the coefficients of structural equations confirm the effect of geo-marketing identity on tourism potential, with the t-value (2.247) and the path coefficient of 0.206; the effect of geo-marketing structure on tourism potential with t-value (1.988) and path coefficient of 0.139; the effect of environmental characteristics on tourism potential with the t-value (6.197) and path coefficient of 0.527; the effect of tourism potential on value creation with  t-value (4.759) and path coefficient of 0.290; the effect of structure tourism on value creation with t-value (4.281) and path coefficient 0.197; the effect of environmental characteristics of geo-marketing on value creation of geo-marketing with t-value (8.195) and  path coefficient of 0.491; and finally the effect of value creation on tourism infrastructure development with the t-value (37.067) and the path coefficient of 0.832. Finally, the variables of geo-marketing and value creation at the rate of 0.832 affect the development of tourism infrastructure.


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