Hybrid journal (It can contain Open Access articles) ISSN (Print) 1741-878X - ISSN (Online) 1741-8798 Published by Inderscience Publishers[439 journals]
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Authors:Salam Abdul Hady, Abduladhem A. Ali, Waleed I. Breesam, Ameer Lateef Saleh, Yasir I.A. Al-Yasir, Raed A. Abd-Alhameed Pages: 1 - 29 Abstract: Location-based marketing (LBM) is becoming an integral element of the media mix for making highly personalised offers to the targeted audience at the most opportune time and place. Yet, the literature calls for more usability studies due to the lack of user-centred research. To fill this gap, this study explores the development of <i>PushMapp</i> - a geomarketing tool for launching LBM campaigns - through a user-centred, parallel-iterative approach. Usability analysis shows that this type of application is affected by issues related to security, privacy, advertisement relevancy, and notification overload. Meanwhile, only performance expectancy, effort expectancy, and hedonic motivation appeared to be the significant factors in an LBM mobile application. Experiences from this study provided valuable insights for marketers and business owners who plan to capitalise on LBM strategies by underscoring the importance of integrating users' input, ensuring usability compliance, and conforming to factors of mobile application utilisation. Keywords: location-based marketing; LBM; geofencing; marketing; advertising; usability; mobile application development Citation: International Journal of Technology Marketing, Vol. 17, No. 1 (2023) pp. 1 - 29 PubDate: 2022-11-30T23:20:50-05:00 DOI: 10.1504/IJTMKT.2023.127322 Issue No:Vol. 17, No. 1 (2022)
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Authors:Ana Ktona, Etleva Muça, Denada Çollaku, Irena Shahini, Irena Boboli Pages: 30 - 47 Abstract: Tourism in Albania is one of the potential pillars of economic development, offering real opportunities for GDP growth and employment. New technology development and the digital transformation of society have led to tourism in the upper social and economic dimensions. Technology can make an impact by improving tourist experiences through: integration of generation mobile, integration of IoT, data evaluation, reputation and promotion. This study presents the potential for using technology and computer science applications in finding models to forecast tourist expenditure. These models can be a support in creating appropriate tourism offers. Data has been collected from tourists in the City of Gjirokastra using a face-to-face questionnaire. Various machine learning algorithms have been applied to our data to determine the best model for forecasting tourist spending. The most appropriate model found is by applying a support vector machine for regression. The model we found can be used in forecasting the expenditure of a first-time visitor. Tourism agencies can use this information to create convenient and affordable offers to increase the number of tourists visiting the area. Keywords: machine learning algorithms; forecasting spending; creating tourism offers; support vector machine for regression Citation: International Journal of Technology Marketing, Vol. 17, No. 1 (2023) pp. 30 - 47 PubDate: 2022-11-30T23:20:50-05:00 DOI: 10.1504/IJTMKT.2023.127333 Issue No:Vol. 17, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Zalfa Laili Hamzah, Muhammad Waqas, Rohayu Binti Rahman, Ezlika Ghazali Pages: 78 - 98 Abstract: The popularity of smart wearable devices has significantly increased in recent years. However, little is known about the factors that can enhance the repurchase intention of smart wearables. This study adopted a mixed-method approach in the form of netnography and semi-structured interviews to explore the benefits that lead to the repurchase intention of smart wearables. Results revealed that consumers look for technological features and agency-based factors that facilitate their technological extension and subtraction. Similarly, individual characteristics such as self-identity can also lead to technological extension and subtraction. This technological extension and subtraction, along with intrinsic hedonic benefits, can lead to perceptions of economic value. This perception of economic value can lead to consumer satisfaction and eventually to repurchase intention of smart wearables. This result validates and enhances the technology integration model by presenting the integration of factors in a consolidated framework that can explain the repurchase intentions of smart wearables. Keywords: smart wearable; repurchase intention; continuance intention; utilitarian benefits; hedonic benefits; economic benefits; technology integration model Citation: International Journal of Technology Marketing, Vol. 17, No. 1 (2023) pp. 78 - 98 PubDate: 2022-11-30T23:20:50-05:00 DOI: 10.1504/IJTMKT.2023.127329 Issue No:Vol. 17, No. 1 (2022)
Please help us test our new pre-print finding feature by giving the pre-print link a rating. A 5 star rating indicates the linked pre-print has the exact same content as the published article.
Authors:Konstantinos Vassakis, Emmanuel Petrakis, Ioannis Kopanakis, John Makridis Pages: 99 - 123 Abstract: Despite the massive volumes of data tourists generate during their visit to a destination, there is little knowledge of their spatial activity and perceptions. An innovative approach that integrates both text and photo data with location-based information is demonstrated using a case study from Crete. Integration of big data techniques, location intelligence, and social networks transforming tourist experiences into valuable assets (new knowledge extraction) for more efficient strategic decision-making. The findings demonstrate how this novel approach of location and big data analytics can provide new and valuable knowledge in contrast to traditional tourist surveys and conventional spatio-temporal data. Implications arising from this study are significant assets for tourism small and medium enterprises (SMEs), destination management organisations (DMOs), and other tourism stakeholders searching for innovative marketing strategies. Keywords: big data analytics; location-based social networks; LBSNs; knowledge; tourism; social networks; big data; management Citation: International Journal of Technology Marketing, Vol. 17, No. 1 (2023) pp. 99 - 123 PubDate: 2022-11-30T23:20:50-05:00 DOI: 10.1504/IJTMKT.2023.127350 Issue No:Vol. 17, No. 1 (2022)
Hybrid journal (It can contain Open Access articles)
[439 journals]
