• Asian Journal of Business Environment
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• v.8 no.2
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• pp.15-22
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• 2018

Purpose - It is important to figure out the relationship between tourism carbon emissions and tourism economics for a healthy tourism development. Research design, data, and methodology - Data of this study are collected from 27 provinces (cities) of China. Tourist consumption stripping coefficient is used to calculate tourism carbon emissions. SBM-Undesirable model is used to measure the efficiency of tourism economics under the constraint of tourism carbon emissions. Results - The results show that: during the year of 2005-2015, there are obvious differences in totals and intensities of tourism carbon emissions among 27 provinces and cities which can be divided into three areas. There is a high possibility of underestimating the actual efficiency of tourism economics by leaving tourism carbon emissions out of account, and a high inefficiency caused by tourism carbon emissions will lead a low efficiency of tourism economics. Conclusions - The development of tourism should give consideration to both economic and environmental benefits, and reduce the inefficiency caused by tourism carbon emissions to improve efficiency of tourism economics by improving the level of technical efficiency and promoting technological progress.

• International journal of advanced smart convergence
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• v.10 no.1
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• pp.24-37
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• 2021

China's "One Belt and One Road" initiative has brought multiple opportunities to the development of tourism in Guangdong, Guangxi and Hainan provinces and the implementation of the Beibu Gulf Urban Agglomeration Development Plan hasset clear goalsforfurther accelerating the coordinated development, in-depth cooperation of the three. This study takes the Beibu Gulf Urban Agglomeration as the research object and utilized the data envelopment analysis (DEA) procedure to estimate the technical efficiency, pure technical efficiency, and scale efficiency scores for each city and Malmquist index was subsequently used to analyze dynamically, then tries to offer an adequate inclusion of sustainable factors in overall tourism development efficiency results through the detection and estimation of potential sources of efficiency. In order to complete the task, data collection was focused on Guangdong, Guangxi and Hainan provinces of China over the period from 2016 to 2018. The results in the first phase show relatively high efficiency scores, particularly in the case of the Beibu Gulf Urban Agglomeration and with room for improvement in the case of other cities of Guangdong, Guangxi and Hainan provinces. The second stage results present several aspects that should be carefully considered in order to analysis tourism efficiency of the Beibu Gulf Urban Agglomerations vertically according to the changes of the frontier.

• Journal of Information Technology Applications and Management
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• v.15 no.3
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• pp.27-41
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• 2008

This paper examines the relationship between IT investment and the improvement of efficiency from the perspective of organizational contingency by the type of organizations and their maturity in IT use in terms of their history of e-commerce use. Organizations are divided into private and public in nature, and into experienced and inexperienced in e-commerce. An analysis was performed on data from 286 organizations in tourism industry. Comparison among the four groups showed differences in competitive and operational efficiency.

• The Journal of Information Systems
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• v.29 no.3
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• pp.145-157
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• 2020

Purpose This study proposed an approach for predicting the efficiency rating of the cultural tourism festivals using DEA and machine learning techniques. The cultural tourism festivals are selected for the best festivals through peer reviews by tourism experts. However, only 10% of the festivals which are held in a year could be evaluated in the view of effectiveness without considering the efficiency of festivals. Design/methodology/approach Efficiency scores were derived from the results of DEA for the prediction of efficiency ratings. This study utilized BCC models to reflect the size effect of festivals and classified the festivals into four ratings according the efficiency scores. Multi-classification method were considered to build the prediction of four ratings for the festivals in this study. We utilized neural networks and SVMs with OAO(one-against-one), OAR(one-against-rest), C&S(crammer & singer) with Korea festival data from 2013 to 2018. Findings The number of total visitors in low efficient rating of DEA is more larger than the number of total visitors in high efficient ratings although the total expenditure of visitors is the highest in the most efficient rating when we analyzed the results of DEA for the characteristics of four ratings. SVM with OAO model showed the most superior performance in accuracy as SVM with OAR model was not trained well because of the imbalanced distribution between efficient rating and the other ratings. Our approach could predict the efficiency of festivals which were not included in the review process of culture tourism festivals without rebuilding DEA models each time. This enables us to manage the festivals efficiently with the proposed machine learning models.

• Industry Promotion Research
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• v.8 no.4
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• pp.267-276
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• 2023

Based on the tourism input-output data of five provinces and cities in China's Bohai Rim region from 2015~2021, this study analyzes the efficiency of regional tourism using DEA-BCC and DEA-Malmquist index, as well as its contribution to regional economic efficiency, and identifies factors influencing the comprehensive efficiency. The research results indicate that the comprehensive efficiency of the tourism industry in the China Bohai Sea region has reached an optimal level of 88.9%, but there is still room for improvement, with overall fluctuations. The overall productivity of the tourism industry exhibits a "U"-shaped fluctuating pattern, with growth mainly driven by technological advancements. Due to the impact of the COVID-19 pandemic, the region experienced a nearly 50% decrease in total factor productivity in 2019~2020. However, in 2021, with the implementation of various government stimulus policies, the tourism efficiency rapidly recovered to 80% of pre-pandemic levels. In terms of the impact of the tourism industry on the regional economy in the China Bohai Sea region, Hebei Province stands out as a significant contributor. Based on the aforementioned research findings, the following recommendations are proposed in three aspects: optimizing the supply structure, increasing innovation investment, and strengthening internal collaboration. These recommendations provide valuable insights for enhancing regional tourism efficiency and promoting regional synergy.

• The Journal of Industrial Distribution & Business
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• v.8 no.7
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• pp.13-20
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• 2017

Purpose - Performance appraisal has a significant influence on the development of low-carbon tourism distribution. Research design, data, and methodology - Data of this study are collected from 27 provinces (cities) of China. SBM-Malmquist model is used to measure the TFP and its dynamic changes of low-carbon tourism distribution; TOBIT model is used to discuss the factors of TFP of low-carbon tourism distribution. Results - The results show that, there are obvious differences among regional TFP of low-carbon tourism distribution, the average change tends to grow positively in general, and the western region grows fastest on average due to the improvement of technical efficiency and technical progress, while there are technical efficiency improvement but technical regresses in eastern and central regions. The economic scale, economic strength, structure of energy consumption, location quotient and government regulation have a significant positive effect on the TFP of low-carbon tourism; energy intensity, industrial structure and opening degree have a negative effect; investments in fixed assets, intensity of R&D fund and urbanization rate have no significant influence on the TFP of low-carbon tourism. Conclusions - Improving the productivity of low-carbon tourism and reducing regional differences are effective ways to develop low-carbon tourism and enhance tourism competitiveness.

• Journal of the Korean Institute of Rural Architecture
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• v.16 no.2
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• pp.45-54
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• 2014

This study aims to examine factor of tourism attraction and tourism satisfaction in order to product plan of tourism policies related to architecture and urban design focused on Marado, Jeju Island. For that, a questionnaire is conducted by tourists who visit to Marado. The results are as follows. 30s and 40s tourists evaluate that Marado is more attractive in natural environment rather than 60s. Tourists who visit more than four times to Marado evaluated low in satisfaction for landscape of Marado but tourists who reside in other area not Jeju evaluate higher in satisfaction for landscape. The difference of residence areas shows same result in tourism attraction factors. Tourists participating in tour activities show higher in satisfaction rather than no-participants but the difference between participants and no-participants is not showed in tourism attraction factors. Tourism attraction is extracted four factors; natural environment, architectural environment, economic efficiency and psychological factor. The factors of natural environment and architectural environment have the relation with satisfaction but the factors of economic efficiency and psychology do not show no relation with satisfaction.

• Journal of Korea Society of Digital Industry and Information Management
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• v.11 no.2
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• pp.67-72
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• 2015

As new Information technology such as IoT develops rapidly, a lot of changes are occurred in our lives. The Internet of Things is the network of physical objects or things embedded with electronics, software, sensors and connectivity to enable it to achieve greater value and service by exchanging data with the manufacturer, operator and/or other connected devices. This change is also applied to tourism industry. These days many people make a tour reservation using the internet. But it is required to consider the efficiency and security of tour reservation system. In this paper, we suggest a tour reservation system. First, we describe the computer reservation system, hotel reservation system and reservation system. Second, we perform the modeling of general reservation system and suggested reservation system. Third, performance evaluation is carried out with respect to efficiency and security. The results show that the suggested reservation system has a better performance than a general reservation system. At last we described the results and future works.

• Journal of Smart Tourism
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• v.1 no.2
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• pp.13-18
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• 2021

Hotels have recently started to implement enterprise information systems to measure and report sustainability indicators in a smart manner. However, a complex ownership structure in a hotel chain prevents full smart systems adoption at the individual property level. This study explores how a smart sustainability performance measurement system (SPMS) for waste management adoption correlates with customer ratings, customer reviews, operational efficiency scores, and between franchised and corporate-managed properties. We derive insights from the secondary data constructed from multiple sources for a large multinational hotel chain hotel. The findings suggest that hotels that adopt SPMS have better operational efficiency scores and more customer reviews. Within the hotels that adopted SPMS, corporate-managed hotels have a lower level of ratings than franchised hotels, but they have higher operational efficiency scores and more reviews. We discuss research implications for the concept of smart tourism and hotel management literature and managerial implications.

• Journal of Multimedia Information System
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• v.5 no.1
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• pp.21-26
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• 2018

Recently, data analysis technology through artificial intelligence is attracting major attention in various industrial fields. In addition, with the increase in personal income, nowadays, the importance of heterogeneous leisure life is becoming more prominent. However, there is a problem that the tourism industry is not out of the traditional service framework. For the ultimate development of the tourism industry, it is time to provide more scientific and systematic tourism services. In this paper, various data analysis techniques in the field of computer science are applied to the field of tourism to realize next generation tourism services. To this end, the scope of this study is limited to the aviation service, and a natural ecosystem of the aviation industry for future-oriented services of aviation tourism that can improve the efficiency of aviation service gradually is established. The proposed method effectively solves the problems of traditional aviation services through data analysis techniques with artificial intelligence techniques in computer science. We expect that it will enhance the customized satisfaction of customers through personalized service and foster loyal customers in aviation companies through the method proposed.