在国家经济新常态的形势下，旅游产业转型升级的需要更加迫切，应该跳出长期以来单纯对规模总量的关注，从一种全新的视角来研究协调旅游经营企业及地区之间的关系。效率评价是提高企业生产效率与管理水平的重要手段和工具。从效率角度出发，对我国旅游产业效率时空演变特征进行分析，可以有效地审视中国旅游产业发展道路，促进地区旅游产业从要素驱动、投资驱动转向创新驱动、科技驱动。本书利用2002—2013年的面板数据，以“指标构建—效率测算—时空对比—驱动机制”为研究主线，综合运用组合赋权、DEA模型、ESDA、重心、标准差椭圆、POOL面板数据模型等方法，对我国31个省份的旅游产业效率、行业效率和要素效率的时空演变特征进行深入分析，并研究旅游产业效率时空演变的驱动机制。研究结果可以为地区旅游产业判断各项资源的投入不足或投资冗余提供定量数据参考，揭示省份间旅游产业相对地位的变化，帮助各地区更好地辨识提升旅游产业效率的最佳路径，为引导企业投资的科学性提供手段和依据，避免旅游发展的盲目性和无效性。

本书研究的主要结论是：

第一，本书对国内外旅游产业效率研究进行梳理，发现研究内容虽不断加深，但有关旅游产业效率的空间研究还不足，且缺乏旅游行业效率间的比较研究，旅游产业内部效率的深层次研究有待深入。书中对旅游产业效率、行业效率和要素效率的概念进行了解析和界定，并对系统论、经济增长理论、空间经济学理论等对旅游产业效率研究的支撑作用进行阐述。

第二，本书对我国31个省份12年间旅游产业效率进行了测算，结果发现，我国旅游产业效率在时序上呈现波动性变化特征，随着旅游产业规模的发展壮大，旅游产业效率增长效应并不明显。从分解后的效率来看，规模效率对综合效率的影响略强，由于很多省份规模效率值低于纯技术效率值，说明要素的合理投入和产业结构的合理布局对提高我国旅游产业效率有很大作用。从空间演变来看，规模效率以“T”形格局占主导，东部规模集聚效益低于中西部地区；纯技术效率比规模效率的省际差异性更大，空间格局年际变化显著，东部比西部地区技术应用能力强。在两者的共同影响下综合效率空间集聚性不强，相邻省份在综合效率值上不存在互相影响、互相制约的关系，空间格局由“T”形向“V”形格局演变。

第三，从景区、酒店和旅行社三大行业效率角度看，景区行业效率最低，受整体旅游环境的影响最强，波动性较强；酒店行业效率较高，最为稳定；旅行社行业则居中。另外，在空间上，景区行业2004年前变动频繁，未表现出一定的规律性，2005—2007年空间分布上向集聚态势演变，2009—2013年西部和东南部两大核心逐渐形成；酒店行业2008年以前空间格局呈倒“几”字形格局，2008年以后东南沿海地区优势突出，中西部地区有所下降，技术改革和创新对提高行业效率的作用逐渐显现，形成东南核心区；旅行社行业以“山”字形格局为主，东南部地区效率较好而西北部地区较差，但近年来地区间差异有缩小的趋势。

第四，从物质资本、人力资本和企业规模三大要素效率的时空演变特征看，三大要素普遍存在投入过剩。景区行业三大要素效率年际变化大于酒店和旅行社行业，稳定性低；酒店行业物质资本效率最高，企业规模效率在逐年升高，但人力资本效率稳中有降；旅行社行业三大要素效率均稳中有降。从空间格局来看，旅游要素效率东部、中部、西部和东北四大区域内部的差异要远大于区域间的差异，近几年来旅游要素效率高地区集聚，形成以北京、上海、广东为代表的东部核心区和西藏、宁夏为代表的西部核心区。

最后，本书选取区位条件、人力支持、市场潜力、第三产业规模、市场化程度、信息化水平和旅游产业规模七方面，分析其对旅游产业效率及三大行业效率的影响程度。发现在微观领域，资源价值、市场需求和旅游方式的转变对旅游要素效率的时空变化产生了重要影响；在中观领域，人力支持、市场化程度、信息化和旅游产业整体发展水平对旅游产业效率的时空变化产生了重要影响；在宏观领域，区位条件、服务业发展水平和社会经济水平对旅游产业效率的时空演变产生深远影响。在这些因素的综合影响下，资源驱动、政策驱动、区位驱动、市场驱动和地缘环境驱动五大驱动力引导着旅游产业效率空间格局的演变。

本书的主要创新和特色之处在于：

首先，对旅游产业效率评价体系进行完善，构建了旅游产业效率评价体系。以往的研究，对旅游产业效率的评价都停留在单一层次，没有形成旅游产业效率评价体系。本书对旅游产业效率评价进行了体系化的深入，构建了旅游产业效率评价体系。该体系由宏观、中观和微观三个层面构成。宏观效率是指旅游产业（行业集合）的总体效率，用旅游产业效率表示；中观效率是指景区、旅行社、酒店等提供某类相同旅游产品的企业集合的效率，用旅游产业效率表示；微观效率是指具体投入到旅游产业中的物质资本、人力资本等各要素产生的效果，用旅游要素效率表示。由此，对旅游产业效率评价体系进行了划分，分层递进式阐述，将研究立体化和具体化。

其次，对旅游产业效率评价方法进行改进，采用组合赋权法和DEA模型相结合，提高测算的科学性。以往的研究，对旅游产业效率产出指标均是从总量上进行考虑和设计的，而对单位产出的高低未给予重视。本书首次尝试采用组合赋权法和DEA方法相结合的研究思路来解决问题，旅游产业效率的投入指标从产业发展规模和产业发展能力两个方面进行衡量，产出指标则从总产出能力和人均效益两个方面进行衡量，整理后得到评价指标体系，对低层次指标通过组合赋权法进行归纳合并，得到更合理的高层次综合指标后，再使用DEA模型进行效率测算，提高结果的合理性和科学性。

最后，重视各因素对旅游行业效率影响的对比研究，构建了统一评价模型，建立了旅游产业效率时空演变驱动机制分析框架。以往对旅游产业效率影响因素的分析都是基于单一层次或者单一行业，缺少对三大行业效率同时进行研究，更缺少三大行业效率的比较研究。本书构建了统一的评价模型，对旅游产业效率及旅行社、景区、酒店三大行业效率的影响因素进行对比分析，综合各影响因素在不同行业的影响强度后，从宏观、中观和微观三个视角出发，建立旅游产业效率时空演变驱动机制分析框架，使旅游产业效率驱动机制研究更加细化和深入，丰富相关研究内容。

本书是以笔者的博士毕业论文为基础修订而成的。感谢我的导师——东北师范大学地理科学学院梅林教授给予我的无限关怀和悉心指导。感谢陈才教授、刘继生教授、王士君教授、杨青山教授、修春亮教授、袁家冬教授、谷国锋教授、房艳副教授等老师在我学习过程中给予的帮助。他们深厚、渊博的学术功底都使我受益匪浅。感谢陈妍、李秋雨、黄悦、于洪燕、王建康、申庆喜、郭付友、朱振华、陈晨、程林等同学在求知道路上给予的帮助。也特别感谢鲁东大学商学院的同事们，尤其是曹艳英教授从我工作之日起就一直给予我无私的帮助，给我提供珍贵的机会。

对于书中出现的错漏和偏颇，希望读者不吝指正。书中还参考并引用了大量学者的相关研究文献，在此一并表示感谢。

Under the situation of the new normal of the national economy, the need for the transformation and upgrading of the tourism industry is more urgent, and it is necessary to jump out of the long-term focus on the total amount of scale and study and coordinate the relationship between tourism operators and regions from a new perspective. Efficiency evaluation is an important means and tool to improve the production efficiency and management level of enterprises. From the perspective of efficiency, the analysis of the temporal and spatial evolution characteristics of China's tourism industry can effectively examine the development path of China's tourism industry and promote the regional tourism industry from factor-driven and investment-driven to innovation-driven and technology-driven. This book uses the panel data from 2002 to 2013, takes "index construction-efficiency measurement-spatio-temporal comparison-driving mechanism" as the main research line, and comprehensively uses methods such as combinatorial empowerment, DEA model, ESDA, center of gravity, standard deviation ellipse, POOL panel data model to conduct in-depth analysis of the spatiotemporal evolution characteristics of tourism industry efficiency, industry efficiency and factor efficiency in 31 provinces in China, and study the driving mechanism of spatiotemporal evolution of tourism industry efficiency. The research results can provide quantitative data reference for the regional tourism industry to judge the insufficient investment of various resources or investment redundancy, reveal the changes in the relative status of the tourism industry between provinces, help each region better identify the best path to improve the efficiency of the tourism industry, provide means and basis for guiding the scientific investment of enterprises, and avoid blindness and ineffectiveness of tourism development. The main conclusions of this book are: First, this book sorts out the research on the efficiency of the tourism industry at home and abroad, and finds that although the research content is deepening, the spatial research on the efficiency of the tourism industry is still insufficient, and there is a lack of comparative research on the efficiency of the tourism industry, and the in-depth research on the internal efficiency of the tourism industry needs to be deepened. The book analyzes and defines the concepts of tourism industry efficiency, industry efficiency and factor efficiency, and expounds the supporting role of system theory, economic growth theory and spatial economics theory in the research of tourism industry efficiency. Second, this book measures the efficiency of tourism industry in 31 provinces in China over the past 12 years, and the results show that the efficiency of China's tourism industry shows fluctuations in time series, and with the development and growth of tourism industry scale, the efficiency growth effect of tourism industry is not obvious. From the perspective of efficiency after decomposition, the impact of scale efficiency on comprehensive efficiency is slightly stronger, because the scale efficiency value of many provinces is lower than the pure technical efficiency value, indicating that the reasonable input of factors and the rational layout of industrial structure have a great effect on improving the efficiency of China's tourism industry. From the perspective of spatial evolution, the scale efficiency is dominated by the "T" pattern, and the scale agglomeration efficiency in the east is lower than that in the central and western regions. The inter-provincial difference between pure technology efficiency and scale efficiency is greater, the spatial pattern changes significantly from year to year, and the eastern region has stronger technology application ability than the western region. Under the joint influence of the two, the spatial agglomeration of comprehensive efficiency is not strong, and there is no relationship between mutual influence and mutual constraint in the comprehensive efficiency value of neighboring provinces, and the spatial pattern evolves from "T" shape to "V" shaped pattern. Third, from the perspective of efficiency of the three major industries of scenic spots, hotels and travel agencies, the scenic spot industry is the least efficient, the most affected by the overall tourism environment, and the volatility is strong; The hotel industry is highly efficient and stable; The travel agency industry is in the middle. In addition, in terms of space, the scenic spot industry changed frequently before 2004 and did not show a certain regularity, and the spatial distribution evolved to the agglomeration trend from 2005 to 2007, and the two cores of the west and southeast gradually formed from 2009 to 2013. Before 2008, the spatial pattern of the hotel industry showed an inverted "several" pattern, after 2008, the advantages of the southeast coastal area were prominent, and the central and western regions declined, and the role of technological reform and innovation in improving the efficiency of the industry gradually appeared, forming the southeast core area; The travel agency industry is dominated by the "mountain" pattern, with better efficiency in the southeast and poor in the northwest, but in recent years, the differences between regions have narrowed. Fourth, from the perspective of the temporal and spatial evolution characteristics of the efficiency of the three major factors of physical capital, human capital and enterprise scale, the three major factors generally have excessive input. The inter-annual variation of the efficiency of the three major elements of the scenic spot industry is greater than that of the hotel and travel agency industry, and the stability is low; The hotel industry has the highest physical capital efficiency, and the scale efficiency of enterprises is increasing year by year, but the efficiency of human capital is steadily decreasing. The efficiency of the three major factors of the travel agency industry has decreased steadily. From the perspective of spatial pattern, the differences within the four major regions of tourism factor efficiency in the east, central, west and northeast are much greater than the differences between regions, and in recent years, areas with high tourism factor efficiency have gathered to form the eastern core area represented by Beijing, Shanghai and Guangdong and the western core area represented by Tibet and Ningxia. Finally, this book selects seven aspects: location conditions, human support, market potential, tertiary industry scale, marketization degree, informatization level and tourism industry scale, and analyzes their impact on the efficiency of the tourism industry and the efficiency of the three major industries. It is found that in the micro field, the transformation of resource value, market demand and tourism mode has an important impact on the temporal and spatial changes of tourism factor efficiency. In the meso field, manpower support, marketization, informatization and the overall development level of the tourism industry have an important impact on the temporal and spatial changes of the efficiency of the tourism industry. In the macro field, location conditions, service industry development level and socio-economic level have a profound impact on the temporal and spatial evolution of tourism industry efficiency. Under the combined influence of these factors, the five driving forces of resource-driven, policy-driven, location-driven, market-driven and geo-environment drive guide the evolution of the spatial pattern of tourism industry efficiency. The main innovations and features of this book are: first, the tourism industry efficiency evaluation system is improved, and the tourism industry efficiency evaluation system is constructed. In previous studies, the evaluation of the efficiency of the tourism industry remained at a single level, and did not form an evaluation system for the efficiency of the tourism industry. This book systematically and deeply evaluates the efficiency of the tourism industry and constructs the efficiency evaluation system of the tourism industry. The system consists of three levels: macro, meso and micro. Macro efficiency refers to the overall efficiency of the tourism industry (industry agglomeration), expressed by the efficiency of the tourism industry; Meso efficiency refers to the efficiency of the collection of enterprises such as scenic spots, travel agencies, hotels, etc. that provide certain types of the same tourism products, expressed by the efficiency of the tourism industry; Micro-efficiency refers to the effect produced by various factors such as physical capital and human capital specifically invested in the tourism industry, and is expressed by the efficiency of tourism factors. Therefore, the efficiency evaluation system of the tourism industry is divided, and the research is three-dimensional and concrete. Secondly, the efficiency evaluation method of the tourism industry is improved, and the combination of combined weighting method and DEA model is adopted to improve the scientific nature of the measurement. In previous studies, the efficiency output indicators of the tourism industry were considered and designed from the total amount, and the level of unit output was not paid attention to. This book attempts for the first time to use the combined empowerment method and DEA method to solve the problem, the input indicators of tourism industry efficiency are measured from the two aspects of industrial development scale and industrial development capacity, and the output indicators are measured from the two aspects of total output capacity and per capita benefit, and the evaluation index system is obtained after sorting, and the low-level indicators are summarized and merged through the combined empowerment method to obtain more reasonable high-level comprehensive indicators, and then the DEA model is used for efficiency measurement to improve the rationality and scientificity of the results. Finally, the comparative study of the influence of various factors on the efficiency of the tourism industry is emphasized, a unified evaluation model is constructed, and an analysis framework for the driving mechanism of the spatiotemporal evolution of the efficiency of the tourism industry is established. In the past, the analysis of the influencing factors of tourism industry efficiency was based on a single level or a single industry, and there was a lack of simultaneous research on the efficiency of the three major industries, and a comparative study of the efficiency of the three major industries. This book constructs a unified evaluation model, compares and analyzes the influencing factors of tourism industry efficiency and the efficiency of travel agencies, scenic spots and hotels, synthesizes the influence intensity of each influencing factor in different industries, and establishes an analysis framework for the spatiotemporal evolution driving mechanism of tourism industry efficiency from the three perspectives of macro, meso and micro, so as to make the research on the efficiency driving mechanism of the tourism industry more detailed and in-depth, and enrich the relevant research content. This book is based on my doctoral dissertation. I would like to thank my mentor, Professor Mei Lin of the School of Geographical Sciences of Northeast Normal University, for his infinite care and careful guidance. I would like to thank Professor Chen Cai, Professor Liu Jisheng, Professor Wang Shijun, Professor Yang Qingshan, Professor Xiu Chunliang, Professor Yuan Jiadong, Professor Gu Guofeng, Associate Professor Fang Yan and other teachers for their help in my learning process. I have benefited a lot from their deep and profound academic skills. Thank you Chen Yan, Li Qiuyu, Huang Yue, Yu Hongyan, Wang Jiankang, Shen Qingxi, Guo Fuyou, Zhu Zhenhua, Chen Chen, Cheng Lin and other students for their help on the way to knowledge. I would also like to thank my colleagues at Ludong University Business School, especially Professor Cao Yanying, for their selfless help and precious opportunities since the day of my work. For the errors and biases in the book, I hope readers will not hesitate to correct them. The book also refers to and cites a large number of scholars' relevant research literature, and I would like to thank you for this.（AI翻译）