五台山景区酒店碳排放效率的典范对应分析

doi:10.11821/dlyj201803010

地理研究 ›› 2018, Vol. 37 ›› Issue (3): 577-592.doi: 10.11821/dlyj201803010

五台山景区酒店碳排放效率的典范对应分析

程占红^1,², 徐娇¹

1. 山西财经大学旅游管理学院,太原 030031
2. 山西财经大学资源型经济研究中心,太原 030006

收稿日期:2017-08-09 修回日期:2017-11-20 出版日期:2018-03-15 发布日期:2018-03-15
作者简介:
作者简介：程占红（1972- ）,男,山西新绛人,博士,教授,主要从事低碳旅游研究。E-mail:chengzhanhong@163.com
基金资助:
教育部人文社会科学研究规划基金项目（14YJA630005）;山西省高等学校哲学社会科学研究项目（2017332）;国家自然科学基金项目（41571141）;山西省高等学校教学改革研究项目（J2014055）;山西省软科学研究项目（2016041012-1）;山西省研究生教育改革研究项目（2017JG65）

Canonical correspondence analysis of hotels' carbon emission efficiency in Wutai Mountain scenic area

Zhanhong CHENG^1,², Jiao XU¹

1. School of Tourism Management, Shanxi University of Finance & Economics, Taiyuan 030031, China;
2. Center of Resource-Based Economy Research, Shanxi University of Finance & Economics, Taiyuan 030006, China;

Received:2017-08-09 Revised:2017-11-20 Online:2018-03-15 Published:2018-03-15
About author:
Author: Shi Zhenqin (1988-), PhD, specialized in regional development and land space management in mountain areas. E-mail: kevinszq@163.com

^*Corresponding author: Deng Wei (1957-), Professor, specialized in mountain environment and regional development.

E-mail: dengwei@imde.ac.cn

摘要/Abstract

摘要：

酒店碳排放效率的测算可以为其实施节能减排提供参考依据。首先采用数据包络分析方法计算五台山景区28家酒店的碳排放效率,其次,采用典范对应分析方法分析酒店碳排放效率与关键性指标之间的关系。结果表明：① 9家酒店技术效率完全有效,15家酒店纯技术效率有效,9家酒店规模效率有效。② 基于碳排放效率的差异,所有酒店可以分为碳排放效率完全型、碳排放效率较高型、纯技术效率最低型和规模效率最低型4类。③ 在典范对应分析图中,从第四象限到第一象限、第二象限,酒店类型依次由第Ⅰ组逐步向第Ⅱ组、第Ⅳ组、第Ⅲ组过渡,在此递变期间,酒店的碳排放效率不断降低。④ 利用典范对应分析的结果表达了关键性指标对酒店碳排放效率的制约作用,并识别了限制因素,为提升酒店碳排放效率指明了路径。

关键词: 五台山景区, 碳排放效率, 典范对应分析

Abstract:

It can provide a reference for the implementation of energy-saving and emission-reducing to measure hotels' carbon emission efficiency. Firstly, the buildings area, rooms and staff number of 28 hotels were taken as the input indicators, and water consumption, power consumption and coal consumption were taken as the output indicators in Wutai Mountain scenic area. Hotels' carbon emission efficiency was calculated by Data Envelopment Analysis. Secondly, the relationship between carbon emission efficiency and key indices was studied by Canonical Correspondence Analysis (CCA) and Two-Way Indicator Species Analysis (TWINSPAN). The results showed that: (1) 9 hotels' technical efficiency was fully effective, 15 hotels' pure technical efficiency was effective, and 9 hotels' scale efficiency was effective. (2) TWINSPAN divided all hotels into four groups. Group I had 9 hotels, accounting for 32% of the total number of hotels in this study, whose three efficiency values of carbon emissions were all 1, so they belonged to the full efficiency group. Group II consisted of three hotels, accounting for 11%. They had higher carbon emission efficiency, but there was still some room for improvement. Group III accounted for 32% of the hotels (9 hotels). They had the lowest pure technical efficiency and should focus on the usage and transformation of low-carbon technology. Group IV had seven hotels, accounting for 25% of the hotels. They should take full advantage of utilization efficiency of the existing resources because of their lowest scale efficiency. (3) By CCA, we could see the relationship between different indicators and the ordination axis, and all of the indicators including hotels' construction area, the number of rooms, the number of employees, coal consumption and water consumption were showing an increasing trend from left to right on the first axis, and the number of practitioners and the number of rooms were showing an increasing trend from bottom to top on the second axis. At the same time, from the fourth quadrant to the first and the second quadrants in the CCA figure, the types of hotels' carbon emission efficiency were transited gradually from group I to group II, group IV and group III. In the process of change, hotels' carbon emission efficiency was decreasing with obvious "arch effect". (4) The restriction of key indices to hotels' carbon emission efficiency was showed by CCA, and the limiting factors were distinguished, which pointed out the path to enhance hotels' carbon emission efficiency.

Key words: Wutai mountain scenic area, hotels, carbon emission efficiency

程占红, 徐娇. 五台山景区酒店碳排放效率的典范对应分析[J]. 地理研究, 2018, 37(3): 577-592.

Zhanhong CHENG, Jiao XU. Canonical correspondence analysis of hotels' carbon emission efficiency in Wutai Mountain scenic area[J]. GEOGRAPHICAL RESEARCH, 2018, 37(3): 577-592.

图/表 12

表1

表2

表3

图1

表4

图2

表5

图3

图4

图5

表6

表7

参考文献 31

[31]	[Wu Leying, Wang Zheng, Xu Chengjin, Yan Yanmei.A CGE model for provincial carbon economy: A case study of Henan province. Geographical Research, 2016, 35(5): 941-952.] doi: 10.11821/dlyj201605011
[32]	张金屯. 数量生态学. 北京: 科学出版社, 2004.
	[Zhang Jintun. Quantitative Ecology.Beijing: Science Press, 2004.]
[33]	Beatriz Rosselló-Batle, Andreu Moià, et al.Energy use, CO2 emissions and waste throughout the life cycle of a sample of hotels in the Balearic Islands. Energy and Buildings, 2010, 42(4): 547-558. doi: 10.1016/j.enbuild.2009.10.024
[34]	李沐纯, 魏卫. 基于低碳技术创新的我国酒店业转型升级发展战略与运营机制研究. 生态经济, 2012, 28(4): 154-157, 161. doi: 10.3969/j.issn.1671-4407.2012.04.034
	[Li Muchun, Wei Wei.Research on Chinese hospitality industry transition and upgrading strategy based on low-carbon technology innovation. Ecological Economy, 2012, 28(4): 154-157, 161.] doi: 10.3969/j.issn.1671-4407.2012.04.034
[35]	程锦红. 五台山景区游客对低碳旅游的认知研究. 太原: 山西财经大学硕士学位论文, 2016.
	[Cheng Jinhong.Study on the cognition of tourists toward low-carbon tourism on Wutai Mountain Scenic Area. Taiyuan: Master Dissertation of Shanxi University of Finance and Economics, 2016.]
[1]	马丽. 基于LMDI的中国工业污染排放变化影响因素分析. 地理研究, 2016, 35(10): 1857-1868.
	[Ma Li.Decomposition of China's industrial environment pollution change based on LMDI. Geographical Research, 2016, 35(10): 1857-1868.]
[36]	马丽, 张博, 杨宇. 东北地区产业发展与工业SO2排放的时空耦合效应. 地理科学, 2016, 36(9): 1310-1319. doi: 10.13249/j.cnki.sgs.2016.09.004
	[Ma Li, Zhang Bo, Yang Yu.The spatio-temporal coupling relationship between industrial development with SO2 emission of northeast China. Scientia Geographica Sinica, 2016, 36(9): 1310-1319.] doi: 10.13249/j.cnki.sgs.2016.09.004
[2]	马丽, 刘立涛. 基于发达国家比较的中国能源消费峰值预测. 地理科学, 2016, 36(7): 980-988. doi: 10.1787/energy_bal_oecd-2015-en.
	[Ma Li, Liu Litao.Peak forecast of Chinese energy consumption based on developed countries's trends. Scientia Geographica Sinica, 2016, 36(7): 980-988.] doi: 10.1787/energy_bal_oecd-2015-en.
[37]	黄蕊, 王铮, 丁冠群, 等. 基于STIRPAT模型的江苏省能源消费碳排放影响因素分析及趋势预测. 地理研究, 2016, 35(4): 781-789. doi: 10.11821/dlyj201604015
	[ Huang Rui, Wang Zheng, Ding Guanqun, et al.Trend prediction and analysis of influencing factors of carbon emissions from energy consumption in Jiangsu province based on STIRPAT model. Geographical Research, 2016, 35(4): 781-789.] doi: 10.11821/dlyj201604015
[3]	Lofgren A, Muller A. The effect of energy efficiency on Swedish carbon dioxide emissions 1993-2004. Working paper of University of Gothenburg, No. 311, 2008.
[4]	Zofio J L, Prieto A M.Environmental efficiency and regulatory standards: the case of CO2 emissions from OECD industries. Resource and Energy Economics, 2001, 23(1): 63-83. doi: 10.1016/S0928-7655(00)00030-0
[5]	Zhou P, Ang B W, Poh K L.Slacks-based efficiency measures for modeling environmental performance. Ecological Economics, 2006, 60(1): 73-78. doi: 10.1016/j.ecolecon.2005.12.001
[6]	Ramanathan R.An analysis of energy consumption and carbon dioxide emissions in countries of the Middle East and North Africa. Energy, 2005, 30(15): 2831-2842. doi: 10.1016/j.energy.2005.01.010
[7]	Ramanathan R.A multi-factor efficiency perspective to the relationships among world GDP: Energy consumption and carbon dioxide emissions. Technological Forecasting & Social Change, 2006, 73(5): 483-494. doi: 10.1016/j.techfore.2005.06.012
[8]	Wang C.Decomposing energy productivity change: A distance function approach. Energy, 2007, 32(8): 1326-1333. doi: 10.1016/j.energy.2006.10.001
[9]	Chen Tser-yiet, Pei-ying, Lai A. Comparative study of energy utilization efficiency between Taiwan and China. Energy Policy, 2010, 38(5): 2386-2394. doi: 10.1016/j.enpol.2009.12.030
[10]	Stern D I, Jotzo F.How ambitious are China and India's emissions intensity targets. Energy Policy, 2010, 38(11): 6776-6783. doi: 10.1016/j.enpol.2010.06.049
[11]	马大来, 陈仲常, 王玲. 中国省际碳排放效率的空间计量. 中国人口资源与环境, 2015, 25(1): 67-77.
	[Ma Dalai, Chen Zhongchang, Wang Ling.Spatial econometrics research on inter-provincial carbon emissions efficiency in China. China Population Resources and Environment, 2015, 25(1): 67-77.]
[12]	刘亦文, 胡宗义. 中国碳排放效率区域差异性研究: 基于三阶段DEA模型和超效率DEA模型的分析. 山西财经大学学报, 2015, 37(2): 23-34. doi: 10.13781/j.cnki.1007-9556.2015.02.003
	[Liu Yiwen, Hu Zongyi.Research on regional difference about carbon emission efficiency in China: Based on three stage DEA model and super efficiency DEA model. Journal of Shanxi University of Finance and Economics, 2015, 37(2): 23-34.] doi: 10.13781/j.cnki.1007-9556.2015.02.003
[13]	王坤, 黄震方, 曹芳东. 中国旅游业碳排放效率的空间格局及其影响因素. 生态学报, 2015, 35(21): 7150-7160. doi: 10.5846/stxb201402260334
	[Wang Kun, Huang Zhenfang, Cao Fengdong.Spatial pattern and influencing factors of carbon dioxide emissions efficiency of tourism in China. Acta Ecologica Sinica, 2015, 35(21): 7150-7160.] doi: 10.5846/stxb201402260334
[14]	钟章奇, 吴静, 许爱文, 等. 中国各省区旅游业碳排放量初步估算及区域差异. 世界地理研究, 2016, 25(1): 83-94.
	[Zhong Zhangqi, Wu Jing, Xu Aiwen, et al.Preliminary estimation of CO2 emission of tourism industry and its regional difference in China. World Regional Studies, 2016, 25(1): 83-94.]
[15]	王铮, 刘晓, 黄蕊, 等. 平稳增长条件下中国各省市自治区的排放需求估算. 中国科学院院刊, 2013, 28(1): 85-93.
	[Wang Zheng, Liu Xiao, Huang Rui, etal. Estimation of carbon emission requirements under balance growth in the Chinese provinces. China Academic Journal, 2013, 28(1): 85-93.]
[16]	Reinhard S, Lovell C A K, Thijssen G J. Environmental efficiency with multiple environmentally detrimental variables: estimated with SFA and DEA. European Journal of Operational Research, 2000, 121(2): 287-303. doi: 10.1016/S0377-2217(99)00218-0
[17]	Chung H S, Rhee H C.A residual-free decomposition of the sources of carbon dioxide emissions: A case of the Korean industries. Energy, 2001, 26(1): 15-30. doi: 10.1016/S0360-5442(00)00045-1
[18]	张秀秀. 基于DEA的航空公司碳排放效率评价研究. 大连: 大连海事大学硕士学位论文, 2014.
	[Zhang Xiuxiu.Evaluation of the efficiency of airline carbon emissions based on DEA. Dalian: The Master Dissertation of Dalian Maritime University, 2014.]
[19]	黄崎, 康建成, 黄晨皓. 酒店业碳排放评估与节能减排潜力研究. 资源科学, 2014, 36(5): 1013-1020.
	[Huang Qi, Kang Jiancheng, Huang Chenhao.An assessment of carbon emissions and the potentiality of energy-saving in hospitality. Resources Science, 2014, 36(5): 1013-1020.]
[20]	刘益. 中国酒店业能源消耗水平与低碳化经营路径分析. 旅游学刊, 2012, 27(1): 83-90. doi: 10.3969/j.issn.1002-5006.2012.01.017
	[Liu Yi.Analysis of energy consumption level and approaches to low-carbon management in lodging industry of China. Tourism Tribune, 2012, 27(1): 83-90.] doi: 10.3969/j.issn.1002-5006.2012.01.017
[21]	Wu X, Priyadarsini R, Eang L S.Benchmarking energy use and greenhouse gas emissions in Singapore's hotel industry. Energy Policy, 2010, 38(8): 4520-4527. doi: 10.1016/j.enpol.2010.04.006
[22]	沈杨, 胡元超, 施亚岚, 等. 城市酒店业的碳排放核算及低碳指标分析. 环境科学学报, 2017, 37(3): 1193-1200.
	[Shen Yang, Hu Yuanchao, Shi Yalan, et al.Carbon emission accounting and low carbon indicator analysis for urban hotel industry. Acta Scientiae Circumstantiae, 2017, 37(3): 1193-1200.]
[23]	Tsai K T, Lin T P, Hwang R L, et al.Carbon dioxide emissions generated by energy consumption of hotels and homestay facilities in Taiwan. Tourism Management, 2014, 42: 13-21. doi: 10.1016/j.tourman.2013.08.014
[24]	黄英. 酒店碳足迹测算研究综述. 生态经济, 2015, 31(10): 95-102. doi: 10.3969/j.issn.1001-2397.2015.04.15
	[Huang Ying.An overview of carbon footprint evaluation of hotel industry. Ecological Economy, 2015, 31(10): 95-102.] doi: 10.3969/j.issn.1001-2397.2015.04.15
[25]	Filimonau V, Dickinson J, Robbins D, et al.Reviewing the carbon footprint analysis of hotels: Life Cycle Energy Analysis (LCEA) as a holistic method for carbon impact appraisal of tourist accommodation. Journal of Cleaner Production, 2011, 19: 1917-1930. doi: 10.1016/j.jclepro.2011.07.002
[26]	Karagiorgas M, Tsoutsos T, Moia-Pol A.A simulation of the energy consumption monitoring in Mediterranean hotels: Application in Greece. Energy and buildings, 2007, 39(4): 416-426. doi: 10.1016/j.enbuild.2006.07.008
[27]	Bohdanowicz P, Martinac I.Determinants and benchmarking of resource consumption in hotels: Case study of Hilton International and Scandic in Europe. Energy and Buildings, 2007, 39(1): 82-95. doi: 10.1016/j.enbuild.2006.05.005
[28]	杨璐, 章锦河, 钟士恩, 等. 山岳型景区酒店与城市中心酒店碳足迹比较分析. 北京第二外国语学院学报, 2015, (9): 52-61.
	[Yang Lu, Zhang Jinhe, Zhong Shien, et al.Comparative analysis of carbon footprint between hotels in mountain resorts and city. Journal of Beijing International Studies University, 2015, (9): 52-61.]
[29]	杨璐, 章锦河, 钟士恩, 等. 山岳型景区酒店碳足迹效率及影响因素分析. 生态经济, 2015, 31(3): 126-130. doi: 10.3969/j.issn.1671-4407.2015.03.027
	[Yang Lu, Zhang Jinhe, Zhong Shien, et al.Carbon footprint efficiency and its influencing factors on the hotels in the mountain resort. Ecological Economy, 2015, 31(3): 126-130.] doi: 10.3969/j.issn.1671-4407.2015.03.027
[30]	朱永彬, 王铮. 排放强度目标下中国最优研发及经济增长路径. 地理研究, 2014, 33(8): 1406-1416. doi: 10.11821/dlyj201408002
	[Zhu Yongbin, Wang Zheng.Optimal R & D investment path for China to fulfill its emission intensity target and the corresponding economic growth path. Geographical Research, 2014, 33(8): 1406-1416.] doi: 10.11821/dlyj201408002
[31]	吴乐英, 王铮, 徐程瑾, 等. 省区碳经济分析的CGE模型及其应用: 以河南省为例. 地理研究, 2016, 35(5): 941-952. doi: 10.11821/dlyj201605011

指标	最大值	最小值	平均值	标准差
注册资本（万元）	2500	100	1215	601.82
建筑面积（m²）	42000	900	11083.79	11922.99
客房数量（间）	500	32	111.43	92.05
从业人员数（人）	260	15	71.50	69.11
耗煤量（kg/a）	600000	50	213928.57	184126.11
耗水量（t/a）	45000	1400	14732.93	13304.72
耗电量（kWh/a）	1905003	12228	333878.07	393660.37

酒店	纯技术效率			规模效率			技术效率
酒店	纯技术效率值		是否有效		规模效率值	是否有效	技术效率值	是否有效
五峰宾馆	1.00	有效		0.40	无效		0.40	无效
栖贤阁	1.00	有效		0.86	无效		0.86	无效
友谊宾馆	0.83	无效		0.66	无效		0.54	无效
花卉山庄	1.00	有效		1.00	有效		1.00	有效
银海山庄	1.00	有效		1.00	有效		1.00	有效
锦绣山庄	1.00	有效		0.94	无效		0.94	无效
金都山庄	1.00	有效		0.54	无效		0.54	无效
云龙宾馆	0.96	无效		0.97	无效		0.92	无效
云峰宾馆	0.92	无效		0.74	无效		0.68	无效
圆缘宾馆	1.00	有效		1.00	有效		1.00	有效
龙华宾馆	0.45	无效		0.97	无效		0.44	无效
税苑山庄	0.35	无效		0.99	无效		0.35	无效
银馨宾馆	0.38	无效		0.99	无效		0.37	无效
武警接待中心	1.00	有效		1.00	有效		1.00	有效
灵峰山庄	1.00	有效		1.00	有效		1.00	有效
胜家酒店	1.00	有效		1.00	有效		1.00	有效
凉城山庄	1.00	有效		1.00	有效		1.00	有效
鑫海宾馆	0.37	无效		0.78	无效		0.29	无效
仰佛山庄	1.00	有效		1.00	有效		1.00	有效
金界山庄	0.62	无效		0.99	无效		0.61	无效
龙泉山庄	0.49	无效		0.99	无效		0.49	无效
佛山宾馆	0.71	无效		0.65	无效		0.46	无效
运政宾馆	1.00	有效		0.42	无效		0.42	无效
石油宾馆	1.00	有效		0.77	无效		0.77	无效
银苑山庄	1.00	有效		1.00	有效		1.00	有效
晋卫宾馆	0.95	无效		0.52	无效		0.49	无效
鑫运泽宾馆	0.47	无效		0.99	无效		0.47	无效
民政宾馆	0.76	无效		0.76	无效		0.58	无效

效率类型	最大值	最小值	平均值	标准差	有效酒店数	有效酒店比例（%）
技术效率	1.00	0.29	0.70	0.26	9	32
纯技术效率	1.00	0.35	0.83	0.24	15	54
规模效率	1.00	0.40	0.85	0.19	9	32

	技术效率值	纯技术效率值	规模效率值
第Ⅰ组	1.00	1.00	1.00
第Ⅱ组	0.91	0.99	0.92
第Ⅲ组	0.45	0.51	0.90
第Ⅳ组	0.55	0.96	0.58

		耗煤量	耗电量	耗水量	注册资本	建筑面积	客房数	从业者人数
典范系数	CCA第一轴	0.76	0.48	0.73	0.38	0.66	0.71	0.65
典范系数	CCA第二轴	-0.04	-0.11	-0.15	-0.28	0.27	0.39	0.34
相关系数	CCA第一轴	0.42	0.26	0.41	0.21	0.36	0.39	0.35
相关系数	CCA第二轴	-0.03	-0.09	-0.12	-0.22	0.21	0.30	0.26

五台山景区酒店碳排放效率的典范对应分析

Canonical correspondence analysis of hotels' carbon emission efficiency in Wutai Mountain scenic area

RichHTML

PDF (PC)

赞

可视化

被引次数

摘要/Abstract

引用本文

使用本文

图/表 12

参考文献 31

相关文章 2

Metrics

本文评价

推荐阅读 0

		非常不同意	不同意	无所谓	同意	非常同意
不同星级酒店的碳排放是不相同的	第Ⅰ组	0	1.75	8.77	56.14	33.33
	第Ⅱ组	4.41	11.76	30.88	41.17	11.76
	第Ⅲ组	0	7.69	33.85	47.69	10.77
	第Ⅳ组	0	0	25.89	53.57	20.54
坚持低碳服务有利于酒店可持续经营	第Ⅰ组	1.75	8.77	5.26	54.39	29.82
	第Ⅱ组	0	4.41	11.76	50	33.82
	第Ⅲ组	0	1.54	24.62	58.46	15.38
	第Ⅳ组	0	2.68	21.61	56.96	18.75
愿意配合酒店低碳措施去提供服务	第Ⅰ组	0	3.51	14.04	57.89	24.56
	第Ⅱ组	0	7.35	17.65	58.82	16.18
	第Ⅲ组	0	6.15	36.92	33.85	23.08
	第Ⅳ组	0	2.68	23.21	60.71	13.39
愿意向顾客宣传节能减排的重要性	第Ⅰ组	0	5.26	21.05	56.14	17.54
	第Ⅱ组	0	1.47	20.59	50	27.94
	第Ⅲ组	0	10.77	43.08	35.38	10.77
	第Ⅳ组	0	2.68	22.32	59.82	15.18

节能设施设备的使用		第Ⅰ组	第Ⅱ组	第Ⅲ组	第Ⅳ组
制冷设备的使用情况^*	电风扇	1	1	0	0
	冷风机	0	1	0	0
	水空调	0	0	1	1
	电空调	0	1	2	3
	未采用	8	1	6	3
制暖设备的使用情况^*	电暖	0	1	1	0
	水暖	7	3	6	6
	空调制暖	3	1	3	3
热水供应设备的使用情况	太阳能	2	1	0	1
	用电	0	0	2	1
	余热回收	7	2	6	5
	锅炉	0	0	1	0
节水系统的使用情况	雨水收集利用系统	2	0	2	1
	蒸汽系统冷凝水回收	1	0	0	0
	中水系统	2	1	0	0
	使用节水器具	4	1	2	2
	没采用	0	1	5	4

[1]	范建双, 虞晓芬, 周琳. 南京市土地利用结构碳排放效率增长及其空间相关性[J]. 地理研究, 2018, 37(11): 2177-2192.
[2]	解雪峰, 濮励杰, 朱明, 许艳, 王小涵, 徐彩瑶, 陈新建. 基于典范对应分析的滨海滩涂围垦区景观格局与土壤盐渍化关系[J]. 地理研究, 2017, 36(3): 495-505.