基于数据包络分析与灰色熵的院线网络营销绩效研究

doi:10.16381/j.cnki.issn1003-207x.2020.1637

中国管理科学 ›› 2023, Vol. 31 ›› Issue (5): 240-248.doi: 10.16381/j.cnki.issn1003-207x.2020.1637

• 论文 • 上一篇

基于数据包络分析与灰色熵的院线网络营销绩效研究

周珍, 见红玉, 黄嘉佩, 林云

首都师范大学管理学院，北京100089

收稿日期:2020-08-25 修回日期:2021-01-11 发布日期:2023-05-23
通讯作者: 黄嘉佩(1996-)，女(汉族)，江西宜春人，首都师范大学管理学院，硕士研究生，研究方向:国际投资与跨国并购，Email：hjp19961024@163.com. E-mail:hjp19961024@163.com
基金资助:
国家自然科学基金资助项目(71874112,72274126)；国家自然科学基金资助重点项目(71532002)；北京市教委社会科学计划面上项目(0142132014)

The Influence of E-marketing on Cinema Performance Based on DEA and Grey Entropy

ZHOU Zhen, JIAN Hong-yu, HUANG Jia-pei, LIN Yun

School of Management, Capital Normal University, Beijing 100089, China

Received:2020-08-25 Revised:2021-01-11 Published:2023-05-23
Contact: 黄嘉佩 E-mail:hjp19961024@163.com

摘要/Abstract

摘要： 本文以42家国内院线作为研究样本，利用数据包络分析(DEA)和灰色熵权法分析了网络营销对院线绩效的影响，得出以下结论：极少部分院线的市场占有率大且网络营销水平高，多数院线在网络营销方面尚有很大进步空间；网络营销与院线绩效呈正向相关的关系；网络营销工具中各属性对于院线绩效正向影响程度由大到小排序分别是：在线交易、影院设施、互动功能、基本信息、促销活动。本文在研究结论基础上，从网络营销实施过程和构建网络营销平台两方面给出了可行性建议。

关键词: 网络营销；院线营销；数据包络分析；灰色熵权法

Abstract: China has now become the second-largest film market in the world. The country vigorously supports the development of the cultural industry, and the film industry's development has been valued and supported. Under the dual guidance of demand and policy, the cinema companies have continuously carried out network marketing. In the existing literature, online marketing researches are mostly concentrated on consumers and third-party platforms. Literature rarely study performance from online marketing providers; the elements of online marketing research are mostly focused on online reviews or online word-of-mouth and online searches. The literature discusses online promotions, online transactions, and other elements of online interaction. There are a few online marketing performances in the literature.

Key words: E-marketing; cinema marketing; data envelopment analysis; grey entropy weight method

中图分类号:

周珍, 见红玉, 黄嘉佩, 林云. 基于数据包络分析与灰色熵的院线网络营销绩效研究[J]. 中国管理科学, 2023, 31(5): 240-248.

ZHOU Zhen, JIAN Hong-yu, HUANG Jia-pei, LIN Yun. The Influence of E-marketing on Cinema Performance Based on DEA and Grey Entropy[J]. Chinese Journal of Management Science, 2023, 31(5): 240-248.

参考文献

［1］杨扬,刘圣,李宜威,等.大数据营销:综述与展望［J］.系统工程理论与实践,2020,40(8):2150-2158.Yang Yang, Liu Sheng, Li Yiwei, et al. Big data marketing: review and prospect［J］. Systems Engineering-Theory & Practice, 2020,40(8): 2150-2158.
［2］ Chen Yanhong, Lu Yaobin, Wang Bin, et al. How do product recommendations affect impulse buying? An empirical study on WeChat social commerce［J］. Information & Management,2019,56 (2):236-248.
［3］ Dabholkar P A, Sheng Xiaojing. Consumer participation in using online recommendation agents: effects on satisfaction, trust, and purchase intentions［J］. Service Industries Journal,2012,32(9):1433-1449.
［4］ Liu Chienliang, Chen Yingchuan. Background music recommendation based on latent factors and moods［J］. Knowledge-Based Systems,2018,159(1):158-170.
［5］胡春华,赵慧,童小芹,等.推荐系统对消费者网购支出的影响研究［J］.中国管理科学,2020,28(6):158-170.Hu Chunhua, Zhao Hui, Tong Xiaoqin, et al. Research on the impact of intelligent recommendation system on consumer online shopping［J］. Chinese Journal of Management Science,2020,28(6):158-170.
［6］毛照昉,冯博,刘伟,等.在线旅游平台混合不透明营销策略选择研究［J］.系统工程理论与实践,2018,38(3):655-664.Mao Zhaofang, Feng Bo, Liu Wei, et al. Choice of mixed opaque marketing strategy of OTA［J］. SystemsEngineering-Theory & Practice,2018,38(3): 655-664.
［7］王聪,杨德礼.电商平台折扣券对制造商双渠道策略的影响研究［J］.系统工程理论与实践,2018,38(6):1525-1535.Wang Cong, Yang Deli. A study of the influence of the platform coupons on the dual-channel supply chain strategy of manufacturers［J］. SystemsEngineering-Theory&Practice,2018,38(6):1525-1535.
［8］王伟,王洪伟.特征观点对购买意愿的影响:在线评论的情感分析方法［J］.系统工程理论与实践,2016,36(1):63-76.Wang Wei, Wang Hongwei. The influenceof aspect-based opinions on user’spurchase intention using sentiment analysis of online reviews［J］. Systems Engineering-Theory&Practice,2016,36(1):63-76.
［9］王安宁,张强,彭张林,等.基于在线评论的区域需求偏好识别方法［J］.中国管理科学,2019,27(7):167-176.Wang Anning, Zhang Qiang, Peng Zhanglin, et al. Identifying regional demand preferences from online reviews［J］. Chinese Journal of Management Science,2019,27(7):167-176.
［10］ Godes D, Mayzlin D. Using Online conversations to study Word-of-Mouth communication［J］. Marketing Science，2004，23(4):545-560.
［11］卢向华,冯越. 网络口碑的价值——基于在线餐馆点评的实证研究［J］. 管理世界,2009(7): 126-132.Lu Xianghua, Feng Yue. The value of online word-of-mouth: an empirical study based on online restaurant reviews［J］. Management World, 2009(7): 126-132.
［12］郝媛媛,叶强,李一军.基于影评数据的在线评论有用性影响因素研究［J］.管理科学学报,2010,13(8):78-88+96.Hao Yuanyuan, Ye Qiang, Li Yijun. Research on online impact factors of customer reviews usefulness based on movie reviews data［J］. Journal of Management Sciences in Chinese, 2010,13(8):78-88+96.
［13］石文华,钟碧园,张绮.在线影评和在线短评对票房收入影响的比较研究［J］.中国管理科学,2017,25(10):162-170.Shi Wenhua, Zhong Biyuan, Zhang Qi. Comparing the effects of online reviews and online comments on box-office incomes［J］. Chinese Journal of Management Science,2017,25(10):162-170.
［14］ Rui Huaxia，Liu Yizao，Whinston A. Whose and what chatter matters? The effect of tweets on movie sales［J］. Decision Support Systems，2013，55(4):863-870.
［15］孙春华,刘业政.电影预告片在线投放对票房的影响——基于文本情感分析方法［J］.中国管理科学,2017,25(10):151-161.Sun Chunhua, Liu Yezheng.The effects of online pre-launch movie trailers on box office revenue—based on text sentiment analysis method［J］. Chinese Journal of Management Science,2017,25(10):151-161.
［16］ Onishi H, Manchanda P. Marketing activity, blogging and sales［J］. International Journal of Research in Marketing，2012，29(3): 221-234.
［17］ Diaz A，Gomez M，Molina A. A comparison of online and offline consumer behavior: an empirical study on a cinema shopping context［J］. Journal of Retailing and Consumer Services，2017，38：44-50.
［18］陈伟华,魏丽.中国寿险公司资金运用效率研究——基于共享投入型两阶段DEA模型［J］.金融评论,2019,11(4):83-94+126.Chen Weihua, Wei Li.Capital utilization efficiency of Chinese life insurance companies: an analysis based on two-stage DEA model［J］. Chinese Review of Financial Studies, 2019,11(4):83-94+126.
［19］龚日朝,刘俞希,潘芬萍.带权重约束的DEA超效率评价模型及其应用研究［J］.中国管理科学,2020,28(4):164-173.Gong Rizhao, Liu Yuxi, Pan Fenping. DEA super efficiency evaluation model with weight constraints and its application［J］. Chinese Journal of Management Science,2020,28(4):164-173.
［20］ Andersen P, Petersen N C. A procedure for ranking efficient units in data envelopment analysis［J］. Management Science,1993,39(10):1261-1264.
［21］ Deng Julong. Control problem of grey systems［J］. Systems & Control Letters,1982,1(5):288-294.
［22］ Angel L Meroo-Cerdan, Pedro Soto-Acosta. External Web content and its influence on organizational performance［J］. European Journal of Information Systems,2007,16(1):66-80.
［23］郭光明. 多功能影院网站的设计与开发［D］.北京: 北京工业大学,2016.Guo Guangming. Design and development of the multifunctional cinema site［D］. Beijing: Beijing University of Technology,2016.
［24］ Angehrn A. Designing mature internet business strategies: the ICDT model［J］. European Management Journal,1997,15(4):361-369.
［25］ Shuai Jiajane, Wu Weiwen. Evaluating the influence of E-marketing on hotel performance by DEA and grey entropy［J］. Expert Systems with Applications,2011,38(7):8763-8769.
［26］ Liu Chang, Arnett K P, Capella L M, et al. Websites of the Fortune 500 companies: facing customers through home pages［J］. Information & Management,1997,31(6):335-345.

[1]	朱星圳, 李莉, 张华, 何向, 胡娇. 考虑消费者偏好差异的网络视频平台和广告商决策研究[J]. 中国管理科学, 2023, 31(1): 216-225.
[2]	刘征驰, 黄雅文, 马滔. 非授权分享、定价分歧与知识付费平台运营策略[J]. 中国管理科学, 2021, 29(3): 168-175.
[3]	吕通, 史乐峰, 邹小燕. 计及网络效应的共享经济商业网络布局分析与两步差分聚类-萤火虫算法[J]. 中国管理科学, 2019, 27(6): 146-157.
[4]	石文华, 钟碧园, 张绮. 在线影评和在线短评对票房收入影响的比较研究[J]. 中国管理科学, 2017, 25(10): 162-170.
[5]	谢兆霞, 李莉. 两寡头序贯进入下的B2B电子商务网站IT投资决策[J]. 中国管理科学, 2014, 22(2): 56-64.
[6]	唐方成, 池坤鹏. 双边网络环境下的网络团购定价策略研究[J]. 中国管理科学, 2013, 21(3): 185-192.
[7]	刘伟, 程平. 基于相互影响的复杂可信软件产品需求变化传播研究[J]. 中国管理科学, 2010, 18(4): 124-132.
[8]	杨瑾, 尤建新, 蔡依平. 产业集群环境下供应链系统快速响应能力评价[J]. 中国管理科学, 2007, 15(1): 34-40.

基于数据包络分析与灰色熵的院线网络营销绩效研究

The Influence of E-marketing on Cinema Performance Based on DEA and Grey Entropy

PDF (PC)

可视化

摘要/Abstract

引用本文

使用本文

参考文献

相关文章 8

Metrics

本文评价

推荐阅读 0