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41.
Exploring the Relationship Between Green Consumption Value,Satisfaction, and Loyalty to Hybrid Car in Elderly Consumers 下载免费PDF全文
The study aimed to examine the relationship between green consumption value, satisfaction, and loyalty of driving hybrid cars among elderly consumers. Data were collected from a cross‐sectional survey of 314 elderly consumers who purchased hybrid cars in the United States. A partial least squares analysis revealed that elderly consumers’ social, price, and quality values positively influenced the satisfaction of their hybrid car experience, and their satisfaction significantly influenced their loyalty of hybrid car. The relationship between green consumption value, satisfaction, and loyalty toward driving hybrid cars among elderly consumers revealed insight into their value orientations toward the hybrid car. Special efforts are suggested in promoting hybrid car use to elderly consumer groups. Marketers should pay attention to changing beliefs and increasing perceived values of driving a hybrid car for consumers to encourage them to use green products. 相似文献
42.
Boumedyen Shannaq Kaneez Fatima Sadriwala Fouad Jameel Ibrahim AIAzzawi 《计算机技术与应用:英文》2013,(6):291-295
The recent trend in tourism marketing is focus on customer relationship management. Tourism industry today is one of the highest revenue generating industry and strategic approach for sustainable development of this industry hosts benefits not only for the tourism related stakeholders but also the community and economy on the whole. Oman is one of the most preferred destinations for the tourists especially after the declaration of Muscat, Arab tourism Capital for 2012. Thus to materialize this honor and position, the scientific study and analysis of tourist behavior will help to predict the future trend of tourism and will give direction for effort investment. This work presents a novel strategy to identify, analyze and highlights the main tourist behavioral factors that could increase tourists' loyalty to a specific destination or agency. The analytical TSS (tourism support system) will also classify customers into two categories--first category will be classified as "LT (loyal tourists)" and second category as "NLT (non-loyal tourists)". Dataset is collected from a tourism business organization. Twenty-four attributes and 545 instances were collected and were analyzed by algorithms like logistics, forest of random trees, naive Bayes, J48 and Id3. The explanatory variables were defined, and some transformations were done to identify the response variable. Entropy was used and adapted in order to find the response variable from the explanatory variables. The results obtained from this work confirm that the generated rules can be used for future prediction and tourism business can be improved and efforts can be directed in right place for the right consumer resulting in high return on investment. 相似文献
43.
Jennie E. Callas 《国际互联网参考资料服务季刊》2013,18(1-2):77-78
SUMMARY Distance learning students may not think of the “campus” library as the first place to fulfill their information needs and may not even be aware of the services available to them. One way to reach these students is to adopt and adapt marketing techniques from the business world. This article examines the findings of a survey conducted at Emporia State University concerning the awareness of distance learning services. It will also examine marketing techniques and illustrate how they can be applied to increase awareness of reference support services for distance learners. 相似文献
44.
The experience of the Mississippi State University (MSU) Libraries illustrates the challenges presented by moving from consortial to local chat, as well as an evaluation of the advantages of chat reference in an academic setting. Countering the consortial, instant-messaging model prevalent in virtual reference today, the MSU Libraries have found chat offers advantages in an academic community. Moving to a local setting, it was possible for the MSU Libraries to maintain quality control over chat transactions while building relationships with faculty and students across campus. 相似文献
45.
《国际互联网参考资料服务季刊》2013,18(3-4):341-355
ABSTRACT Like other academic libraries, the University Library System of the University of Pittsburgh (ULS) continues to invest in providing anytime, anywhere access to research materials in electronic format. While there are obvious benefits for users in this concomitant increase in complexity for these same users, with many of them, especially undergraduates, turning to the speed and simplicity of Google and away from the complexity of library sponsored electronic resources. Seeking ways to both maximize our investment in full text resources, and promote easy access to this universe of electronic resources for our users, the ULS felt strongly that a navigational solution had to be found, and in 2004 began the process of implementing a federated search tool. This article discusses the collaborative process between the University Library System and its federated search vendor, and discusses the decision making process behind the customizations made by the ULS to its federated search system. The article also addresses the process of working with a professional marketing organization to developing a marketing message and supporting materials to promote its federated search system, and finally briefly looks at usability and usage statistics to assess the degree to which the Zoom! federated search system has met the goal of providing fast, easy access to high quality information. doi:10.1300/J136v12n03_07 相似文献
46.
《国际互联网参考资料服务季刊》2013,18(4):13-21
ABSTRACT With the emergence of the browser searchable Internet in the early 1990s, accessing the World Wide Web has become commonplace. In regards to its impact on student research, current undergraduates have become savvy searchers when it comes to accessing and integrating Internet documents into their research papers. However, this ease of use has come at a price. The overall quality of research being submitted by our students has suffered. Many incoming undergraduates don't make the distinction between documents located via a typical Internet search engine and full-text information generated from academic proprietary databases housed on the library's home page. 相似文献
47.
48.
着重分析智能决策支持系统在网络营销方面的应用。首先,从Internet出发提出本文课题的讨论背景。接着,叙述电子商务与决策支持系统的发展现状及其发展趋势。通过网络营销智能决策支持系统的设计和开发表达了决策支持系统的重要性。 相似文献
49.
皮微云 《数字社区&智能家居》2009,(36)
国内中小企业的网络营销前景已经毋庸置疑,而互动性亦已成为网络营销活动中的重要组成部分。企业源源不断地发掘出多种多样的互动元素和互动方式,并将其广泛应用于与顾客之间的网上营销活动中。这样一种网络互动营销方式不但冲击并改变着过去被动消极的传统营销模式,而且最终极大地推动并形成了企业与顾客之间的双赢局面。因此,研究分析网络互动营销活动中可能的一些操作方法则具有一定的实际意义与价值。正是基于上述背景,该文尝试探讨并提出了网络营销活动中的一些可行有效且较为实用的具体操作方法。 相似文献
50.
Sebastiano Battiato Giovanni Maria Farinella Giovanni Giuffrida Catarina Sismeiro Giuseppe Tribulato 《Multimedia Tools and Applications》2009,42(1):5-30
Traditionally, direct marketing companies have relied on pre-testing to select the best offers to send to their audience.
Companies systematically dispatch the offers under consideration to a limited sample of potential buyers, rank them with respect
to their performance and, based on this ranking, decide which offers to send to the wider population. Though this pre-testing
process is simple and widely used, recently the industry has been under increased pressure to further optimize learning, in
particular when facing severe time and learning space constraints. The main contribution of the present work is to demonstrate
that direct marketing firms can exploit the information on visual content to optimize the learning phase. This paper proposes
a two-phase learning strategy based on a cascade of regression methods that takes advantage of the visual and text features
to improve and accelerate the learning process. Experiments in the domain of a commercial Multimedia Messaging Service (MMS)
show the effectiveness of the proposed methods and a significant improvement over traditional learning techniques. The proposed
approach can be used in any multimedia direct marketing domain in which offers comprise both a visual and text component.
Sebastiano Battiato was born in Catania, Italy, in 1972. He received the degree in Computer Science (summa cum laude) in 1995 and his Ph.D in Computer Science and Applied Mathematics in 1999. From 1999 to 2003 he has lead the “Imaging” team c/o STMicroelectronics in Catania. Since 2004 he works as a Researcher at Department of Mathematics and Computer Science of the University of Catania. His research interests include image enhancement and processing, image coding and camera imaging technology. He published more than 90 papers in international journals, conference proceedings and book chapters. He is co-inventor of about 15 international patents. He is reviewer for several international journals and he has been regularly a member of numerous international conference committees. He has participated in many international and national research projects. He is an Associate Editor of the SPIE Journal of Electronic Imaging (Specialty: digital photography and image compression). He is director of ICVSS (International Computer Vision Summer School). He is a Senior Member of the IEEE. Giovanni Maria Farinella is currently contract researcher at Dipartimento di Matematica e Informatica, University of Catania, Italy (IPLAB research group). He is also associate member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006. His research interests lie in the fields of computer vision, pattern recognition and machine learning. In 2004 he received his degree in Computer Science (egregia cum laude) from University of Catania. He was awarded a Ph.D. (Computer Vision) from the University of Catania in 2008. He has co-authored several papers in international journals and conferences proceedings. He also serves as reviewer numerous international journals and conferences. He is currently the co-director of the International Summer School on Computer Vision (ICVSS). Giovanni Giuffrida is an assistant professor at University of Catania, Italy. He received a degree in Computer Science from the University of Pisa, Italy in 1988 (summa cum laude), a Master of Science in Computer Science from the University of Houston, Texas, in 1992, and a Ph.D. in Computer Science, from the University of California in Los Angeles (UCLA) in 2001. He has an extensive experience in both the industrial and academic world. He served as CTO and CEO in the industry and served as consultant for various organizations. His research interest is on optimizing content delivery on new media such as Internet, mobile phones, and digital tv. He published several papers on data mining and its applications. He is a member of ACM and IEEE. Catarina Sismeiro is a senior lecturer at Imperial College Business School, Imperial College London. She received her Ph.D. in Marketing from the University of California, Los Angeles, and her Licenciatura in Management from the University of Porto, Portugal. Before joining Imperial College Catarina had been and assistant professor at Marshall School of Business, University of Southern California. Her primary research interests include studying pharmaceutical markets, modeling consumer behavior in interactive environments, and modeling spatial dependencies. Other areas of interest are decision theory, econometric methods, and the use of image and text features to predict the effectiveness of marketing communications tools. Catarina’s work has appeared in innumerous marketing and management science conferences. Her research has also been published in the Journal of Marketing Research, Management Science, Marketing Letters, Journal of Interactive Marketing, and International Journal of Research in Marketing. She received the 2003 Paul Green Award and was the finalist of the 2007 and 2008 O’Dell Awards. Catarina was also a 2007 Marketing Science Institute Young Scholar, and she received the D. Antonia Adelaide Ferreira award and the ADMES/MARKTEST award for scientific excellence. Catarina is currently on the editorial boards of the Marketing Science journal and the International Journal of Research in Marketing. Giuseppe Tribulato was born in Messina, Italy, in 1979. He received the degree in Computer Science (summa cum laude) in 2004 and his Ph.D in Computer Science in 2008. From 2005 he has lead the research team at Neodata Group. His research interests include data mining techniques, recommendation systems and customer targeting. 相似文献
Giuseppe TribulatoEmail: |
Sebastiano Battiato was born in Catania, Italy, in 1972. He received the degree in Computer Science (summa cum laude) in 1995 and his Ph.D in Computer Science and Applied Mathematics in 1999. From 1999 to 2003 he has lead the “Imaging” team c/o STMicroelectronics in Catania. Since 2004 he works as a Researcher at Department of Mathematics and Computer Science of the University of Catania. His research interests include image enhancement and processing, image coding and camera imaging technology. He published more than 90 papers in international journals, conference proceedings and book chapters. He is co-inventor of about 15 international patents. He is reviewer for several international journals and he has been regularly a member of numerous international conference committees. He has participated in many international and national research projects. He is an Associate Editor of the SPIE Journal of Electronic Imaging (Specialty: digital photography and image compression). He is director of ICVSS (International Computer Vision Summer School). He is a Senior Member of the IEEE. Giovanni Maria Farinella is currently contract researcher at Dipartimento di Matematica e Informatica, University of Catania, Italy (IPLAB research group). He is also associate member of the Computer Vision and Robotics Research Group at University of Cambridge since 2006. His research interests lie in the fields of computer vision, pattern recognition and machine learning. In 2004 he received his degree in Computer Science (egregia cum laude) from University of Catania. He was awarded a Ph.D. (Computer Vision) from the University of Catania in 2008. He has co-authored several papers in international journals and conferences proceedings. He also serves as reviewer numerous international journals and conferences. He is currently the co-director of the International Summer School on Computer Vision (ICVSS). Giovanni Giuffrida is an assistant professor at University of Catania, Italy. He received a degree in Computer Science from the University of Pisa, Italy in 1988 (summa cum laude), a Master of Science in Computer Science from the University of Houston, Texas, in 1992, and a Ph.D. in Computer Science, from the University of California in Los Angeles (UCLA) in 2001. He has an extensive experience in both the industrial and academic world. He served as CTO and CEO in the industry and served as consultant for various organizations. His research interest is on optimizing content delivery on new media such as Internet, mobile phones, and digital tv. He published several papers on data mining and its applications. He is a member of ACM and IEEE. Catarina Sismeiro is a senior lecturer at Imperial College Business School, Imperial College London. She received her Ph.D. in Marketing from the University of California, Los Angeles, and her Licenciatura in Management from the University of Porto, Portugal. Before joining Imperial College Catarina had been and assistant professor at Marshall School of Business, University of Southern California. Her primary research interests include studying pharmaceutical markets, modeling consumer behavior in interactive environments, and modeling spatial dependencies. Other areas of interest are decision theory, econometric methods, and the use of image and text features to predict the effectiveness of marketing communications tools. Catarina’s work has appeared in innumerous marketing and management science conferences. Her research has also been published in the Journal of Marketing Research, Management Science, Marketing Letters, Journal of Interactive Marketing, and International Journal of Research in Marketing. She received the 2003 Paul Green Award and was the finalist of the 2007 and 2008 O’Dell Awards. Catarina was also a 2007 Marketing Science Institute Young Scholar, and she received the D. Antonia Adelaide Ferreira award and the ADMES/MARKTEST award for scientific excellence. Catarina is currently on the editorial boards of the Marketing Science journal and the International Journal of Research in Marketing. Giuseppe Tribulato was born in Messina, Italy, in 1979. He received the degree in Computer Science (summa cum laude) in 2004 and his Ph.D in Computer Science in 2008. From 2005 he has lead the research team at Neodata Group. His research interests include data mining techniques, recommendation systems and customer targeting. 相似文献