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Auswahl der wissenschaftlichen Literatur zum Thema „Channel switching intentions“
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Zeitschriftenartikel zum Thema "Channel switching intentions"
Youn, Song-yi, Jung Eun Lee und Jung Ha-Brookshire. „Fashion Consumers’ Channel Switching Behavior During the COVID-19: Protection Motivation Theory in the Extended Planned Behavior Framework“. Clothing and Textiles Research Journal 39, Nr. 2 (28.01.2021): 139–56. http://dx.doi.org/10.1177/0887302x20986521.
Der volle Inhalt der QuelleCambra-Fierro, Jesús, Iguácel Melero-Polo, Lia Patrício und F. Javier Sese. „Channel Habits and the Development of Successful Customer-Firm Relationships in Services“. Journal of Service Research 23, Nr. 4 (06.04.2020): 456–75. http://dx.doi.org/10.1177/1094670520916791.
Der volle Inhalt der QuelleJeon, So Young, und Hanjoo Yoo. „A Study on the Effects of Switching Barriers to Non-facing Channel on Switching Intentions in Car Insurance“. Journal of Korea Service Management Society 21, Nr. 3 (30.09.2020): 277–300. http://dx.doi.org/10.15706/jksms.2020.21.3.013.
Der volle Inhalt der QuelleSingh, Jaywant, und Benedetta Crisafulli. „Managing online service recovery: procedures, justice and customer satisfaction“. Journal of Service Theory and Practice 26, Nr. 6 (14.11.2016): 764–87. http://dx.doi.org/10.1108/jstp-01-2015-0013.
Der volle Inhalt der QuelleMaggioni, Isabella, Sean James Sands, Carla Renee Ferraro, Jason Ian Pallant, Jessica Leigh Pallant, Lois Shedd und Dewi Tojib. „Consumer cross-channel behaviour: is it always planned?“ International Journal of Retail & Distribution Management 48, Nr. 12 (05.08.2020): 1357–75. http://dx.doi.org/10.1108/ijrdm-03-2020-0103.
Der volle Inhalt der QuelleSombultawee, Kedwadee. „Mobile Commerce Switching Intentions in Thai Consumers“. Mediterranean Journal of Social Sciences 8, Nr. 6 (27.11.2017): 123–34. http://dx.doi.org/10.1515/mjss-2017-0049.
Der volle Inhalt der QuelleShankar, Amit, Rambalak Yadav, Manish Gupta und Charles Jebarajakirthy. „How Does Online Engagement Drive Consumers' Webrooming Intention?“ Journal of Global Information Management 29, Nr. 6 (November 2021): 1–25. http://dx.doi.org/10.4018/jgim.20211101.oa19.
Der volle Inhalt der QuelleShankar, Amit. „How does convenience drive consumers' webrooming intention?“ International Journal of Bank Marketing 39, Nr. 2 (14.01.2021): 312–36. http://dx.doi.org/10.1108/ijbm-03-2020-0143.
Der volle Inhalt der QuelleTussa'diah, Halimah, Eka Anggaini und Selamat Husni Hasibuan. „CODE SWITCHING UTTERANCES OF PUBLIC FIGURES’ VLOG IN YOUTUBE CHANNEL“. PROJECT (Professional Journal of English Education) 4, Nr. 3 (11.05.2021): 513. http://dx.doi.org/10.22460/project.v4i3.p513-520.
Der volle Inhalt der QuelleKim, Do Yeon, und Ho Jung Choo. „The Effects of Department Store Customers' Satisfaction and Commitment on Relationship Switching Intention and Multi-channel Use Intention“. Fashion & Textile Research Journal 15, Nr. 5 (31.10.2013): 753–62. http://dx.doi.org/10.5805/sfti.2013.15.5.753.
Der volle Inhalt der QuelleDissertationen zum Thema "Channel switching intentions"
Radaciova, Romana, und Alexandra Klacanova. „To try on or send back? Shopping in post-pandemic times : Exploratory study of pandemic effects on consumer behaviour“. Thesis, Umeå universitet, Företagsekonomi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-184366.
Der volle Inhalt der QuelleRong, Zeng Ying, und 曾盈蓉. „A Study on Customers’ Switching Intention between Virtual Channels“. Thesis, 2013. http://ndltd.ncl.edu.tw/handle/87022223729727138929.
Der volle Inhalt der Quelle國立勤益科技大學
流通管理系
101
According to the data from the Department of Statistics, Ministry of Economic Affairs in Taiwan, the total revenue from non-store retailing had broken through 181 billion and 800 million NT dollars in 2012. Trendgo Research investigated what the customers of online shopping, online auction, TV shopping, radio shopping, mail order and direct selling in the first half of 2010, the online shopping was the most popular non-store retailing in Taiwan; 13.9% of Taiwan’s population, about 2.78 million persons, had experience of online shopping and the others included 7.0% of TV shopping, 5.5% of online auction and 5.1% of direct selling. This study, uses PPM model, is designed to discuss the factors that interfering the TV shopping model to shift to e-commerce based shopping.All descriptive statistical analyses, reliability and validity, hypothesis testing, path coefficients and T values were accomplished using SPSS software, version19.0 and PLS software, version 2.0.The results showed the risks from TV shopping, including financial risk、social risk 、product risk 、time risk, produced a push effect that make customers to quit TV shopping. On the other hand, the plenty of information, the service, the quality and the delivery system of online shopping generated a pull effect that significantly attracted the client to use online shopping. However, the service of TV shopping also had a mooring effect that interfere the customer's intention to switch their shopping habit. The final analysis of the push - pull - mooring effect on the switching intension revealed that the test of pull effect (β = -0.601, t = 16.132) supported the hypothesis 2,which meant the advantages of online shopping did attract the people to use it , while the test of push and mooring effects showed no significant result. However, when the mooring effect was seen as a moderator variable , the push effect became significant (β = -0.089, t = 2.123) that made hypothesis 4 true, which meant despite of the disadvantages, the advantages of TV shopping could also reduce the customers' intention for online shopping. The conclusion can contribute to a managerial implications and suggestions applied in the future.
Ching-Fu, Huang, und 黃清福. „The study of consumers' switching intention between online and offline channel ─ An Example of The Convenience Goods“. Thesis, 2015. http://ndltd.ncl.edu.tw/handle/7gnbsm.
Der volle Inhalt der Quelle中國文化大學
企業實務管理數位學習碩士在職專班
103
With the rapid development of e-commerce, network speed, the technologies of web page and Internet payment are advancing with the times, the popularity of smart phones has raised e-commerce to mobile commerce, it is paid more attention on the impact of the Internet shop, such as the choices of consumer made between physical store and internet store, and how it convert between those two kind of stores. It forced the vendor to face the impaction. Therefore, this study is to explore the consumer switching his intention between online and offline channel by vendor to provide commodity promotion, to buy convenience goods as the scope of the investigation. This study used a structured questionnaire, with keypal as the sampling target, divided into 2 group of questionnaire that internet shop with or without providing merchandise promotion, total recovery of 255 buy convenience goods in a physical channel. This study investigated the relationship of merchandise promotion that interfere with consumer perception sacrifice, store loyalty, perceived convenience and converted intention. The results showed that merchandise promotion to perception sacrifice have significant interference, and couldn’t prove the existence of interference effects to the remaining variables.
Sae-Lao, Salisa, und 劉秋梅. „The relationship among consumer intention and consumer behavior in channel switching from the physical store to virtual store“. Thesis, 2009. http://ndltd.ncl.edu.tw/handle/67126137754790917166.
Der volle Inhalt der Quelle南台科技大學
企業管理系
97
ABSTRACT Keywords: Theory of Planned Behavior, Trust, Switching cost, The intention to switch, Behavior. Since the Internet was made available for commercial use, Taiwan is the well known country for the Business-to-Consumer electronic commerce. Nowadays, Taiwanese consumers are now entering a new era which the consumers can shop through virtual store on World-Wide-Web (WWW) 24 hours with various market sectors of goods and services. In this paper, the main objective of this research is to investigate the impact of the Theory of Planned Behavior (TPB) and moderating factors – trust and switching cost which might take significantly influence on the intention to switch and the behavior in channel switching from the physical store to virtual store. Moreover, to identify the relationship among transfer consumer’s intention and transfer consumer’s behavior in channel switching from the physical store to virtual store. The research setting was in Tainan, Taiwan. The data was collected through 200 survey questionnaires. Statistical analysis included descriptive statistics, Factor analysis, R2, and the Structural Equation Modelling (SEM) techniques. The result support that Theory of Planned Behavior (TPB) which consist of attitude toward behavior, subjective norms and perceived behavior control and the physical store-trust can explain the intention to switch in positive way. However another variable- switching cost explains the intention to switch in negative way. Finally, consumer’s intention has the relationship with consumer’s behavior.
Yang, Jhong-Min, und 楊忠民. „The Customers’ Switching Intention between Bricks-and-Mortar Channel and 7net Click-and-Mortar Store: The Perspective of Push-Pull-Mooring Model of Human Geography“. Thesis, 2012. http://ndltd.ncl.edu.tw/handle/51697018983661838816.
Der volle Inhalt der Quelle國立勤益科技大學
流通管理系
100
With the growth of the Internet population and the maturing of online shopping environment, the online channel has become the next new energy leads to the growth of retail business. Whether the space constraints or market size, Convenience stores are limited in the development of entity store and sales growth. “The 7net Click-and-Mortar Store” developed based on the concept of “cloud supermarket” is the major strategy leading to initiate new growth. The PPM, a theoretical framework of population migration, is applied in this research to study the customers’ intention between Bricks-and-Mortar Channel and 7net Click-and-Mortar Store. We attempt to clarify the relationship between push-pull-mooring effects and switching intention, and examine the moderating effect by useing the moderator variable--mooring effects, pull effects and retail channel formats. In this study, 353 examples were obtained by conducted a field survey and found that: First, “push effect”, “pull effect” and “mooring effect” were produced by the poor performance of service, convenience and store image of the Bricks-and-Mortar channels, and the perceptions of lower price, lower search effort, and perceived product variety from 7net Click-and-Mortar Store and The perceived risk of online shopping, technology anxiety, relationship quality with physical channel. Second, only pull effects have a significant effect between the push-pull-mooring effects and switching intention. Third, through PPM model indicate that customers from different formate retail channel presented a consistency of results. Fourth, mooring effects for the moderator variables do not have a significant interaction effect with both the pull effect and push effects. Fifth, when pull effects as moderator variable to test interaction effects, the pull effect have significant interaction effect with both push effects and mooring. Finally, management and academic implications and recommendations are discussed at the end.
Buchteile zum Thema "Channel switching intentions"
Kessenbrock, Andreas, und Sören Köcher. „Information Search at the Point of Sale: How Information Source Influences Customers’ Purchase Channel Switching Intention: An Abstract“. In Back to the Future: Using Marketing Basics to Provide Customer Value, 407–8. Cham: Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-66023-3_141.
Der volle Inhalt der QuelleTenenbaum, Sergio. „Persisting Intentions“. In Rational Powers in Action, 143–67. Oxford University Press, 2020. http://dx.doi.org/10.1093/oso/9780198851486.003.0006.
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