Results 201 to 210 of about 70,716 (243)
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Abhijit Banerjee, Drew Fudenberg
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Australasian Marketing Journal, 2007
In the social sciences there are a number of important topics that do not lend themselves to experimentation or direct observation. The socialisation of children and the formation of delinquent gangs are examples. In consumer behaviour, word of mouth (WOM) is of this type.
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In the social sciences there are a number of important topics that do not lend themselves to experimentation or direct observation. The socialisation of children and the formation of delinquent gangs are examples. In consumer behaviour, word of mouth (WOM) is of this type.
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Asia Pacific Journal of Marketing and Logistics, 2014
Purpose – This research was designed to expand the understanding of how brand familiarity may affect the motivation to process word-of-mouth (WOM) information in brand evaluation. The pre-WOM brand attitude certainty is expected to explain the moderation effect. The paper aims to discuss these issues.
Boon Chong Lim, Cindy M.Y. Chung
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Purpose – This research was designed to expand the understanding of how brand familiarity may affect the motivation to process word-of-mouth (WOM) information in brand evaluation. The pre-WOM brand attitude certainty is expected to explain the moderation effect. The paper aims to discuss these issues.
Boon Chong Lim, Cindy M.Y. Chung
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2015
La voce illustra le teorie canoniche e gli approcci teorici più recenti al fenomeno del word of mouth, soprattutto in relazione alla comunicazione politica.
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La voce illustra le teorie canoniche e gli approcci teorici più recenti al fenomeno del word of mouth, soprattutto in relazione alla comunicazione politica.
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Services Marketing Quarterly, 2013
Customers are increasingly using social media channels in their purchase decisions. We explore the influence of interpersonal word-of-mouth (WOM) and various forms of electronic word-of-mouth (eWOM). WOM is found to have more influence on behavioral intentions, trust in WOM, and attitude toward the firm compared to all eWOM channels explored.
Matthew L. Meuter +2 more
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Customers are increasingly using social media channels in their purchase decisions. We explore the influence of interpersonal word-of-mouth (WOM) and various forms of electronic word-of-mouth (eWOM). WOM is found to have more influence on behavioral intentions, trust in WOM, and attitude toward the firm compared to all eWOM channels explored.
Matthew L. Meuter +2 more
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Personal Word of Mouth, Virtual Word of Mouth, and Innovation Use
Journal of Product Innovation Management, 2012The authors examine the impact of word‐of‐mouth communication on innovation use. Hypotheses are developed linking both personal and virtual word of mouth (vWOM) directly to innovation use. The authors also examine the mediating role of two additional variables that link word of mouth and innovation use.
Tomoko Kawakami +2 more
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Managing Service Quality: An International Journal, 1992
Discusses “Welcome Host”, the programme launched by the Wales Tourist Board which aims to provide whole communities with the customer care skills required to deliver service excellence to visiting tourists. Outlines the structure of the programme, highlighting the use of seminars and the key focus of such events.
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Discusses “Welcome Host”, the programme launched by the Wales Tourist Board which aims to provide whole communities with the customer care skills required to deliver service excellence to visiting tourists. Outlines the structure of the programme, highlighting the use of seminars and the key focus of such events.
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Proceedings of the ICMI-MLMI '09 Workshop on Multimodal Sensor-Based Systems and Mobile Phones for Social Computing, 2009
Word-of-mouth communication has been shown to play a key role in a variety of environments such as viral marketing and churn prediction. A family of algorithms, generally known as information spreading algorithms has been developed to model such pervasive behavior.
Manuel Cebrian, Enrique Frias-Martinez
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Word-of-mouth communication has been shown to play a key role in a variety of environments such as viral marketing and churn prediction. A family of algorithms, generally known as information spreading algorithms has been developed to model such pervasive behavior.
Manuel Cebrian, Enrique Frias-Martinez
openaire +1 more source

