Exploring Tourist Satisfaction with Mobile Experience Technology
Notice bibliographique
Résumé
[Abstract] Wireless access with handheld devices is a promising addition to the WWW and traditional electronic business. Handheld devices provide convenience, portable access, and large amounts of information to travelers. Tourism presents considerable potential for the use of new mobile technologies; however, limited research exists on mobile users' perspectives with regard to satisfaction towards mobile technology. There is a need to develop an understanding of travelers' satisfaction with mobile commerce in order to gain optimum competitive advantage. In this paper, we adapted and developed the American Customer Satisfaction Model (ACSM) to m-commerce in the tourism industry. The results of this study suggest that the degree of perception and perceived value are key factors affecting mobile travelers' satisfaction with their mobile experiences. Satisfaction, in turn, influences the extent of intention to continue to use mobile devices during travel. The study concludes with recommendations based on our findings, as well as provides directions for future research. [Keywords] Mobile commerce; customer satisfaction; American Customer Satisfaction Model (ACSM); mobile technology Introduction In recent years, there has been significant growth in the use of mobile devices, such as hand-phones, personal digital assistants (PDAs), and handheld computers. In U.S., mobile commerce revenue doubled to $58.4 billion in 2007 from $29 billion in 2006 (Jupiter, 2008) Mobile technology not only extends the reach of wired networks, but also serves as an alternative information channel providing new range of opportunities to travelers, as well as changing the way certain information-related activities are conducted. In the past, mobile devices were regarded as a luxury for individuals. However, mobile commerce (m-commerce) now offers great flexibility for the tourism industry both to suppliers and travelers. Users can surf the web, check e-mail, read news, pay transactions, and quote stock prices using these handheld devices. From the supplier's perspective, the promotional message can be changed much more quickly than through the use of traditional media. M-commerce is now becoming the standard in handung travel yields effectively (Eriksson, 2002). Ninety percent of households in Japan, South Korea, and urban China now own cell phones, as do 80% of households in Western Europe, 60% in Canada, and three out of four households in the U.S. (Lombard, 2006). With this skyrocketing rate of ownership of mobile devices (Fernadez, 2000; Bughin, et al., 2001), considerable research efforts are now being devoted to understanding how mobile technology could support the information needs of travelers, ranging from touring in museums (Oppermann & Specht, 1999), transportation and parking information (Rodseth et al., 2001), location identification (Eriksson, 2002), to tracking and navigation (Corona & Winter, 2001). The findings of these research efforts imply that travelers are interested in new ways to carry out their travel plans. However, limited research exits on traveler's satisfaction with mobile technology and mobile devices. The purpose of this study, therefore, is to develop a conceptual framework that examines and explains the factors influencing mobile users' satisfaction and purchase intention. The study is organized as follows: first, the background of the study is described; second a tourist satisfaction model for mobile devices is proposed with corresponding hypotheses; third, the proposed model was tested using confirmatory factor analysis and structural equation modeling. The study ends by presenting conclusions and discussing study implications. Study Background M-commerce M-commerce, in this study, is defined as a transaction that takes place via wireless Internet-enabled technology (through handheld computers, cellular phones, personal digital assistants (PDAs), or palmtop computers) while allowing for freedom of movement for the end user (Wei & Ozok, 2005). …
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,000 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,001 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
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