Why Seniors use Mobile Devices: Applying an Extended Model of Goal-Directed Behavior

Kim, Myung Ja; Preis, Michael W.

doi:10.1080/10548408.2015.1064058

Cited by 58 publications

(80 citation statements)

References 64 publications

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“…Specifically, the results suggest that among Vietnamese hardy tourism enthusiasts, attitude, positive anticipated emotions, and frequency of past behavior are among the most critical indicators of visit intention. Consistent with the original conceptualization of the MGD and previous studies, desire played a central role in mediating between the independent variables and the dependent variable effectively [34,38,39]. This lends credit to the concept that for individuals to engage in a hardy activity, they first need to form a level of desire for the activity.…”

Section: Discussionsupporting

confidence: 70%

“…Moreover, the frequency of past behavior refers to how often the behavior was performed in the past by individuals [35,61]. Researchers believe that when a person performs a particular activity regularly and habitually in the past, their behavioral intention to do that kind of activity again will be enhanced [38,39,54]. Past research projects have produced evidence supporting the role of frequency of past behavior in predicting behavioral intentions in many tourism contexts [11,40,53].…”

Section: The Model Of Goal-directed Behaviormentioning

confidence: 99%

“…In the second stage, Structural Equation Modeling (SEM) was used to test the proposed hypotheses. The two-step approach has been the prominent analysis method for research projects, adopting the MGD as it first helps establish the reliability and validity between the data and the model before conducting path analysis to test the proposed hypotheses [34,38,39]. Moreover, the data were initially screened for potential violations of the basic multivariate assumptions.…”

Section: Confirmatory Factor Analysismentioning

confidence: 99%

“…The model of goal-directed behavior (MGD) emphasized that people's intention and behavior are affected by not only attitude, subjective norms, and perceived behavior control, but also other habitual (past behavior), motivational (desire), and affective (positive and negative anticipated emotions) aspects [33][34][35][36]. With this significant development, MGD was used to explain humans' behavioral intention in various fields such as sporting goods online purchasing [37], mobile device usage [38], software learning [34], and restaurant re-patronage [39]. In tourism, researchers have applied the MGD in different contexts of tourism to explain tourists' behavioral intention such as festival visitors' decision-making process [36], slow tourist's intention [40], and the oriental medicine festival tourists' behavioral intention [41].…”

Section: Introductionmentioning

confidence: 99%

“…Reviewing previous literature reveals the MGD to be a suitable theoretical framework. The MGD proposes key antecedents predicting tourists' visit intention [38,40,41]. Moreover, this present study attempts to update and extend the MGD by adding two new constructs.…”

Section: Introductionmentioning

confidence: 99%

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Examining Vietnamese Hard-Adventure Tourists’ Visit Intention Using an Extended Model of Goal-Directed Behavior

Bui

Kiatkawsin

2020

Sustainability

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Although adventure tourism is divided into two subgroups based on the level of risk, most previous research has not made a distinction in their research. However, due to the high risk, skills, experience, and physical condition required of participants, hard adventure tourism should be studied separately from soft tourism activities. Thus, this study investigates the antecedents influencing hard adventure tourists’ visit intention by adopting the model of goal-directed behavior. Furthermore, two new variables, social media consumption and hardy tourism knowledge, were added to improve the model’s predictive ability. Using 441 Vietnamese hard adventure tourists as research samples, the results have shown the conceptual model to be robust and effective in explaining behavioral intention. Generally, the results were consistent with previous research. However, subjective norms, negative anticipated emotion, and frequency of past behavior produced unexpected results.

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Section: Discussionsupporting

confidence: 70%

Section: The Model Of Goal-directed Behaviormentioning

confidence: 99%

Section: Confirmatory Factor Analysismentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Examining Vietnamese Hard-Adventure Tourists’ Visit Intention Using an Extended Model of Goal-Directed Behavior

Bui

Kiatkawsin

2020

Sustainability

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What motivates people to visit an unknown tourist destination? Applying an extended model of goal‐directed behavior

Kim

Lee

Kim

2020

Journal of Tourism Research

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This study aims to identify the motivations of people travelling to North Korea, and to determine the effects these have on the travel decision‐making process. An on‐site survey was conducted with Chinese tourists in Dandong, China. The results of an exploratory factor analysis identified four motivation factors: red (communist identity), uniqueness, convenience, and escape. The results suggest that motivations for tourism to North Korea have at least a partial influence on attitudes. “Uniqueness” has the greatest impact on tourist attitudes, implying that the most powerful motive stimulating Chinese tourists to North Korea is their “curiosity” about that isolated society.

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Acceptance and Adoption of eTourism Technologies

Pourfakhimi

Duncan

Ould

et al. 2020

Handbook of E-Tourism

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The field of eTourism research encompasses a plethora of research on users' adoption and acceptance of technologies. As a multidimensional phenomenon, an in-depth understanding of eTourism technology acceptance requires crossing the boundaries of tourism and hospitality, information and communication technologies, and marketing. Taking such a multidisciplinary approach enables researchers to integrate knowledge from the broader disciplines of psychology, sociology, and economics to construct a deep understanding of users' behavior. However, while there have been some recent advances in broadening the horizons of research in this field, the majority of eTourism technology acceptance research relies on a few classical technology acceptance and consumer behavior theories. This chapter presents a summarized overview of the most important determinants of technology acceptance behavior and critically reviews most influential theoretical models that have been used as the foundation of the majority of existing research in this field. Subsequently, some major areas of theoretical and empirical gaps in our understanding of eTourism technology acceptance will be discussed to provide researchers with a pathway towards further expanding the boundaries of research in this field. This chapter assists emerging researchers in this field to gain an overall understanding of the progress of research so far. It also directs emerging researchers towards developing alternative research agendas to diversify the theoretical foundations of eTourism technology acceptance research and expand the boundaries of knowledge in this field beyond the status quo.

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Why Seniors use Mobile Devices: Applying an Extended Model of Goal-Directed Behavior

Cited by 58 publications

References 64 publications

Examining Vietnamese Hard-Adventure Tourists’ Visit Intention Using an Extended Model of Goal-Directed Behavior

Examining Vietnamese Hard-Adventure Tourists’ Visit Intention Using an Extended Model of Goal-Directed Behavior

What motivates people to visit an unknown tourist destination? Applying an extended model of goal‐directed behavior

Acceptance and Adoption of eTourism Technologies

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