Marketing implications of traditional and ICT-mediated leisure activities

Zorn, Steffen; Lee, Richard; Murphy, Jamie

doi:10.1080/01449290903121360

Cited by 4 publications

(3 citation statements)

References 34 publications

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“…The occupation of the head of household affects travel intention and level of expenditure. These results match the data from Zorn et al (2012). To summarize the above findings, with respect to social status, the education level and occupational classification should be used as a reference for marketing segmentation when planning tourism products.…”

Section: Resultssupporting

confidence: 79%

“…Therefore, higher education levels also increase travel expenditure. Zorn et al (2012) found that the demographic variables leisure activities and consumer behaviour were significantly different from each other. In other words, participation in leisure activities will be affected by individual and family behaviours, characteristics and occupations.…”

Section: Financial Factors Dsp1mentioning

confidence: 81%

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Analysis of the Relationship between Household Life Cycle and Tourism Expenditure in Taiwan: An Application of the Infrequency of Purchase Model

2015

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The infrequency of purchase (IP) model was used to explore the impact of financial factors, limiting factors, social status and household life cycle on family travel intention and travel expenditure in Taiwan. The empirical results indicate that family travel intention and level of expenditure vary at different stages of the household life cycle. Additionally, family incomes, the education level of the head of the household, women's employment and home ownership have significantly positive impacts on travel intention and level of expenditure. The findings also suggest that the presence of a family member's health problems or the number of seniors over 65 years of age in a household will reduce travel intention and thus the level of travel expenditure.

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Section: Resultssupporting

confidence: 79%

Section: Financial Factors Dsp1mentioning

confidence: 81%

Analysis of the Relationship between Household Life Cycle and Tourism Expenditure in Taiwan: An Application of the Infrequency of Purchase Model

2015

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“…Another difficulty for companies implementing churn models is that a firm's customers can be highly heterogeneous (Bell et al , 2002; Lewis, 2006), and, therefore, different churn models are required for different segments of the firm's customers. Demographics are easily measured, but tend to be poor tools for predicting membership in different PB segments; firms require insights into how each individual customer thinks and feels about their products (Sivadis et al , 1998; Zorn and Murphy, 2007). These differences in preferences usually relate to situation‐specific variables, such as each customer's level of commitment to the relationship, their satisfaction with the firm's products, and their perceptions of the firm's quality and trustworthiness.…”

Section: Introductionmentioning

confidence: 99%

Attitudinal perspectives for predicting churn

Zorn

Jarvis

Bellman

2010

Journal of Research in Interactive Marketing

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PurposeAs acquiring new customers is costly, putting effort into satisfying and keeping customers over the long term can improve profitability. Firms usually do not know how each individual customer is feeling at any time (their attitude to the firm), so typically a customer's likelihood of leaving (“churning”) is predicted from behavioural data. The purpose of this paper is to investigate how a firm can add attitudinal variables to these churning models by deriving proxy indicators of satisfaction and commitment from behavioural data. The paper tests whether adding these proxies improved predictions of churning compared to a typical model based on purchasing behaviour (PB).Design/methodology/approachAnalysing data from 6,000 regular customers from an Australian digital versatile disc rental company, logistic regression predicted membership termination (i.e. churning=1) versus continuation (=0). A baseline model used three traditional behavioural variables directly linked to members' PB. A second model including proxies for satisfaction and commitment from the customer database was compared against the baseline model to investigate improvement in churn prediction.FindingsThe most significant predictor of churn is an indicator of commitment: the uncertainty of a customer's commitment, indicated by number of times they changed their subscription plan.Practical implicationsThe more customers change their plan, the more likely they are to quit the relationship with the firm, most likely because they are uncertain about how they can benefit from a long‐term commitment to the firm. Monitoring uncertainty indicators, such as plan changing, allows firms to intervene with special offers for uncertain customers, and, therefore, increase the likelihood of them staying with the firm.Originality/valueThe paper discusses the use of customer behaviour recorded in databases to identify proxy indicators of attitude before this attitude translates into churning behaviour.

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Tourists’ virtual reality adoption: an exploratory study from Lake District National Park

Dieck

Jung

et al. 2018

Leisure Studies

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Virtual reality (VR) transforms the way destinations market their tourism offerings. To fully understand the opportunities of a technology, initial research is required assessing user adoption. However, empirical research and particularly exploratory qualitative research on VR adoption in tourism context is limited. Therefore, this study uses an exploratory interview approach with 35 participants near Lake District National Park, UK. Using thematic analysis, this study explores factors that influence VR adoption as well as the influencing factors on tourists' behavioural intentions. This study adds to academia by qualitatively exploring the adoption of a scarcely researched technology within the tourism context. the VR experience were influenced by the novelty of the experience itself rather than the VR content. As such when it comes to "intention to use" the study might paint a skewed picture. Second, the qualitative nature of this study enabled to identify new and contextspecific factors of VR adoption. However, findings are therefore not generalisable and need to be tested on a bigger sample. Third, testing the model in another context would help to understand its power in explaining adoption behaviours across multiple settings.

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Marketing implications of traditional and ICT-mediated leisure activities

Cited by 4 publications

References 34 publications

Analysis of the Relationship between Household Life Cycle and Tourism Expenditure in Taiwan: An Application of the Infrequency of Purchase Model

Analysis of the Relationship between Household Life Cycle and Tourism Expenditure in Taiwan: An Application of the Infrequency of Purchase Model

Attitudinal perspectives for predicting churn

Tourists’ virtual reality adoption: an exploratory study from Lake District National Park

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