A general theory of tourism consumption systems: a conceptual framework and an empirical exploration

A tourism consumption system (TCS) is defined as the setof related travel thoughts, decisions, and behaviors by a discretionarytraveler prior to, during, and following a trip. Thecentral proposition of a theory of TCS is that the thoughts,decisions, and behaviors regarding one activity influence thethoughts, decisions, and behaviors for a number of other activities.Using exit interview travel data and quick clusteringanalysis, this article empirically examines seven basic TCSpropositions pertaining to decisions made once the destinationhas been selected. The findings support and extend thebasic propositions specifically indicating clear patterns inthe behaviors of visitors to Prince Edward Island, Canada.The authors conclude by recommending that this approach isuseful for tourism marketers and practitioners in general.Suggestions are provided for analyzing TCS to increase theeffectiveness of tourism marketing strategies.

Culture and corporate voluntary reporting: a comparative exploration of the chairperson's report in India and New Zealand

Purpose – The purpose of this paper is to explore the cultural underpinnings of accounting practices through a comparative analysis of India and New Zealand, using the chairperson's report, which is increasingly becoming one of the most important segments of the corporate annual report.
Design/methodology/approach – The annual reports of Indian and New Zealand companies from 2001 to 2005 were selected to investigate the extent and nature of information disclosure in their chairperson's report. “Content analysis” is the main methodological orientation of the paper.
Findings – The paper argues that, contrary to propositions based on Hofstede's cultural framework, Indian companies provide more disclosure in their chairperson's report than their New Zealand counterparts. This leads to the conclusion that voluntary disclosure, more generally, is a complex phenomenon and cultural variables alone may not be sufficient predictors of the voluntary disclosure practices of a country.
Originality/value – Using India and New Zealand, two countries with significant cultural differences, according to Hofstede's typology, the paper extends the literature by focusing on the chairperson's report, a more recent accounting phenomenon which is gaining popularity across the globe.

Estimating the proportion of metabolic health outcomes attributable to obesity: a cross-sectional exploration of body mass index and waist circumference combinations

BACKGROUND: Recent evidence suggests that a substantial subgroup of the population who have a high-risk waist circumference (WC) do not have an obese body mass index (BMI). This study aimed to explore whether including those with a non-obese BMI but high risk WC as 'obese' improves prediction of adiposity-related metabolic outcomes.

METHODS: Eleven thousand, two hundred forty-seven participants were recruited. Height, weight and WC were measured. Ten thousand, six hundred fifty-nine participants with complete data were included. Adiposity categories were defined as: BMI(N)/WC(N), BMI(N)/WC(O), BMI(O)/WC(N), and BMI(O)/WC(O) (N = non-obese and O = obese). Population attributable fraction, area under the receiver operating characteristic curve (AUC), and odds ratios (OR) were calculated.

RESULTS: Participants were on average 48 years old and 50 % were men. The proportions of BMI(N)/WC(N), BMI(N)/WC(O), BMI(O)/WC(N) and BMI(O)/WC(O) were 68, 12, 2 and 18 %, respectively. A lower proportion of diabetes was attributable to obesity defined using BMI alone compared to BMI and WC combined (32 % vs 47 %). AUC for diabetes was also lower when obesity was defined using BMI alone (0.62 vs 0.66). Similar results were observed for all outcomes. The odds for hypertension, dyslipidaemia, diabetes and CVD were increased for those with BMI(N)/WC(O) (OR range 1.8-2.7) and BMI(O)/WC(O) (OR 1.9-4.9) compared to those with BMI(N)/WC(N).

CONCLUSIONS: Current population monitoring, assessing obesity by BMI only, misses a proportion of the population who are at increased health risk through excess adiposity. Improved identification of those at increased health risk needs to be considered for better prioritisation of policy and resources.