The impact of Blue Flag status on tourist decision- making when selecting a beach

Abstract The Blue Flag programme holds many benefits when looking from a conservation point of view, such as preserving the natural environment. But what are the benefits when looking from a tourism perspective? In the literature it is stated that a beach's Blue Flag status has little to no impact on the decision making of visitors when selecting a beach at which to spend their holiday. The aim of this article is to determine the impact of Blue Flag status on visitors' decision-making when selecting a beach. Probability sampling was used with systematic sampling methods. A survey was conducted from between March and April, 2013 at six beaches across the Margate area. A total of 572 usable questionnaires were collected. The results showed whether or not a beach has Blue Flag status has little influence on the decision-making of beach visitors as little difference was found between the decision-making aspects of Blue Flag and non-Blue Flag beach visitors. It was noted that aspects of importance for decision-making for both groups of visitors form mostly part of the criteria set by the Blue Flag programme. This article makes three main contributions to the current literature; firstly, new information was identified regarding the role of the Blue Flag programme and what visitors are looking for when selecting a beach. Secondly, important aspects considered by visitors selecting a beach, such as cleanliness, landscape and popularity are identified. Lastly, this was the first time such research was conducted within a South African setting

The influence of Blue Flag status on tourist decision–making in South Africa

MCom (Tourism Management), North-West University, Potchefstroom Campus, 2014Marine tourism has been growing over the years to a diverse and large industry providing for a variety of markets. Across the world tourists enjoy activities of different types including kayaking, scuba diving, snorkelling, surfing and travelling to beaches for leisure reasons. Travelling to coastal towns with the purpose of visiting a beach has always been a great attraction for people across the world. Not only resulting in beaches becoming one of the tourism industry’s biggest markets but also a great contributor to local economies. In 200,1 South Africa adopted the Blue Flag Programme, a beach award which focuses on clean bathing water and pollution free environments. The programme was first established on the French coastline in Europe by the Foundation for Environmental Education (FEE). Since then 244 beaches and 208 marinas across 10 countries now boast with a Blue Flag award. The award requires beaches to adhere to four sets of criteria. These are water quality, environmental management, environmental education and information and safety and security. The programme also has specific periods allocated to beaches in which the beach has to meet all the stipulated standards. *Previous research has stated that the programme has great drawing power for tourists. *In contrast, other studies revealed that it has no benefits for the tourism industry, whatsoever. *Some studies have stated that it is a symbol of quality recognised by all across the world. The literature review conducted for this study revealed that the programme holds great benefits for conservation of the environment. Seen from a tourism point of view, however, it is still unclear whether the programme benefits the tourism industry or has any impact on it whatsoever. The primary goal of this dissertation is to determine the influence of Blue Flag status on the decision-making process of beach visitors when they select a beach, thereby determining whether or not the Blue Flag programme adds any value to the tourism industry. A literature review was conducted on important aspects concerning this study, namely the Blue Flag Programme, the tourist decision-making process, travel behaviour of tourists and tourist behaviour, to gain insight into the type of research. Thereafter an empirical study was conducted on six beaches in KwaZulu-Natal which involved the distribution of a self-administered questionnaire. The sampling method used for the study was quantitative, probability sampling with systematic sampling which involved the fieldworkers to approach every second person/group of people on the beach. The survey took place from 28 March to 4 April 2013. A total of 572 usable questionnaires was collected from a sample of 600 beach visitors. The data was captured using Microsoft™ Excel™ 2010 and analysed using Statistical Package for Social Sciences (SPSS version 21). Exploratory factor analyses were performed as well as a linear mixed-effect model analysis to analyse the impact of the Blue Flag Programme on tourism. To achieve the goal set for this study, two articles were produced. The aim of chapter 3 (article 1) was to determine the push and pull motives of beach visitors. The results revealed the profile of respondents to be female, married with an average age of 39 years and originating from Gauteng. They have a diploma or degree from a tertiary institute and like to visit the beach for an average of eight nights at a time. To identify the push and pull motives of beach visitors, the travel motives were first identified by means of a principal axis factoring analysis, with Oblimin and Kaiser Normalisation. The aspects yielded three factors, familiarity, family relaxation and escape and beach characteristics. The most important factor was determined to be familiarity. The analysis further revealed two push and two pull motives. The push factors are escape and relaxation (most important push motive) and familiarity. The pull motives are beach attributes (most important pull motive) and cognizance. This article showed that the familiarity of a beach plays an important role as to the motives of beach visitors as well as the fact that visitors to these beaches want to escape and relax away from everyday life. The aim of the chapter 4 (article 2) was to identify the influence of Blue Flag status on visitors’ decision-making when selecting a beach as well as to determine whether any statistically significant differences exist between the visitors to Blue Flag beaches and visitors to non-Blue Flag beaches. A principal axis factoring analysis was conducted to determine the decision-making aspects of beach visitors. This analysis yielded five actors, environmental education, safety and access, cleanliness, landscape and popularity. The most important factor was identified as cleanliness with a mean value of 4.37. Furthermore, a linear mixed-effect model analysis was conducted which identified one statistically significant difference with the factor popularity, which has a p-value of 0.002. No other differences were identified. This study thus found that Blue Flag status does not influence visitors’ decision in selecting a beach. What was interesting was the fact that the aspects which are of importance to beach visitors (such as cleanliness) form part of the criteria on which the programme is based (environmental education and information, environmental management, safety and security and water quality). Thus having Blue Flag status does impact positively on tourism. Since this was the first study of its kind in South Africa, it can benefit all beach destinations in the country. From the findings it is clear that marketing needs to be conducted regarding the Blue Flag programme and the benefits that could be reaped for both the local community and beach visitors. Furthermore, beach management can make use of the motives identified in chapter 3 as well as the decision-making aspects identified in chapter 4 to increase visitor numbers to the beach and gain competitive advantage. Tailor-made marketing strategies can be implemented which will improve the efforts of beach managers and municipalities as well as managers of the Blue Flag Programme to market the programme and raise awareness. Recommendations are made regarding further study on the Blue Flag programme to identify ways in which awareness of the programme amongst the public can be raised. Similar research can also be conducted on other environmental and tourism award systems, such as the Seaside award. This research contributes to the literature on marine tourism, seeing as this was the first time such a study was conducted in a South African setting.Master

Prospective observational cohort study on grading the severity of postoperative complications in global surgery research

Background The Clavien–Dindo classification is perhaps the most widely used approach for reporting postoperative complications in clinical trials. This system classifies complication severity by the treatment provided. However, it is unclear whether the Clavien–Dindo system can be used internationally in studies across differing healthcare systems in high- (HICs) and low- and middle-income countries (LMICs). Methods This was a secondary analysis of the International Surgical Outcomes Study (ISOS), a prospective observational cohort study of elective surgery in adults. Data collection occurred over a 7-day period. Severity of complications was graded using Clavien–Dindo and the simpler ISOS grading (mild, moderate or severe, based on guided investigator judgement). Severity grading was compared using the intraclass correlation coefficient (ICC). Data are presented as frequencies and ICC values (with 95 per cent c.i.). The analysis was stratified by income status of the country, comparing HICs with LMICs. Results A total of 44 814 patients were recruited from 474 hospitals in 27 countries (19 HICs and 8 LMICs). Some 7508 patients (16·8 per cent) experienced at least one postoperative complication, equivalent to 11 664 complications in total. Using the ISOS classification, 5504 of 11 664 complications (47·2 per cent) were graded as mild, 4244 (36·4 per cent) as moderate and 1916 (16·4 per cent) as severe. Using Clavien–Dindo, 6781 of 11 664 complications (58·1 per cent) were graded as I or II, 1740 (14·9 per cent) as III, 2408 (20·6 per cent) as IV and 735 (6·3 per cent) as V. Agreement between classification systems was poor overall (ICC 0·41, 95 per cent c.i. 0·20 to 0·55), and in LMICs (ICC 0·23, 0·05 to 0·38) and HICs (ICC 0·46, 0·25 to 0·59). Conclusion Caution is recommended when using a treatment approach to grade complications in global surgery studies, as this may introduce bias unintentionally

The surgical safety checklist and patient outcomes after surgery: a prospective observational cohort study, systematic review and meta-analysis

© 2017 British Journal of Anaesthesia Background: The surgical safety checklist is widely used to improve the quality of perioperative care. However, clinicians continue to debate the clinical effectiveness of this tool. Methods: Prospective analysis of data from the International Surgical Outcomes Study (ISOS), an international observational study of elective in-patient surgery, accompanied by a systematic review and meta-analysis of published literature. The exposure was surgical safety checklist use. The primary outcome was in-hospital mortality and the secondary outcome was postoperative complications. In the ISOS cohort, a multivariable multi-level generalized linear model was used to test associations. To further contextualise these findings, we included the results from the ISOS cohort in a meta-analysis. Results are reported as odds ratios (OR) with 95% confidence intervals. Results: We included 44 814 patients from 497 hospitals in 27 countries in the ISOS analysis. There were 40 245 (89.8%) patients exposed to the checklist, whilst 7508 (16.8%) sustained ≥1 postoperative complications and 207 (0.5%) died before hospital discharge. Checklist exposure was associated with reduced mortality [odds ratio (OR) 0.49 (0.32–0.77); P\u3c0.01], but no difference in complication rates [OR 1.02 (0.88–1.19); P=0.75]. In a systematic review, we screened 3732 records and identified 11 eligible studies of 453 292 patients including the ISOS cohort. Checklist exposure was associated with both reduced postoperative mortality [OR 0.75 (0.62–0.92); P\u3c0.01; I2=87%] and reduced complication rates [OR 0.73 (0.61–0.88); P\u3c0.01; I2=89%). Conclusions: Patients exposed to a surgical safety checklist experience better postoperative outcomes, but this could simply reflect wider quality of care in hospitals where checklist use is routine

Critical care admission following elective surgery was not associated with survival benefit:prospective analysis of data from 27 countries

Purpose: As global initiatives increase patient access to surgical treatments, there is a need to define optimal levels of perioperative care. Our aim was to describe the relationship between the provision and use of critical care resources and postoperative mortality. Methods: Planned analysis of data collected during an international 7-day cohort study of adults undergoing elective in-patient surgery. We used risk-adjusted mixed-effects logistic regression models to evaluate the association between admission to critical care immediately after surgery and in-hospital mortality. We evaluated hospital-level associations between mortality and critical care admission immediately after surgery, critical care admission to treat life-threatening complications, and hospital provision of critical care beds. We evaluated the effect of national income using interaction tests. Results: 44,814 patients from 474 hospitals in 27 countries were available for analysis. Death was more frequent amongst patients admitted directly to critical care after surgery (critical care: 103/4317 patients [2%], standard ward: 99/39,566 patients [0.3%]; adjusted OR 3.01 [2.10–5.21]; p < 0.001). This association may differ with national income (high income countries OR 2.50 vs. low and middle income countries OR 4.68; p = 0.07). At hospital level, there was no association between mortality and critical care admission directly after surgery (p = 0.26), critical care admission to treat complications (p = 0.33), or provision of critical care beds (p = 0.70). Findings of the hospital-level analyses were not affected by national income status. A sensitivity analysis including only high-risk patients yielded similar findings. Conclusions: We did not identify any survival benefit from critical care admission following surgery