CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

Differences from Assessment 1
It is expected that you will be developing the work you undertook for Assessment 1, but that you will (1) respond to the formative feedback provided in your feedback for Assessment 1, and (2) add inferential statistics where appropriate.
CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

CA4051 Statistics For Travel & Tourism Assignment

Given that you are adding content to your existing report, the page limit has increased from 10 to 12 pages. Count research questions can only be answered with descriptive statistics because they do not have an independent variable, so you should not add inferential statistics to such questions.

NB: If you have only used count research questions in Assessment 1, then you need to add cross-sectional or correlational questions so to be able to include inferential statistics, as required for assessment 2.

Where you have used cross-sectional research questions, you need to add an inferential statistic. If your independent variable has 2 categories, you should use a t-test, but if it has 3 or more categories, you should use A NOVA.

NB: If you used dependent variables that were categorical variables, you are only able to report frequencies (i.e., counts, percentages) per category, but you cannot report Means. Thus, to compare means, you need to make sure that your dependent variables are continuous variables, so to run inferential statistics (i.e., t-test, ANOVA).

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

It was not expected that you pose correlational research questions in assessment 1 because these questions cannot be answered by descriptive statistics. As such, you would need to write a new correlational research question to include simple linear regression (e.g., the association between length of stay IV and spend DV).

Below I update the model answer for Assessment 1 by adding appropriate inferential statistics. The additions that I have made are highlighted in yellow. Except for count research questions, you should follow your descriptive statistics analysis with your inferential statistics analysis, as demonstrated below.

Report Structure

Your Insights report should follow the following structure:

Component Model Answer (A+)Introduction (20%, 1 page)
Client Description:
Who is your client and what are their needs?Choose a ‘real life’ industry client from your field (aviation or travel & tourism) and describe their business and current state. Identify challenges and problems that they currently face and which could be tackled by statistical research from which they could undertake data-driven decisions and strategies.

Tip: Research industry news stories to identify a client with a clear and real need.

Model Answer (A+):Lugano Tourist Board are responsible for the development of tourism to the Swiss city of Lugano in the Province of Ticino. This client is concerned that Lugano has an unwarranted image as a sleepy destination, which may lead to Lugano being unable to access a broad market of tourists (Lugano Tourist Board, 2020). Further to the destination image of Lugano, tourism to the city suffers from close proximity to Italy, specifically the destinations of Como and Milan, which have more to offer a younger tourist, particularly in terms of nightlife, and which are cheaper than Lugano (TripAdvisor, 2020).

Research is required to better understand the challenges of the Lugano Tourist Board and to inform strategies that can help the Lugano Tourist Board to overcome their challenges.

Research Questions: What are the questions you will answer via your Insights report? Pose three or four questions for which answers to can help your client overcome the challenges and problems they face. Your questions should be structured such that it is clear what research design and analysis you will be undertaking, whether that be looking for differences in a dependent variable between levels of an independent variable or whether that be looking for an association between an independent variable and a dependent variable.

1.What is the influence of destination choice (independent variable; Lugano, Como, or Milan) on age (dependent variable) of tourists (participants) to Southern Switzerland/Northern Italy (setting)?

2.What is the influence of age category (independent variable; 18-30, 31-50, 51-70, 71+) on importance of core destination choice motivations (dependent variable; relaxation, beauty, activities, cultural, social) for tourists (participants) to Southern Switzerland/Northern Italy (setting)?

3.What is the influence of destination (independent variable; Lugano, Como or Milan) on strength of attributes (dependent variable; relaxation, natural beauty, outdoor activities, cultural, social) for tourists (participants) to Southern Switzerland/Northern Italy (setting)?

Label the following components of your research questions:

  • Independent Variable
  • Dependent Variable
  • Participants or Units
  • Setting

Tip: Work backwards from the data in the database you are using so that your questions are viable (i.e., they can actually be answered).

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

Practical Importance:

How will your anticipated findings make a difference, and where? Establish the importance of seeking an answer to your research question from the perspective of your client. Detail how the insights that you provide will inform strategies that can overcome the client’s challenges and problems.

Tip: Think through what the challenge is and how it can be overcome with evidence-based decision making.

Answers to the above research questions will inform the positioning strategy of Lugano in relation to its primary competitors of Como and Milan, as follows:

The first research question will give insight into Lugano’s current market in terms of tourist age, relative to its competitors of Como and Milan, providing a starting point from which Lugano can consider its positioning strategy.The second research question will give insight into the relationship between age and motivations to choose a destination. In other words, what are the destination choice motivations of different market segments?

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

The third research question will give insight into motivations to choose Lugano and its competitors as a destination. In other words, from the perspective of tourists, what are the relative strengths of Lugano and its competitors?

Taken together, these insights can directly inform the positioning strategy of Lugano by identifying its destination attributes and the age groups that most value these attributes when making a destination choice. With this knowledge, Lugano can reposition itself to attract a new and viable market, communicating messages that support this new position via channels that most efficiently reach the new and viable market.

Data Collection:

How effectively does the sample in the database allow for inferences back to the populations of interest?

Describe your database in terms of size, underpinning data and quality (validity and reliability issues). Critically analyse the database’s sampling method and sample size relative to your population of interest.

Tip: Identify or estimate the size of your population of interest and calculate the minimal sample size based upon a 5% margin or error and 95% confidence interval, then conclude whether the sample size is big enough for generalization (Hint: It probably is, but you need to evidence this).

This report makes use of the Southern Switzerland/Northern Italy Tourism Database. This database contains responses to a survey conducted with 1,500 respondents who visited Southern Switzerland/Northern Italy destinations in 2016.The population of interest for this database is all tourists to Southern Switzerland/Northern Italy. The annual number of visitors to this region is 30 million. The ideal sample size for a population of 30 million when working with a 95% confidence level and 5% margin of error is 385. As such, even though 1,500 respondents is very small in relation to the large population of interest, it is sufficient.

For the research questions that use destination choice as the independent variable, the population of interest changes to only tourists to Lugano, Como and Milan. This reduces the sample size being used in the analysis to 600 and the size of the population of interest to 18 million. The ideal sample size for a population of 18 million when working with a 95% confidence level and 5% margin of error is again 385. As such, even though 600 respondents is very small in relation to the 18 million population of interest, it is also sufficient.

The database was constructed by using systematic random sampling, a means of probability sampling, whereby surveyers operated in randomly selected tourist destinations in the region and surveyed every fourth person that passed them. However, a limitation of this sampling method was that not all people approached were willing to complete the questionnaire, thus there is some non-response bias that limits the generalisability of the sample to the population of interest. However, this sampling method is the most robust available as a sampling frame does not exist, so simple random sampling is not possible, thus the limitation is accepted for this research.

Data Analysis:

How did you analyse your data and why? Re-state each research question and describe for each research question the

How did you analyse your data and why? Re-state each research question and describe for each research question the research design it represents (and why) and the statistical analysis undertaken, justifying its use with reference to the assigned readings and broader research methods and statistics literature (see reading list).

Tip: Different questions will require different analysis:
a.Questions about ‘how many’ and‘how much’ only require descriptive
statistics.
b. A1 and A2: Percentages,Counts,Means,Minimums,Maximums,Range.
c.Questions about ‘differences’ require statistical analysis that compare Mean averages.
d. A1: Compare Means and report percentage difference

What is the influence of destination choice (Lugano, Como or Milan) on age of tourists to Southern Switzerland/Northern Italy? This question represents a cross-sectional research design looking at the influence of a categorical variable (destination choice) on a discrete variable (age recorded to nearest year) with both variables recorded at a single point in time.

To answer this question, using statistical software, the ages of respondents who were visiting each of the destinations of interest (Lugano, Como, Milan) were summed separately for each destination choice and then divided by the number of respondents for each destination choice to return a Mean average of age by destination choice (Buglear, 2019). The statistical software also calculated the Standard Deviation for the Mean. Comparisons were made and percentage differences between Means were calculated. Furthermore, using statistical software, a one-way ANOVA test was run to determine whether any mean age differences between destinations were statistically significant or not. Where there was a significant difference, a Tukey post hoc test was used to determine which pairs of destinations differed significantly.

What is the influence of age category (18-30, 31-50, 51-70, 71+) on importance of core destination choice motivations (relaxation, natural beauty, outdoor activities, cultural, social) for tourists to Southern Switzerland/Northern Italy? This question represents a cross-sectional research design looking at the influence of a categorical variable (age group) on a discrete variable (Likert scale for importance of destination choice motivation) with both variables recorded at a single point in time.

To answer this question, using statistical software, the strength of each destination choice motivation (relaxation, beauty, activities, cultural, social) were summed separately for each age group (18-30, 31-50, 51-70, 71+) and divided by the number of respondents for each age category to return a Mean average of strength of each destination choice motivation by age group (Buglear, 2019). The statistical software also calculated the Standard Deviation for the Mean. Comparisons were made and percentage differences between Means were calculated. Furthermore, using statistical software, a one-way ANOVA test was run to determine whether any mean strength of motivation differences between age groups were statistically significant or not. Where there was a significant difference, a Tukey post hoc test was used to determine which pairs of age groups differed significantly.

What is the influence of destination (Lugano, Como or Milan) on strength of attributes relaxation, natural beauty, outdoor activities, cultural, social) for tourists to Southern Switzerland/Northern Italy? This question represents a cross-sectional research design looking at the influence of a categorical variable (destination choice) on a discrete variable (Likert scale for strength of destination choice motivation) with both variables recorded
at a single point in time.

To answer this question, using statistical software, the importance of each destination choice motivation (relaxation, beauty, activities, cultural, social) were summed separately for each destination choice (Lugano, Como, Milan) and divided by the number of respondents for each destination choice to return a Mean average of strength of each destination choice motivation by destination choice (Buglear, 2019). The statistical software also calculated the Standard Deviation for the Mean. Comparisons were made and percentage differences between Means were calculated. Furthermore, using statistical software, a one- way ANOVA test was run to determine whether any mean importance of attribute differences between destinations were statistically significant or not. Where there was a significant difference, a Tukey post hoc test was used to determine which pairs of destinations differed significantly.

Findings:

Re-state each research question and under each one provide the following:

Evidence: What are your findings? Undertake descriptive statistical analysis to answer your research questions, presenting your findings in tables and appropriate graphs.

Tip: Detail your technical interpretation of the statistical findings in objective terms. Objectively and efficiently present your data in terms of :

  • Descriptive statistics summarizing data too large to be ordinary observation, in terms of:
  • Central tendency(i.e.,location,typical value)
  • Dispersion (i.e.,variability).\
  • Valid interpretation of analysis in terms of differences.

Insight: What essential insight do your statistical findings provide about your client’s situation and challenges/problems?

Tip: Identification of knowledge that was previously unknown, but which is essential to provide a clearer and deeper understanding of your client’s challenges/problems. Frame your evidence in terms of your client’s situation and their challenges/problems and translate your objective and technical analysis into a meaningful business context.

Strategy: Based upon your insight, what strategies are you recommending that your client undertakes?

Tip: Based upon the new knowledge that provides a clearer and deeper understanding of the situation or problem, describe what should be done. Action the insight and detail the evidence- based decisions that should be taken.

What is the influence of destination choice (Lugano, Como or Milan) on age of tourists to Southern Switzerland/Northern Italy?

Evidence:

Figure 1: Bar chart of average tourist age by destination choice

The average age of tourists to Lugano is 68.7 years. The average age of tourists to Como is 53.2 years, which is 29% lower than that of Lugano. The average age of tourists to Milan is 47.9 years, which is 43% lower than that of Lugano. The relatively small standard deviation (6.7 years) for Lugano tells us that the age of Lugano tourists is concentrated around the Mean, whereas the higher standard deviations for Como (20.9 years) and Milan (18.7 years) tells us that the age of tourists to these destinations is considerably less concentrated around their Means.

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in age between participants grouped by destination. There were 125 visitors to Lugano, 230 visitors to Como and 245 visitors to Milan.

There was a statistically significant difference between destinations as determined by a one-way ANOVA (F(2,597) = 9.587, p= .000).A Tukey post hoc test revealed that age was statistically significantly higher for Lugano visitors (68.7 ± 6.8) compared to Como visitors (53.2 ± 20.9, p = .000) and Milan visitors (47.9 ± 18.7, p = .000). There was no statistically significant difference between Como and Milan visitors (p = .689).

Insight: The tourist market that Lugano is currently accessing is distinct from its competitors. On average, Lugano is accessing an older market than its competitors of Como and Milan. The average tourist to Lugano is retired (in Switzerland retirement age is 65 for men and 64 for female), but the average tourist to its competitors are below retirement by some margin.

Furthermore, the market accessed by Lugano is concentrated around 68.7 years, suggesting a very restricted market. In contrast, the markets accessed by Como and Milan are much less concentrated around the average age of their tourists, suggesting that they are accessing a broad market of tourists.

Strategy: Currently, Lugano is accessing a restricted market of older tourists. To increase tourism numbers and revenues, there is a need to diversify their market and appeal to a broader age group of tourists. Subsequent analysis will inform the specific strategies that can contribute to this overall objective.What is the influence of age category (18-30, 31-50, 51-70, 71+) on importance of core destination choice motivations (relaxation, natural beauty, outdoor activities, cultural, social) for tourists to Southern Switzerland/Northern Italy?

Evidence: Table 2: Average destination choice motivation by age group

Figure 2: Bar chart of average destination choice motivation
by age group

The importance of relaxation as a motivation increases as the age group gets higher; there appears to be a positive relationship between age and relaxing. For the youngest age group of 18-30 year olds, the average importance of relaxation (on a scale of 1-5, where 1 represents not at all importance and 5 represents of utmost importance) was 2.1. This increased by 81% to 3.8 for the next age group of 31-50 year olds. This increased by another 8% to 4.1 for the next age group of 51-70 year olds. This increased by another 2% to 4.2 for the oldest age group of 71 plus year olds.

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in the importance of relaxation as a motivation between participants grouped by age. There were 130 tourists aged 18-30, 233 tourists aged 31-50, 148 tourists aged 51-70 and 89 tourists aged 71+.

There was a statistically significant difference between age groups as determined by a one-way ANOVA (F(3,596) = 8.143, p= .000).

A Tukey post hoc test revealed that importance of relaxation as a motivation was statistically significantly lower for 18-30 0.4, p = .000), to 51-70 year olds (4.1 ± 0.3, p = .000) and 71+ year olds (4.2 ± 0.4, p = .000). There was no statistically significant difference between 31-50 and 51-70 year olds (p = .145), between 31-50 and 71+ year olds (p = .896) and between 51-70 and 71+ year olds (p = .786).

The importance of natural beauty as a motivation is not associated with age, whereby all age groups regard this as a highly important motivating factor in their choice of destination, with importance measured at 4.2, 4.3, 4.2 and 4.3 for the age groups of 18-30 year olds, 31-50 year olds, 51-70 year olds and 71 plus year olds respectively.

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in the importance of natural beauty as a motivation between participants grouped by age. There were 130 tourists aged 18-30, 233 tourists aged 31-50, 148 tourists aged 51-70 and 89 tourists aged 71+. 31-50, 148 tourists aged 51-70 and 89 tourists aged 71+. groups as determined by a one-way ANOVA (F(3,596) = 1.276, p= .786).

The importance of outdoor activities as a motivation decreases as the age group gets higher; there appears to be a negative relationship between age and outdoor activities. For the youngest age group of 18-30 year olds, the average importance of activities (on a scale of 1-5, where 1 represents not at all importance and 5 represents of utmost importance) was 4.3. This decreased by 12% to 3.8 for the next age group of 31-50 year olds. This decreased by another 26% to 2.8 for the next age group of 51-70 year olds. This decreased by another 11% to 2.2 for the oldest age group of 71 plus year olds.

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in the importance of outdoor age. There were 130 tourists aged 18-30, 233 tourists aged 31-50, 148 tourists aged 51-70 and 89 tourists aged 71+.There was a statistically significant difference between age groups as determined by a one-way ANOVA (F(3,596) = 6.743, p= .000).

A Tukey post hoc test revealed that importance of relaxation as a motivation was statistically significantly higher for 18-30 year olds (4.3 ± 0.4) compared to 31-50 year olds (3.8 ± 0.5, p = .000), which was statistically significantly higher compared to 51-70 year olds (2.8 ± 0.5, p = .000), which was statistically significantly higher compared to 71+ year olds (2.2 ± 0.4, p = .000).

The importance of culture as a motivation is not associated with age, whereby all age groups regard this as a highly important motivating factor in their choice of destination, with importance measured at 4.1, 4.2, 4.2 and 4.3 for the age groups of 18-30 year olds, 31-50 year olds, 51-70 year olds and 71 plus year olds respectively.

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in the importance of culture as a motivation between participants grouped by age. There were 130 tourists aged 18-30, 233 tourists aged 31-50, 148 tourists aged 51-70 and 89 tourists aged 71+.

There was no statistically significant difference between age groups as determined by a one-way ANOVA (F(3,596) = 1.586, p= .583).

The importance of social as a motivation (e.g. nightlife) decreases as the age group gets higher; there appears to be a negative relationship between age and socialising. For the youngest age group of 18-30 year olds, the average importance of socialising (on a scale of 1-5, where 1 represents not at all importance and 5 represents of utmost importance) was 4.4. This decreased by 16% to 3.7 for the next age group of 31-50 year olds. This decreased by another 24% to 2.8 for the next age group of 51-70 year olds. This decreased by another 25% to 2.1 for the oldest age group of 71 plus year olds.

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in the importance of social as a motivation between participants grouped by age. There were 130 tourists aged 18-30, 233 tourists aged 31-50, 148 tourists aged 51-70 and 89 tourists aged 71+.

There was a statistically significant difference between age groups as determined by a one-way ANOVA (F(3,596) = 8.753, p= .000). A Tukey post hoc test revealed that importance of social as a motivation was statistically significantly higher for 18-30 year olds (4.4 ± 0.33) compared to 31-50 year olds (3.7 ± 0.4, p = .000), which was statistically significantly higher compared to 51-70 year olds (2.8 ± 0.5, p = .000), which was statistically significantly higher compared to 71+ year olds (2.1 ± 0.4, p = .000).

Insight: For tourists to Southern Switzerland/Northern Italy, of the five types of motivations for tourism destination choice, two areas of motivation (beauty and culture) are high for all age groups, so do not provide an opportunity for targeted marketing. Of the three other types of motivations, the importance of relaxation increases with age, whereas the importance of outdoor activities and socialising decrease with age, providing opportunities for targeted marketing.

Strategy: To overcome the challenge of the restricted market of older tourists, established by answering the first research question, the Lugano Tourist Board need to diversify their market. The average age of Lugano tourists is at the top end of the 51-70 year old age group, but from the standard deviation we can conclude that their current market is also heavily populated by tourists from the top age group of 71 years and older. To diversify their market the Lugano Tourist Board should communicate the offerings of Lugano as a destination that would motivate a younger market to choose Lugano as a destination. The answer to this current research question has established that a destination seeking to diversify via a younger market can do so by meeting a younger audience’s desire for activities and socialising. That said, a destination should not market based upon desires it cannot effectively meet. As such, further research into the attributes of Lugano relative to its competition is required to inform how Lugano can most effectively position itself.

What is the influence of destination (Lugano, Como or outdoor activities, cultural, social) on strength of attributes relaxation, natural beauty, for tourists to Southern Switzerland/Northern Italy?

Evidence:

Table 3: Average tourism attribute by destination

Figure 3: Bar chart of average tourism attribute by destination

A strength of Lugano as a tourism destination is as a place to relax. On average, respondents strongly agreed (4.6 on a scale of 1-5, where 1 represents strongly disagree and 5 represents strongly agree) that Lugano is a destination for relaxation. This was equal to its competition of Como (4.6) and 59% stronger than Milan (2.9).

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in strength of relaxation as an attribute between destinations. There were 125 visitors to Lugano, 230 visitors to Como and 245 visitors to Milan.

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

There was a statistically significant difference between destinations as determined by a one-way ANOVA (F(2,597) = 4.537, p= .000).

A Tukey post hoc test revealed that the strength of relaxation as an attribute was statistically significantly lower for Milan (2.9 ± 0.7) compared to Lugano (4.6 ± 0.3, p = .000) and Como (4.6 ± 0.3, p = .000). There was no statistically significant difference between Lugano and Como (p = .769).

A further strength of Lugano as a tourism destination is as a place of natural beauty. On average, respondents strongly agreed (4.5 on a scale of 1-5, where 1 represents strongly disagree and 5 represents strongly agree) that Lugano is a destination of natural beauty. This was 2% weaker than its competition of Como (4.6), but 18% stronger than Milan (3.8).

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in strength of natural beauty as an attribute between destination. There were 125 visitors to Lugano, 230 visitors to Como and 245 visitors to Milan.

There was a statistically significant difference between destinations as determined by a one-way ANOVA (F(2,597) = 4.537, p= .000).

A Tukey post hoc test revealed that the strength of natural beauty as an attribute was statistically significantly lower for Milan (3.8 ± 0.4) compared to Lugano (4.5 ± 0.3, p = .000) and Como (4.6 ± 0.2, p = .000). There was no statistically significant difference between Lugano and Como (p = .564).

A further strength of Lugano as a tourism destination is as a place for outdoor activities. On average, respondents strongly agreed (4.5 on a scale of 1-5, where 1 represents Lugano is a destination for outdoor activities. This was 15% stronger than its competition of Como (4.6) and 41% stronger than Milan (3.2).

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in strength of outdoor activities as an attribute between destination. There were 125 visitors to Lugano, 230 visitors to Como and 245 visitors to Milan.
There was a statistically significant difference between destinations as determined by a one-way ANOVA (F(2,597) = 5.537, p= .000).

A Tukey post hoc test revealed that the strength of outdoor activities as an attribute was statistically significantly higher for Lugano (4.5 ± 0.4) compared to Como (3.9 ± 0.5, p = .005), which was significantly higher compared to Milan (3.2 ± 0.6, p = .012).

Relative to other attributes and its competition, culture is less of a strength for Lugano. On average, respondents felt neutral or agreed (3.5 on a scale of 1-5, where 1 represents strongly disagree and 5 represents strongly agree) that Lugano is a destination of culture. This was 10% weaker than its competition of Como (3.9) and 22% weaker than Milan (4.5).

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in strength of culture as an attribute between destination. There were 125 visitors to Lugano, 230 visitors to Como and 245 visitors to Milan.

There was a statistically significant difference between destinations as determined by a one-way ANOVA (F(2,597) = 4.537, p= .008).

A Tukey post hoc test revealed that the strength of culture as an attribute was statistically significantly higher for Milan (4.5 ± 0.2) compared to Como (3.9 ± 0.3, p = .012), which was significantly higher compared to Lugano (3.5 ± 0.4, p = .005).

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

Relative to other attributes and its competition, social opportunities is also less of a strength for Lugano. On average, respondents disagreed (1.9 on a scale of 1-5, where 1 represents strongly disagree and 5 represents strongly agree) that Lugano is a destination of socialising. This was 49% weaker than its competition of Como (3.7) and 69% weaker than Milan (4.6).

A one-way ANOVA was run on a convenience sample of 600 tourists to Lugano, Como and Milan to determine if there was a mean difference in strength of social as an attribute between destination. There were 125 visitors to Lugano, 230 visitors to Como and 245 visitors to Milan.There was a statistically significant difference between destinations as determined by a one-way ANOVA (F(2,597) = 9.543, p= .000).

A Tukey post hoc test revealed that the strength of social as an attribute was statistically significantly higher for Milan (4.6 ± 0.3) compared to Como (3.7 ± 0.4, p = .000), which was significantly higher compared to Lugano (1.9 ± 0.5, p = .000).

Insight: As a destination, Lugano excels as a destination for relaxation (4.6 out of 5), of natural beauty (4.5 out of 5) and for outdoor activities (4.5 out of 5).

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

Relative to desires by age category Lugano’s attribute as a destination for relaxation (4.6 out of 5) is meeting it’s current market’s desire (average age of 68.7) for this attribute (51-70s and 71s plus view this motivation as important, 4.1 and 4.2 out of 5). Lugano’s attribute as a destination of natural beauty (4.5 out of 5) is also meeting it’s current market’s desire for this attribute (51-70s and 71s plus view this motivation as important, 4.2 and 4.3 out of 5), but also meeting the desires of younger tourists (18-30s and 31-50s view this motivation as important, 4,2 and 4.3 out of 5). In terms of factors that are desirable for younger tourists, so to diversify its market, Lugano best meets younger tourists’ desire for outdoor activities (Lugano’s strength = 4.5; negative association with age, 18-30s on average regard as of utmost importance and 31-50s regard as important).

Relative to its competition of Como and Milan, Lugano excels as a destination for outdoor activities (15% stronger than Como and 41% stronger than Milan), but is equal to Como in terms of relaxation (Lugano 4.6 out of 5; Como 4.6 out of 5) and natural beauty (Lugano 4.5 out of 5; Como 4.6 out of 5).

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

Strategy: So to diversify its market by attracting younger tourists, the Lugano Tourist Board should primarily position Lugano as a destination for outdoor activities, an attribute that it excels in its own right and relative to competition and which is desirable for younger tourists. Secondarily, the Lugano Tourist Board should position itself as a destination of natural beauty, an attribute that it excels in its own right and relative to Milan and which is desired by all age groups. Together, the destination brand should convey that Lugano is a hotspot of outdoor activities in an area of outstanding natural beauty and messages that convey this should be communication via media channels, such as social media, which more effectively reach the new target market of younger tourists.

CA4051 Statistics For Travel & Tourism Assignment-London Metropolitan University UK.

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