The UK Travel Agency Industry

Business Analytics and Intelligence

Word Report

November

List of Tables

Table 1: Percentage Daily Internet Usage Rates and Users Shopping Online in the UK

Table 2: Profit Margin Summary Statistics

Table 3: Turnover Summary Statistics

Table 4: Current Ratio Summary Statistics

Table 5: Return on Assets Summary Statistics

Table 6: Return on Capital Employed Summary Statistics

Table 7: Correlation Results

Table 8: Regression Results

Table of Contents

List of Tables 2

Table of Contents 3

List of Figures 4

Introduction 5

Background of the UK Travel Agency Industry 6

Visualization of the Whole Industry 6

Business Analytics and its Role in Decision-Making 9

Descriptive Analytics 9

Predictive Analytics 12

Conclusion 14

List of Figures

Figure 1: Number of Businesses in the UK Travel Agency Industry

Figure 2: Revenue Trends in the UK Travel Agency Industry

Introduction

This report analyses the travel agency industry in the UK using descriptive and predictive analytics to predict future prospects. Data from Statista shows that there were 4,640 travel agencies in the UK as at September 2022 (Statista, 2022). This analysis covers 10 of these agencies, and uses six variables to guide predictions.

Background of the UK Travel Agency Industry

Travel agencies engage in selling tourism and travel products and services on behalf of cruise lines, airlines, accommodation companies, and other travel suppliers (Statista, 2022b). Travel agencies are categorized based on the number of retail outlets they run. Independents and miniples are travel agencies with few branches that mostly operate in a certain niche market, region or town, while multiples operate a large number of outlets in multiple towns (Statista, 2022b).

Visualization of the Whole Industry

As figure 1 shows, the number of businesses in the UK travel industry grew by 20 percent between 2012 and 2021 (Statista, 2022). In terms of revenues, the industry grew by 13.3 percent between 2012 and 2019, with annual revenues ranging between 21.9 billion and 32.5 billion GBP (Statista, 2022b). Industry revenues fell to 7.6 billion in 2020 and have remained below pre-pandemic levels (Statista, 2022).

Figure 1: Number of Businesses in the UK Travel Agency Industry

Figure 2: Revenue Trends in the UK Travel Agency Industry

(Figure 1: Industry Revenues in the UK Travel Agency Industry 2008 to 2020 (Statista, 2022))

Recent trends, however, point to a growth in revenues (IBIS Report, 2022). The projected growth is attributable to the growth in online travel agencies, which increased by over 700 businesses in 2021 (Statista, 2022). Revenues from online travel agencies are expected to grow significantly with the increase in the number of customers who prefer to shop online as shown in table 1 below:

Table 1: Percentage Daily Internet Usage Rates and Users Shopping Online in the UK

Daily Internet Users (%)

Users Shopping online (%)

Source: ONS, 2019, n.pag.

Business Analytics and its Role in Decision-Making

Business analytics is the process of visualizing and extracting useful insights from data to inform business decision-making (Camm et al., 2020). Descriptive analytics involves using historical data to obtain insights on past trends (Camm et al., 2020). Predictive analytics is the use of past data to create models that can then be used to predict future performance (Camm et al., 2020). Finally, prescriptive analytics is the course of action that follows predictive analytics. Since business analytics is based on data, it provides a more accurate way to quantify risk, weigh decision alternatives, and make forecasts for planning (Camm et al., 2020).

Descriptive Analytics

Table 2: Profit Margin Summary Statistics

Profit Margin 2019

Profit Margin 2021

Mean

Mean

Standard Error

Standard Error

Median

Median

Mode

#N/A

Mode

#N/A

Standard Deviation

Standard Deviation

Sample Variance

Sample Variance

Kurtosis

Kurtosis

Skewness

Skewness

Range

Range

Minimum

Minimum

Maximum

Maximum

Sum

Sum

Count

Count

Profit Margin 2019

Profit Margin 2021

Table 3: Turnover Summary Statistics

Turnover 2019

Turnover 2021

Mean

Mean

Standard Error

Standard Error

Median

Median

Mode

#N/A

Mode

#N/A

Standard Deviation

Standard Deviation

Sample Variance

Sample Variance

Kurtosis

Kurtosis

Skewness

Skewness

Range

Range

Minimum

Minimum

Maximum

Maximum

Sum

Sum

Count

Count

Table 4: Current Ratio Summary Statistics

Current Ratio 2019

Current Ratio 2021

Mean

Mean

Standard Error

Standard Error

Median

Median

Mode

#N/A

Mode

#N/A

Standard Deviation

Standard Deviation

Sample Variance

Sample Variance

Kurtosis

Kurtosis

Skewness

Skewness

Range

Range

Minimum

Minimum

Maximum

Maximum

Sum

Sum

Count

Count

Table 5: Return on Assets Summary Statistics

Return on Assets ROA 2019

Return on Assets ROA 2021

Mean

Mean

Standard Error

Standard Error

Median

Median

Mode

Mode

#N/A

Standard Deviation

Standard Deviation

Sample Variance

Sample Variance

Kurtosis

Kurtosis

Skewness

Skewness

Range

Range

Minimum

Minimum

Maximum

Maximum

Sum

Sum

Count

Count

Table 6: Return on Capital Employed Summary Statistics

Return on Capital Employed ROCE 2019

Return on Capital Employed ROCE 2021

Mean

Mean

Standard Error

Standard Error

Median

Median

Mode

#N/A

Mode

#N/A

Standard Deviation

Standard Deviation

Sample Variance

Sample Variance

Kurtosis

Kurtosis

Skewness

Skewness

Range

Range

Minimum

Minimum

Maximum

Maximum

Sum

Sum

Count

Count

The profit margin provides a measure of overall industry profitability, while the turnover measures the industry’s total sales revenues. The current ratio is an indicator of liquidity or companies’ ability to settle short-term goals and would be beneficial in measuring how well the industry is recovering from the effects of the pandemic. Finally, both ROCE and ROA are measures of efficiency in the industry.

All five variables yield a low standard deviation relative to the mean, pointing to a relatively normal distribution (Camm et al., 2020). Only the profit margin and ROA yield negative skewness values, while the rest of the variables all yield a positive value for skewness. The positive skewness implies that the industry is still attractive to investors as it is still likely to give rise to large gains. All variables except profit margin have positive kurtosis, indicating that the distribution is peaked and thick-tailed and the level of risk is relatively low.

Predictive Analytics

Correlation Analysis

Table 7: Correlation Results

Profit Margin 2021

Turnover 2021

Current Ratio

ROA

ROCE

Profit Margin 2021

Turnover 2021

Current Ratio

ROA

ROCE

Correlation results show a association between profit margin (the independent variable) and turnover, current ratio, ROA, and ROCE. The associations between profit margin and turnover (r = 0.224, p = 0.2, 2 tailed), current ratio (r = 0.191, p = 0.2, 2 tailed), and ROA (r = 0.574, p = 0.1, 2 tailed) are all weak at the P=0.05 significance level, making ROCE the only variable that significantly influences profit margin in the travel agency industry (r = 0.659, p = 0.05, 2 tailed.

Regression Results

Table 8: Regression Results

Table 8 above presents the results of the regression between profit margin, turnover, current ratio, ROA, and ROCE. The resultant regression equation is y (profit margin) = 0.89*Turnover + 0.65*Current Ratio + 0.68*ROA + 31.1*ROCE). However, none of the variables gives a p-value equal to or less than 0.05, implying that the relationship between the variables is weak. The intercept value of 42.87 shows that if all the variables ae equal to 0, the industry profit margin will be equal to 42.87. This would be due to the effect of other variables not included in the model. The R square value of 0.47 implies that only 47 percent of changes in profit margin are due to the four variables, while 33 percent are attributable to factors not included in the model (Chicco, 2021). Possible factors that would influence profitability could include the number of employees, the employees’ skill level, use of technology, and changing customer preferences, such as the growing popularity of online shopping over in-store shopping (Dimitric, 2019).