BUSINESS RESEARCH ANALYSIS

Running head: BUSINESS RESEARCH1

Business Research

Name

Institution

Date

BUSINESS RESEARCH2

Table of ContentsIntroduction.........................................................5

Part I...............................................................5

1.1. Questionnaire Development......................................5

1.2. Questionnaire Distribution Methods.............................5

1.3. Questionnaire Critical Evaluation..............................6

Part II..............................................................8

2.1. Data Analysis, Findings and Managerial Implications............8

(i) Holidays.......................................................8

(ii) Children....................................................14

(iii).......................................................Ratings15

(iv) Satisfaction................................................18

(v) Regression Model............................................21

Conclusion..........................................................23

List of References..................................................25

Appendices..........................................................27

Appendix 1: Questionnaire Introduction..............................27

Appendix 2: Questions for the questionnaire........................28

Appendix 3: Coding Plan for the Questionnaire......................31

Appendix 4: Variable List..........................................33

Appendix 5: Tables.................................................34

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List of Figures

Figure 2: Number of holidays taken last year..................10

Figure 3: Destination for the holiday.........................11

Figure 4: No. of previous holidays with the company...........12

Figure 5: Satisfaction levels.................................19

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List of Tables

Table 1: Holidays taken last year.............................10

Table 2: Destination of holiday...............................10

Table 3: No. of previous holidays taken with the company......12

Table 4: Measures of association between destination and whether or not respondents travelled with children....................14

Table 5: T-tests for equality of means........................16

Table 6: Association between destination and accommodation rating..............................................................16

Table 7: Association between destination and travel rating. . . .17

Table 8: Overall satisfaction.................................18

Table 9: Satisfaction-number of children correlation..........20

Table 10: Regression Table A..................................22

Table 11: Regression Table B..................................22

Table 12: Association between destination and accommodation rating, travel rating and resort rating.......................35

Table 14: Cross tabs for grouped satisfaction and whether one hadchildren or not...............................................36

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Introduction

The travel and hospitality industry is one of the fastest growing

industries in the world. The growth is enhanced, in present days, by

modern forms of information and communications technology such as the

internet. Through internet, it has become possible for tour companies

to easily connect with their clients. However, there is a need to

explore the level of satisfaction of clients. The purpose of this

research is to establish clients’ opinions towards the packages

offered by the travel and hospitality company. The other purpose of

the survey is to get suggestions from both individual and corporate

clients on how the services of the company could be improved. In order

to accomplish this, the research process is divided into two parts.

The first part deals with questionnaire development, distribution

methods and critical evaluation. In the second part, the findings are

presented and data analyzed. The analysis also addresses the

implications of the findings in management practice.

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Part I

1.1. Questionnaire Development

See Appendix 1.

1.2. Questionnaire Distribution Methods

Distribution of questionnaires is a critical stage in research.

According to Armstrong and Fildes (2006), questionnaire distribution

depends on the sampling method that is used. In modern times, there

has been improved efficiency in the way documents are delivered. Berg

(2009) applauds the role of information and communications technology

in research. However, this must be catered for in the research design

or methodology. Nevertheless, the rapid development and use of

internet has helped the process of research. In this case, email will

be a major distribution method of the questionnaires. They will be

sent as word documents such that the client fills with ease. Creswell

(2008) and Patton (2002) observe that PDF files discourage respondents

from participation because they have to print, fill by hand, scan and

send again. The traditional mailing systems are also being phased out.

As earlier noted technology does not mar the research process but

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rather enhances it. This implies that before questionnaires are

distributed, consent is sought from the potential respondent. Seeking

consent will be done either through email or cell phone. This is what

Franklin (2012) calls “online consent.” The company has a huge

database of clients.

Although technology assists in making work easier, it cannot be

ignored that hard copies are also important. There will also be

physical distribution of questionnaires at the company’s physical

office. Target respondents are the ones defined in the sampling

methods and procedures. These include return clients who come to the

offices of the company; as well as clients who came in the past but

are followed up for survey purposes. These two approaches are expected

to optimize the entire process in a bid to inform the management about

policy areas to improve.

1.3. Questionnaire Critical Evaluation

Questionnaires are very important in any research. This is

because the measure aspects being studied (Armstrong & Soelberg,

1968). This is done through questions that are designed in a way that

actually measures what is supposed to be measured. According to Kara

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(2012), this is called validity. The firs aspect in evaluating this

questionnaire is looking at the construct of validity. According to

Silverman (2011), validity has to do with whether a tool, such as a

questionnaire, measures what it is supposed to measure. The

development of this questionnaire was based on a wide range of

principles; hence the belief that it is a valid instrument. There are

several examples that can illustrate this fact. For instance, one of

the key objectives of the study was to measure client’s opinions

towards the services and packages offered by the company. In order to

achieve this, this question was asked, “How can you rate our

packages?” The responses that are provided as based in principles of

ordinal measurement. According to Eisner (1981), ordinal measures have

direction. This means that they can be ranked. However, they cannot be

quantified. For instance, very bad, bad, moderate, goo and very good

follow each other in terms of directionality. If a client, for

example, say that the packages are very good; it implies that the

company did well in serving him or her.

The questionnaire used in this study has three sections. These

include demographic information, travel information and information

regarding the services and packages of the company. Demographic

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information is very essential because it offers an opportunity for the

company to explore and profile the characteristics of its customers.

This is important for several reasons. The first one is that a company

is able to define its target market. For instance, if more young

people are traveling with the company, then the implication for

management is to diversify products and services in that regard. In

addition, studies could be carried out to establish why other age

groups are not as interested in the services of the company as others.

The question on nationality can be used to measure the

representativeness of the sample. According to Lesage (2009), samples

that do not cover wide geographical areas are likely to be biased. In

the words of Herrman (2009), results obtained from such a sample

cannot be generalized for the entire population. Hence some test

statistics such as Chi Square are used. Therefore, the first part is

very essential in capturing the characteristics of the participants as

well as the sample.

Travel information helps a company to analyze the behavior of

consumers in a market (Armstrong & Fildes, 2006; Joubish, 2009).

This is done by exploring the trends in purchase patterns and decision

making. For instance, question six that seeks to ask whether one

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travelled alone or in a group is useful in measuring consumer

behavior. For instance, if data is collected for a long time, it is

possible to realize patterns such as shift from individual to group

tours. This kind of knowledge is importance in the development of

other aspects of a package. Another indicator of the need to develop

other products is the increase of, for instance, corporate travels as

opposed to personal tours. This questionnaire appears to have covered

very thematic areas in market research; yet in a simple outline and

content. Furthermore, the questionnaire is very easy to understand. It

is not complicated nor is it long. In about 10 minutes, any person

would have completed it. Moreover, the researcher indicated that it

could be filled in 15 minutes as a way of taking into consideration

those that a slow.

The questionnaire has several strengths. First, the questions in

section B are able to give a rough idea on return customers. The

question seeks to enquire how many times the client ever traveled with

the company. The smaller the number, the more customers do not return.

Thus the questionnaire has succeeded in helping the analyst formulate

a hypothesis about the services of the company. If most clients report

that they have travelled with the company for more than five times, it

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is expected that their response to the question on how to rate the

company would be “very good.” By asking questions about children,

spouses, the number of days spent of travel and the like, the

questionnaire is able to assess changes in preferences of consumers

over time and across space (Alana, Slater & Bucknam, 2011). However,

the questionnaire may not fully get the differential in destination

areas. The category “outside Europe” is too general to cover all the

areas that people from North East England visit. For instance, it is

expected that British visits to the East such as China and Japan are

fewer than those to America and those to Africa (Creswell, 2008). The

questionnaire could have included these other categories as

independent categories without mixing them under a broad category.

Part II

2.1. Data Analysis, Findings and Managerial Implications

(i)Holidays

Number of holidays taken in the last year:

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Tests are carried out to test hypotheses for holidays taken in

the last year. The research hypothesis is that most people went for 2

holidays. The table below shows results for one sample t-test. From

the table, the mean number of holidays taken last year is 2.07. The

second table shows that this difference is not statistically

significant (sig 0.359). The significance level is 0.05. The null

hypothesis is that most people did not take 2 holidays in the last

year. Since 0.359>0.05, reject the null hypothesis.

One-Sample StatisticsN Mean Std.

DeviationStd. Error

MeanHolidays last year

155 2.07 .961 .077

One-Sample TestTest Value = 2 Decision

t df Sig. (2-tailed)

MeanDifference

95% ConfidenceInterval of the

Difference

Reject thenull

hypothesisLower Upper

Holidays last year

.919

154 .359 .071 -.08 .22

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The number of holidays taken last year ranged from 1 to 5. Most

respondents had traveled only once; that is 53 out of 155. This

represented a 34.2% of all respondents. There were also considerable

numbers of those respondents who traveled twice and thrice. The

percentages were 31.0% and 30.3% respectively. Hardly had any

respondents travelled 5 times. As far as management is concerned, it

implies that more efforts should be directed towards marketing.

Moreover, there are other reasons as to why people do not travel a

lot. These may include the cost of travel and busy schedules. If this

is the case, the management could carry out campaigns on the need to

holiday. For instance, health benefits could be used as a reason for

travel. These results are also shown in the graph.

Table 1: Holidays taken last year

Holidays last yearFrequen

cyPercent

ValidPercent

CumulativePercent

Valid

1 53 34.2 34.2 34.22 48 31.0 31.0 65.23 47 30.3 30.3 95.54 4 2.6 2.6 98.15 3 1.9 1.9 100.0Total 155 100.0 100.0

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Figure 1: Number of holidays taken last year

Holiday destination:

The summary statistics for holiday destination are presented

below.

Table 2: Destination of holiday

Holiday destinationFrequen

cyPercent

ValidPercent

CumulativePercent

Valid

UK 62 40.0 40.0 40.0Within Europe 30 19.4 19.4 59.4

Outside Europe 63 40.6 40.6 100.0

Total 155 100.0 100.0

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From the above frequency distribution table, it is clear

that fewer respondents traveled within Europe. Most of them, 63%

traveled outside Europe. Contrastingly, while few people travel

within Europe, a huge percentage of 62% travel within UK. This

implies that the UK is a preferred destination as opposed to

other European countries. For management purposes, there is a

need to increase marketing efforts in other European countries;

this includes strengthening the existing strategies for the UK.

Notably, there is no significant difference between respondents

who traveled outside Europe and those who traveled within UK.

This could pose an issue of consumer behavior to the management.

The underlying question is “why should British from North Eastern

prefer to go to other countries and the UK but not other European

countries?” That area requires additional research. This is also

represented in the graph below.

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Figure 2: Destination for the holiday

Number of previous holidays taken with the company:

The results show that most respondents have taken 4 to 6

previous trips with the company. Since the first set of analysis

on the number of holidays in the last year showed that most

respondents had had one visit, it implies that the 4 to 6

holidays may be spread in the past 4 to 6 years. This is

unhealthy trend as far as business is concerned. There is a need

for marketing managers to make clients travel more with the

company. It is also important to point out that the distribution

of the number of previous did not form a perfect normal curve. As

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shown in the corresponding graph below the table, those who

previously travelled with the company 5 times were unexpectedly

low. In order to deal with these fluctuations it the number of

return customers, the company should reconsider its incentives.

Table 3: No. of previous holidays taken with the company

Previous holidays with companyFrequen

cyPercent

ValidPercent

CumulativePercent

Valid

1 19 12.3 12.3 12.32 17 11.0 11.0 23.23 24 15.5 15.5 38.74 32 20.6 20.6 59.45 17 11.0 11.0 70.36 32 20.6 20.6 91.07 14 9.0 9.0 100.0Total 155 100.0 100.0

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Figure 3: No. of previous holidays with the company

There is also a need to test whether the number of previous holidays taken with the company differs significantly across gender divide. An independent t-test is carried out and the results presented thus:

Group StatisticsGender

N Mean Std.Deviation

Std. ErrorMean

Decision:Rejectnull

hypothesisPrevious holidays with company

Female

79 4.11 1.941 .218

Male 76 3.99 1.785 .205

Independent Samples TestLevene's Test for

Equality ofVariances

t-test for Equality of Means

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F Sig. t df Sig.(2-tailed)

MeanDifferen

ce

Std.ErrorDifference

95%ConfidenceInterval of

theDifferenceLower Upper

Previous holidays with company

Equal variances assumed

1.592 .209.424

153 .672 .127 .300 -.465 .720

Equal variances not assumed

.424

152.692

.672 .127 .299 -.464 .719

The null hypothesis is that there is no difference between group means. The test shown in the first table (sig 0,05) shows that there is a difference. Mean for males is 3.99 while for females is 4.11. It means that more females than males have travelled with the company. For management, it implies that more products are developed for women.

(ii) ChildrenRecoding into different variable, those who traveled without

children are assigned “0” and those who had children are assigned “1”.

The null hypothesis is that there is no difference between those who

travelled with children and those who did. The Chi square value is

0.166 with 2 degrees of freedom (p=0.921). Significance level used was

0.05. Since p>0.05, the null hypothesis is rejected.

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Table 4: Measures of association between destination and whether or not respondents travelled with children

Chi-Square TestsValue df Asymp. Sig. (2-sided)

Pearson Chi-Square .166a 2 .920Likelihood Ratio .166 2 .921Linear-by-Linear Association .156 1 .693N of Valid Cases 155a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 6.19.

The measures show that the null hypothesis is rejected. As

can be seen in the table in Appendix 6, 20.6% of respondents

travelled without children while 79.4% traveled with children. In

other words, more travelers travel with children. This has some

managerial implications. It implies that among other things, the

company should avail services that are in tandem with children.

This would greatly attract parents to travel with the company as

opposed to those companies that do not provide complimentary

services. This is also shown in the graph below.

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Among those who traveled with children, 40.7% went traveled

within UK, 19.5% within Europe and 39.8% outside Europe. As can be

seen, there is not much difference between “within UK” and “outside

Europe.” This has far reaching implications for management. It implies

that travel to other European countries should not be promoted as much

because it does not make much business sense. It appears that there is

some consumer behavior that is not needs to be addressed before

investing more in non-UK European market. Among those who traveled

with children, 37.5% went to UK, 18.8% within Europe and 43.8%

traveled outside Europe. The latter could imply that the cost involved

in traveling with children may have deterred those who did not travel

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with them outside Europe to not to travel with them. The company could

consider giving more incentives in line with complementary services

for family travel.

(iii) RatingsThe null hypothesis is that accommodation rating is not below 50%

which means more than 5. From the second table, the results are significant (sig level at 0.05). A t-test is carried out and results presented below. Since all means are >5, accept null hypothesis.

Table 5: T-tests for equality of means

One-Sample StatisticsN Mean Std.

DeviationStd. Error

MeanDecision

Accomm rating

155 6.03 2.118 .170Accept null hypothesis

Resortrating


Travel rating


ANOVASum ofSquares

df Mean Square F Sig.

Resortrating

Between Groups 8.415 2 4.208 .990 .374Within Groups 645.933 152 4.250

Total 654.348 154

Accomm ratingBetween Groups 18.542 2 9.271 2.096 .126Within Groups 672.297 152 4.423Total 690.839 154

Travel rating Between Groups 172.382 2 86.191 16.774 .000

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Within Groups 781.011 152 5.138

Total 953.394 154

The above table shows that it is only travel rating mean which differs significantly from destination. F value is 16.774 and p=0.000 (significance level is 0.05). The results show that the means for destination and the other variables (accommodation rating and resort rating) do not differ significant because p>0.05. The posthoc tests are shown in the appendix.

Null Hypothesis Test Significance

Decision

Destination mean=Resort rating mean

F-Test

.374 Reject null hypothesis

Destination mean=Accommodation rating mean

F-Test

.126 Reject null hypothesis

Destination mean=Travel rating mean

F-Test

.000 Accept null hypothesis

Table 6: Association between destination and accommodation rating

Directional MeasuresValue

Nominal by Interval

Eta

Holiday destination Dependent

.181

Accomm rating Dependent

.164

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There is a weak positive association between the

accommodation rating and destination. This is because Eta was

0.181 for destination and 0.164 for accommodation rating.

Although the relationship is weak, it is significant. It was

established that Spearman’s correlation significance was at 0.758

based on normal approximation. Generally, accommodation ratings

in Europe are less that in the other two destinations. The

ratings for UK appear to be the best followed by “outside

Europe.” On a general sense, accommodation rating could be

averaged at 5 and 6. These results are shown in appendix 6.

The relationship between travel rating and destination is

also weak. Moreover, it is in a positive direction; and stronger

than that of accommodation. This is because the value of Eta is

0.459 for destination and 0.425 for travel rating. It is also

significant because Spearman correlation is at 0.0000. Most

ratings are between 4 and 6. In UK, travel did not receive any

“negative” rating until at option or level 4 of answers. Rating

within Europe begins at score 3 and peaks at 5 while the

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respective scores for “outside Europe” were 0 and 5 respectively.

Appendix 6 and the table below show this fact.

Table 7: Association between destination and travel rating

Directional MeasuresValue

Nominal by Interval

Eta


.459

Travel rating Dependent

.425

The table below shows summary statistics for the association

between destination and resort rating. The association is weaker

than that of travel but stronger than that of accommodation. Eta

is 0.263 for destination and 0.113 for resort rating. Resort

rating in the UK is the highest followed by outside Europe than

within Europe. Overall, compared to accommodation and travel,

resorts were higher rated. For management, this has an

implication; that travelers mind a lot about where they will

spend their nights.

Directional Measures

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Value

Nominal by Interval

Eta


.263

Resortrating Dependent

.113

(iv) SatisfactionSatisfaction levels were out of 100. In this case, they were

grouped into 6 classes whose interval was 10. If least satisfaction is

considered to be below 50%, then 25.2% of respondents were least

satisfied. Moderate satisfaction is considered between 50% and 70%.

This implies that 45.8% of respondents were moderately satisfied. If

excellent satisfaction is that which is above 80%, the 21% of the

participants were excellently satisfied. This means that the

satisfaction distribution is normal. In terms of assigned 10-interval

groups, it implies that most people reported satisfaction levels of

between 50% and 59%: they formed the leading percentage of 25.8%.

Further information is illustrated in the corresponding graph below.

Table 8: Overall satisfaction

Grouped SatisfactionFrequen

cyPercent

ValidPercent

CumulativePercent

Valid

30-39

10 6.5 6.5 6.5

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40-49 29 18.7 18.7 25.2

50-59 40 25.8 25.8 51.0

60-69 31 20.0 20.0 71.0

70-79 34 21.9 21.9 92.9

80-89 11 7.1 7.1 100.0

Total 155 100.0 100.0

Figure 4: Satisfaction levels

The table below summarizes the association between overall

satisfaction and whether or not travelers were with children:

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Symmetric MeasuresValue Approx.

Sig.

Nominal by Nominal

Phi .151 .617Cramer's V .151 .617

N of Valid Cases 155a. Not assuming the null hypothesis.b. Using the asymptotic standard error assuming the null hypothesis.

From the table, it can clearly be seen that there is a

strong positive relationship between the two variables. The

significance level is set at 0.05. This means that although the

results obtained showed strong association, they were not

significant. This is because the value of Phi is 0.151. Details

of the variation of satisfaction with children are illustrated in

the table (appendix 6).As the table shows, the level of

satisfaction when the respondents had children was higher than

those who did not have children. For instance, for category 30-

39, those who were satisfied without children and with children

were 3.1% and 7.3%. For 50-59, the percentages of respondents

were 28.1% and 25.2%; while for 80-89, the percentages of

respondents were 6.2% and 7.3%. In other words, children add

satisfaction to the trip. For management, this implies that

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complementary services must be increased. There should also be

deliberate campaigns to encourage clients to travel with children

as they would be more satisfied. However, as shown in the table

below, correlations reveal negative relationship between

satisfaction and “number” (not whether or not) of children. This

is because Pearson’s correlation co-efficient is -0.052.

Table 9: Satisfaction-number of children correlation

CorrelationsChildrennumber

Satisfaction

Children number

Pearson Correlation 1 -.052

Sig. (2-tailed) .519

N 155 155

Satisfaction

Pearson Correlation -.052 1

Sig. (2-tailed) .519

N 155 155

The relationship between satisfaction and whether or not thegroup had children can also be tested by independent sample t-test. The table below shows results of the independent t-test. Since standard deviations for the two groups are the same, 13.1 and 13.2, equal variances are assumed and corresponding test used.

Group StatisticsWith or without children

N Mean Std.Deviation

Std. ErrorMean

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Satisfaction

Without children 32 60.91 13.175 2.329With children 123 59.43 13.323 1.201

The results below show that there was no statistically significantly different means for those who had and had no children (60.91 and 59.43; without children and with children respectively). This is because t=0.781 with 153 degrees of freedom and p=.577.

Independent Samples TestLevene'sTest for

Equality ofVariances

t-test for Equality of Means

F Sig. t df Sig.(2-tailed)

MeanDifferen

ce

Std.Error

Difference

95% ConfidenceInterval of

the DifferenceLower Upper

Satisfaction

Equal variancesassumed

.078 .781 .559 153 .577 1.475 2.638 -3.736 6.687

Equal variancesnot assumed

.563

48.813 .576 1.475 2.621 -3.791 6.742

The table below shows analysis of variance between overall

satisfactions rating and destination chosen. The null hypothesis

is that there is no difference between the two means. However,

according to the table, there was a statistically significant

difference between the means (F=7.832 and p=0.001).

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ANOVASatisfaction

Sum ofSquares

df Mean Square F Sig.

Between Groups 2531.134 2 1265.567 7.832 .001Within Groups 24561.021 152 161.586Total 27092.155 154

(v)Regression ModelThere are associations between overall satisfaction and each as

well as all ratings: resort, accommodation and travel. This is

illustrated in the tables below:

CorrelationsSatisfac

tionTravelrating

Satisfaction

Pearson Correlation 1 .427**

Sig. (2-tailed) .000N 155 155

Travel rating

Pearson Correlation .427** 1

Sig. (2-tailed) .000N 155 155

**. Correlation is significant at the 0.01 level (2-tailed).

Weak positive association at 0.01 significance level.


tionAccommrating

Satisfaction


Sig. (2-tailed) .000N 155 155

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Accomm rating


Sig. (2-tailed) .000N 155 155


The above table also shows weak positive association between satisfaction and accommodation rating at 0.01 significance level.


tionResortrat

ing

Satisfaction


Sig. (2-tailed) .000N 155 155

Resortrating


Sig. (2-tailed) .000N 155 155


This is the highest correlation at the same significance level (.835 at 0.01).

Table 10: Regression Table A

Model SummaryModel

R RSquare

Adjusted RSquare

Std. Error of theEstimate

1.988a .976 .975 2.089

a. Predictors: (Constant), Travel rating, Resortrating, Accomm rating

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As per the model summary table, the three variables can

explain up to 97.5% of the overall satisfaction (Adjusted R

square). The co-efficients are as shown below:

Table 11: Regression Table B

Coefficientsa

Model UnstandardizedCoefficients

StandardizedCoefficients

t Sig.

B Std. Error Beta

1

(Constant) 2.436 .809 3.010

.003

Resortrating 5.226 .082 .812 63.5

69.000

Accomm rating 1.795 .080 .287 22.3

39.000

Travel rating 2.515 .068 .472 37.0

00.000

a. Dependent Variable: Satisfaction

Based on the coefficients, the regression model is:Satisfaction=2.436+5.226(Resort) +1.795(Accommodation) +2.515(Travel)Thus:For one who gives scores of 4, 5 and 10 for travel, accommodationand resort respectively, satisfaction is given thus;Satisfaction=2.436+5.226(10) +1.795(5) +2.515(4)=73.841%

For one who gives scores of 1, 3 and 5 for travel, accommodation and resort respectively; satisfaction is given thus;

Satisfaction=2.436+5.226(1) +1.795(3) +2.515(5)=25.732%

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From the above table of co-efficients, resort rating

contributes most to satisfaction. A high score such as 10

translates into greater satisfaction (first model). The

management should ensure that they take their clients to better

hotels and restaurants. On the contrary, if resorts are given low

scores such as 1 in the second model, there is expected to be low

satisfaction.

ConclusionAs a matter of conclusion, this study aimed at establishing

the opinions of clients towards the services, packages and

related aspects of the company. This was done through designing a

questionnaire that captured all the objectives. After carefully

evaluating the questionnaire, it was apparent that it had more

strengths than weaknesses. In the first part of the report, it

was evident that development and critical analyses of the

questionnaire were handled. In the second part of the paper, data

analysis and findings were presented. It was found out that type

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of resorts were the greatest predictor of satisfaction among

clients in North East England.

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Freshwater, D., Sherwood, G. & Drury, V. (2006) International research collaboration. Issues, benefits and challenges of the global network. Journal of Research in Nursing, 11 (4), 9295–303.

Herrman, C. S. (2009). “Fundamentals of Methodology,” a series of papers On the Social Sciences Research Network (SSRN).

Joubish, F. (2009). Educational Research, Federal Urdu University, Karachi,Pakistan.

Kara, H. (2012) Research and Evaluation for Busy Practitioners: A Time-Saving Guide. Bristol: The Policy Press.

Lesage, D. (2009). "Who’s Afraid of Artistic Research? On measuring artistic research output". Art &Research: A Journal of Ideas, Contexts and Methods, 2 (2).

Patton, M. Q. (2002). Qualitative research & evaluation methods, 3rd ed. Thousand Oaks, CA: Sage Publications.

Silverman, D. (Ed). (2011). Qualitative Research: Issues of Theory, Method and Practice, 3rd ed. London, Sage Publications.

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Appendices

Appendix 1: Questionnaire Introduction

Dear Customers,

We are carrying out an evaluation of our services and products. We wish to ask your opinion so that we can improve where necessary and make them more relevant for you. We assure you that this information will only be used for research purposes (Do not write your name anywhere in this questionnaire).

Filing the questionnaire will take about 15 minutes. Kindly tick or fill as is appropriate.

Thanking you in advance.

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Appendix 2: Questions for the questionnaire

Customers Satisfaction Survey2013

-Questionnaire-

Section A: Demographic Information

1. Gender

Male Female

2.Age

3. NationalityBritish French German

Spaniard Dutch Other (Specify)

Section B: Travel Information

4. How many times have you ever travelled with us?1 2 3 4 5 6

Official use only

Question…………

1…………

2…………

3…………

4…………

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5. Was the last travel corporate or individual?

Individual Corporate

6. Did you travel alone or as a group?Alone (Skip to no. 8)

Group (Proceed to no. 7)

7. How many people were in the group?1 2 3 4 5 6 Other (specify)

8. Did you travel with children?Yes (Proceed to no. 9) No (Skip to no. 10)

9. How many children did you travel with? 10.Did you travel with spouse?

Yes No

11. How many days did you stay away from your family?

12.Which country did you visit?UK

5…………

6…………

7…………

8…………

9…………

10…………

11…………

12…………

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Europe Outside Europe

Section D: Information Regarding our Packages and Services

13.How can you rate our packages?Very Good Good Moderate Bad Very bad

14.Do you see the need for complementary services?Yes No

15.Which of our events have you attended before?Motor race Rugby Soccer Tennis Other

16.On a scale of 4, how would you rate our staff? Very effective Effective Ineffective Very ineffective

17.What do you think we should improve on?

...................................................................

....................................

...................................................................

....................................

...................................................................

....................................

14…………

15…………

16…………

17…………

18…………

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18.Any other comment?

Thank you very much for taking the time to complete thisquestionnaire.

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Appendix 3: Coding Plan for the Questionnaire

Question

Label Code/Absolutes

1. Male

Female

1

2

2. Age

3. British

French

German

Spaniard

Dutch

Other (Specify)........

1

2

3

4

5

6

4. No. of times

5. Individual

Corporate

1

2

6. Alone

Group

1

2

7. No. of people

8. Yes

No

1

0

9. Yes _

10. Yes 1

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No

2

11. No. of days away

12. UK

Europe

Outside Europe

1

2

3

13. Very Good

Good

Moderate

Bad

Very bad

1

2

3

4

5

14. Yes

No

1

2

15. Motor race

Rugby

Soccer

Tennis

Other

1

2

3

4

5

16. Very effective

Effective

Ineffective

Very

1

2

3

4

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ineffective

17. _ _

18. _ _

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Appendix 4: Variable List1) Gender

2) Age

3) Holidays

4) Previous

5) Adults

6) Children

7) Seniors

8) Destination

9) Resort

10) Accommodation

11) Travel

12) Satisfaction

13) Childrenornot

14) Newsatisfaction

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Appendix 5: Tables

Holiday destination * With or without children CrosstabulationWith or without

childrenTotal

Withoutchildren

Withchildren

Holiday destination

UK

Count 12 50 62Expected Count 12.8 49.2 62.0% within With or withoutchildren 37.5% 40.7% 40.0%

Within Europe


Outside Europe


Total

Count 32 123 155Expected Count 32.0 123.0 155.0% within With or withoutchildren 100.0% 100.0% 100.0

%

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Table 12: Association between destination and accommodation rating, travel rating and resort rating.

Multiple ComparisonsDependent Variable (I) Holiday

destination(J) Holidaydestination

MeanDifference

(I-J)

Std.Error

Sig.

95% ConfidenceInterval

LowerBound

UpperBound

Resortrating

Tukey HSD

UK

Within Europe .639 .458 .34

7 -.45 1.72

Outside Europe .275 .369 .73

6 -.60 1.15

Within Europe

UK -.639 .458 .347 -1.72 .45

Outside Europe -.363 .457 .70

7 -1.45 .72

Outside Europe

UK -.275 .369 .736 -1.15 .60


7 -.72 1.45

Games-Howell

UK


0 -.38 1.66


0 -.63 1.18

Within Europe

UK -.639 .427 .300 -1.66 .38


3 -1.35 .62

Outside Europe

UK -.275 .380 .750 -1.18 .63


3 -.62 1.35

Accomm rating

Tukey HSD UK


5 -.30 1.92


5 -1.00 .78

Within Europe

UK -.812 .468 .195 -1.92 .30


2 -2.02 .18

Outside Europe UK .109 .376 .95

5 -.78 1.00

Within Europe

.921 .467 .122

-.18 2.02

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Games-Howell

UK


6 -.32 1.95


5 -1.00 .78

Within Europe

UK -.812 .472 .206 -1.95 .32


5 -2.04 .20

Outside Europe

UK .109 .376 .955 -.78 1.00


5 -.20 2.04

Travel rating

Tukey HSD

UK

Within Europe 1.981* .504 .00

0 .79 3.17

Outside Europe 2.224* .406 .00

0 1.26 3.18

Within Europe

UK -1.981* .504 .000 -3.17 -.79


9 -.95 1.43

Outside Europe

UK -2.224* .406 .000 -3.18 -1.26

Within Europe -.243 .503 .87

9 -1.43 .95

Games-Howell

UK

Within Europe 1.981* .354 .00

0 1.14 2.83

Outside Europe 2.224* .434 .00

0 1.19 3.25

Within Europe

UK -1.981* .354 .000 -2.83 -1.14


9 -.78 1.27

Outside Europe

UK -2.224* .434 .000 -3.25 -1.19

Within Europe -.243 .429 .83

9 -1.27 .78

*. The mean difference is significant at the 0.05 level.

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Table 13: Cross tabs for grouped satisfaction and whether one had children or not

Grouped Satisfaction * With or without children Cross tabulationWith or without

childrenTotal

Withoutchildren

Withchildren

Grouped Satisfaction

30-39

Count 1 9 10% within With or without children 3.1% 7.3% 6.5%

40-49


50-59


60-69


70-79


80-89


TotalCount 32 123 155% within With or without children 100.0% 100.0% 100.0

%

BUSINESS RESEARCH ANALYSIS

Documents