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    WATERFORD INSTITUTE OF TECHNOLOGY

Course Title:  Bachelor of Business Year 3

   

Subject:  Marketing Research & Analytics

   

Lecturer:   Dr. Mary T. Holden   

Group 2:   Karen Cloke  20075742

Aideen Cummins  20076502

Donal Fitzgerald  20075710

Bernadette Iorianni  20083142

Niamh Windsor  20075852

    

    

Declaration

I hereby declare that this is my own work and that I have clearly identified with the appropriate referencing system where I have obtained assistance from a third party (e.g. internet, textbooks, newspapers, interviews).

Signed:     

Date:      

Introduction  4

1. Findings  6

1.1 Sample Profile  6

1.2 Major Findings  6

1.2.1 Objective One: To Define the Concept of Motivation  6

1.2.2 Objective Two: To determine usage differences, if any, between males and females  7

1.2.2 Objective Two: To determine usage differences, if any, between males and females  9

1.2.3 Objective Three: To identify what types of apps students are continuously using  11

2. Discussion and Implications for Marketing Managers  12

Bibliography  12

male v female - no. of apps  14

Introduction

The aim of this paper is to investigate the correlation between students at Waterford Institute of Technology and mobile application usage. The overarching research goal is to identify what makes student app usage continuous, using marketing research. This is because it “provides information for management about the company's actual or potential markets and information on the existing or potential users of the goods or services marketed by the company” (Armstrong, 1995, p. 70). As a result, marketing research will need the use of both primary and secondary research. The method of primary research chosen was a questionnaire investigating mobile app usage and the motives behind it, which was handed out to a random sample of students between the ages of 18 and 30 years old.

The objectives chosen for the research project are shown in the following table:

1

To determine what motivates students to continuously use apps

2

To define the concept of motivation

3

To identify what types of apps students are continuously using

4

To measure, on a daily basis, how much time students spend on apps

5

To identify the positive and negative aspects of using apps.

6

To determine usage differences, if any, between males and females

7

To make recommendations concerning designing a successful app

Table 1.1 - Objectives. Source: Compiled by the Authors

In conclusion, through this research project, this study aims to determine what factors motivate students to use mobile apps continuously. In order to do this, the authors of the paper decided to choose the hypothesis shown in Table 1.2, that will be investigated using the software SPSS.

H1

There is significant difference between males and females concerning the number of apps continuously used in their devices.

H2

There is significant difference between males and females concerning their opinion on convenient app usage.

Table 1.2 - Hypothesis chosen for the research

1.  Findings

1.1  Sample Profile

According to Bhattacherjee (2012, p. 65) “we must select a representative sample from the population of interest for observation and analysis. It is extremely important to choose a sample that is truly representative of the population”. As a result, the sampling process requires the following steps:

Define the population: in this case, the population can be identified in all the potential Irish students that have a smartphone as a filter question was put in the beginning of the survey. In order to define the population, it is important to define the following:

Population Element: Males and Females 18-30

Unit: Waterford Institute of Technology

Geographical Dimension: Ireland

Select a Sample Frame

Choose a Sampling Method

Choose a Sampling Type

Determine the Sample Size

“Sampling enables us to study some cases instead of all the cases, while still enabling us to draw conclusions about all the cases.” (Domegan and Fleming, 2003, p. 350)

….

    1.2  Major Findings

    In the following paragraphs, the objective chosen by the authors will be investigated, defining the concepts used and proving them with useful references.

1.2.1  Objective One: To Define the Concept of Motivation

The first objective chosen by the authors of the paper is the definition of motivation. According to the Oxford English Dictionary (2018), it is “a reason or reasons for acting or behaving in a particular way” or “ a desire or willingness to do something”. This study positions motivations as antecedents of functional and contextual factors in identifying mobile app use, as “individuals have different motivational reasons for technology use” (Kang, 2014, p. 363). This is because it “comes from within an individual, out of will and

interest in the activity at hand. No external rewards are required to incite the intrinsically motivated person into action. The reward is the behaviour itself.” (MSU, nd) In conclusion, motivation can be defined as the main reasons that might encourage a student to use apps and manifests itself differently from person to person, based on the varied interests that the students have.

1.2.2  Objective Two: To determine usage differences, if any, between males and females

    As said in the introduction of this paper, one of the main objective chosen is to determine usage differences, if any, between males and females. For this reason, the authors of this paper decided to carry on an independent sample t-test using the software SPSS, based on the following hypothesis:

    H1: there is significant difference between male and female concerning the number of apps continuously used in their devices.

Using data collected in the survey, two groups of variables were chosen:

q1, concerning the number of apps continuously used by the respondents (test variable)

Gender (group variable)

Gender

N

Mean

Std Deviation

Std Error Mean

Male

83

18.7711

15.40140

1.69052

Female

78

18.2949

17.09873

1.93605

Table X - Group Statistics. Source: Adapted by the Authors from SPSS

Considering the Table above, the two groups might be taken in consideration because the number of observation (second column) has to be at least 6 for each and they have to be no more that 1.5 times, as in this case. The mean of the groups (third column) is similar, so it's possible to go ahead with the second box (Table X)

Levene's Test for Equality of Variances

95% Confidence Interval of the Difference

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

Lower

Upper

Equal Variances Assumed

.002

.964

.186

159

.853

.47621

2.56189

-4.58351

5.53594

Equal Variances Not Assumed

.185

154.720

.853

.47621

2.57024

-4.80109

5.55351

Table X - Independent Sample Test. Source: Adapted by the Authors from SPSS

    As it is possible to see in the Table above, there are two lines that can be followed: equal variances assumed and equal variances not assumed. The first value that has to be considered it the Sig. (second column). In this programme, it represents the p-value: if it is >.05, the first line has to be looked; conversely, if it is <.05, second line has to be looked. In this case, our Sig. is 0.964, obviously more than .05. As a result, continuing looking at the first row, it is possible to find the second value in which we have to focus: Sig. (2-tailed). Another time, if this value will be over .05, it means that the hypothesis is not supported. In the opposite way, the hypothesis is supported. In this particular case, as it is possible to see the p-value of .853, there is no significant difference between males and females concerning the number of apps continuously used in their devices.

1.2.2  Objective Two: To determine usage differences, if any, between males and females

As said in the introduction of this paper, one of the main objective chosen is to determine usage differences, if any, between males and females. For this reason, the authors of this paper decided to carry on an Independent Sample t Test using the software SPSS, based on the following hypothesis:

    H2: there is significant difference between male and female concerning their opinion on convenient app usage.

Using data collected in the survey, two groups of variables were chosen:

q3b, concerning the number of apps continuously used by the respondents (Test Variable)

Gender (Group Variable)

Gender

N

Mean

Std Deviation

Std Error Mean

Male

83

4.1176

.83683

.09077

Female

78

4.2821

.64259

.07276

Table 1.1 - Group Statistics. Source: Adapted by the Authors from SPSS

Considering the Table above, the two groups might be taken in consideration because the number of observation (second column) has to be at least 6 for each and they have to be no more that 1.5 times, as in this case. The mean of the groups (third column) is similar, so it's possible to go ahead with the second box (Table XXX)

Levene's Test for Equality of Variances

95% Confidence Interval of the Difference

F

Sig.

t

df

Sig. (2-tailed)

Mean Difference

Std. Error Difference

Lower

Upper

Equal Variances Assumed

1.7828

.191

-1.398

161

.164

-.16440

.11763

-.39671

.06790

Equal Variances Not Assumed

-1.413

156.253

.160

-.16440

.11633

-.39418

.06538

Table 1.2 - Independent Sample Test. Source: Adapted by the Authors from SPSS

    As it is possible to see in the Table above, there are two lines that can be followed: equal variances assumed and equal variances not assumed. The first value that has to be considered it the Sig. (second column). In this programme, it represents the p-value: if it is >.05, the first line has to be looked; conversely, if it is <.05, second line has to be looked. In this case, our Sig. is 0.191, more than .05. As a result, continuing looking at the first row, it is possible to find the second value in which we have to focus: Sig. (2-tailed). Another time, if this value will be over .05, it means that the hypothesis is not supported. In the opposite way, the hypothesis is supported. In this particular case, as it is possible to see the p-value of .164,

there is no significant difference between males and females concerning their opinion on convenient app usage.

1.2.3  Objective Three: To identify what types of apps students are continuously using

Our overarching research goal was to identify what types of apps students use continuously and why this usage is continuous after initial adoption. It has been found that the apps that students use can predominantly be divided into five main categories, social networks, shopping sites, informative apps, entertainment/gaming apps and tool apps. It can be drawn from this that Generation Y could be described as technology dependent and it is clear they value convenience, functionality and wish to multi-task, however, it also highlights their need for fun, individuality and to make social connections. This report will analyse our market research to determine if this is also true of students in WIT. These factors explain why students adopt mobile applications but not why their use of them would remain continuous. Continuous use then depends more on how efficiently the app performs and how it will aid them  in their own tasks and goals, “performance expectancy, effort expectancy, social influence, and facilitating conditions are factors influencing behavioural intention or use behaviour of communication technology”, explains Venkatesh et al. (2003) It is clear that the intention of continuous mobile application use is decided by the functionality of the app after downloading and how it benefits students in their life and the ease and simplicity of use, this could be in the social networks it although students to develop, the entertainment it provides or it's practical organisational features and how they can be used to assist in their studies.

Considering the survey carried out, all the table of the question 2 has to be taken in consideration. Based on these data, can be said that the most used apps are Social apps, Messaging Apps, Utility Apps and Entertainment apps. Considering the answer from <- 30 times and more than 50 times, considered by the authors as an interval for a continue use of the app, the results are shown in the following Table:

Social Media

64.63%

Messaging apps

73.17%

Shopping apps

4.27%

Entertainment apps

31.10%

Health apps

4.27%

Gaming apps

7.32%

Finance apps

3.68%

Travel apps

3.05%

Gambling apps

4.91%

Sports apps

4.91%

Information apps

5.49%

Utility apps

23.78%

Table 1. X - Percentage of daily app usage in the interval [≤ 30 times; > 50 times]

2.  Discussion and Implications for Marketing Managers

    As the world of marketing continues and expands,  marketing manager have a tough task with keeping up on recent developments in the marketing area.

Discussion/Implications for Marketing Managers

Interpret and discuss your findings, summarise whether your findings are in-line with the secondary research you have read – cite appropriately.  Close with a discussion on what these results mean re managers.

Discussion & Implications for Marketing Managers

Bibliography

Armstrong, M., 1995. A handbook of Management Techniques, p. 70, chapter 10. Snd Edition Kogan

Bhattacherjee, A. (2012) ‘Social Science Research: Principles, Methods, and Practices' 2nd edition. Textbooks Collection. [Online] Available at: http://scholarcommons.usf.edu/oa_textbooks/3 (Accessed 18 November 2018)

Domegan, C. and Fleming, D. (2003) Marketing Research in Ireland: Theory and Practice. p.350, 2nd edition. Dublin: Gill & MacMillan.

Kang, S. (2014). Factors influencing intention of mobile application use. International Journal of Mobile Communications, 12(4), pp.360-365. [Online] Available at: https://www.researchgate.net/publication/264813293_Factors_influencing_intention_of_mobile_application_use (Accessed 18 November 2018)

Oxford English Dictionary (2018) Motivation | Definition of motivation in English by Oxford Dictionaries. [Online] Available at: https://en.oxforddictionaries.com/definition/motivation (Accessed 17 November 2018)

MSU (n.d.). Intrinsic Motivation. [Online] Available at: https://msu.edu/~dwong/StudentWorkArchive/CEP900F01-RIP/Webber-IntrinsicMotivation.htm  (Accessed 18 November 2018)

https://www.statista.com/statistics/270291/popular-categories-in-the-app-store/

B. Kuhlmeier, D and G.Fowler, J (2003) The Motives of Adopting Mobile Apps among College Students: A Cross-Cultural Examination

male v female - A mobile phone app(s) is more convenient to use than an app(s) on

other devices (tablet, PC, etc.).

male v female - no. of apps

    

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