The first part of your project will focus on television and movies. It should be at minimum 4 pages

LUBS5334 © UNIVERSITY OF LEEDS Semester 1 2018/19 Assessed Coursework for the

LUBS5334

© UNIVERSITY OF LEEDS

Semester 1 2018/19

Assessed Coursework for the degree of MA HRM

LUBS5334 Employment relations

75% Assignment

Choose just ONE of these questions for your assignment. You must use the EXACT title. Do not change the assignment question. Write the full question at the top of your essay as set out below. Do NOT write in report format.

Explain the meanings of the unitarist, pluralist and radical perspectives on the employment relationship. Drawing on examples, critically assess the relevance of these perspectives for contemporary industrial relations.

How do different management styles impact on employment relations? Please illustrate your answer with empirical examples of firms adopting different approaches.

Dunlop’s ‘systems theory’ focused on three key actors in the employment relationship (employers, workers and trade unions, and governments), but in recent years we have seen greater involvement of ‘new actors’. Who are these ‘new actors’ and how are they intervening in the employment relationship?

Why, and in what ways, is employment relations influenced by politics?

In what ways are traditional mechanisms of voice at work changing as result of the growth of social media? Your answer should present an analysis from the perspectives of employers, employees and trade unions.

‘Trade unions are responsible for their own decline’. Critically discuss this claim.

Assignments should be a maximum of 4000 words in length.

All coursework assignments that contribute to the assessment of a module are subject to a word limit, as specified in the online module handbook in the relevant module area of the MINERVA. The word limit is an extremely important aspect of good academic practice, and must be adhered to. Unless stated specifically otherwise in the relevant module handbook, the word count includes EVERYTHING (i.e. all text in the main body of the assignment including summaries, subtitles, contents pages, tables, supportive material whether in footnotes or in-text references) except the main title, reference list and/or bibliography and any appendices. It is not acceptable to present matters of substance, which should be included in the main body of the text, in the appendices (“appendix abuse”). It is not acceptable to attempt to hide words in graphs and diagrams; only text which is strictly necessary should be included in graphs and diagrams.

You are required to adhere to the word limit specified and state an accurate word count on the cover page of your assignment brief. Your declared word count must be accurate, and should not mislead. Making a fraudulent statement concerning the work submitted for assessment could be considered academic malpractice and investigated as such. If the amount of work submitted is higher than that specified by the word limit or that declared on your word count, this may be reflected in the mark awarded and noted through individual feedback given to you.

The deadline date for this assignment is 12.00 noon on Tuesday 28 November 2018

An electronic copy of the assignment must be submitted to the Assignment Submission area within the module resource on the Blackboard MINERVA website no later than 12:00:00 noon prompt on the deadline date.

Faxed, emailed or hard copies of the assignment will not be accepted.

Failure to meet this initial deadline will result in a reduction of marks, details of which can be found at the following place:

https://lubswww.leeds.ac.uk/TSG/coursework/

SUBMISSION

Please ensure that you leave sufficient time to complete the online submission process, as upload times can vary. Accessing the submission link before the deadline does NOT constitute completion of submission. You MUST click the ‘CONFIRM’ button before 12:00:00 noon for your assignment to be classed as submitted on time, if not you will need to submit to the Late Area and your assignment will be marked as late. It is your responsibility to ensure you upload the correct file to the MINERVA, and that it has uploaded successfully.

It is important that any file submitted follows the conventions stated below:

FILE NAME

The name of the file that you upload must be your student ID number only.

ASSIGNMENT TITLE

During the submission process the system will ask you to enter the title of your submission. This should also be your student ID number only: NOT the title of your essay.

FRONT COVER

The first page of your assignment should always be the Assessed Coursework Coversheet (individual), which is available to download from the following location:

https://lubswww.leeds.ac.uk/code-of-practice/downloadable-forms/

STUDENT NAME

You should NOT include your name anywhere on your assignment

END

The Impact of changes in energy prices on stock prices— Empirical evidence

The first part of your project will focus on television and movies. It should be at minimum 4 pages Writing Assignment Help The Impact of changes in energy prices on stock prices— Empirical evidence from the Chemical Industry and the Overall Stock Index in China

Background and question statement

1.1 Research background

As one of the primary representatives of the developing countries, China has entered the stage of the development of the heavy chemical industry. The economic take-off has made China the most important driving force for the growth of the world’s crude oil demand, and the demand for oil has risen year by year. China’s oil demand grew rapidly from 1/3 barrels per day to ten thousand barrels per year. China has replaced Japan as the world’s second largest oil consumer after the United States. Due to insufficient oil production in China, oil imports have become an important means to meet domestic demand. A large number of oil imports have increased the sensitivity of our economy to international oil prices. Thus, the expansion of oil imports in the future will make China’s economy more and more affected by the fluctuation of international oil prices.

As the highest form of market economy, stock market concentrates and condenses the basic mechanism, core elements and main values of market economy. Since the establishment of the first stock exchange in England, the stock market has been in history for many years. The world economy starts to grow continuously and the stock exchange is almost synchronous, which is not accidental but inevitable. Stock system and stock exchange are the products of modern enterprise system and market economy system. The development of a country’s economy determines the development of the stock market. The rise and fall of the stock market can directly reflect the quality and speed of the country’s economic development. Therefore, since oil is a key factor in economic development, oil prices will inevitably be an important factor affecting economic growth and stock market. When oil prices are low, it means that economic prosperity can be expected and stock prices will rise. Conversely, when the price of oil rises, it means that the economy will go to recession, and the stock price will decline, showing oil. The fluctuation of price is closely related to the economy and stock market.

With the rapid development of Chinese economy, its dependence on energy is also increasing. For companies with a close relationship with energy, the volatility of energy prices will affect the company’s earnings to a large extent, thus affecting the stock price of the company. According to the stock pricing theory, the fluctuations in the energy price will react in a very short period of time to the change in the stock price rather than waiting for changes in business conditions.

1.2 Research question

As the rapid development of China’s economy has led to the increasing dependence on foreign oil, the continuous rising of the energy price represented by oil is self-evident to the Chinese economy. The process from production to consumption will also have a negative impact on all walks of life in China. Under the background of rising international oil prices, rising oil price volatility and the increasing correlation between international crude oil market and financial market, stock investors not only care about the impact of the volatility of crude oil prices on the stock returns of energy companies, but also pay more attention to the impact of the volatility of other energy prices on the yield of energy stocks. Although petroleum is China’s main energy component, natural gas and coal also play an important role in China’s economy. Therefore, the author argues that the price of coal and natural gas should be introduced into the existing research on oil prices and stock prices, which is the main question will be researched in this dissertation.

Research aim and research objectives

2.1 Research aim

The research aim of this dissertation is to explore the impact of energy price change on the stock price of Chinese chemical industry companies.

2.2 Research objectives

The main objectives of this paper are the following points: (1) Summarize and analyze the existing theory and research about stock price fluctuation; (2) Collect and sort price change data of oil, coal and natural gas and synthesize the total energy price of three kinds of energy prices using Divisia method; (3) Evaluate the impact of energy price change on the stock price of chemical industry; (4) Promote some investment suggestions according to the conclusions of this study.

Research structure

The research mainly includes five chapters.

Chapter 1 is introduction. The research background, research aims and objectives, research structure and research significance will be given in this part.

Chapter 2 is literature review. The basic theories about the stock price fluctuation and energy prices will be introduced. The existing research about the impact of the change of energy prices on stock prices will also be analyzes in this part.

Chapter 3 is methodology. In this chapter, the research methods, data collection and model design will be presented in detail.

Chapter 4 is Empirical results. The empirical results of the dissertation based on the model and data in chapter 3 will be presented in detail and the results will also be further discussed.

Chapter 5 is Conclusion. In this chapter, some basic conclusion and recommendations of this dissertation will be given

Literature review 1000

4.1 Research on influence factors of energy price and stock price

As for the factors affecting the fluctuation of energy prices, the academic community generally believes that it is affected by many factors, which mainly includes supply and demand, stock, dollar exchange rate, speculation and sudden political events. Traditional economic theory holds that supply side and demand side can determine prices, that is to say, oil price is determined by two aspects of supply and demand (Taal, Bulatov, Klemeš & Stehlı́k, 2003). The theory of peak oil is one of the most famous theories of the supply side in the traditional economic theory, which was first proposed by Finn (2000). Finn (2000) successfully predicted that US oil production reached its peak in the twentieth Century ten generations in twentieth Century, based on the theory of peak oil, and then showed the trend of son-in-law. On the side of the demand side, the traditional economic theory believes that the economy is bound to drive up the price of oil, and the high oil price will restrict the growth of the economy.

For the influence factors of the stock price, some scholars believe that traditional economic theories can not explain the fluctuation of oil prices nowadays and the fluctuation of oil prices will be more and more affected by finance (Metcalf, 2008; Kilian, 2008). These scholars believe that the long-term price of oil is affected by supply and demand. But after entering twenty-first Century, the fluctuation of oil price began to intensify, while the supply side and demand side did not fluctuate and fluctuate. Therefore, Arouri & Nguyen (2010) believe that traditional economic theory can not explain this phenomenon after twenty-first Century. Li, Zhu & Yu (2012) suppose that oil price fluctuation is influenced by two financial factors, the US dollar exchange rate and speculative behavior. Cheng Weili (2005) pointed out in his research that most of the international crude oil market is currently settled in US dollars. Therefore, the change of US dollar exchange rate has a deep impact on international crude oil prices, and the two are negatively related. In his research, Li, Zhu & Yu (2012) also compiled the trend of the WTI spot price and the dollar exchange rate, and found that the trend of W’s price of crude oil is in the opposite direction from the dollar exchange rate. Ergun & Ibrahim (2013) found in his research that the devaluation of the dollar can explain one of the H points of the fall of oil price from 2002 to 2012, and the marginal politics and market speculation are also one of the important factors that affect the fluctuation of oil prices. Whether the futures market speculation has promoted the rise of international crude oil prices has not reached any agreement. Norasibah & Yusof & Upsi (2012) study the relationship between the futures market, speculation and the fluctuation of international crude oil price based on the vector autoregressive model (VAR model). Their research shows that speculation has not caused long-term rise in international crude oil prices nor has it amplified the short-term fluctuations in international crude oil prices.

4.2 Relationship between energy price and stock market

At present, the conclusion of the empirical study on the relationship between the international primary energy grid and the overall stock market has not reached a unified conclusion. The impact of energy prices on the overall stock market is with the types of countries (such as oil importers, exporters of crude oil), market environment (such as economic recession or economic expansion, economic crisis or non-economic crisis), oil shock types (such as oil supply shock, crude oil demand shock and crude oil) Specific demand shocks, and the frequency of sample data (e.g., weekly data, data, monthly data) vary with measurement methods. The impact of international crude oil price shocks on the overall stock market yields can be basically divided into the following 4 categories.

First, Kaul and Jones (1996) have found that the correlation between international crude oil price shocks and the overall stock market returns is significantly negative. The negative impact of crude oil prices on the overall stock market yield was first studied by Kaul and Jones (1996) through the study of the relationship between stock returns and crude oil prices in the United States, Canada, Japan and the UK. Cunado & Gracia (2014) confirm that the negative correlation between stock market yield and international oil price exists in most European countries (Belgium, Denmark, Finland, France, Germany, Italy, Luxemburg, Holland, Portugal, Spain and Britain). And they further point out that stock returns are mostly affected by the impact of crude oil supply (Cunado & Gracia, 2014). The impact of crude oil demand can only affect several European countries, such as Germany, Italy, Luxemburg, Portugal, the United Kingdom, France and Denmark.

Second, some scholars have found that the correlation between the international crude oil price shocks and the overall stock market returns is significantly positive. For example, Hammoudeh and Choi (2006) uses the VECM model to find that the positive impact of the price of crude oil can benefit most Gulf States.

Third, the correlation between the international energy price shocks and the overall stock market returns is found to be different under different circumstances. For example, Park and Ratti (2008) use a multiple VAR model to find that the impact of the international oil price impact on the stock market yield depends on whether the sample country is a crude oil importer or an exporter of crude oil. They found that as a crude oil exporter, Norway’s stock return had a positive reaction to the rise in crude oil prices (Park and Ratti, 2008). However, the reaction of other European countries (Austria, Belgium, Denmark, Finland, France, Germany) to the rise in crude oil prices is significantly negative.

Finally, some scholars believe that the correlation between the international crude oil price shocks and the overall stock market returns is not statistically significant. The relationship between the price impact of crude oil and the non-statistical significance of the overall stock market was first proposed by Chen et.al. (1986) by studying the impact of oil prices on the yield of the stock market in the United States. Then, Huang et.al. (1996) use the US stock market daily transaction data and the crude oil futures trading data. Through the VAR model, it is found that the impact of international oil prices on the stock market is not significant.

4.3 Research gap

Through the above literature review, we can see that there is a lot of research on the impact of stock price on energy prices, but most of the current research is focused on the study of oil as a representative of energy prices. At the same time, most researches focus on the changes of energy and the overall stock price. Few studies involve the study of the price of energy in a certain industry. Therefore, based on the above analysis, the author thinks that the price of natural gas and coal can be added to the existing research, and the focus of the research can be put on the chemical industry because it is closely related to the change of energy price.

Research methodology 600

5.1 Research philosophy

According to the study of Webb (1989), three points must be made clear before the study of social science. The first point is what is the object of research. The second point is what is the scale of research and the final point is what kind of research should be used. For the object in this research, this dissertation will focus on the impact of energy prices on stock prices. For the scale of the research, this dissertation will study the impact of Chinese energy price (including oil, gas and coal) on Chinese chemical industry stocks. For the research methods, this dissertation will mainly use the method of quantitative research, which will be further introduced in the following.

Research methods

5.2.1 Data

For the energy, three kinds of energy prices will be included in this dissertation, which are the price of Dubai crude oil, the price of coal exported from Australia to China and the monthly price of natural gas in the 36 large and medium-sized cities of the country. Stock prices and other macroeconomic indicators are selected from website of Chinese Statistics Bureau and the Shanghai Stock Exchange. The research period of this dissertation is from January 2010 to December 2017.

5.2.2 Model and empirical approaches

The main research method of this dissertation is time series modeling, which includes Unit root test, cointegration test, VECM model or VAR model, pulse correlation and variance decomposition. Through the above analysis, the relationship between energy prices and stock prices can be studied. This dissertation will use the following empirical methods

Calculation of Divisia Index

Considering that the focus of this paper is to synthesize the price of oil, coal and natural gas into an index reflecting the change of overall energy price, the method of divisia index will be used.

(1)

In the above equation (1), the p and q in the left of the equations mean the price and the quantity of the energy, which can be calculated by the formula.

(2)

Based on the calculation in equation (1), the divisia index can be calculated further through the equation (2), which is presented by the s in the left of the equation (2). The results of the calculation of s can be used to evaluate the total energy price.

Unit root test

Because the time series modeling method is used in this dissertation, it is very necessary to check the stationarity of variables. Unit root test can be used to test the stationarity of variables. The methods of unit root test mainly include DF test, ADF test and PP test. In order to increase the credibility of the test, we will use the three methods mentioned above to carry out unit root test for variables in the model.

Cointegration test

Cointegration is a mathematical description of the equilibrium relationship between variables of first order and single integer. Nonstationary phenomena exist in large daily economic data. Therefore, Engle and Granger (1987) formally put forward a cointegration test. Cointegration test is a “pseudo regression” phenomenon.

In order to test the equilibrium relationship between energy prices and chemical industry stock prices, the author will use co-integration test to test whether there exists equilibrium relationship between them. The commonly used cointegration methods include E-G two step method and Johansen cointegration test. The method used in this dissertation is Johansen cointegration test. Johansen cointegration test is based on the foundation of VAR. The reason why Johansen’s cointegration test is used is that the EG test can only test the equilibrium relationship between the two variables. The variables in this dissertation will be more than two.

Vector autoregressive model (VAR)

The foundation of vector error correction model is the cointegration relationship among variables. The foundation of VECM model is based on VAR model. Therefore, the VECM model can be regarded as a VAR model with cointegration constraints. The establishment of VECM is based on the unit root test of each variable and is I (1).

In this dissertation, VECM will be used to analyze and evaluate the impact of energy price on stock price. On this basis, this dissertation will further analyze the impact of energy price shocks on stock prices by using the methods of impulse response and variance decomposition.

Timeline

Time

Item

4.20 – 4.30

Read the related literature

5.1 – 5.20

Finish the literature review

5.21 – 5.30

Finish the methodology

6.1 – 6.25

Collect and summarize the data

6.26 – 7.15

Analyze the data according to the methodology

7.16 – 7.30

Finish the results and discussion of the research

8.1 – 8.15

Finish the introduction and conclusion

8.16 – 9.1

Review and submit the first draft

REFERENCE

Arouri, M. E. H., & Nguyen, D. K. (2010). Oil prices, stock markets and portfolio investment: Evidence from sector analysis in Europe over the last decade. Energy Policy, 38(8), 4528-4539.

Chen, N. F., Roll, R., & Ross, S. A. (1986). Economic forces and the stock market. Journal of business, 383-403.

Cunado, J., & de Gracia, F. P. (2014). Oil price shocks and stock market returns: Evidence for some European countries. Energy Economics, 42, 365-377.

Engle, R. F., & Granger, C. W. (1987). Co-integration and error correction: representation, estimation, and testing. Econometrica: journal of the Econometric Society, 251-276.

Ergun, U., & Ibrahim, A. (2013). Global energy prices and the behavior of energy stock price fluctuations. Asian Economic & Financial Review, 3(11), 1460-1465.

Finn, M. G. (2000). Perfect competition and the effects of energy price increases on economic activity. Journal of Money, Credit and banking, 400-416.

Hammoudeh, S., & Choi, K. (2006). Behavior of GCC stock markets and impacts of US oil and financial markets. Research in International Business and Finance, 20(1), 22-44.

Huang, S. W., Frankel, E. N., Schwarz, K., Aeschbach, R., & German, J. B. (1996). Antioxidant activity of carnosic acid and methyl carnosate in bulk oils and oil-in-water emulsions. Journal of Agricultural and Food Chemistry, 44(10), 2951-2956.

Jones, C. M., & Kaul, G. (1996). Oil and the stock markets. The Journal of Finance, 51(2), 463-491.

Kilian, L. (2008). The economic effects of energy price shocks. Journal of Economic Literature, 46(4), 871-909.

Li, S. F., Zhu, H. M., & Yu, K. (2012). Oil prices and stock market in China: A sector analysis using panel cointegration with multiple breaks. Energy Economics, 34(6), 1951-1958.

Metcalf, G. E. (2008). An empirical analysis of energy intensity and its determinants at the state level. The Energy Journal, 1-26.

Norasibah, Abdul & Yusof, Hamidah & Upsi, Rosmini. (2012). STOCK PRICE AND ENERGY PRICE: A DISAGGREGATE ANALYSIS. Journal of Contemporary Issues and Thought. 2.

Taal, M., Bulatov, I., Klemeš, J., & Stehlı́k, P. (2003). Cost estimation and energy price forecasts for economic evaluation of retrofit projects. Applied thermal engineering, 23(14), 1819-1835.

Webb, C. (1989). Action research: philosophy, methods and personal experiences. Journal of Advanced Nursing, 14(5), 403-410.

Dissertation structure: Chapter 1: Setting the Scene (Introduction 1500-2000) 1.1 background to

Dissertation structure:

Chapter 1: Setting the Scene (Introduction 1500-2000)

1.1 background to the research problem

1.2 research aims and objective

1.3 outline of methodology

1.4 research significance (e.g. contributions derived from this research…theoretical or practical)

1.5 dissertation structure:

Chapter 2: Literature review (4000-4500 words)

2.1 chapter overview( one paragraph outlining the structure of this chapter )

2.2 -Theme 1

2.3 -Theme 2

2.4 -Theme 3

2.5 -Theme 1&2&3

2.6 research framework and hypotheses/propositions

2.7 conclusion

Chapter 3: research methodology (2500)

3.1 chapter overview

3.2 research philosophy and justification (e.g. positivism, interpretive or pragmatism)

3.3 research approach and justification (e.g. deductive, Inductive and abductive)

3.4 research method/strategy and justification(e.g. case study, servey, action research, experiment, grounded theory)

3.5 data collection method and justification (e.g. questionnaire, interviews, focus group, observation, documents/report)-note: discuss how you have designed questionnaire/ interviews guide in details …sampling method,pilot testing etc.

3.6 data analysis method (e.g. statistical method for quantitative studies .e.g. descriptive statistics, hypothesis testing using, t-test, chi square, correlation and regression )

For qualitative research, you could use thematic analysis



3.7 ethical considerations

Chapter 4: result and analysis (2500)

4.1 chapter overview

4.2 descriptive analysis

4.3 hypotheses tests

4.4 model testing

4.5 summary of results

Chapter 5: discussion of results:(1500-2000)

Recap of results

Here the emphasis in to Link results to theory/literature and identify any similarities/differences… so provide references to back your arguments

Chapter 6: conclusion and recommendations (1500)

6.1 chapter overview

6.2 conclusion (recap research objectives and results)

6.3 research implications/ contributions/recommendations(theoretical and practical)

6.4 research limitations and further research

Market Research and Grey Nomads Part A Management Decision Problem and Management

Market Research and Grey Nomads

Part A

Management Decision Problem and Management Research Question

Management Decision Problem refers to a situation where the management has to consider between various decisions choices, as such these decisions are in a systematic order, which is first identification of the problem, identification of what are the decision alternatives and the corresponding criteria for selecting the decision. This decision making criteria is based on what is most urgent and critical, development decision alternatives which also include how the decisions made are to be best implemented (Lyon, Mšllering & Saunders, 2015). On the other hand management research question entails the hierarchy in terms of processes that leads to a decision. As such this includes formulation of a research problem that sheds light on what are the critical aspects that need to be managed within a research, this follows the identification of a challenge within the research and by answering they how and why question it becomes easier to solve the problem (Kanki, 2009).

As such it is evident that Global tourism has witnessed a paradigm shift in the increase of global tourists. This growth is more pronounced in the US, Europe and in Australia where the number of tourists who are aged 55 years and above is on the rise. These populations bring about unique requirements into the tourism circuit, one is that they have a higher disposable income and secondly they enjoy a relatively long lifespan. This is a group that tourism players seek to actively engage and even have gone ahead to give them names; for example in the US they are referred to as “Snowbirds” since they tend to move away from colder regions during winter while in Australia they are referred to as “Grey Nomads” who enjoy going around the country in Caravans. While their existence is well known what lacks is information/ feedback from these populations about accessibility and usability of the grey nomad’s app which is essential for the future design of the app.

The lack of this critical information seems to hamper the management from making critical management about how best the company is to grow, so as to ensure that the company continues to grow. It is on this need that there has been a necessitated need to conduct market research to establish the position of the company especially among the retired community and its contribution to the local economy especially among across various towns in Australia. According to Prasad, Rao, and Rehani (2001), there are three types of a research question which are either descriptive, observational or cause-effect type of question. By using a descriptive type of question the study intends to establish whether the Grey Nomad app has any benefit among the users and does it bring any benefit to the communities and towns across Australia.

However, a researcher question does not make much sense without clearly articulated objectives for the research. The study’s objective include but not limited to; 1) to establish whether the grey-nomad app fulfills and satisfies the need of its users especially the 55-year-old and older, the second objective of the study is to establish whether there is a benefit to the economy as a result of increased use of the grey-nomad app in Australia.

Proposed research methodology

A research methodology is an outline of the steps that will be followed in sequence until the desired outcome as per the objectives has been realized. Thus a detailed methodology covers various aspects that are critical for the success of any study.

This study has two broad objectives that are being studied which are Management Decision Problem and Management Research Question. In order to clearly understand how the study will be carried out two broad methods will be used for data analysis. One is quantitative and the other is qualitative.

The Management Research Question

A quantitative study measure and categorizes the factors in the study into numerical value and as such be able to predict the outcome of a phenomenon under study. The Management Research Question will be analyzed quantitatively in order to establish the different factors that influence management decisions. As such the study will come up with statistical data in form of means, mode and averages.

Management Decision Problem

On the other hand a qualitative study measure the non-numerical aspects of the study variables. The results is that there a deeper understanding of the underlying motivations, the difference in opinions and motivations. In other words it seeks to answer the why rather than what. In this study the Management Decision Problem will be studies and answered from a qualitative perspective. Having established the qualitative and quantitative aspect of the study, the study will following the following in terms of methodology in order to achieve its objectives.

According to Hakim (2012), a research design intends to ensure that the process of collecting and analyzing data is done in such a way that will ensure and lead to success of the project that is highly calibrated. The design used in this study is a descriptive case study design aimed at establishing the impact of the grey nomad’s app among the Australian population who have used the Grey Nomad app previously. Further, a case study elaborates in detail the characteristics of subject understudy in detail and within its context thereby allowing for a deeper understanding of the challenges and issues around the Grey Nomad App. The study seeks to establish and understand clearly what grey nomads users desire to find in their app, the number of users and areas for improvement.

The population under study will cover primarily users of the grey-nomad app which will include tourists and service providers who have subscribed to the services. This is a critical group as defined by Ducombe and Boateng (2009) that a “population is the sum of all the elements about which the researcher intends to make assumptions”. Having identified the population the next step is to clearly come up with how the sample will be selected from the population. This step is known as the sampling technique- which is a method that is used to select the sample. In this case, according to Johnson (2001), there are several factors to consider for various studies. In this case, the study being a descriptive case study 10% of the accessible population study will be used. Thus the sample size will be randomly selected from the database accessible from Grey Nomad app user in the last one year.

This study will utilize online questionnaires for data collections, according to Tull and Hawkins (1993) they state that questionnaires provide room for respondents to indicate their feelings and attitudes about the study subject while at the same time cutting down on expenses that are associated with other data collection methods. Secondary data will be collected from Grey Nomad staff and records which will be used to verify the information obtained from the respondents.

Bryman and Cramer (2012) state that in any study it is important to conduct a pilot test, this type of study is important to the main study since it enables the researcher to identify pertinent issues that may arise from the main study and rectify beforehand. Therefore the pilot study will be conducted among grey nomad users in Queensland before the rollout begins. After the pilot study, the researchers will conduct a reliability and validity test, George and Mallery (2003) aver that reliability test enables the establishment whether the study will yield the same study if it is conducted among the same population. Thus the reliability test intends to establish whether the study has obtained the 0.7 index on the Cronbach alpha index. In addition, the study shall conduct a validity test to establish whether the study measures exactly what was intended to be measured by the study.

The study data will be analysed using SPSS with the intention of establishing whether Grey Nomad app has any impact of the users traveling and enhances their experiences, in addition, analyse whether the service provider have realized any tangible benefits from incorporating the app into their operation. All this is aimed at finding how best the app can be improved to satisfy the future needs of users. This will be achieved through the computation of averages, percentages, and frequencies against various measures. In addition, the study will compute a correlation test to test the strength between the dependent and independent variable (Levin and Rubin, 2008) which is does Grey Nomad app enhance user and traveling experience among its users. A correlation analysis gives rise to an index between +1 and -1 which indicates the strength between the variables. In addition, the study will measure the regression between the various variables which in this case is how does age, technology know-how usability of the grey-nomad app affect user experience. Draper and Smith (2014) states that a “regression analysis as a statistical process for estimating the relationships among variables”.

The data will be presented in the form of tables, figures, narrations and diagrams. The benefits of the above are that it allows for data to be compressed thus making it easy to be understood by the reader and trace a trend-line over a period of time.

Limitations

Considering that majority of the users are not a people that can be found within one location, this presents one of the major limitations in terms of accessing the population to interview and collect data from. This is evidently going to be a challenge however the researcher intends to access contact information from users who will then be approached to provide their opinions about the usability of the app.

Secondly, the other limitation would be a lack of willingness by the respondents as a result of a bad experience or the respondents being not contactable. The researcher will eliminate this by ensuring that the respondents are contactable as well as this will be achieved through data cleaning thereby remaining with information that is sufficient to prove or disprove the study objectives.

The third will be the issue of time, considering that the time consumed to reach the group is will be much, the researcher will use research assistants who will reach out and do follow up with prospective respondents to ensure that there is a higher response rate and where possible they will assist in filling online question.

PART B

Independent-samples t-test

Gender

Mean

Sig

Unit materials – learning

Male

4.15

.578

Female

4.38

Unit materials – knowledge and skills

Male

4.20

.397

Female

4.29

Teaching methods – help to learn

Male

4.54

.289

Female

4.60

Topics and content

Male

4.44

.555

Female

4.97

Assessment tasks

Male

4.54

.811

Female

5.02

Guidelines and criteria

Male

5.78

.412

Female

6.17

Requirement of overall assessment program

Male

5.41

.496

Female

5.90

Resources – help to learn

Male

5.78

.083

Female

6.26

Feedback from students used

Male

5.22

.688

Female

5.66

Overall importance of unit

Male

5.59

.908

Female

5.46

Teaching staff – understanding expectations

Male

5.80

.601

Female

5.91

Teaching staff – class atmosphere

Male

6.00

.057

Female

5.79

Teaching staff – friendly, enthusiastic, helpful

Male

6.39

.056

Female

6.32

Teaching staff – genuine interest

Male

5.76

.373

Female

6.00

Teaching staff – feedback

Male

6.17

.290

Female

6.36

Teaching staff – developing knowledge, understanding and skills

Male

5.80

.008

Female

6.21

Use of T&L resources and aids

Male

6.10

.851

Female

6.08

Use of student feedback to improve teaching

Male

5.80

.322

Female

5.86

Teaching, learning and assessment tasks used to help students learn

Male

5.66

.741

Female

5.75

Overall importance of teaching

Male

5.88

.983

Female

6.19

It is evident from the data analyzed and findings posted above that there is no major difference between the mean obtained by boys and that which is obtained by girls. This is from the results which show that male had a mean of 4.5714 and female had 5.020. This could be as a result of more female students in the study which could imply that the variance was higher as compared to their male counterparts. However, the standard deviation indicates that the finding is more or less similar to the male students having a standard deviation of 2.52927 while female students had a standard deviation of 2.62844.

The significance for Equal variance not assumed is greater than 0.05. This is reported as Sig .723≥ .05. Secondly the Sig. (2-tailed) > 0.05 which implies that the population mean between male and female students are equal. In addition P= .350 (35% probability) that the means between that of male and female are equal. Therefore the null hypothesis is accepted.

Analysis of variance (ANOVA)

ANOVA

Sig.

Unit materials – learning

.000

Unit materials – knowledge and skills

.000

Teaching methods – help to learn

.000

Topics and content

.000

Assessment tasks

.000

Guidelines and criteria

.000

Requirement of overall assessment program

.436

Resources – help to learn

.499

Feedback from students used

.744

Overall importance of unit

.161

Teaching staff – understanding expectations

.005

Teaching staff – class atmosphere

.329

Teaching staff – friendly, enthusiastic, helpful

.960

Teaching staff – genuine interest

.978

Teaching staff – feedback

.574

Teaching staff – developing knowledge, understanding and skills

.814

Use of T&L resources and aids

.313

Use of student feedback to improve teaching

.553

Teaching, learning and assessment tasks used to help students learn

.871

Overall importance of teaching

.682

The findings above indicate that the Anova output has a P value of .000 -.978. The findings indicate that there is sufficient information to occasion that the mean for the assessment task and year of starting a degree vary to a great extent. However, what is not known is between which years the difference originates.

Bivariate correlation matrix

The correlation index a strong relationship between the two variables as per the above table which indicates that there is a high correlation between the two variables. The findings therefore indicate that there was a strong positive correlation between the two variables at a sig value of 74.9%. This implies that when one variable increases by one point the other would increase with almost a similar value.

References

Bryman, A., & Cramer, D. (2012). Quantitative data analysis with IBM SPSS 17, 18 & 19: A guide for social scientists. Routledge.

Draper, N. R., & Smith, H. (2014). Applied regression analysis (Vol. 326). John Wiley & Sons.

Ducombe, R., & Boateng, R. (2009). Mobile Phones and Financial Services in Developing Countries: A Review of Concepts. Methods, Issues, Evidence and Future Research. Third World Quarterly, 30(7), 1237-1258.

George, D., & Mallery, P. (2003). SPSS for Windows step by step: A simple guide and reference. 11.0.

Hakim, C. (2012). Research Design: Successful Designs for Social Economics Research. Routledge.

Johnson, B. (2001). Toward a new classification of non-experimental quantitative research. Educational Researcher, 30(2), 3-13.

Kanki, B.G., 2019. Communication and crew resource management. In Crew resource management (pp. 103-137). Academic Press.

Levin, R. I. (2011). Statistics for management. Pearson Education India.

Lyon, F., Mšllering, G. and Saunders, M.N. eds., 2015. Handbook of research methods on trust. Edward Elgar Publishing.

Prasad, S., Rao, A., & Rehani, E. (2001). Developing hypothesis and research questions. 500 research methods. September 18th.

Tull, D., & Hawkins, D. l. (1993). Marketing Research. Measurement and Method. Upper Saddle River, NJ: Prentice Hall.

Data collection instrument.

State your age. ______________________________________

Gender. Male Female

Are you’re a) Working Retired

Area of Residency i.e. Sydney etc. ______________________________

Have you used the Grey Nomad App before Yes No

If yes please answer the following

Please indicate your level of agreement with the following questions, where 5 is the strongest and 1 is the least.

Q. No

Question

1

2

3

4

5

1

How is the ease of usability of the Grey Nomad App

2.

Are there areas that you did not understand while using the App

3.

The App provided me with all the information that I needed

4.

Grey app connected me to service providers across Australia

5.

I was able to locate where I was going with assistance from the App

6.

The app is user-friendly

7

I will have no problem using the app in the future

8.

The app satisfied my travels across Australia

8. Would you recommend the Grey Nomad App Yes No

9. Give Reason for your answer. __________________________________________________

____________________________________________________________________________________________________________________________________________________________