Business论文模板 – Alipay Research Report

Introduction

Summary of the Proposal

The research project introduced the possibility of investigation on Third Party Payment. The Chosen firm for the study is Alipay, an online TPP that has outgrown competition. Alipay is China’s largest third-party payment company. The online company cuts across all the industries allowing online transactions a chance to prove that virtual business is not only possible across The Web, but the future model of doing business. The company that is more than the equivalent of the most popular US Third Party Payment Company- Paypal makes more than one billion USD in a year. The firm is now worth more than four trillion USD, making the statement that digital money and the online market is the solidifying market that will exceed any platform that ever existed.

Research Question and Objectives

Research Question

The research question I will be dealing with is:

How is Alipay outshining competition?

I have selected Alipay as the case study for my research because the company has outgrown its online competition in more ways than one. Therefore, there are various ways in which the research leads to utilizing qualitative and quantitative research methods. Also, studies in the field of online markets and transaction are interesting and involving.

Research Objectives

The research objectives were:

  • To identify if the competition has led to the strengthening of Alipay
  • To investigate the role of China business model in the growth of Alipay

From studying the factors that have affected the company, the closest guesses that could have brought the firm into supremacy, I will should that Alipay is the biggest TPP business in the world given subtle facts provided by achieving the two outlined objectives.

The Hypothesis

The first hypothesis to be tested is:

H1a: competition has strengthened Alipay

H1b: China Business ecosystem has contributed to the growth of Alipay

Therefore, the study is two-fold in responding to the research problem outlined in the specific objectives. The conditional statements are offering two stand-alone factors that have affected the growth of Alipay. It is important to mention that in the finding that the two factors had received support from external forces will render the hypothesis incorrect. Therefore, the null hypothesis represents the occurrence of the opposite of the dual factor causatives that explain the growth of Alipay.

H0: A mesh of factors caused the complex growth of Alipay business.

The null hypothesis is meant to present the controversial risks that exist in the online business landscape, showing how Alipay used a combination of factors to win the trust of the online users. The politics involved in the making of the new business model across societies is usually the propeller that works for the advancement of that business (Lovelace, 2015, p. 281). I see the hypothesis as the competition between traditional business models and the modern structures that are continuously forming the new landscape. The aim is to find out exactly how the standards are applicable to online transactions and which new developments have occurred as opposed to the brick and motor industries.

Quantitative Analysis

After collecting data from 2000 online users who randomly filled out the research questions that I uploaded on social media platforms, the results were staggering. In fact, I had to slash some information to stick to the present sample size. The response alone was informative of how the public positively responds to the internet, virtually appreciating the platform. Therefore, even at the beginning of the analysis, I had formed a rational belief that the results would be enlightening. The figures below show the demographic responses regarding gender and age

Fig. 1 Gender response to the survey

Fig. 2 the use of online payment services based on age

From Fig. 2 the largest number of users of online payment services is between the ages of twenty-five years at the age of thirty-three. The trends may change in the future as the individuals who are used to online payment from the age of sixteen are not bound to stop once they get to their forties. Therefore, there is a need for time series data analysis on the research to authenticate such predictions.  

The graph below shows the response to the question of favorite TPP

Fig. 3 Favorite TPP firm

An ideal company receives 38% response on the issue. I believe that the context of the research influences the results here giving the respondents the idea about which is the best firm. However, assuming that the respondents were unaffected by the expectations of the research question, the two largest competitors in the TPP industry Alipay and Paypal represent the real world, the population of business transactions happening online.

Business modeling

In today’s business sceneries, it ‘s hard to breed a monopoly company that controls the entire market (Korea Institute for International Economic Policy (South Korea), 2014, p. 281). The process was standard at the beginning of industrialization, the era that depended on enhancing factors of production. Today, legislation and knowledge of the market trends by almost every potential participant alludes to the ecosystem of international business rules (Turban, King, Lee, Liang, & Turban, 2015, p. 163). Therefore, instead of fending off competitors, modern corporations are welcoming business rivals seeing that the move has a hidden opportunity to increase the industry and improve productivity (Gervasi, 2016, p. 37). For example, the outset of Alipay playing it out with Paypal has provided the opportunity for upcoming firms. As the company’s increase, populations begin to understand the business given that it is not a one-company show (Luo, Chen, Xu, & Zhou, 2013, p. 23).

Statistical analysis

Looking at the data once more provides an interesting trend. The relationship I was attempting to discover is between the success of Alipay Company and the factors that affect it. Putting the statement in a more analytical way is that performance is a function of competition and business environment. The aim is to find out the relationship between the three variables (Eric D. Kolaczyk, 2014, pp. 2-6). The question was on how to measure performance, competition and business environment. Performance units of measurement exist in the level of profits, the competition in market share and the business climate can be allocated a rating as in the table below (Datta & Nettleton, 2014, p. 57). The t-test analysis of the data is as follows

 performanceCompetitionBusiness Environment
best6057801003
good1005740600
worse200340294
worst190140103
t-Test: Two-Sample Assuming Unequal Variances
 CompetitionBusiness Environment
Mean500500
Variance97066.66667154351.3
Observations44
Hypothesized Mean Difference0
df6
t Stat0
P(T<=t) one-tail0.5
t Critical one-tail1.943180274
P(T<=t) two-tail1
t Critical two-tail2.446911846 

The sample size of 2000 limits the outcome of the t-test. However, one can see that the variances are far from being equal in the case (Myers, Well, & Jr, 2014, p. 93). The four observations were a consolidation of the four ratings that the questionnaire provided; best, good, worse and worst.

Qualitative Data Analysis

The section in the questionnaire that required the respondent to explain the experience with the TPP firms provided more insight as to why the quantitative data became skewed towards Alipay. For example,

“Alipay transactions are cheaper and more efficient. I have used several platforms, and Alipay is simply the best in my experience. I do not have to wait several days to clear with them from my home bank account; the transaction is instant.”

More clients of the online transactions gave mere allusions of “it is just wow!”

Others revealed that they do not cut across the platforms; the experience with one of the providers is enough to satisfy their needs. Take the comment below for a respondent who favored Bpay

“I like to have Bpay as my online payment agent because they give me good service and I have not had problems with them so far”

The mood in online transactions is that safety comes first ahead of all the other factors (Paganetto, 2015, p. 242). The clients need to feel that the money linked to their visa will not, in the end, wipe out all that is left in the home accounts. Others, however, who have online businesses have trusted their TPP firms to conduct the transactions for them, making the entrepreneurs think that the result will enhance growth and create a decent reputation for their businesses (Alipay, 2016).

Deep-seated concerns of cyber crime and fraudulent online activities also came up in the comments

“I believe that the online transaction process is secure to the point where the TPP firm gives credit. However, the rate at which hackers are outdoing systems in organizations is alarming making me think twice about a number of transactions I do online.”

Another respondent mentioned terrorism

“I had my fears at first, but Alipay has never disappointed. The method of doing business online has been fast and seemingly secure. Although it is all over the news how cyber-terrorism is the new cause of terror, I cannot say that for sure on my behalf.  Since I have not heard the stories of individuals complaining, I think I will continue using Alipay.”

The international attention given to cyber terrorism has risen in the past decades. The Superpower governments like the federal government are investing heavily in making online activities safe for the societies (Chen, Jarvis, & Macdonald, 2014, p. 34). However, the crimes are still skyrocketing as more cyber-criminals are finding ways to go around the enhanced systems. The problem with the era of knowledge is that everybody knows something about the complex systems and sometimes the degree of understanding in the public domain, where lies the enemies of the public, could be just enough to bring down the security measures put in place (Janczewski & Colarik, 2008, p. 23). The reason for the shift of the transactions to Alipay from competitors is supposedly from the country in which the firm operates. China is apparently a communist state, and the government runs most of the activities, therefore, preventing information leakage to the public (Gustin, 2003, p. 34). Also, the way of the Chinese way of working is crucial to the growth of Alipay business. In the modern business world, security is the single most prioritized factor. Firms that can provide services and protection get a higher market share simultaneously  (Centre of Excellence – Defence Against Terrorism, Ankara, Turkey, 2008, p. 73).

Conclusion

Results

H1a: competition has strengthened Alipay

H1b: China Business ecosystem has contributed to the growth of Alipay

H0: A mesh of factors caused the compound growth of Alipay business.

From the Data analysis, it is clear that the stand-alone factors that H1a and H1b present are false. The success of Alipay could not have been due to the competition alone that the TPP companies provide.Also, the China ecosystem could not have been the only element of success. However, the interplay of both factors contributed to the high strength of the firm. Therefore, the null hypothesis is correct in the case. Additionally, the sentiments from the online users illuminate the reasons why they think that the interactions of the predictive factors are the main causes of market dominance for Alipay. The issues of money security during transactions are a major concern. However, none of the respondents gave a firsthand experience of fraud or malicious activity in the online accounts. From that aspect of observations, I conclude that the security issues have not materialized. The concerns are the result of public fear that probable competitors of motor and brick business models have spread to avert the public from following the paradigm shift.

Objectives met

The research objectives were:

  • To identify if the competition has led to the strengthening of Alipay
  • To investigate the role of China business model in the growth of Alipay

The analysis ascertains that competition played a role in the supremacy of Alipay and that the China business model had a way of affecting the growth of Alipay. Therefore, the factors interplayed to give a stunning performance; they could not work out independently as that would mean that one of the factors was out of the question not effective. Also, I aimed at using the both qualitative and quantitative methods of data collection to achieve the research objectives. The results were parallel, providing the intended confidence in the conclusions. However, the study was limited to a sample of 2000 respondents. More respondents with different segmentation such as nationalities would suffice to give a clearer view of the online business landscape. Also, I feel that the analysis of time series data would have been more forthcoming, giving the fore-taste the changing trends.

References

Alipay. (2016, December 3). Online payment. Retrieved from Cross-Border Website Payment: www.alipay.com

Centre of Excellence – Defence Against Terrorism, Ankara, Turkey. (2008). Responses to Cyber Terrorism. Washington: IOS.

Chen, T., Jarvis, L., & Macdonald, S. (2014). Cyberterrorism: Understanding, Assessment, and Response. New York: Springer.

Datta, S., & Nettleton, D. (2014). Statistical Analysis of Next Generation Sequencing Data. New York: Springer.

Eric D. Kolaczyk, G. C. (2014). Statistical Analysis of Network Data with R. New York: Springer.

Gervasi, M. (2016). East-Commerce: China E-Commerce and the Internet of Things. New Jersey: John Wiley & Sons.

Gustin, J. F. (2003). Cyber Terrorism: A Guide for Facility Managers. Lilburn: The Fairmont Press Inc.

Janczewski, L., & Colarik, A. M. (2008). Cyber Warfare and Cyber Terrorism. London: Information Science Reference.

Korea Institute for International Economic Policy (South Korea). (2014). Financing Economic Integration and Functional Cooperation for Northeast Asia: Toward a Northeast Asian Economic Community. Beijing: 길잡이미디어.

Lovelace, D. (2015). The Rise of China. Oxford: Oxford University Press.

Luo, T., Chen, S., Xu, G., & Zhou, J. (2013). Trust-based Collective View Prediction. New York: Springer Science & Business Media.

Myers, J. L., Well, A. D., & Jr, R. F. (2014). Research Design and Statistical Analysis: Third Edition. London: Routledge.

Paganetto, L. (2015). Achieving Dynamism in an Anaemic Europe. Springer: New York.

Porterfield, J. (2011). Careers as a Cyberterrorism Expert. New York: The Rosen Publishing Group.

Stefano Baldi, E. G. (2003). Hacktivism, cyberterrorism and cyberwar: the activities of the uncivil society in cyberspace. Mexico City: Diplo Foundation.

Turban, E., King, D., Lee, J. K., Liang, T.-P., & Turban, D. C. (2015). Electronic Commerce: A Managerial and Social Networks Perspective. New York: Springer.

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