Financial Analysis- Subject: Finance & Accounting

 



Question 1.

The liquidity and profitability ratios are essential in giving insight into the current

financial performance of Southwest Airlines. The liquidity ratios like the quick ratios and the

current ratio assure whether a firm can settle the current debts obligations. On the other hand,

profitability ratios include the net profit margin, operating profit margin, and the return on total

assets (Hitt et al., 2017). These ratios are critical in ascertaining whether Southwest Airlines is

generating enough profits to finance its expenses.

One can determine whether the calculations yield positive or negative results through the

general rule that any ratios surpassing 1.0 are positive while ratios below 1.0 are negative. In

addition, one can rule out a negative outcome by comparing ratios obtained by the industry

averages. Some ratios that can indicate an area of concern regarding the current Southwest

Airlines strategy include the low liquidity ratios, low profitability ratios, high leverage ratios, or

low activity ratios.

Low liquidity ratios, marked by ratios below 1.0, indicate that Southwest Airlines cannot

meet short-term financial obligations accruing to the firm. Cases of low operating profit margin

and low net profit margin can suggest that the Airline is obtaining reduced income from various

operations conducted by the Airline. The low-profit margin and low net profit margin can also

indicate that the Airline is making losses. Regarding the activity ratios like low total asset

turnover, the ratio suggests that the current Southwest Airlines strategy is underutilizing the

firm's assets. The underutilization of the company assets challenges the ability of the firm to

generate revenues effectively. The high leverage ratios, which are also critical in the evaluation

of the Airline, indicate the firm is operating on negative net worth. These ratios help inform that


3

the financing of Southwest Airlines is through debt. The percentages help ascertain any

ineffectiveness of the Airline's strategy and the likelihood of running bankrupt or seizing to

operate.

Question 2.

A strategic alliance within the field of business refers to a mutual agreement between two

or more firms to work together to achieve shared objectives. The coalition is key to realizing the

shared goals, which would otherwise be unattainable if one firm was to commit to the objectives

independently. Through a strategic alliance that enjoys different benefits, the alliance is also

prone to some risks. If Southwest Airlines were to enter into a strategic partnership based on

profitability ratios, it would be inclined to some risks.

            Some of the risks of forming alliances based on the firm's profitability ratios include the

firm's size, timing problems, and failure to consider long-term strategies of the firm. In regards to

the organization's size, small firms tend to record higher profitability ratios than larger firms.

However, in a real sense, larger businesses are more profitable compared to smaller firms. In

regards to the timing problem, the profitability of some firms is based on seasonal factors. This

situation means that the ratios might be below at different times, while at other times, the

business might record low ratios. The timing risk also indicates that the services or products of

the company might be profitable at a particular time while also at risk of being absolute in the

future. Another threat to forming strategic alliances based on profitability ratios is that

profitability ratios do not consider the prevailing long-term activities of the organization that

might deem it profitable in the future.

Amongst the five ratios, leverage ratios are the most likely to show immediate information to

analyze the effectiveness of a strategic alliance. The leverage ratios outline the sources of the


4

organization's capital, either from shareholder equity or debt. The balance is also essential in

providing a long-term outline regarding the financial position of the organization.

Question 3.

As the COVID pandemic ravages different economies globally, it makes it difficult for

Southwest Airlines to obtain capital to fund an aggressive value-enhancement strategy. The

traveling business has been highly affected by the travel restrictions and risk for spreading the

virus, which has seen a reduction in the number of travelers. Under this type of environment,

creditors are demanding assurances and well-thought strategies that will guarantee the creditors'

support. Capital for financing a value-enhancement plan can, however, be obtained from private

equity loan lenders. Based on the prevailing interest rates, an interest rate of 3% would be better.

The quick ratios will be affected by the inflow of capital as this ratio indicates the capability of

the business to settle short-term debt obligations.

Part Two

Calculations for Southwest Airline Financial ratios based on the financial data posted by

(Southwest Airlines, 2020) annual 2020 report to shareholders.

A1.

 Return Total Assets = Profits after taxes/Total assets

3074\34,588 =0.088

At 8.88%, it indicates that the Airline enjoys a good return on its asset investment. Over 20%

percent ROA would suggest that the firm is excellently utilizing its assets to generate profit.

A2. 

Current Ratios = Current assets/ Current Liabilities (Amount in Millions)

15,173/ 7506 = 2.02


5

A current ratio between 1.5 to 3.0 generally indicates a good percentage indicating the firm's

ability to cater to its current financial liabilities.

A3. 

Debt-to-assets = Total debt/ Total assets

10,111/34,588 = 0.29

The ratio indicates that 29% of Southwest Airline assets have been financed through borrowing.

A4.

 Total Assets Turnover = Sales/ Total assets

4336/34,588 = 0.125

The ratio indicates that Southwest Airlines generated $ 0.125in sales for every $1 in total assets.

This result means that there is inefficiency in the ability of the firm to use its assets to generate

sales.

A5.

Dividend Pay-out Ratio = Annual dividends per share/ After tax earnings per share

0.180/5.44 = 0.0033

The results mean that Southwest Airlines pays 3.3% of its net income to the firms' shareholders

while re-investing 96.75% to the business.

Algorithmic/super power policing in Canada   -  Subject: Political Science

 

 



Summary

Algorithms in policing are applied in Canada, yet the pace is slower than in the U.S. Still, there are questions on algorithms usage in screening. Discrimination cases and criminal charges are still in question. The human rights people are also coming on the front to discuss that just because algorithms are helpful does not mean that these must be allowed, as these lose human rights. However, the algorithms functions have proven to be good in data collection as scattered data about an individual or event at different places can be collected instantly. This information can further be used for predictive measures. The purpose of algorithmic policing is to ensure the better safety of Canadians. 

 

Introduction

The current reflection critically analyzes the algorithm's system implication on the Canadian landscape. The implication has already been started, and artificial intelligence is applied in surveillance and predictive programs. The paper has concerned journals and reports to make an undetailed analysis of the algorithmic system. The algorithmic approach has benefitted Canadian society as mentioned:

"with the rise of algorithmic governance…people experiencing homelessness can be policed and punished."[1]

Thesis statement: Algorithms systems have become an important policy tool in the Canadian policing system; however, the human rights charter is not explainable as the rights to privacy, equality, and liberty are violated.

 

One Concept Learned From Topic

Algorithmic policing in Canada will help to monitor crimes more closely by taking a good grip on criminals through tracking Algorithmic data. Social media communication comments and posts, including facial and personal tracking, may help reduce crime and increase city safety measures. The algorithm in policing is shown as a positive side for policing departments; however, there are threats to human rights as humans are no safer concerning privacy, livery, and equality. 

 

Significance of the Topic

Algorithmic policing is revolutionizing the informational world as people are classified at regional, provisional and federal levels. The information about the people scattered in different private and public sectors is now available in one place. This is more or less like a surveillance technology, which has been legalized by now via legislation. Algorithmic technologies are legalized to collect disparate information as mentioned:

"provide an alternative understanding and implementation of citizenship, belongings, rights, ethics, morality, human agency, security and borders."[2]

 This is not only about data collection; the data can also be used to make trends and analyze the future. The police services are holding some severe deleterious cases, and the instances of races are resolved by surveillance technology. The unfairness of individuals can be predicted, and due to this, professionals have raised concerns that surveillance technologies are working within the ideal limits of the law.

Views from Other Scholars

Different implications of algorithmic policing systems are observed in other parts of Canada. Departments like the Toronto Police Service and Saskatoon Police Service collaborate with ministries to make predictive analytic labs in different regions, including Vancouver. The purpose is to ensure better safety measures by using Algorithmic work and c extension to hub for community safety. The at-risk individuals can also be identified. The Calgary police service also uses such services along with the Ontario Ministry of the attorney general. The pretrial risk assessment tool is also applied, and technology helps decision-making. The paper summarizes the linkage between university machine learning projects and risk assessment instrument development to release the right decisions for young offenders. The majority use surveillance technologies such as license plate readers, and the Calgary police service uses them for social media surveillance. Chat room scraping and facial recognition technology is applied by almost all police station in Ontario[3]

In addition, Algorithmic policy technology has helped in two ways, i.e. making predictions or finding trends and increasing surveillance. The human rights implications draw inferences; these methods can be location-focused or person-focused. The methods predict the individual likelihood of engaging in any illicit activity. Alike the authors mentioned above, the report of Kenyon has also said the types of surveillance technologies, i.e. facial and social media surveillance technology, along with many others. Canadian law enforcement agencies are using it to preoptic the policing methods. The program's names are divided into GeoDASH algorithmic policing systems, and the Toronto police service utilizes it as Environics Analytics. Person-focused algorithm policing is a new technology mentioned in detail in this paper, and there is police predictive analytic land in Saskatchewan police stations. Social media content and telecommunications information are also used in person-focused Algorithmic policing technologies. Though it is debated if civil liberties are violated this way, in reality, the international human rights law completely protects the Canadian charter of rights and freedom. Algorithmic functions may endanger the right to privacy and rights to freedom of expression along with rights to livery and equality; however, Algorithmic technology is still expanding by the time[4]

Analyzing it from human rights expert's point of view, it is not wrong to say that human rights violations must not be justified as explained. This is a fact owing to development in technology. Canadian police stations have applied this technology, and A.I. has accounted for 48 law enrolment agonies across Canada. The correction systems are utilized in deciding bail and parole as well. The case of Nijeer Parks is famous in which consigned lived in jail for 11 days before going on a pretrial monitoring program. However, human rights are at risk due to a lack of transparency. The peer review journal has raised serious questions about the inaccuracy of the Algorithmic system and discriminatory-based questions. Kate knows that Ontario police, due to false facial recognition, arrested a person, and this was an act of racialized. As mentioned in a peer reviews journal:

Can police officers serve as the harbingers of human rights in a world that desperately needs it?[5]

Outstanding Questions

Several questions can be anticipated, such as whether law enforcement agencies are transparent in utilizing algorithmic policy or not and also argue about the working of surveillance technologies made under the jurisdiction of the law. It is essential to note that the algorithmic policing that defines human rights character and what explanations can be given in this instance is also an important factor to consider. Historic police data sets and current Algorithmic policing technologies are under the control of the police; thus, who will monitor the department of police and how federal, regional, or provisional governments will limit the role of the police is also a serious matter of discussion.

 

Conclusion and Potential Areas for Improvement or Future Research

Public information is not shared regarding Algorithmic matters. The policing technologies used by law enforcement agencies are, however, the other applications of this policy have not been explored yet. It can also be used in other matters of life; however, those matters are not considered yet. Moreover, the statistics related to dark net websites and location-based services have not been discussed yet. The information must be publicized so that the people may know that life has been revolutionized by Algorithmic policing now. No public data is available in this instance[6]

  

     References

Arrigo, Bruce A., Brian G. Sellers, and Faith Butta. "Introduction: The Ultramodern Age of Criminology, Control Societies and 'Dividual' Justice Policy." The Pre-Crime Society, 2021, 1–14. https://doi.org/10.1332/policypress/9781529205251.003.0001.

CHRC. "Annual Report - Algorithms in policing." (2021). https://2021.chrcreport.ca/algorithms-in-policing.html.

Humphry, Justine. "Policing Homelessness: Smart Cities and Algorithmic Governance." Homelessness and Mobile Communication, 2022, 151–81.

"Kate Robertson, Cynthia Khoo, Yolanda Song, "To Surveil and Predict: A Human Rights Analysis of Algorithmic Policing in Canada [2020 C4EJ 67]." C4E Journal, October 10, 2020. https://c4ejournal.net/2020/10/06/kate-robertson-cynthia-khoo-yolanda-song-to-surveil-and-predict-a-human-rights-analysis-of-algorithmic-policing-in-canada-2020-c4ej-67/.

Kenyon, Miles. "Algorithmic Policing in Canada Explained". 2020. Algorithmic Policing in Canada Explained - The Citizen Lab

Marina, Peter, and Pedro Marina. "Police, Power, Agency, and Human Rights." Human Rights Policing, 2022, 36–59. https://doi.org/10.4324/9781003220282-4.

Pekic, Alexander. "Toronto the Good? the Access T.O. Policy - Making Toronto a Sanctuary City," 2021. https://doi.org/10.32920/ryerson.14660754.v1.

Singh, Shawn. "Algorithmic Policing Technologies in Canada". Manitoba law journal. 44,6. 2021.



[1] Humphry, Justine. “Policing Homelessness: Smart Cities and Algorithmic Governance.” Homelessness and Mobile Communication, 2022, 151–81. https://doi.org/10.1007/978-981-19-3838-2_6. 1

 

 

[2] Pekic, Alexander. “Toronto the Good? the Access T.O. Policy - Making Toronto a Sanctuary City,” 2021. https://doi.org/10.32920/ryerson.14660754.v1. 1.

 

[3] Kate Robertson, Cynthia Khoo, Yolanda Song, “To Surveil and Predict: A Human Rights Analysis of Algorithmic Policing in Canada [2020 C4EJ 67].” C4E Journal, October 10, 2020. https://c4ejournal.net/2020/10/06/kate-robertson-cynthia-khoo-yolanda-song-to-surveil-and-predict-a-human-rights-analysis-of-algorithmic-policing-in-canada-2020-c4ej-67/.

 

[4] Kenyon, Miles. “Algorithmic Policing in Canada Explained”. 2020. Algorithmic Policing in Canada Explained - The Citizen Lab. 1

[5] Peter Marina and Pedro Marina, “Police, Power, Agency, and Human Rights,” Human Rights Policing, 2022, pp. 36-59, https://doi.org/10.4324/9781003220282-4. 47.

[6] Singh, Shawn. “Algorithmic Policing Technologies in Canada”. Manitoba law journal. 44,6. 2021.1.

  

Netflix

 



Table of Contents
1 CHAPTER 1: INTRODUCTION 2
1.1 Background 2
1.2 Company Description 2
1.3 Problem statement 2
1.4 1.4 Research question 3
1.5 1.5 Organization of report 3
2 References 4

CHAPTER 1: INTRODUCTION
1.1 Background
This study, which was conducted as part of a Business Research 2 class at Amsterdam University of Applied Sciences, examines the factors that led to Netflix's significant decline in revenue as well as the company's decision to let go of some of its employees as a result of this decline. We were given a collection of five different case studies to select from, and we were instructed to choose one of them to utilize as a springboard for a more in-depth inquiry into the issue, its roots, and any potential solutions.
1.2 Company description
Netflix, Inc. is a production company and internet streaming service based in Los Gatos, California. Reed Hastings and Marc Randolph founded Netflix, Inc. in Scotts Valley, California in 1997. Through distribution agreements and Netflix Originals, it gives its users access to a collection of movies and television series (Lobato & Lotz, 2020). The global firm provides users with access to streaming media, DVDs, and television shows on demand through the internet. Specifically, Netflix enables users to make full use of the internet to view an almost infinite library of television series and motion pictures (Evens, et al., 2021). In addition, the business has its own movie collection that subscribers may access and see instantaneously on their computers. Over 93 million people across 190 countries are Netflix members (Widia, et al., 2021). The firm is now the largest provider of internet television services worldwide, with operations in over 193 countries.
1.3 Problem statement
According to BBC News (2022), Netflix announced another round of layoffs at the beginning of this year as the firm continues to struggle with poor growth and increasing competition. Following the layoff of 150 employees in May, the streaming powerhouse said in June that it would lay off another 300 employees (about 4% of the workforce), mostly in the United States (Widia, et al., 2021). This comes after the company reported its first loss in subscribers in more than a decade in April. In order to grow, the firm is contemplating introducing a freemium version supported by adverts and is restricting password sharing. Netflix said it would continue to spend aggressively in the company and has implemented these steps to align expenditure growth with slower revenue growth. The corporation also said it will continue to hire in other sectors. With 220 million members, Netflix is the market leader in streaming, but it has faced fierce competition in recent years from the likes of Disney Plus and Amazon Prime Video (Meng, et al., 2022). In addition to losing customers, the company has recently enacted a series of price increases in the United States, the United Kingdom, and across the world.
Following a 200,000 decline earlier this year, the business expects another two million subscriber losses in the three months ending in July. Even in the United States, where overall streaming subscriptions have stayed steady (unlike in the United Kingdom), Kantar research firm polls consistently mention cost savings as the most prevalent reason for canceling streaming services (kantar, 2020).
1.4 1.4 Research question
1. Why Netflix is suffering from financial difficulties and firing employees?
1.5 1.5 Organization of report
The following is an overview of some of the chapters that will be covered in the next three chapters that are all connected to Netflix:
In chapter two, we will lay out the theoretical and conceptual frameworks that are necessary to answer the research question that was posed in chapter 1.4 of this report. Additionally, we will provide summaries of two articles that separately address this instance and issue.
The third chapter will provide a descriptive analysis of the variables that were used in the study, as well as the findings and theoretical implications of that analysis. Finally, the conclusion chapter will provide an overview of the data and how it connects to the research question and problem statement, as well as describe the key findings of the article and examine the issue that was brought up in the first chapter.

2 References
BBCNews, 2022. Netflix cuts 300 more jobs after subscriptions fall. [Online]
Available at: https://www.bbc.com/news/business-61914167
[Accessed eo JUNE 2022].
Evens, T., Henderickx, A. & De Marez, L., 2021. Generation stream: the audiovisual repertoire of teenagers. Journal of Broadcasting & Electronic Media, 65(2), pp. 185-204.
kantar, 2020. Netflix is winning the video streaming wars. [Online]
Available at: https://www..com/north-america/inspiration/tv/netflix-is-winning-the-video-streaming-wars
[Accessed 04 March 2020].
Lobato, R. & Lotz, A., 2020. Imagining global video: The challenge of Netflix.. JCMS: Journal of Cinema and Media Studies, 59(3), pp. 132-136.
Meng, H., Zhang, J., Zhang, Y. & Zhou, W., 2022. An Assessment about the Business and Profitability Analysis for Netflix. In 2022 2nd International Conference on Enterprise Management and Economic Development (ICEMED 2022, pp. 467-477.
Widia, F., Rosanensi, M. & Rahmawati, L., 2021. Netflix's Strategy to Dominate the World's Entertainment Media Market After the Death of Blockbuster. JBTI: Jurnal Bisnis: Teori dan Implementasi, , 12(3), pp. 155-171.
P.S: Please share your views and thoughts in the comment section.
Thank you so much for reading.
Any queries please email at
info@writers24hr.com


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