bluuebunny/crossref_metadata_2025 huggingface dataset:
Sistem Pendukung Keputusan Untuk Pemilihan Hotel di Kota Medan Dengan Menggunakan Metode Simple Additive Weighting
Authors: Tjokro Stanley , Romindo Romindo
Published: May 2023

The increasing number of tourist locations in the city of Medan has led to growth in the arrival rate of tourists from abroad, and this has caused the hotel business to also increase rapidly. Even though the hotel business is increasing rapidly, not all tourists want to choose any hotel in the city of Medan, because tourists will still pay attention in terms of price, service, location, stars, and cleanliness, even though there are at least 177 hotels in the city of Medan. To overcome the problem of choosing the right hotel, a decision support system will be made to assist users in selecting hotels, and the system will be designed using the Simple Additive Weighting (SAW) method, which will produce alternatives according to the criteria, values, and weights that have been determined. determined by the users. In collecting data for the system, methods such as surveys, field observations, interviews, and literature studies based on official documents will be used. This website-based decision support system generates output in the form of hotel rankings from highest to lowest level.
Selection of parents and segregating populations of carioca common bean resistant to Fusarium wilt
Authors: Cavalheiro Sâmela Beutinger , Melo Leonardo Cunha , Souza Thiago Lívio Pessoa Oliveira de , Pereira Helton Santos
Published: May 2023

Fusarium wilt (Fusarium oxysporum f. sp. phaseoli) is one of the most common diseases in the common bean (Phaseolus vulgaris) crop, and the most viable alternative for its control is the use of resistant cultivars. However, the number of “carioca” cultivars, the most important commercial group in Brazil, which has a good level of resistance to this disease, is still low. To obtain populations with a higher degree of resistance, seven parents with different levels of resistance to Fusarium and which produce carioca grains were crossed in a complete diallel design. The 21 segregating populations obtained were evaluated in the years/generations 2012/F3, 2013/F4, and 2014/F5 in experiments in Santo Antônio de Goiás, GO, in the winter crop season (sowing in May), together with the check cultivars BRS Notável (resistant) and BRS Cometa (susceptible) in an area naturally infested with Fusarium oxysporum f. sp. phaseoli, under a center pivot irrigation system. Reaction to Fusarium wilt, yield, and 100-seed weight were evaluated. Additive and non-additive effects contributed to control of reaction to Fusarium wilt, yield, and 100-seed weight. The statistically negative general combining ability ( ) estimates for BRS Notável (-0.51), CNFC 15872 (-0.20), IPR Juriti (-0.18), and BRSMG Talismã (-0.13) indicate that these parents are recommended for obtaining populations more resistant to Fusarium wilt. Among them, cultivar BRS Notável also showed a statistically positive  estimate for grain yield (87.90). Among the parents recommended for resistance to Fusarium wilt, cultivars IPR Juriti (0.99) and BRS Notável (0.23) are those that most contributed to obtaining populations with larger-sized beans. Cultivar BRS Notável is the most promising parent for participation in new crossing blocks, showing non-zero  estimates for all traits, favoring an increase in resistance to Fusarium wilt, yield, and 100-seed weight. Populations BRS Notável / CNFC 15872, BRS Ametista / BRS Notável, BRS Notável / BRSMG Talismã, and BRS Ametista / BRSMG Talismã showed good mean values for reaction to Fusarium wilt, yield, and 100-seed weight and at least one parent with a good general combining ability estimate for resistance to Fusarium wilt. These four populations are promising for obtaining lines with superior performance for resistance to Fusarium wilt, yield, and larger-sized grains.
Iron-induced Hypophosphatemic Osteomalacia—An Atypical Case of Bilateral Femoral Stress Fractures
Authors: Kancherla Kiran , Constantin Harry , Kanawati Andrew , Graham Edward
Published: May 2023

We present a case of a 61-year-old healthy man who had bilateral femoral neck insufficiency fractures attributed to repeated iron transfusions, causing iron-induced hypophosphatemic rickets, requiring surgical intervention. Atraumatic insufficiency fractures present a diagnostic dilemma in orthopaedics. Chronic fractures with no acute precipitating trigger can often go unrecognized until complete fracturing or displacement occurs. Early identification of the risk factors in conjunction with a comprehensive history, clinical examination, and imaging can potentially avoid these serious complications. Atraumatic femoral neck insufficiency fractures have been sporadically reported in the literature, often unilateral and attributed to the use of long-term bisphosphonates. Through this case, we elaborate on the relatively unknown link between iron transfusions and insufficiency fractures. This case highlights the importance of early detection and imaging of such fractures from an orthopaedic perspective.
Frequency of Work-Related Neck Pain in Freelancers
Authors: Ghaffar Tamjeed , Fatima Tyyiba , Azfar Hanan , Shouket Mehwish , Jahanara . , Javed Hina , Bin Siddique Usama , Khalid Amna
Published: May 2023

The use of electronic devices like tablets, smartphones, desktop and laptop users has been increased to a lot of extent from past few years. So, the workers are more prone to be affected by neck pain, shoulder pain and other forms of musculoskeletal problems, due to lack of awareness about bad posture and ergonomics about workstation in their environment. Objectives: To find out the frequency of work-related neck pain in freelancers. Methods: It was a cross-sectional study containing of questionnaire based online survey in which the data were collected by asking the participants to fill the form online. There were 100 participants who were actively working in this field from last 6 months and all of them were having neck related problems. The data was analyzed using statistical packages of social sciences and different tests were performed including Chi-square and standard deviation and square tab. Results: Statistics show that 27% of freelancers were suffered from neck and shoulder pain, 43% suffered from neck pain along with other symptoms and followed by headache in which 34% rarely suffered from headache, 38% suffered from moderate headache and 28% from severe headache. Emotional findings show that 44% faced frustration, anger and sadness to some extent. Conclusions: The neck discomfort due to working online increases with sitting still for more than 1 hour, making physical activity difficult as well as making lifestyle change. A significant Association was found between lifestyle changes due to neck pain, neck pain intensity with online working.
Management of weight loss in a patient with Prader-Willi syndrome with satietogenics: a case report
Authors: Pina Neto José Marques , Madureira Larissa Erikarla Negreiros , Palhares Felipe Da Paixão Martinez , Pimentel Rodrigo Fernandes Weyll , Maduro Isolda Prado de Negreiros Nogueira
Published: May 2023

Objective: To report the evolution and therapeutic approach in a patient with PraderWilli Syndrome (PWS) associated with literature data assessment with a focus on the pharmacological treatment of obesity in patients with this pathology, since there are currently not many studies that contribute or name a strategy with the use of satietogenics. Methods: The present study was elaborated according to the rules of CARE case report. Due to the cognitive impairment present in the syndrome, the patient’s mother was first contacted about the writing of this paper and was given consent through the signing of the Free and Informed Assent Term for this paper. The patient was treated at a hospital-adjacent Nutrology outpatient clinic in 2019. Case Description: YSP, 20 years old, diagnosed with PWS and Grade III obesity (initial BMI of 55.4kg/m², 140kg) attended the Nutrology outpatient clinic of Adriano Jorge Hospital Foundation – FHAJ in 2019 under referral from a third party, and his companion (relative) reporting hyperphagia and poor school performance, initially without a nutrition plan, during follow-up, nutritional guidance and multi-professional care have been initiated. Results: During the follow-up of the years 2019-2021, resulting from the SARS-CoV-2 pandemic in Brazil and the consequent confinement, the patient presented worsening anxiety and hyperphagia, evolving with increased binge eating and discontinuation of physical activities and diet adherence. During the follow-up in the same period, there were 03 returns denoting weight maintenance, later (2021) the use of on-label (Sibutramine), off-label (Fluoxetine), and Metformin medications were associated with the therapeutic regimen for obesity, due to evidence of insulin resistance. Final considerations: The patient evolved with progressive weight loss and better adherence to the food plan and physical activities.
Sholawat Uhudiyah dalam Meningkatkan Self Esteem Perspektif Psikoterapi Islam di Yayasan Kyai Syarifuddin Wonorejo Lumajang
Authors: Nafissatul Zaqiyah
Published: May 2023

Peneliti memilih pemaparan teori John W Santrock mengenai beberapa indikator Self Esteem, karena John W Santrock merupakan Penulis Buku Psikologi Yang Menjelaskan Tentang Perkembangan Manusia yang  telah banyak digunakan pada penelitian-penelitian lainnya. Nama John W Santrock menjadi populer karena John merupakan anggota dewan redaksi Perkembangan Anak dan Psikologi Perkembangan. Penelitian ini, menggunakan pendekatan kualitatif. Teknik pengumpulan data dengan teknik wawancara, dokumentasi dan observasi. Hasil penelitian dapat disimpulkan bahwa Sholawat Uhudiyah dapat meningkatkan Self Esteem (Harga diri, rasa bangga, kepuasaan, kelegaan) bagi seseorang  yang mendengar maupun melantunkan Sholawat tersebut. Sholawat uhudiyah adalah sebuah bentuk eksplorasi dengan menggunakan syair-syair (perpaduan antara ayat suci Al-Qur’an dan sya’ir pujian kepada Nabi) yang dilantunkan dengan suara-suara manusia. Sedangkan suara manusia merupakan sebagai instrumen penyembuhan (terapi). Terapi yang dimaksud adalah terapi kesehatan mental yang didapat dari Al-Qur’an, As-sunnah, orang-orang yang shalih dan ilmu pengetahuan dengan basic psikoterapi Islam.
Pengaruh Fasilitas, Promosi, Harga dan Faktor Demografi Terhadap Keputusan Wali Santri dalam Menentukan Pendidikan Anak di PPS. Kyai Syarifuddin Wonorejo-Lumajang
Authors: Siti Lailatul Fitriyah
Published: May 2023

Penelitian ini bertujuan untuk menganalisis faktor-faktor yang berpengaruh terhadap keputusan wali murid dalam menentukan pendidikan anaknya. Variabel independen dalam penelitian ini ada empat variabel yakni: a) Fasilitas, b) promosi c) harga dan d) faktor demografi. Variabel dependen dalam penelitian ini adalah keputusan. Variabel X1 menggunakan perspektif teori Tjiptono sedangkan variabel X2 menggunakan perspektif teori Promosi Philip Kotler dan variabel X3 menggunakan perspektif teori Philip Kotler dan yang terakhir variabel X4 menggunakan perspektif teori David yaitu faktor Demografi dengan jumlah dua dimensi. Penelitian ini menggunakan pendekatan penelitian kuantitatif. Populasi penelitian ini adalah wali santri Pps. Kyai Syarifuddin berjumlah 798 orang, teknik pengambilan sampel yang digunakan adalah metode purposive sampling dan diperoleh sampel 70 orang. Teknik pengumpulan data yang digunakan menggunakan kuisioner. Metode analisis data yang digunakan adalah analisis regresi linier berganda. Hasil penelitian ini pengujian signifikasi koefisien korelasi diperoleh nilai koefisien R square = 0,535 sehingga dapat disimpulkan bahwa pengaruh atau hubungan antara variabel independen (fasilitas, promosi, harga dan faktor demografi) dengan variabel dependen (keputusan) adalah sebesar 53,3%, artinya memiliki pengaruh yang besar.
Frailty in peripheral arterial disease
Authors: Welsh SA , Martin P , Pathmanathan S , Hussey K , Brittenden J , Orr DJ , Quinn T
Published: May 2023

It has been consistently demonstrated that frail vascular patients have poorer outcomes compared with their robust counterparts.1 Consideration of frailty is particularly important, not only as our population continues to age but as advances in anaesthetic, surgical and endovascular techniques are enabling a broader range of interventional options for those people who may have traditionally been labelled as unsuitable for surgery.2 Frailty has implications for health and social care at the micro and macro level, and failure to consider the differing needs and natural histories of people living with frailty could result in avoidable harm and suboptimal resource allocation. National guidelines recognise the growing urgency in the need to recognise and manage frailty, yet standardised methods for this have not been identified and agreed upon.3 Despite undeniable prognostic value, the aetiology and pathophysiology of frailty in peripheral arterial disease (PAD) remains poorly understood, albeit new data are emerging. This has challenged a uniform approach to assessment and management. This editorial considers the theories of frailty and applies these to the assessment and management of patients with peripheral arterial disease.
Bringing mycobacterial secretion inhibitors to maturation
Authors:   , Ho Quang Tri Vien
Published: May 2023

Tuberculosis caused by Mycobacterium tuberculosis is one of the deadliest infectious diseases worldwide. With the increasing rate of drug-resistant Mycobacterium tuberculosis isolates, there is an urgent need for development of novel effective drugs to combat against this disease.
In this thesis, we initially introduced about the type VII ESX-5 system of Mycobacterium tuberculosis and explained why this system is a good candidate for development of new anti-tubercular drugs. We established an assay to screen for potential compounds targeting this ESX-5 system. In the end, two hits were selected and further characterized.
Moreover, special properties of anti-tubercular drugs including whether these drugs are prodrugs or their in vivo activities were further investigated and emphasized. In the end, we identified potential anti-tubercular compounds with promising activities that can progress into further pre-clinical studies, clinical phases and possible treatment of human tuberculosis in the future.
Co-creating value between retail consumers and retailers
Authors: Li Meiyi
Published: May 2023

This paper explores the concept of co-creating value between retail consumers and retailers. Co-creation of value is a collaborative process where consumers and retailers work together to create value for both parties. In the context of retail, co-creation of value involves the exchange of information, knowledge, and resources to develop products and services that meet the needs and preferences of consumers. The paper first provides a comprehensive overview of the concept of value co-creation, including its historical development and theoretical foundation. Then, it focuses on the specific context of retail and the factors that enable and hinder co-creation of value between consumers and retailers. The paper also examines the various strategies that retailers can use to foster co-creation of value with consumers, such as customer feedback, crowdsourcing, and social media engagement. It concludes by highlighting the benefits of co-creating value for both consumers and retailers, including improved customer satisfaction, increased loyalty, and higher profitability. It also offers practical implications for retailers on how to successfully implement co-creation of value strategies and improve their relationship with customers.
Portfolio Analysis of Different Industries under Constraints
Authors: Liang Shuhan
Published: May 2023

Building an effective portfolio is critical for it can decrease investment risk and the impact of fluctuations in the share price of a single firm. This paper selects five example stocks from diverse industries, using the mean variance model and the Index model to estimate the best combination of these stocks, then adds five significant limits to both models to see how components in the real financial market effect the portfolio. The Minimal Variance Frontier is used to compare the impact of five constraints in this paper, and it is discovered that different models have different effects under the same constraints, constrained portfolios have less volatility than unconstrained portfolios, and not allowing short positions reduces risk while also lowering the overall return rate. The findings in this paper are valuable to the industry's research on the best allocation of financial assets and can benefit financial market investors.
Constructing An Optimal Portfolio Based on Markowitz And Nonlinear Programming Methods
Authors: Jiao Suning
Published: May 2023

Portfolio construction is extremely essential for the trading of stocks construct an optimal portfolio is one of the frequently asked questions in the financial sector as it is directly related to the profits of investors. While some people use financial theory only in their investments and do not combine it with mathematical methods. So, we explore how to construct an optimal portfolio through financial and mathematical models and theories based on the analysis of stock prices of some Chinese companies in the past year. We find that the stock of Xi'an Catering Co., Ltd and Joyvio Group Limited is extremely attractive for us, at 91 percent and 6 percent of our cash invested respectively. The Sharpe ratio is 0.09948, which means the reward of unit risk is 0.09948. So, we need to invest more in stocks with higher expected returns compared to others. Because it could bring more profits for us. Usually, the companies with an increased stock price during a period will satisfy the requirements as they have better development potential. Our study can also be improved by using the Fama-French three factors model and Machine learning.
Predicting Click Behavior Based on Machine Learning Models
Authors: Zhou Xiaoyu
Published: May 2023

As businesses spend a great amount of advertising dollars each year and hope to achieve marketing objectives, advertising practitioners often advise them to understand customer behavior and customize target audience. This study gains information about click behavior and uses those to help brands make targeting decisions. In the study, a predictive analysis on whether a viewer clicks on the ad was conducted to build a model that forecasts user clicks and forms a list of potentially interested viewers. The predictive model included variables that mainly contained viewer information, such as ‘Daily Time Spent on Site’, ‘Age’, ‘Area Income’, etc., and were chosen based on correlations with each other. After splitting the samples with a 7:3 ratio, machine Learning algorithms, including Logistic Regression, Random Forest, and Support Vector Machine, were used to build the model. Each model was implemented on both datasets, and with no sign of overfitting shown, Support Vector Machine model outperformed other models with a 97% prediction accuracy on training data and a 96% prediction accuracy on testing data. With this model being able to generalize well on new data points, businesses can start implementing it to filter out the audience who will click on an ad and show interests in the brand/product. This deeper understanding of the audience will help improve targeting for campaigns with different objectives and achieve higher advertising efficiency and effectiveness.
Prospect Forecast and Rectification Strategy of American Takeout Industry
Authors: Kong Xiangyu
Published: May 2023

The global pandemic has a serious impact on economic and social development of all countries. The production and demand of many industries have greatly shrunk. However, the takeout industry in the United States is an exception. Under the influence of COVID-19, the supply and demand of American takeout industry have increased significantly compared with that before the pandemic. The market has become increasingly hot. Once the current market environment changes, it is uncertain whether the American takeout industry can continue to be popular. Due to this reality, the research explores the market trend of American takeout industry in recent years, and forecasts the future takeout market. The study also analyzes whether the American takeout market should follow the Chinese market’s approach. The research reveals that there are several disadvantages in the American takeout market in terms of labor cost and the price of buyers. To address these issues, the study develops new sale method through several ways, for example, reducing the buyer's cost of delivery fee, making the delivery fee paid by the seller as well as by the platform. Moreover, the platform can send vouchers to the buyers together with seller.
Research on Financial Strategy and Prospect of Internet Company: Taking Tencent as Evidence
Authors: Ke Jinbei
Published: May 2023

In the new economic era, business model innovations emerge endlessly, especially with the entry of the Internet, a variety of business models and companies associated with the Internet appear. By analyzing the overall situation of the industry, market, revenue and profit that Tencent has developed into finance, this paper discusses the comparability and effectiveness of Internet economy, and expounds the difficulties and deficiencies of Internet companies in the financial development strategy, and gives examples of Tencent's financial development strategy divided into several main fields or levels. Based on this analysis of the Internet economy for the company's development prospects and strategic basis. The data of Tencent were sorted out from five aspects of Tencent's development history, general situation, business categories, business models and valuation difficulties, and the background of the empirical study was introduced. As the Internet company with the highest market value in China, Tencent has abundant historical data from both financial and non-financial indexes. Empirical analysis is applicable to establish a good value evaluation system, which indicates that the valuation of Internet companies should pay more attention to non-financial indexes such as the size and business type of Internet companies.
Decision-Making: Human and Machine
Authors: Ma Yunqi
Published: May 2023

Background: in modern society, decision-making happens everywhere and anytime. There are many factors influencing people in making decisions, which will be analyzed with examples in the paper. Technologies also help humans in making decisions: merits and demerits of them are briefly introduced with a discussion of the example in a hedge fund in which there have already been technologies used in the industry for years. Method: qualitative research -- case study research and record keeping by searching and reading articles written by scholars or official institutions, and reviewing and analyzing them to have a conclusion on the matter relating to humans and machines’ performance in decision-making. Conclusion: By comparing the merits and demerits of humans and machines in the decision-making process, it can be concluded that cooperation between humans and machines may lead to better results at a time since they have a supplementary relationship. In other words, machines might be excellent in the fields in which humans are weak, and vice versa, which makes the collaboration of them to be the best solution so far.
Business Analysis of Walmart - Success Factors and Challenges
Authors: Ren Xiaolong
Published: May 2023

Nowadays, people will be more inclined to go shopping online rather than opting for offline shopping. Walmart, the world's No.1 for 7 years in a row in the previous years, dropped in the ranking last year. Although part of the reason is the new crown virus, also is it can represent the decline of offline stores and the rise of online stores. This research will analyze the current general environment market by studying the success factors and challenges of Walmart. Through the research, we can find that Walmart's success factors mainly focus on its unique localization and differentiation, Sam's Membership Supermarket, and the powerful information supply chain system behind Walmart's high efficiency and low cost. At the same time, Walmart is currently facing many challenges, such as the super APP, some online products that cannot meet the demand, and the single payment method. All of these can be analyzed to show that Walmart is not prepared for online stores in the current context of the big data era, which has led to Walmart's current declining situation.
Customer Churn Prediction Based on the Decision Tree and Random Forest Model
Authors: Zhao Shiyunyang
Published: May 2023

The rate at which customers discontinue utilizing a company's services during a predetermined time period is known as the customer churn rate, also known as the attrition rate. Hence, developing a prediction model to predict the potential churn customers will generate an early alert for the company to provide them with better service. This study is divided into two main parts: dealing with a dataset about customer behaviors in a bank and building churn prediction models using machine learning algorithms. The data preprocessing part includes dataset description and some adjustments on original dataset to make it accessible for analysis, including deleting unimportant feature and adjusting feature names. Then the study apportions the modified dataset into train set and test set with an 80-20 split. Next, the study imports two kinds of machine learning algorithms, random forest classifier and decision tree classifier, to build churn prediction models. In each model, the study first performs feature selections and visualizes feature importance in bar graphs. Then the study tests each model on testing set and visualizes model performances using confusion matrices and accuracy scores. The results show that both models get most predictions correct while random forest model has a better performance due to its higher accuracy score of 91%.
Analysis of Stock Price and Price Movement Prediction based on Machine Learning Models for E-Hualu
Authors: Han Linyuan
Published: May 2023

At present, many multi-information input models are used in various stock forecasts, but for most Chinese investors, it is difficult to obtain effective stock information, and most of them buy and sell stocks only based on stock trends and stock prices. Therefore, in order to get better prediction results based on basic information, the author tries to use some machine learning methods to predict E-Hualu in the Chinese stock market, and the aim is to select the best prediction model. In this study, five machine learning models were applied to predict stock prices, namely linear regression, SVR, random forest, XGBoost, and LSTM, then the close price of the previous 14 days were converted into the input of each model to estimate the close price of the next day. After the price prediction results were obtained, secondary processing was carried out, transforming previous outputs into trend prediction results. The research results indicate that the LSTM model has outstanding performance in both price prediction and trend prediction. Hopefully, the results of this research can provide some suggestions for investing in E-Hualu.
Stock Prediction of TSMC and Intel using Machine Learning
Authors: Zhang Ningjing
Published: May 2023

The advancement of communications, computers, healthcare, military systems, transportation, renewable energy, and numerous more uses is made possible by semiconductors, which are a crucial part of electronic equipment. Semiconductors have been experiencing a shortage due to various reasons. Thus, the increasing demand for chips has attracted countless people to invest in the semiconductor industry. Intel Corporation and Taiwan Semiconductor Manufacturing Company Limited (TSMC) are two companies that can be said to be dominating the industry currently as they have been making very advanced chips. As two giant suppliers in the semiconductor industry, they are close substitutes and competitors. This essay is going to evaluate Intel and TSMC s’ stocks for investors by using the method of machine learning to estimate and predict the future trend of the two stocks. The two models that will be used in the essay are the Linear model and the Long Short-Term Memory model (LSTM), showing the outcome of prediction and determining which stock is better for the investment.
The Analysis of Bitcoin’s Price Fluctuation
Authors: Han Ziling
Published: May 2023

The objective of this article is to examine Bitcoin's price fluctuations. To uncover Bitcoin's dramatic movements and unpredictability, I'll depict the cryptocurrency's price data using a variety of visualization tools, including Python. Additionally, we will discuss the causes for Bitcoin's past increase and rise in 2021, such as how the insane attention generated by certain news stories will fuel Bitcoin's ascent. Bitcoin provides investors with a more profitable investment opportunity, but it is also an exceedingly dangerous one.
Optimizing the Performance of Factor Analysis Model by Using Clustering——Take Electric Vehicle as an Example
Authors: Wang Ziyu
Published: May 2023

As people pay more attention to environmental protection, electric vehicles occupy a larger share of the entire automobile sales market. However, due to the rapid development of electric vehicles and their structure being quite different from that of traditional fuel vehicles, many potential consumers still have some misunderstandings when buying electric vehicles, they still use the logic of traditional fuel vehicles to examine electric vehicles. This paper uses factor analysis and EM cluster analysis to analyze the data on electric vehicles (EVs) and try to maximize the information on EVs at a smaller cost. This paper first introduces the ideas of factor analysis and EM cluster analysis as well as the data related to EVs and then states the generated models. Then, analyzes the data of electric vehicles using two methods respectively and obtains the analysis results. Finally, this paper combines the two analysis methods to get the final model with higher universal applicability and pertinence.
An Assessment of Starbucks' Profitability Through Financial and Operational Strategy
Authors: Zhang Xinyue
Published: May 2023

The market was economically weakened as a result of covid-19. Starbucks has long had a considerable market share in the coffee industry, particularly in the United States. Therefore, this article will examine Starbucks' profitability and provide insight into the aspects that influence Starbucks' profitability. Some models will be used to analyze this, including earnings per share, P/E ratio, dividend payout ratio, return on assets, operating margin, sales profit margin, fixed asset ratio, financial leverage ratio, sales to equity ratio, and expense revenue ratio. This article will use the SWOT model to analyze the internal and external influences and the strengths and weaknesses of Starbucks in the market. Based on the analysis, while Starbucks has a huge market share and a great brand image, the pricey product can be a disadvantage during economic downturns. Starbucks' new approach to expanding into new markets will help to counteract the negative image of self-erosion in its primary US coffee market due to overcrowding. This article will explain why it was decided to invest in Starbucks as a corporation. This paper will provide some insight into the operational strategy and profitability of existing competitors to companies wishing to enter the coffee market.
Improve the Incentive Mechanism Base on Boxed-pigs Game Model
Authors: Jin Yueyao
Published: May 2023

An effective incentive mechanism is very important for all countries and companies, whether it is the innovation incentive mechanism for small and medium-sized enterprises or the work incentive mechanism for employees. However, the general incentive mechanism will have the problem of ineffective incentive, which needs to be improved and optimized. The failure of incentive mechanism will lead to the lack of enthusiasm of small and medium-sized enterprises that have no competitive advantage in technological innovation, and will also lead to the lack of work motivation of employees, resulting in low work efficiency and other problems. This paper analyzes real life cases through the theory of the Boxed-pigs game model. The boxed-pigs game is a classic example of a failed incentive mechanism. The big pig and the small pig in the model vividly represent the two opposing roles in real life. In different situations, the big pig and the small pig will make different strategies. By changing the conditions in the model and considering the reality, we can get solutions to improve the actual problems, such as tax incentives, employee compensation incentives, etc. Hope to improve the ineffective incentive mechanism.
Research on Bank Runs Based on Game Theory
Authors: Sun Yizhe
Published: May 2023

In contemporary society, with the continuous development of social economy, the financial industry has also made considerable progress. As one of the three pillars of the financial industry, banks will inevitably affect the development of the entire social economy while developing and improving. The global financial crisis that broke out in September 2008 has had a profound impact on the entire world economy. A bank run occurs when a large number of people withdraw cash from a bank, and the bank reserves are insufficient to pay them, resulting in a cash shortage. The research results show that the sources of funds and investment directions of banks are related to bank runs. Banks must appropriately diversify their sources of funds and investment, and pay attention to good operating performance, so as to make people believe in repayment ability. It is of great significance for the stability and development of the financial market to use the game model to understand the causes of bank runs, analyze the relationship between bank depositors and find out the correct countermeasures.
Trade Liberalization and Trade Protection Based on Game Theory
Authors: Wang Yujia
Published: May 2023

Under the background of economic globalization, economic and trade exchanges are increasingly close. While countries enjoy the dividends brought by the global economy, trade competition is also more intense. In order to protect their own economic and political interests, countries usually adopt the policies of trade liberalization or trade protection policy protectionism. The total economic volume of China and the United States is huge, so the trade frictions between the two countries will attract the attention of the world trade countries. The choice of trade policies between the two countries will also affect the economic level and economic and trade relations of both countries and even the development of the entire world economy. Therefore, from the perspective of game theory and international trade, this paper analyzes the choice of trade policy in world trade by calculating the Nash equilibrium in the choice of trade policy and the welfare changes caused by the implementation of tariffs. Through game theory analysis, the results show that trade protection and trade liberalization in world trade are both contradictory and coexist. In order to protect the development of their important industries, countries can adopt reasonable subsidy policies or protection policies to support them under the framework of WTO. However, countries should actively promote global economic governance and actively promote the development of multilateral trade and regional economy. It provides some ideas for the choice of trade policy in the context of trade war.
Research on the Impact of Sunk Cost on Chinese Households
Authors: Luan Yufei
Published: May 2023

In real life, the impact of sunk cost fallacy on people is hard to be ignored. It is of practical significance for people to find out these impacts and find ways to improve them. This paper first describes the research background and motivation. By citing examples, it is proved that the existence of sunk costs has seriously affected our life decisions and also had a direct impact on Chinese households. Therefore, it is of practical significance to study how to minimize the sunk cost fallacy and the actual impact of the sunk cost fallacy on the family. Secondly, the definition, causes and avoidance methods of sunk cost fallacy are described in detail. Thirdly, it discusses the impact of sunk cost fallacy on Chinese families. Three main influences are listed through reading literature and induction. First, the phenomenon of high bride price in remote and backward areas. Second, mothers tend to take more responsibility for taking care of their children. Third, the mother will endure an unhappy marriage for a long time because her child does not grow up in a single-parent family. And give corresponding suggestions for the three bad effects listed. Basically, it is to improve laws and regulations, strengthen men's sense of responsibility, and stop losses in time. Finally, it is concluded that the misunderstanding of sunk costs has mainly caused three bad effects on Chinese families.
Comparison of Different Machine Learning Prediction about Stock based on Multi-Factor Input-Taking the Nasdaq Index as an Example
Authors: Guo Yingshan
Published: May 2023

Stock investment has always been widely concerned, and the prediction of future stock trends is what many investors look forward to. There are numerous techniques that can be used to predict stocks as machine learning advances. The commonly used method is support vector machine, random forest, linear regression, etc. Recurrent neural networks, multi-layer perceptron, single-layer LSTM networks, naive Bayes networks, convolutional neural networks, back propagation networks, etc. are examples of deep learning techniques. In historical studies, researchers have tended to predict directly from stock prices or used time series as an independent variable to build a forecasting model for stock prices. In this study, we propose input training parameters based on stock indicators and build a sliding window of it to predict the future price. Based on LSTM, ANN, support vector machine regression, Linear Regression to make predictions on price, and analyze the differences between them. Our research is based on the Nasdaq and the evaluation values show that the neural network approach is effective for stock return forecasting.
Inflation Crisis under COVID-19 Pandemic and Ukraine Conflict
Authors: Jin Yuxi , Yan Ruiting
Published: May 2023

With the development of economic globalization, the economies of all countries are influencing each other and holding each other in check. Globalization is a double-edged sword, which brings both opportunities for development and serious challenges and risks to all countries in the world. Compared with developed countries, developing countries are more affected by crises and other shocks. This paper focuses on the changes of inflation in three major countries, the U.S., the U.K. and China, under the impact of two major events, the COVID-19 epidemic and the Russia-Ukraine conflict. During the first half year of 2020, the COVID-19 epidemic caused inflation in all three countries. This paper provides an overview of the current economic situation before going on to discuss the economic effects of the COVID-19 pandemic and the conflict in Russia and Ukraine on these three nations in terms of CPI, food prices, and energy costs. It concludes by summarizing how the economies of the United States, the United Kingdom, and China will develop in the future.
The Impact of Digital Transformation on the Fashion Industry in the Post-Pandemic Era
Authors: Zhu Zhengjia
Published: May 2023

The Covid-19 pandemic has brought significant challenges to the global luxury market since 2020. The economic downturn, declining customer incomes, lockdowns in public places, and a sharp reduction in international travel have all reduced customer demand for luxury goods. On the other hand, with brands' digital sales soaring during the pandemic and a younger customer base, more luxury brands are doubling down on online channels to compensate for physical store closures or limited sales due to safety regulations and lockdowns. In this context, this study uses Burberry Group plc as an example to analyze how a traditional fashion house can gain an advantage in the post-pandemic era through digital transformation strategies. The first is to analyze the brand's status quo through financial strategy analysis to understand the epidemic's impact on luxury brands. The second is to show Burberry's strengths and weaknesses through SWOT ANALYSIS. Third, analyze Burberry's digital transformation strategy. For research methodology, this study conducted a literature analysis of books and papers and kept the case studies' Timeliness through websites, social media, and news articles. The results show that Burberry avoided the epidemic's impact through online channels and broke geographical restrictions, further influencing consumers through digital platforms and deepening consumers' impressions. Burberry's case shows that digital transformation can flexibly respond to the disruption caused by the epidemic and minimize losses, thereby helping to build its advantage. As a result, the report contends that digital transformation will be a crucial component of fashion firms' future business plans.
Stock Daily Return Prediction of Amazon and Alibaba using Linear Regression and LSTM
Authors: Lyu Jinxian
Published: May 2023

The stock plays a key role in the economy market. As an individual investor, predicting stock return is always a hot research topic. In recent years, Amazon and Alibaba have become the head of e-commerce and the competition between them is becoming intense. In this paper, linear regression model and LSTM model based on machine learning are introduced and applied to predict the stock return of these two companies. RMSE and R2 are used to choose the number of variables and evaluate those models. This study finds that the simplest linear regression is even better than LSTM model with limited sources. The negative R2 scores of these two methods implies the nonlinearity and instability of stock return. However, predicting stock return is still possible. To investigate more about predicting stock return, more information such as the turnover rate and other non-numerical variables can be included in other models. Different types of LSTM model with different parameter setting can be applied to investigate deeply.
Credit Card Default Prediction based on Machine Learning Techniques
Authors: Zhang Zixuan
Published: May 2023

In recent years, with the development of society and economy, credit cards have been popularized due to their low interest rate and easy payment. However, with the advent of the epidemic era, the unemployment rate has increased, making the probability of credit card defaults rising. The prediction of credit card default helps banks and financial institutions balance the risk and economic interests, contributes to the stable and healthy development of the financial industry, and plays an important role in bank credit control. Therefore, this paper addresses the credit card default prediction problem by using Random forest, Decision tree, LightGBM, XGBoost, Logistic regression, and Adaboost models to make predictions and compare the results. The outcomes demonstrate that LightGBM algorithm has the most outstanding prediction score, and its AUC value can reach 0.78 and recall rate reaches 0.95.
Application of Artificial Intelligence in Enterprise Digitalization
Authors: Li Jingrong
Published: May 2023

In the past 10 years, the general trend of digital economy development has further promoted the application of core technologies including artificial intelligence. It is clear that artificial intelligence technology has started to play a significant role in many facets of business development in recent years. The "tentacles" of artificial intelligence technology can be said to have reached into every sphere of social economy, from design to production, from management to marketing. From an industrial standpoint, a number of sectors, including manufacturing, energy, and transportation, have started to "polish" with the use of artificial intelligence technology. This paper first analyzes the relationship between artificial intelligence and enterprise digitalization from two perspectives, then examines how AI is affecting business digitalization from various angles. Besides, I predicted the future of artificial intelligence in enterprise digitalization after researching chatbots, intelligent agent assistant, and other key application.
The Ongoing Importance of Venture Capital in the Economy
Authors: Zhong Wenkai
Published: May 2023

An essential part of the economy, venture capital supports emerging businesses with strong growth potential financially and strategically. In exchange for stock, venture capitalists make investments in early-stage enterprises and start-ups, actively influencing their success and direction. These businesses can launch cutting-edge goods and services, generate employment, and stimulate economic growth thanks to their support. Additionally, venture capitalists often bring a wealth of industry expertise and connections to the table, providing valuable mentorship and guidance to the companies they invest in. In today's fast-paced, technology-driven market, venture capital is more important than ever. With the rise of new industries and the increasing pace of innovation, young companies need support to bring their ideas to life and compete with established players. Venture capital provides that support, providing the necessary funding, expertise, and connections to help these companies succeed. Despite the changes in the market and regulatory environment, the ongoing importance of venture capital in driving economic growth and innovation is clear. Whether it's through the creation of new jobs, the launch of groundbreaking products and services, or the development of entire new industries, venture capital is a vital force in the economy.
Analysis of Starbucks' Financial Strategy and Operational Strategy
Authors: Wang Yinuo
Published: May 2023

People increasingly appreciate drinking coffee as a hobby due to the success of coffee goods. Numerous coffee brands have devoted followers. Starbucks, a major player in the coffee industry, is one of the brands that many consumers favor over others. Despite experiencing ups and downs throughout its history, Starbucks is still expanding. Many people have been interested in Starbucks' expansion and detailed numbers, yet it is challenging to summarize Starbucks' growth in detail. This article will analyze Starbucks' unique developments and then offer suggestions using the company's financial and market analyses and the SWOT, PEST, and Porter's Five Forces analysis models. According to the report, Starbucks' total sales and net income increased significantly between 2022 and 2021. Besides, the cash flow from financing activities decreased after the corporation sold its assets in 2022. What is more, in 2022, Starbucks employs an ambitious growth strategy, and its strong brand image gives Starbucks a significant advantage. However, Starbucks also faces other obstacles to its expansion, including a shift in consumer attitudes toward DIY projects and the proliferation of rival retailers, which will present substantial difficulties for Starbucks in the future.