The purpose of developing this software project is to fully automate salarysystem for an organization sweden sports academy. This software is capableof calculating monthly salaries, tax and social security of employees of thatorganization. On the basis of certain formulas it will generate files as anoutput such as bank files and salary slips etc. The system is also capable ofcalculating tax payable by the organization and social security. The tax fileis generated for the tax office. All the data such as, employee information,salaries, social security and tax will be stored in database as a track record.

The purpose of this research is to find out the Upward-Influence factors, which were used by domestic employees. In addition, by applying cluster analysis, this paper tried to identify the types of upward influence and the salary differentials between those types. As follows, one may see the research results: 1.This research finds five major upward influence strategies namely, Upward Tactics, Reason, Ingratiation, Image Management and Blocking. Among these five upward influence strategies, the one most frequently utilized by domestic employees is Reason (mean=2.9, SD=0.791). 2.By using a hierarchical cluster analysis of five upward influence strategies, we identified four types that characterized the way employees influence their superiors. ¡§Shotgun¡¨ employees used most upward influence and emphasized upward tactics and blocking; ¡§Gentle¡¨ employees used an average amount of upward influence and emphasized reason and ingratiation; ¡§Passive¡¨ employees used little upward influence with their superiors; and ¡§Bystander¡¨ employees, 41.3% of the sample, used moderate upward influence. 3.There are salary differentials between four upward influence types. ¡§Gentle¡¨ employees had significantly highest salaries than others. On the contrary, ¡§Passive¡¨ employees received lowerest salaries. There is no significantly salary differential between ¡§Shotgun¡¨ and ¡§Bystander¡¨ employees.

The study is mainly focus on the scope of corporate welfare system and stock dividend in order to get a profile on : 1. In current circumstances, if non-salary reward can affect employee's salary and satisfaction. 2. What effect can various welfare policies create on employee. The study takes observation from 164 working people, it comes up with the following conclusion: 1. No any replacement ties between welfare system & salary. 2. Welfare and stock dividend is parallel to salary. In other word, the better corporate welfare system is, the higher salary level it can reach, the more sound stock dividend distribution it can be, the high salary it can access. 3. Job satisfaction is mainly subject to salary, but it indeed happens that non-salary can somewhat elevate job satisfaction. 4. For the senior workers (in age or working experience), generally their job satisfaction are the highest, followed by freshmen.

Abstract Using data from the 2017 Major League Soccer Season, this thesis investigates the relationship between salaries, individual player performance, nationality and previous career trajectory for player in the MLS. Through analysis of 6 model specifications, it is found that previous career trajectory, performance and nationality are all significant factors in salary determination. Further, it is concluded that the results of the model show that MLS franchises are in general allocating salaries efficiently relative to performance.

Through a mixed methods approach, this study provides a greater understanding of salary inequality in U.S. business schools and how it changed between 1998 to 2004. The quantitative research examines full-time faculty using individual-level salary data from both a constant sample of 307 institutions and a larger 2004 sample of 464 schools, allowing for in-depth examination of inequality including within institutions. The qualitative research used interviews with business school deans to uncover decisions that, in the aggregate, can impact faculty salary inequality.Quantitative analysis of faculty salary utilized descriptive statistics as well as several inequality measures, along with regression analyses, to reveal the level and structure of inequality and the contributions of within-institution and between-institution inequality. Salary inequality increased between 1998 and 2004. However, contrary to previous research, salary inequality isn't attributed to superstar salaries; the growth in salary inequality is attributable to negative real growth in the lower tail of the salary distribution. Analysis between institutions reveals that the highest paying 10% of institutions are pulling away, increasing stratification between the most prestigious institutions and the others. Although private school faculty earn more than their public counterparts, salary inequality among faculty at public institutions increased more rapidly. Institutional characteristics including Carnegie classification, MBA ranking, degrees offered, accreditation, faculty size, tuition and fees, state appropriations per student and endowment per student contribute to differences in salary inequality between institutions. Within institutions, unionization and higher MBA ranking correspond to lower salary inequality; whereas research/doctoral, public institutions, and larger faculty size correspond to more salary inequality. Differences also exist in the inequality source: upper tail or lower tail.While the primary interview theme is the rule of the market, deans do make individual decisions based on their own competitive marketplace. The qualitative inquiry revealed four decision categories that can affect salary inequality, including: hiring strategies, environmental influences--colleges and fields, compensation challenges and market response strategies, all which may collectively increase or decrease faculty salary inequality. Interview analysis revealed additional questions that need to be answered using quantitative data, from changes in faculty composition, to compression/inversion, and salary inequality differences across fields.

In the last two decades, the National Basketball Association (NBA) has made extensive efforts into expanding its reach outside of the North American market. Numerous attempt have been made by the league to spread the game of basketball into such areas as Europe, South America, and East Asia. As popularity for the sport grew, so did the potential for NBA teams to draft foreign talent. Indeed, the 1990’s and 2000’s saw an influx of foreign talent into the NBA. By the 2014-2015 season, there were a record 101 foreign players on opening day rosters, nearly five times as many as during the 1990-1991 season (21 players). This papers examines whether discrimination of foreign players exist via two value outcomes: salary and minutes per game. Based on an analysis of performance metrics, this paper found significant nationality effects on minutes per game, specifically that foreign players receive less playing time for commensurate performance. This paper did not find evidence to suggest salary or minute per game discrimination by race.

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With the advent of globalisation the sports industry has shown exponential growth in the last 20 years. The surge of commercialisation of sport, the unprecedented internationalisation of the sports labour market, the enormous sums of money paid for the broadcasting rights of big sporting events, the attraction by multinational blue chip sponsors as well as the direct private investment by the worlds super wealthy have all contributed to the growing economic and social importance of sports. This massive influx of big money into sports does have its drawbacks. The criminal world has always shown adaptability in finding new channels to launder the proceeds of their illegal activities. Ever increasing and stricter measures and standards put in place by inter-governmental bodies like the Financial Action Task Force (FATF) as well as the increasing compliance of financial institutions the world over with these standards has meant that various legitimate sectors are at risk of being infected with criminal money. In a Report released by the FATF entitled ‘Money Laundering through the Football Sector’ one of the vulnerabilities of football clubs that was identified was the increased strain on their financial needs. Big Clubs require large budgets to be able to compete and afford the best players. Prices for players appear irrational and are very difficult to control. Player salaries comprise a substantial portion of the clubs total budgets. The result of this factor is that a large percentage of clubs are in financial trouble. This financial vulnerability can make clubs more susceptible to offers made from criminals looking for avenues to launder their ill-gotten gains. A salary cap is simply put a limit on the amount of money a club is permitted to spend on salaries. This limit or cap comes in various forms but is usually implemented as a percentage of the club’s annual average revenues. It is a rather controversial measure and certainly has its detractors, but it has shown to increase competitive balance and maintain financial stability in the leagues that they have been introduced. Salary caps are in effect in professional team sports all around the world. It has been used successfully in North America in their National Football and National Basketball leagues respectively, as well as in Australia in the Australian Football League and the National Rugby League and into UK professional rugby by the Rugby Football League and later by the Rugby Football Union. This mini dissertation aims to illustrate the threat posed to professional football by criminal organisations seeking to find new ways to launder the proceeds of their crimes as well as provide an overview of money laundering as a crime. It further aims to provide an overview of salary capping and then tie in the purpose and benefits of the implementation of a salary cap and how it may inadvertently be used to curb money laundering. / Dissertation (LLM)--University of Pretoria, 2014. / Mercantile Law / unrestricted

The thesis is to examine the relationship of the employees¡¦ salary satisfaction, job involvement and turnover intention in the internet industry to know whether the degree of salary satisfaction and job involvement will affect the turnover intention of employees or not. It also examines whether the employees have different salary satisfaction for the future and how this will affect their turnover intention. The result provide the managers of the industry to draw up appropriate salary management strategy to lift the salary satisfaction and job involvement, lower the turnover intention effectively and make the companies more competitive. Considering of the time, manpower and resources, the thesis take ten Internet companies as the samples. Effective questionnaires sent back are 108 and the effective rate is 12.9¢M. By using the statistic methods, the findings of this research indicate that: 1. The sex of the employees in the Internet industry has significant difference on ¡§salary satisfaction for the current¡¨. 2. The sex of the employees in the Internet industry has significant difference on ¡§salary satisfaction for the future¡¨. 3. The sex of the employees in the Internet industry has significant difference on ¡§job involvement¡¨. 4. The sex of the employees in the Internet industry has significant difference on ¡§turnover intention¡¨ 5. Female employees of the Internet industry have obviously higher ¡§turnover intention¡¨ than male employees. 6. The age of the employees in the Internet industry has significant difference on ¡§salary satisfaction for the future¡¨. 7. The marriage status of the employees in the Internet industry has significant difference on ¡§job involvement¡¨. 8. The current service length of the employees in the Internet industry has significant difference on ¡§turnover intention¡¨. 9. For the employees of the Internet industry, to appear significant negative correlations between ¡§current service length¡¨ and ¡§turnover intention¡¨. 10. The working service length of the employees in the Internet industry has significant difference on ¡§salary satisfaction for the current¡¨. 11. The working service length of the employees in the Internet industry has significant difference on ¡§salary satisfaction for the future¡¨. 12. The working service length of the employees in the Internet industry has significant difference on ¡§job involvement¡¨. 13. For the employees of the Internet industry, to appear significant positive correlations between ¡§working service length¡¨ and ¡§salary satisfaction for the current¡¨. 14. For the employees of the Internet industry, to appear significant positive correlations between ¡§working service length¡¨ and ¡§salary satisfaction for the future¡¨. 15. The department of the employees in the Internet industry has significant difference on ¡§salary satisfaction for the future¡¨. 16. The department of the employees in the Internet industry has significant difference on ¡§job involvement¡¨. 17. The department of the employees in the Internet industry has significant difference on ¡§turnover intention¡¨. 18. The grade of the employees in the Internet industry has significant difference on ¡§salary satisfaction for the future¡¨. 19. The monthly salary of the employees in the Internet industry has significant difference on ¡§salary satisfaction for the current¡¨. 20. The monthly salary of the employees in the Internet industry has significant difference on ¡§salary satisfaction for the future¡¨. 21. The monthly salary of the employees in the Internet industry has significant difference on ¡§job involvement¡¨. 22. For the employees of the Internet industry, to appear significant positive correlations between ¡§monthly salary¡¨ and ¡§salary satisfaction for the current¡¨. 23. For the employees of the Internet industry, to appear significant positive correlations between ¡§monthly salary¡¨ and ¡§salary satisfaction for the future¡¨. 24. For the employees of the Internet industry, to appear significant positive correlations between ¡§monthly salary¡¨ and ¡§job involvement¡¨. 25. For the employees of the Internet industry, to appear significant negative correlations between ¡§salary satisfaction¡¨ and ¡§turnover intention¡¨. 26. For employee of in the Internet industry, to appear significant positive correlations between ¡§salary satisfaction ¡§ and ¡§job involvement ¡§. 27. For employee of the Internet industry, to appear high positive correlations between ¡§salary satisfaction for the current ¡§ and ¡§salary satisfaction for the future¡§. 28. For employee of the Internet industry, to appear significant negative correlations between ¡§salary satisfaction for the current¡¨ and ¡§turnover intention ¡§. 29. For employee of the Internet industry, to appear significant negative correlations between ¡§salary satisfaction for the future¡¨ and ¡§ turnover intention ¡§. 30. For employee of the Internet industry, to appear significant positive correlations between ¡§salary satisfaction for the current¡¨ and ¡§ job involvement ¡¨ 31. For employee of the Internet industry, to appear significant positive correlations between ¡§salary satisfaction for the future¡¨ and ¡§ job involvement ¡¨. 32. The ¡§working service length¡¨ has significant positive forecast ability on job involvement. 33. The ¡§sex¡¨ has significant negative forecast ability on job involvement. 34. ¡§The salary satisfaction for the future¡¨ has significant positive forecast ability on job involvement. 35. The ¡§sales department¡¨ has significant positive forecast ability on job involvement. 36. The ¡§marital status¡¨ has significant positive forecast ability on job involvement. 37. The ¡§sex¡¨ has significant negative forecast ability on turnover intention. 38. The ¡§planning department¡¨ has significant positive forecast ability on turnover intention. 39. The ¡§current salary satisfaction¡¨ has significant positive forecast ability on turnover intention. 40. The ¡§marketing department¡¨ has significant positive forecast ability on turnover intention. According to the above result, I can discover the turnover intention of the employees of the Internet industry is getting higher. The employees are confident of their turnover ability, which will induce company loss. Thus I suggest that Internet companies shall combine the fiction with the substantiation to form a new type of enterprise. Furthermore, the result that the female employees have higher turnover intention but higher job involvement is worthy for proprietor of the Internet industry to pay attention to. Because the characteristics of female employees are helpful to the busy Internet working environment, the proprietor or professional managers shall consider to adjust or change the working environment, job content or management system to let female employees fully contribute their talent, lower their turnover intention and benefit the company.

The professional sports industry is one of the most engaging and entertaining markets in the United States. Specifically, Major League Baseball is unique in the sense that it is America’s pastime and oldest American sport. Professional baseball teams are businesses that trade commodities in the form of baseball players. Unlike publicly traded stocks, baseball players are not traded on an exchange. So, what determines the “price” of professional baseball players? More specifically, what determines the price of professional pitchers in the MLB? My study reveals that pitching is an extremely subjective aspect of baseball and there is no one statistic that can be used to forecast a pitcher’s salary. Based on my research and analysis, I investigate which performance metrics are the most important in determining a professional pitcher’s salary and if these metrics can ultimately be used to forecast future pitchers’ salaries in order for baseball franchises to acquire undervalued pitchers.