Managing Service Operations

Managing Service Operations Raised in Tokyo, Hiroaki Aoki managed to launch his first business in the United States. Taking advantage of his origin, he opened a Chinese-Japanese cuisine restaurant offering a unique experience to its customers. The food process was transformed to an exceptional food experience and with the opening of a chain of in total 15 restaurants Hiroaki Aoki proved to be a pioneer in the restaurant industry. The way he managed to succeed this, was through revolutionary moves regarding restaurants environment, financial operations and service structure. By decorating his restaurant with Japanese elements and employing Japanese chefs as showmen, the perception of dining at Benihana changed. This new perspective was further supported by reducing the kitchen-room as to have more space for tables and fully adapt the Japanese philosophy as well as creating an unparalleled image for his business. Due to the uniqueness of the Benihana restaurants, franchise as a growth strategy brought upon many problems: starting from a lack of communication between managers and the Japanese speaking personnel, to inexperienced managers in franchised businesses abroad. This led Hiroaki Aoki to reconsider his options and deciding to expand through other models (joint-venture and hotel-corporation) and in other areas of food industry (retail and quick service food sector). Whether this is a sustainable move or not will be identified within this report. Benihanas concept is based on an authentic Japanese atmosphere. The use of American food favourites (chicken, steak, etc.) combined with the hibatchi method of presentation makes this restaurant very different from others (Sasser, 2004). Glushko and Tabas (2008) state that service management and design success depend on the interaction between employees and customers. Thus the quality of the service experience relies on the front stage activities displayed in a restaurant. Furthermore, Frei (2006) adds that the line of visibility is the factor that separates the front stage and the back stage (Appendix 3). If Benihana was to compare with a McDonalds and a Gourmet Restaurant the service encounters would be very different (Appendix 4) (Frei, 2006). In the case of McDonalds the line of visibility for the front-stage is very small and depends on waiting lines and self-service, whereas all the production lines occur in the back stage, thus the customers experience is very limited (ibid.). A customers experience in a gourmet restaurant has a balance between the front-stage, dining room experience, and the kitchen-backstage-area (ibid.). Compared to both of these, Benihana enhances the experience of their customers by treating the chef as a showman and having a different production line to service (ibid.). The front stage is the largest part of the operations with the chef cooking and serving the dishes together with the waiter, whereas the kitchen preparation is a very small part of their process (Sasser, 2004). This different concept increases customer satisfaction: 9 As seen in Figure 2, customer satisfaction is rated as excellent, which implies that the Benihana service concept is successful. In order to further develop this aspect of their business, Benihana also developed several other concepts in relation to their design, their bar and their customer batching in groups, which will be further discussed in Chapter 3.2.2 Benihanas Restaurant Design. 10 Benihana created a concept that includes food, atmosphere, entertainment and hospitality, while trying to be consistent, with their Japanese heritage. Furthermore, the owner is planning expansion steps to appeal to a wider range of clientele. However, Hiroaki Aoki has two major concerns. The first issue is how to sustainably expand and upgrade his product and services to cater a wider range of audience, while keeping the quality and the Japanese traditional atmosphere. The second issue is how to define what Benihana is selling. Data Analysis Benihanas Strategy Considering the growth of Benihana from a humble 40-seat unit to a chain of 15 units across the country, Hiroaki Aoki had a very successful strategic planning behind the concept of his restaurant (Figure 1) (Sasser, 2004). Strategic planning can be defined as an organizational process of allocating its resources in order to pursue a strategy that includes its capital, employees and most important its clients (Haines Schmidt, 2005). The owner, Rocky, approached a combination of inputs (operations), customers satisfaction and outcomes (financial results) in order to provide a new idea behind the strategy of a normal restaurant, maximizing its strengths and diminishing its weaknesses (Appendix 2) (Heskett, Sasser Schlesinger, 1997). Figure 1 : Benihana Strategic Planning Note: Adapted from Heskett, Sasser Schlesinger, 1997 Benihanas strategic planning took into consideration five important aspects: Construction, Finance, Marketing, Human Resources and Operations (Heskett, Sasser Schlesinger, 1997). They provide the framework for understanding how the firms operational investment is translated into its profit. Furthermore, Benihanas concept and cost-structure will be presented in relation to this model in order to understand the true authenticity behind this different restaurant management approach. Benihanas Concept Benihanas concept is based on an authentic Japanese atmosphere. The use of American food favourites (chicken, steak, etc.) combined with the hibatchi method of presentation makes this restaurant very different from others (Sasser, 2004). Glushko and Tabas (2008) state that service management and design success depend on the interaction between employees and customers. Thus the quality of the service experience relies on the front stage activities displayed in a restaurant. Furthermore, Frei (2006) adds that the line of visibility is the factor that separates the front stage and the back stage (Appendix 3). If Benihana was to compare with a McDonalds and a Gourmet Restaurant the service encounters would be very different (Appendix 4) (Frei, 2006). In the case of McDonalds the line of visibility for the front-stage is very small and depends on waiting lines and self-service, whereas all the production lines occur in the back stage, thus the customers experience is very limited (ibid.). A customers experience in a gourmet restaurant has a balance between the front-stage, dining room experience, and the kitchen-backstage-area (ibid.). Compared to both of these, Benihana enhances the experience of their customers by treating the chef as a showman and having a different production line to service (ibid.). The front stage is the largest part of the operations with the chef cooking and serving the dishes together with the waiter, whereas the kitchen preparation is a very small part of their process (Sasser, 2004). This different concept increases customer satisfaction: Figure 2 : Customer Satisfaction Note: Own design according to Exhibit 4, Sasser, 2004 As seen in Figure 2, customer satisfaction is rated as excellent, which implies that the Benihana service concept is successful. In order to further develop this aspect of their business, Benihana also developed several other concepts in relation to their design, their bar and their customer batching in groups, which will be further discussed in Chapter 3.2.2 Benihanas Restaurant Design. Benihanas Cost Structure In terms of Benihanas cost arrangement the owner implemented a strategic cost structure to the business by lowering the cost of labour and food and beverage. The cooking labour is cost efficient due to the cost reduction that was done through their chefs; they did not only prepare the food, but also served it (Sasser, 2004). With concerns to the food and beverage costs, due to their limited menu, inventory reduction also occurred (ibid.). Taking into account all the mentioned measures, the results have a direct impact on the financial statement of the restaurant. Figure 3: Benihana ´s Partial Income Statement Note: Sasser, 2004; Bank of America, 1968 As seen in Figure 3, Benihana ´s Earnings Before Income Tax and Depreciation (EBITDA) is on average between 15 and 35% higher than ones of a typical service restaurant (Sasser, 2004). It is observed that there are two factors, which increase profitability: lower food and beverage cost (limited menu, fewer inventories) as well as lower labour cost. The lower labour cost is the influential reason behind this high difference in marginal profit. Analyzing the employee that plays the most important role in the restaurant, the Benihana chef, an employee profile was created (Appendix 5). PayScale (2010) provides an immediate accurate snapshot of the job market and gives facts of employees salary data in the world. Thus it was used as a source to calculate the annual average salaries of the food and beverage segment as well as the job specification of a chef in 1964 (Appendix 6) (ibid.). The average annual salary of a Benihana chef can be analyzed through the figure below. Figure 4 : Benihana ´s Chef Annual Average Salaries 1964 Note: PayScale, 2010 It can be noticed that the Benihana master-chefs have a slightly above average income compared to the market. As the success and the reputation of the restaurant depend on these employees, it is very important to keep them motivated and this further demonstrates that the owner, Rocky, also has a human resources operation strategic planning as seen in Figure 1. Benihanas Restaurant Capacity Managers are continuously challenged with balancing customer demand and service capacity (Klassen Rohleder, 2002). The capacity of a business can be seen as their ability to meet the demand; for the production of goods this can be easily done, but for services it is very difficult as four critical factors have to be taken into account: time, labour, infrastructure and equipment (ibid.). Thus capacity has to be planned ahead in order to achieve cost effectiveness and the customer satisfaction. In the case of Benihana, an estimation of the maximum demand rate for an evening dinner period was calculated in order to foresee the capacity to sustain it: Figure 5: Benihana ´s Capacity vs. Demand Rate Note: Own design; Sasser, 2004 It can be noted from Figure 5 that in a case of maximum demand rate, Benihanas capacity will not be able to fit 360 clients in one night. Although the restaurant has already a limited menu, Benihana also took into consideration a decrease in dining time. The chefs also plays an important part by offering the guests the ultimate gastronomic experience and politely annoucing them that their dinner is over by bowing at the end of the meal-presentation (Sasser, 2004). Benihanas Production Process System Before a company can actually decide on which customer target market it will serve, it has to define its value proposition and its position in the market (Kotler Armstrong, 2010). The positioning of a company is defined as a consumer`s appreciation of the product compared to competing products (ibid.). As one can see in Appendix 7, Benihana has a high customer value and a differentiated position in the market. Hiroaki Aoki achieved this position, through an unprecedented service experience and design (Sasser, 2004), which will be highlighted in the following chapter. Benihana`s Service Design Every service idea starts with a service concept, where the purpose, target market and the customer experience are defined (Russell Taylor, 2009). By opening an authenticable Japanese restaurant in the United States, Hiroaki Aoki focused on two main criteria, Americans enjoy when they are going out for dinner: an exotic surrounding and a place where they can watch the preparation of their food (Sasser, 2004). Referring to the previous chapter, out of this observation, he created a completely new service concept: the Benihana dining concept, where the food is prepared by professional chefs on hibachi tables right in front of the guests. This newly developed concept was both, revenue- and cost-effective (Heskett, Sasser Schlesinger, 1997). A service package is a mixture of physical items, sensual benefits, and psychological benefits (Russell Taylor, 2009). The specialty of a Benihana restaurant is their design according to historical authenticity. All the physical items (walls, ceilings, lights, etc.) are from Japan and the materials are originally shipped to the United States (Sasser, 2004). Sensual benefits are supported by the highly trained native Japanese chefs whose form of cooking is mainly showmanship (ibid.). The psychological benefits in a Benihana restaurant are the exotic surroundings and authenticity of the place. The combination of all three components concludes in an effective service design (Russell Taylor, 2009). Therefore, the connection is presented in the service design process: Figure 6: The Service Design Process Note: Adapted from Russell Taylor, 2009 Derived from the service package, specifications for performance, design and delivery are specified. Based on the customer expectations (exotic surrounding), the design (original materials from Japan) and delivery (downtown Manhattan) are created (Russell Taylor, 2009). Benihana`s Restaurant Design The design of a typical Benihana restaurant is created to increase efficiency and profitability. A typical Benihana restaurant design, which presents the floor plan of the Benihana West restaurant on West 56th Street in Manhattan (Sasser, 2004), is shown in Figure 7. It is comprised of 112 to 120 seats in the dining area as well as 55 to 60 seats in the cocktail lounge and the typical operation has between 5,000 and 6,000 square feet (ibid.). Figure 7: A typical Benihana Floor Plan Note: Sasser, 2004 Once guests enter the restaurant, they first pass the cocktail lounge. The bar in the first Benihana restaurant only seated eight guests as the design was concentrated on food-service sales (Sasser, 2004). Along the openings of new restaurants, the founder realized, that the small space was insufficient and enlarged the bar space with every opening. He found out, that in peak times, the bar is well used as a buffer and therefore increases the beverage sales (ibid.). When all the 14 tables in the dining area are occupied, the guests are waiting here for an aperitif, until there are seats available. In the bar, the guests are batched in groups of 8 and are leaded to the dining area. The main attractions in the dining area are the teppanyaki tables, which cover eight diners per table and are served by one chef and a waitress (Sasser, 2004). Due to the hibachi tables, the conventional back-stage kitchen can be reduced as the cooking itself takes place front-stage at the customer`s table. This leads to shorter serving distances and one team of chef and waitress can handle two tables at once. The arrangement of the tables (see also Figure 6), also results in lower cost of labour (Sasser, 2004). Examination of the Production System The design of the production process comes along with the design of the restaurant space. The whole production line moves towards the service of the customer. It starts in the bar, where the guests are grouped together in batches of eight before having their dinner (Verweire Van den Berghe, 2005). It has to be taken into consideration that the combination of batches is satisfactory for smaller groups arriving, since they do not know each other (Appendix 8). This batch concept leads to higher beverage sales and allows using the whole provided capacity in the restaurant. According to Russell and Taylor (2009) design simplification reduces the number of parts, subassemblies, and options in a product. Benihana`s menu consists of four main food items (filet mignon, steak, chicken and shrimp) accompanied by unvaried side dishes (zucchini, onions, bean sprouts, fresh mushrooms and rice), which can be combined as entrees or main dishes (Sasser, 2004). As seen in Figure 4 this standardization of ingredients cuts the food costs down to 30-35% of food sales and leaves nearly no waste (Sasser, 2004; Russell Taylor, 2009). This also minimizes the space for food storage, which results in less space in the back stage of the restaurant. Since services are defined as front-stage activities, the dining room of a restaurant is the service part, whereas the kitchen is classified as the production part (Teboul, 2006). Through the preparation of the meal in front of the customer, not only the service experience is greater, but also a conventional kitchen is not necessary anymore. This enlarges the productive dining area and reduces the back area (preparation areas, dressing rooms, storage and office space) of about 22% of the total space (Sasser, 2004). According to Verma and Boyer (2010), the aim of successful process design is to maximize the output. To identify possible limitations, a bottleneck analysis is helpful. A bottleneck in a process is the step with the slowest cycle time in a given process (Verma Boyer, 2010) and verifies the process productivity. Figure 8: Process Flow Diagram of the first Benihana Restaurant in Manhattan, 1964 Note: Adapted from Verma Boyer, 2010 While analyzing the process flow diagram (Figure 8) of a Benihana restaurant, one can see that the bottleneck hereby is the dining time of 60 minutes. This bottleneck determines the pace of the whole system even though the waiting time at the bar in peak times is only 12 minutes (Verma Boyer, 2010). As identified in Chapter 3.1.3, Figure 9 the demand of a Benihana restaurant exceeds capacity. To resolve the problem of the bottle neck, Benihana decreased the dining time and enlarged the bar capacity to cover more waiting customers. Over the years, Benihana first doubled the bar area to 16 seats and eventually reached up to 55-60 seats (Sasser, 2004). Figure 9 shows some scenarios for different bar and dining area arrangements and waiting times. The maximum dining capacity of 120 seats allows a bar capacity of 48 seats (Figure 9). Figure 9 : Scenarios for different Bar and Dining Area Arrangements and Waiting Times Note: Own Calculations Concerns regarding Diversification Plans According to Ansoffs Growth and Expansion Matrix, one can find four different options of development: market development, diversification, market penetration and product development (Campbell Craig, 2005). Benihana took into consideration the following strategies: Figure 10 : Expansion Plan of Benihana Note: Adapted from Campbell Craig, 2005 The first one, market development (1), is the growth of an existing product into new market sectors (Campbell Craig, 2005). Regarding their diversification plans, Benihanas attempt is to expand in other countries where they have to take into consideration the customs of each nation, its rules and regulations. The same principles cannot be applied for all regions, so in order to develop successfully the restaurant chain these concerns should be well evaluated. Furthermore, it is very difficult for the company to be franchised, since not all owners have previous experience in the restaurant business (Sasser, 2004). Communication with the staff is also very difficult, since the majority is Japanese. Moreover, it is very demanding to supervise and keep control of what is happening in restaurants around the world. Hence, Rocky decided for the near future, instead of attempting to franchise his restaurant business, to move either into a joint-venture or into hotel-corporations and expand in two areas: Japan and overseas (ibid.). Diversification (2) is known as an approach of involving new products in new markets (Campbell Craig, 2005). Rocky also decided to widen his business into other fields connected to the food industry. A first attempt in the retail production and selling is under discussion. Entering the retail-sale-market is time consuming and has high advertising costs, so Benihana should probably re-evaluate their advertisement budget and more likely reduce the promotion funds for the restaurants, which is a risky move (Restaurant Worx, 2010). If someone is not satisfied by the quality of the product he/she will probably create a negative idea about the company and never visit a Benihana restaurant. It is also uncertain how unique the product is or how likely it is for other similar products to be created in the near future (ibid.). Product development (3) is known as increasing the market share by developing new products (Campbell Craig, 2005). In general Benihana restaurants have middle-income customers as its target group (Sassa, 2004). This is linked directly to the quality of the services offered, restaurants atmosphere and prices. Alternatively, they have no young audience in Benihana restaurants. This is one of the reasons why Rocky is considering of opening a quick service restaurant as to be able to satisfy younger crowds needs as well (ibid.). To put this project into action, firstly a market research was made about the restaurant needs of the people, the food that will be provided in these restaurants, deciding on a combination of Asian cuisine Chinese and Japanese and their location. Furthermore, cooperation between Rocky and an oil company will be formed as to provide small gas units to his new restaurants (ibid.). Even though a thorough research was conducted for this expansion a very significan t element was neglected; the culture of the locals. Maybe the proposal of a Chinese-Japanese quick service restaurant was innovative for that time, but not all the neighbourhoods were prepared to welcome that idea (ibid.). The last one, market penetration (4), is known as the use of existing products in existing markets, which are already served (Campbell Craig, 2005). The United States therefore give three areas for growth: primary markets (New York, Los Angeles), secondary markets (Pennsylvania, Harresburg, etc) and Suburbia. Due to the already mentioned inefficient franchise strategy, Benihana will not only expand internationally but also domestically through joint-ventures and hotel-affiliations (Sasser, 2004). Concerns regarding the loss of identity Benihana is selling to its customers a whole new perception of food consumption. Starting its business in 1964 in the U.S., it introduced to the market an innovative procedure of food preparation and presentation to the customers (Sasser, 2004). Instead of cooking the food inside a spacious kitchen, they used more room for the restaurant area as to prepare meals in front of the customers on a teppanyaki table with the hibachi cooking method. Benihana created a culture for the chain based on Japanese cooking method by well trained chefs and Japanese design. The environment of Benihana restaurants decoration and atmosphere is of vast importance for the company, since the philosophy of Benihana is to make people happy through the food experience (Bitner, 1992; Sasser, 2004). However, the environment is important not only for the customers who should feel satisfied, but also for the employees. In turn for the employees to feel motivated and perform their best, their working surrounding s should support their needs, as to be able to enhance companys values to the customers (ibid.). Consequently, Benihana should continue providing such services and facilities to its customers and employees as to sustain the chemistry between them and therefore continue to be a successful company. Presentation of Solution and Recommendations Benihana had a very successful strategy so far due to its construction, finance, marketing, human resources and operations management. They were able to translate market trends into their concepts and adapt them efficiently. Furthermore, they managed to reduce the back stage kitchen area into a front stage environment that displayed cooking and entertaining as one. The concept was so innovative that Rocky was actually able to reduce expenses. According to the diversification plan, Rocky intended to expand his business into more fields of the food industry. To develop his company, he tried to take advantage of the Benihana recognition, as to enter further markets, but on the other hand this step would be risky, because if the new concepts would fail, it could damage Benihanas reputation. Sasser (1976) states, that good planning is the key to successful management of supply and demand in service industries. As discussed in this paper one of the biggest problems that Benihana is facing, is how it will sustainably expand, while keeping their quality and their concept (limited menu, chef as a showman, Japanese atmosphere). Furthermore, as seen in Figure 10, Rocky has made a lot of plans regarding the growth and diversification of the Benihana restaurant. It is recommended that before attempting to implement all his ideas, a development strategic plan should be developed in order to best fit this expansion. Therefore the supply and demand matching concept should be taken into consideration: Figure 11 : Strategies for Matching Supply and Demand for Benihanas services Note: Adapted from Wisner, Leong, Tan, 2005 Lovelock (1994) further states that this can be accomplished through shifting demand to match capacity or adjusting capacity to meet demand (Appendix 9). In order to resolve the second issue, Benihana should focus on selling Japanese food and promoting their philosophy. One of the main key points of Benihanas achievements is the unique food experience it sells to its customers. Therefore, the basic elements of this successful recipe should be included in any other expansion step the company and Rocky decide to take. Without the fear of being imitated, they should take advantage of their uniqueness and develop in other areas of food industry. Through this move they would also be able to focus on other target groups, such as younger audience, which currently are not part of Benihanas targeted clientele. In this way Rocky will be able to launch his restaurant name and not only become a current trend, but also establish his brand in the hospitality industry, by providing Japanese authentic services. Action Plan Evidence Of Success Evaluation Process : Increase in Demand Increase in Profitability Customer Satisfaction Survey Employee Satisfaction Survey References: Benihana (2010). About Benihana. Retrieved 18.09.2010, from: http://www.benihana.com/about Benihana Training Guide (2004). Benihana Training Guide. Al Bustan Rotana Hotel Bitner, M. J. (1992). Servicescapes The Impact of Physical Surroundings on Customers and Employees. Retrieved 18.09.2010, from: http://proquest.umi.com/pqdweb?did=585119 sid=3Fmt=3clientId=45065RQT=309VName=PQDuserid=008BW87KK7passwd=WELCOME Campbell, D.J. Craig, T. (2005). Organisations and the Business Environment. Burlington: Elsevier Butterworth-Heinemann Glushko, R.J. Tabas, L. (2008). Bridging the Front Stage and Back Stage in Service System Design, in: Proceedings of the 41st Hawaii International Conference on System Sciences Big Island, Hawaii: IEEE Computer Society Press, January (2008), p. 106 Frei, F.X. (2006). Breaking the Trade-Off between Efficiency and Service. Boston: Harvard Business Review, Vol. 84, No. 11, page: 93-101 Haines, S.G. Schmidt, T. (2005). ABCs of Strategic Management The Systems Thinking Approach to Creating a Customer-Focused, High Performance, Learning Organization. San Diego: System Thinking Press Heskett, J.L., Sasser, W.E. Schlesinger L.A. (1997). The Service Profit Chain How Leading Companies Lead Profit and Growth to Loyalty, Satisfaction, and Value. New York: The Free Press Ivy Thesis (2010). Executive Summary Benihana International Restaurant. Retrieved 18.09.2010, from: http://ivythesis.typepad.com/term_paper_topics/2009/09/executive-summary-benihana-international-restaurant.html Klassen, K.J. Rohleder, T.R. (2002). Demand and Capacity Management Decisions in Services, How They Impact One Another. Bingley: International Journal of Operations and Production Management, Emerald: Vol. 22, No. 5, p. 527-548 Kotler, Ph. Armstrong, G. (2010). Principles of Marketing. Upper Saddle River: Prentice Hall Lovelock, C. (1994). Getting the Most Out of Your Productive Capacity. Boston: McGraw Hill PayScale (2010). Free Salary Report based on Job Title, Location, Education, Skills and Experience. Retrieved 19.09.2010, from: http://www.payscale.com Restaurant Worx (2010). Restaurant Retail Sales. Retrieved 18.09.2010, from: http://restaurantworx.com/services-2/restaurant-marketing-solutions/restaurant-sales-solutions/retail-sales/ Retail Fix (2010). Features Benihana. Retrieved 19.09.2010, from: http://www.retailfix.com/ featured_benihana.cfm Russell, R.S. Taylor B.W. (2009). Operations Management Along the Supply Chain. Upper Saddle River: John Wiley Sons Sasser, E.W. (2004). Benihana of Tokyo. Boston: Harvard Business School Teboul, J. (2006). Service is Front Stage- Positioning Services for Value Advantage. New York: Palgrave MacMillan Verma, R. Boyer K.K. (2010). Operations Supply Chain Management World Class Theory and Practice. Mason: South-Western Verweire, K. Van den Berghe, L. (2005). Integrated Performance Management- A Guide to Strategy Implementation. London: SAGE Wisner, J.D., Leong, K.G. Tan, K.C. (2005). Principles of Supply Chain Management A Balanced Approach. Mason: South-Western

Why We Study Torism and Hospitality at University

With the considerable growth of hospitality and tourism industry and more governments recognizing the industry’s contribution to national and local economies, a number of academic institutions have expanded degree offerings and started specializing in these disciplines (Garside 1991). Study tourism and hospitality at University are essential not only for academic advances but also for developing practical applications. Wiley (1995) argues that the success of every hotel company is conditioned by the capability of its managers to coordinate the business with the changes that characterize the modern international environment.Marketing is a required course for the University. Through study of the Marketing, the managers of hotel companies can strategically plan to direct the studing constantly searching and choosing ways to be competitive, to decide how to attract new tourists, how to keep the permanent tourists, how product to be more attractive from the competitors ones, how to position successfully on the competitive tourist market. So study Marketing at university is necessary for tourism and hospitality.Furthermore, Langbert (2002) also argues that Tourism in general and food service in particular contribute to a nation's economic development in many ways, in addition to the immediately apparent prospects of creating jobs and boosting overall income. Food and Beverage is interesting course at University. Before go to hotel to practice, students have to pass the test about alcohol and food service. Through study the Food and Beverage, it will be improve the ability of practical, easier get job and adapt to working at hotel. So study this course at University is very important for students.In conclusion, some 6,000 new employees are needed every year to service the expanding hospitality and tourism industry, according to Failte Ireland, the national tourism development authority (Cohen, 2005). From this, it can be seen that Tourism and Hospitality person nel are in the world has been very scarce. Through study Tourism and Hospitality at University, it can be improve students quality, skills, adaptability, communication skills. Thus, students need to study Tourism and Hospitality at University and study it well.

Marketing goals Essay

In order to set SMART (Specific, Measurable, Achievable, Realistic and Time bound) goals, it is highly important that there is a compatibility between the marketing and business goals. (Write Market). The broader marketing goal is to become a cost leader and gain a larger market share in the market of toy manufacturers (Locally) in 25-30 years since the company at present is at its infancy stage. Company’s focus at present unlike its competitors is to give customers â€Å"More for less† in terms of value. However, this long-term goal represents where the company wants to be in the future. The short-term goals include enhancing external positioning in the toy market by conducting ATL (Above the line marketing communication strategies like advertising, working on store ambiance and layout to make them more consumer friendly, etc) and BTL (Below the Line advertising like events, stalls, discounts, etc), maintaining and enhancing relationships with suppliers. Stakeholder engagement, Up-to-date Knowledge about market trends, customer needs and changes in customer needs are also important marketing goals. It is also important that the toys Unique Selling Proposition i. e. low price, environmental friendliness, distinct benefits of using ORIGIN, innovative uses, etc are clearly communicated.

The Numerical Methods for Real Options - Free Essay Example

Sample details Pages: 18 Words: 5491 Downloads: 4 Date added: 2017/06/26 Category Finance Essay Type Analytical essay Did you like this example? According to Mun(2006), Real Options(RO) is a systematic and comprehensive method used to value real tangible assets. The term Real Options, first used by Myers(1977), refers to the application of financial options theory to investment decisions made by firms (Krychowski and Que ´lin, 2010). RO has been of growing interest to the academic community as a promising approach to supporting investment decisions under uncertainty. Don’t waste time! Our writers will create an original "The Numerical Methods for Real Options" essay for you Create order Pioneering scholars such as Trigeorgis(1996) and Copeland(2001), have contributed valuable work to topics on real options such as the RO value in resource allocation and capital budgeting. Generally speaking, there are three main methods which are used as the tools to value the embedded RO. They are the Black-Scholes Model, the Binomial Model and Monte Carlo Simulation. Each of the method requires certain assumptions and can be best applied under specific situations. On the empirical side, RO analysis has been applied widely in a range of industries such as pharmaceutical drug development, oil and gas exploration and production, and the like. Survey results of 4,000 CFOs published in 2001 by Graham and Harvey revealed that 27% of the respondents claimed they always or almost always used some kind of options approach to evaluating and deciding upon growth opportunities (Copeland Tufano, 2004). Compared with the traditional discounted cash flow methods which assumed that the future ca sh flows can be discounted by a single fixed rate, RO analysis enjoys the merit of being highly flexible because it incorporates the managers ability to actively respond to the unfolded uncertainties. It is noted by Hall (2005) that around 30 percent of the values of high-growth, high volatility firms come from the value of embedded options. Primarily motivated by the usefulness of RO, after doing a general research on its background, I did further reading on approaches employed to value the embedded options. In this paper, my work can be divided into three parts. In the first section, a background on the real option analysis is presented. This includes an overview of typical categories of RO, the classical methods employed to value the RO and also the industrial practices of applying the RO Analysis. Additionally, a brief comparison between the traditional methods and RO is also presented. In the second section, I demonstrate the three methods in detail with elaboration on their assumptions and steps of analysis, as well as examples of application. In the final section, I conclude with a discussion of these numerical methods, including their merits and limitations as well as responses to some of the critics that RO analysis has incurred. I hope that this paper could serve as a motivator for further research. Literature Review Managers nowadays are facing a rather volatile environment because of the mixed effects of globalization, deregulation and technology break through (Krychowski and Que ´lin, 2010). RO helps them to make use the advantages of uncertainty and their flexibility. It has been crucial in the way that it helps the firm to identify, understand, value, prioritize, select, time, optimize and manage strategic investment and capital budgeting decisions (Mun, 2006). Similar to the financial option models, RO is useful both to evaluate an investment project and to determine the optimal investment timing (Krychowski and Que ´lin, 2010). The most common forms of RO, based on the division given by Copeland and Antikarov(2001) and Mun (2006), are : option to abandon, option to expand, option to switch, option to defer and sequential compound options. In detail, for example, an option to expand enables the management to expand into different markets, products, and strategies or to ex pand its current operations under the right conditions (Mun, 2006, p19). Multiple methodologies and approaches are used in RO to calculate the embedded options value. These range from using closed-form equations like the Black-Scholes model and its modifications, Binomial Models (for example, binomial lattices and binomial trees) and Monte Carlo simulations and other numerical techniques. Since this will be the main part of this paper, it will be illustrated in detail in the next section. Primarily used as a tool for strategic decision making in natural resource companies, in the recent decade, RO has been applied in a broader ranges of industries, including private equity, oil and gas exploration and production, manufacturing, IT infrastructure, pharmaceutical drug development, e-commerce and e-business, technology development, and the like ( Mun,2005). The following are some of the industry examples of applying RO. Equity According to Berger, Ofek and Swary (1996), a cons iderable proportion of equity value should be attributed to the equity holders abandonment option. They prove a difference of 11.5 percent between equity market value and the present value of cash flows for more than seven thousands firm over a 6-year period horizon. By running a series of regressions the authors find an interaction between the market value to present value premium and variables which should be linked to higher values for the abandonment option. Natural resource While evaluating the investment projects for natural resource, Brennan and Schwartz (1985) isolate the disadvantages and inadequacies of the traditional DCF approach. Particularly, they point out that obvious deficiencies are due to the overlook of the stochastic nature of output prices and of potential managerial reactions to price changes. Price uncertainty is of central concern in many natural resource industries where price fluctuates around 30 percent per year are usual. Under such circumstances the evaluation results obtained through substituting the expected values of future prices by their distributions is likely to be misleading. Oil By extending the financial option theory, Paddock, Siegel and Smith (1988) develop a new approach to valuating options on a real asset, an offshore oil lease. The authors show us how to utilize an explicit model of equilibrium in the market for the underlying real asset, i.e. the developed petroleum reserves, with option-pricing technique to derive the value of a real option. At the same time, they examine a valuation problem in sufficient detail by using the oil leases as an example. This allows close reviewing of the many theoretical and practical issues involved in applying financial option valuation theory to RO. Gold In 1998, Kelly adopts an eight period binomial option approach to estimate the value of a discovered but yet unexploited gold mine, Lihir Gold Limited. In particular, she compares the value calculated from the option mod el to what was obtained from the traditional method. The option approach appears to provide a more useful and accurate technique to evaluate the value of the gold mine . In 2002, Moel and Tufano conduct a research on the opening and closing events of 285 gold mines in North America from the year of 1988 to 1997. Strong evidence is found to support the conclusion that, compared with other methods, real (switching) options provide better explanations for the decisions on openings and closings of the gold mines. Manufacturing Newbhard, Shi and Park (2000) use a case-study to stimulate the academic and practical research needed to support a real option framework for system changes in four major manufacturing transitions which are launch of new product, commercialization of RD product, site selection of new plant and restarting production of existing commodities. By presenting a framework, they quantify manufacturing changes, develop a real option model for these activities, value the options, identify the best scenarios and integrate these elements in order to monitor and manage the overall process. They also propose a general model for optimizing real option valuation based on typical RO models such as the Black-Scholes Option Model, the Binomial Option Model. They conclude that a model that incorporates flexibility and economic factors could effectively enhance companies manufacturing strategy. Unlike the traditional valuation approaches, such as the discounted cash flow (DCF) method which bases itself on a static environment, real option analysis takes into account the potential for possible future gains and incorporates active decision making. Thus it tackles uncertainty in a better way. Specifically, deterministic models such as DCF method bases itself on some rather flawed assumptions. It assumes that all the future outcomes are fixed and can be evaluated as individual cash flows. Even more unreasonable, it seems to give a Once for All solution whic h assumes once initiated, all projects are passively managed. RO, on the contrary, accepts the facts that projects are correlated and can be actively managed through its life path. By taking the fluid environment and managerial flexibility into account, RO provides value-added insights to decision making (Mun, 2006). Numerical Methods As I have mentioned in the previous section, multiple approaches have been employed by researchers and practitioners in RO. This part will introduce the readers to three common types of methods in RO, namely, the Binomial methods, the Black-Scholes Model and Monte Carlo Simulation, from the origins of them to present application examples. More specifically, a step-by-step binomial approach is used to analyzing a compound option problem in the case study with two different techniques, so as to offer a deeper understanding for the readers. As for the Black-Scholes and Monte Carlo Simulation, due to the word limit and time constraint, I used two simplified examples from Newbhard et al (2000) and Damodaran( 2005) in the hope that the readers could have a general sense of how the two methods work. Binomial approach Work by John Cox, Steve Ross, and Mark Rubinstein has led to the creation of binomial, or lattice, models that are built around decision trees and are ideally suited to real-option valuation. As it noted by Copeland and Tufano (2004), RO dont have to be a black box. Binomial methods, with its advantage of easy math and apparent illustration has make Real option analysis a more practical tool for manager in the new era. According to Brandao et al (2005), a binomial lattice may be viewed as a probability tree with binary chance branches, with the unique feature that the outcome resulting from moving up(u) and then down (d) in value is the same as the outcome from moving down and then up. This probability tree, also referred as decision tree, can be used in modeling managerial flexibility by incorporating the decision nodes which represent decisions the managers can make to optimize the value of the project. A three-step binomial tree is illustrated below in figure1. Before enterin g details about how to use the binomial method, it is worthwhile to make certain clarifications on the assumptions behind this approach. In their book RO, Copeland and Antikarov (2001) made the marketed asset disclaimer assumption (henceforth MAD) that the market value of a project is best estimated by the present value of the project without options. Additionally, if the movements in the value of the project without options are then assumed to change over time according to a geometric Brownian motion (GBM), then the value of options can be obtained through traditional option pricing methods. Generally, there are three essential steps that need to be gone through when a binomial approach is adopted. Step1 Calculating the expected present value of the project at Time0 Step2 Obtaining estimates of the standard deviation of returns (or volatility of the project) by using a Monte Carlo simulation. Step3 Constructing a binomial tree to model the dynamics of the project value using the estimated parameters of the second step and add the decision nodes to model the projects RO. No matter what real option model is of interest, the basic structure almost always exists, taking the form: Inputs: S, X,, T, rf, b u= and d== P= Source: Mun, 2006 The basic inputs are the present value of the underlying asset(S), present value of implementation cost of the option( X), volatility of the natural logarithm of the underlying free cash flow returns in percent(,time to expiration in years(T), risk-free rate or the rate of return on a riskless asset(rf), and continuous dividend outflows in percent(b). In addition, the binomial lattice approach requires two additional sets of calculations, the up and down factors ( u and d). The up factor is simply the exponential function of the cash flow returns volatility multiplied by the square root of time-steps or stepping time (.The volatility measure is an annualized value; multiplying it by the square root o f time steps breaks it down into the time steps equivalent volatility. The down factor is simply the reciprocal of the up factor. In addition the higher the volatility measure, the higher the up and down factors. This reciprocal magnitude ensures that the lattices are recombining signs. The second required calculation is that of the risk-neutral probability, defined simply as the ratio of the exponential function of the difference between risk-free rate and dividend, multiplied by the stepping time less the down factor, to the difference between the up and down factors. In order to give the readers a more clear understanding on this, below is a case study of a sequential compound option problem, in which the execution and value of future strategic options depend on previous options. It represents a simplification of the business decision-making case and my purpose is to illustrate how a RO valuation is implemented using binomial approaches. Case Study A chemical company is considering a phased investment in a plant. There are three periods. In the beginning of year one, an initial outlay of $50 million is required to cover the cost of permits and preparation. At the end of that year, the firm has the choice to pay a commitment of $200 million to enter into the design phase. Once the design is finished one year later, the firm is believed to have a two year window during which to make the final investment in constructing the plant for $400 million. If the firm chooses not to make any investments during these two years, it can no longer to build the plant. For managers who think from the real-options perspective, this phased investment opportunity is a sequential compound option. Clearly, the initial payment of $50 million allows the firm to have the option to go on with the project for one year. At the end of year one, it again faces the choice of whether or not enter the stage of design by investing an additional $200 million . As the result, the execution of the design phase gives the firm the option to construct the plant at the end of year three or at the end of year four for $400 million. The firm estimates that if the plant existed today it would be worth $550 million by using non-option valuation techniques such as the DCF. In applying Binomial method, basically there are two techniques. The one is the decision tree approach the other is the replicating portfolio technique. I will use both of them to analyze the above case and give some comments on these two techniques. Decision Tree Analysis Prior to analyzing this problem, we must make some assumptions concerning the uncertainty in the future value of the project. We assume that current prices of the project have already incorporated all relevant information available at this point, known as part of the efficient market theory. At the same time, future changes are modeled as a random walk. This facilitates the use of a Geometric Brownian Motion (GBM) to model the dynamic uncertainty associated with prices movements (Hull, 2003). The key parameters required here are the estimated initial value, $550 million, the annual risk-free interest rate r, assumed to be 6% and the volatility, represented by, which is the annualized percentage standard deviation of the returns and is given as 18.23% here. By using the calculating structure given previously, we can calculate the corresponding values of u and d, and values for each branch of the binomial approximation. We then obtain the risk-neutral probability p ==. In this case study, the model have three periods and choose time interval to be t = 1. Therefore, u = 1.2, d =0.83, and p =0.673. For details about this binomial approximation, see Hull (2003). The value of the project is calculated via Vi,j =V0ui-jdj.For example in the right top scenario, the value of the project is $798 million which equates $550 million multiplied by 1.23. (Note: Values shown at each node in the tree are discounted Year 3 values, instead of the actual values at each point.) After approximate the project value according to the GBM, now we are going to value the Value of the Option to invest in this project. Here we used the same parameters in a decision tree with binary chance nodes to yield an equivalent binomial tree for the project value, as shown in Figure 3 below. Decision tree analysis works in the way that it models managerial flexibility in discrete time by constructing a tree with decision nodes. These nodes represent choices the manager can make to optimiz e the value of the project as uncertainties are resolved over the projects life. Note: represents a chance node in which the project can either move up or down with the probabilities of up=0.673, down=0.327 represents a decision node in which the firm can chose to invest or not denotes the termination of one possible case the line in bold shows the optimal investment strategy in different cases Lets suppose that at the end of year3, we arrive at the best scenario in which the project value is $798 million (See Figure2). If we choose to invest the extra $400 million, we will have an income of $223 million. Otherwise we will lose what we have paid for the preparation and design phase, say, $239 million. Rational managers will of course choose to invest further. The same calculation applies in the scenario with the increases in first two years and a decline in year three. By multiplying the values obtained from the decision nodes with their up and down probabilities, we arrive at the option value in year2. Using this rollback method, finally we obtain the value of option at year0, which is $31million. Replicating portfolio technique Using the binomial model which adopts replicating portfolio technique also requires two main steps. First, we need to figure out the full range of possible values for the underlying asset, in other words, draw the event tree, as shown in figure4. Figure4 (It has to be noted that, unlike the numbers for the binomial tree which have been discounted to present value, the numbers I used here are the value in that specific period.) Secondly, our task is to calculate the possible values of the project as an option at each stage. It is a backward working process and we have to begin from the end. If we abandon the project, its value is zero. Otherwise, the value at the end of that year, year three, for example, is the difference between the value of the plant at the end of year three and the expense of building it. As you can see from the figure5, we have got three potential scenarios in which the projects incremental value at the end of year three is positive and one in which th e costs of the project exceed the plants value, so the project value is zero. We now work back from the end of year three to determine the projects potential values at the end of year two. The decision rule is that in each scenario, the value will be the larger of the value of exercising the option by building the plant at that point for a cost of $550 million and the value of keeping the option window open-deferring the decision until the next period. The steps can be summarized in the followings and Figure5 serves as an illustration of the results. Step1: Calculate the potential final project values by subtracting the $400 million cost (from the event tree of Figure5). For the $314 million scenario at the bottom right of the event tree, the projects value is zero due to the cost is greater than the plant value. Step2: Obtain the potential end-of-year-two project values by comparing two calculation results. One is the value by exercising the project immediately, the oth er is the value if the project is kept alive by applying the replicating portfolio technique. Step3 ¼Ãƒâ€¦Ã‚ ¡Similar to step2, yet the number used to be compared with the value derived from replicating portfolio technique is $200 million, since immediate exercise of the project is not possible. Step4: Calculate the starting project value of $81million. Since the initial required investment is $50 million, the project is profitable. The option value is the same as what is derived by the decision tree method, which is $31 million. Figure5 Some Comments: As we can see from the above, the results obtained from Binomial Decision Tree and Replicating portfolios Techniques are largely similar. It is worthwhile to compare them briefly. The binomial approach is suggested by Copeland and Antikarov(2001), they emphasize the use of binomial lattices and replicating portfolios while Brandao et al( 2005) believe that the use of binomial trees is more intuitive appealing. The replicating approach bases itself on traditional option pricing methods, requiring that markets be complete. An important advantage of this approach to valuation is that the value of option can be calculated from market data. This avoids the estimation of the probability q of an up move in the stock price. However, for most projects involving real assets, there is no such a complete market. In this sense, using this approach appears to be complicated. Additionally, it is criticized for its computational cumbersomeness especially in a multi-stage project. Black Scholes model With their article from 1973, Fisher Black, Myron Scholes, and Robert Merton were the first to give a closed form solution for the equilibrium price for a European call option, the Black Scholes Model (BS model). It has since been the basis for numerous studies and papers about the pricing of options and empirical testing hereof. In essence, the model is a special case of the binomial model where the underlying asset is assumed to follow a continuous stochastic process instead of a discrete. Otherwise, it is based on the same underlying assumptions of no arbitrage and market replicating portfolio and that the movement of the underlying asset follows a lognormal distribution (Copeland Antikarov, 2001) It has to be noted that variants of the BS model have been made, which relaxes some of these assumptions. BS models are based on calculus of stochastic differential equation which is highly complex. So unless one can find a modified BS model that fits one own specific situation, th e process of deriving a BS model that does is very cumbersome and complex. The Black Scholes model is a so called closed form solution, meaning that a value can be found with an equation using a set of inputs. The inputs in the BS model are the same as the binomial model, with dividend as the one exception. The value of a call option( C) is calculated as: Source: Copeland Antikarov, 2001,p.106 Where and is the cumulative normal probability of unit normal variable and respectively. They are calculated as: ; Source: Copeland Antikarov, 2001, p.106 Other than the assumptions also applying to the binomial model mentioned above, the BS model has several other restrictive assumptions embedded (Copeland Antikarov, 2001 and Mun, 2002) which are: The option can only be exercised at maturity-it is a European option There is only one source of uncertainty It can only be used on a single underlying risky asset; ruling out compound options No dividends on the underlying asset The current market price and stochastic process of the underlying asset I known (observable) The variance of the underlying asset is constant over time The exercise price is known and constant over time No transaction costs Benaroch and Kauffman (1999) provide a formal theoretical grounding for the soundness of the BS option pricing model in capital budgeting methods that might be employed to assess Information Technology (IT) investments. They also demonstrate why the assumptions of both the BS and the binomial option pricing models impose constraints on the spectrum of IT investment situations that can be evaluated similarly by traditional capital budgeting methods such as discounted cash flow analysis. Most importantly, they demonstrate the first application of the BS model that uses a real-world IT business case as its experimental area. To illustrate the application of BS more clearly, I borrow an example of Brennan and Schwartz (1985) which uses option pricing theory to value a gold mine and present it with a simplified version below. Option to delay for a Gold Mine Consider a gold mine with an estimated reserve of 1 million ounces and a capacity output rate of 50,000 ounces annually. The firm maintains the ownership of this mine for the next 20 years. We expect the gold price will grow at 3% per year. It will cost $100 million to open the mine and the average variable cost is $250 per ounce; once the mine opened, the variable cost is expected to grow 5% a year. The current price of gold is $375 per ounce and its standard deviation is estimated as 20%. The riskless rate is given as 6%. The inputs to the model are summarized as follows: S = $ 47.24 million X= $100 million = 0.04 t=20 years rf= 6% Dividend Yield = = 1 / 20 = 5% Based upon these inputs, the Black-Scholes model provides the following value for the call: The value of the mine as an option is $ 3.19 million which is recognized as the mines embedded option. Monte Carlo Simulation : Because of the difficulty in obtaining the needed parameters for analytical models such as the Black-Scholes model, researchers find an alternative way to value RO by using an approximate numerical method such as Monte Carlo simulation. Monte Carlo simulation, named for the famous gambling capital of Monaco, is a very powerful methodology (Mun, 2006). Monte Carlo, in its simplest form, is a random number generator that is useful for forecasting, estimation, and risk analysis. A simulation calculates numerous scenarios of a model by repeatedly picking values form a user-predefined probability distribution, such as the normal, uniform and lognormal distributions, for the uncertain variables and using those values for the model (Mun,2006,p317-318). Boyle (1977) was among the first to propose using Monte Carlo simulation to study option valuation. What distinguishes this approach is its generality in being able to model imperfect market conditions which are difficult to be captured in other models. The Monte Carlo method proves to be most effective in situations where it is difficult to proceed using a more accurate approach (Boyle, 1977). Researchers share a common emphasis on the need for investigating practical issues related to efficiently approximating various option models via Monte Carlo simulation and including sensitivity analysis and Quasi-Monte Carlo simulation approaches (Boyle,1977; Fu and Hu,1995; Birge 1994; Newbhard, Shi and Park ,2000 ). Example: For a manufacturing company A, market research revealed a demand for a new product. The unit price of the new product is $100. The initial monthly demand for this product is 1,000 units with a standard deviation of ÃÆ' Ãƒâ€ Ã¢â‚¬â„¢ = 0.33. The product will be introduced over a four month period (T = 4) with monthly fixed interest rate of1%. Suppose we let S equal X, i.e. $100 multiplied by 1,000 which gives $100,000. To imitate the path followed by the state Variable S, we divide the phase of the variable into four time intervals. If dt is the length of one interval, then the relation between the S values is offered by Source: Newbhard, Shi and Park , 2000 Executing 1,000 Monte Carlo runs of this equation obtains an option value of $8,203, which is quite similar compared to the value of $8,155 derived from the BS model. Discussion For the practitioner, simulation opens the door for solving difficult and complex but practical problems with great ease. Monte Carlo creates artificial futures by generating thousands and even millions of sample paths of outcomes and looks at their prevalent characteristics (Mun, 2006). When modeled correctly, Monte Carlo simulation provides similar answers to the more mathematically elegant methods. Closed-form solutions can be obtained from models such as the Black-Scholes, given that a set of input parameters are estimated. BS model is exact, quick, and easy to implement with the assistance of some basic programming knowledge but is difficult to explain because applying it requires high skills of technical stochastic calculus mathematics. They are also very specific in nature, with limited modeling flexibility. Closed-form solutions are mathematically elegant but very difficult to derive and are highly specific in nature. The use of algebra distinguishes binomial models a nd enables the models to be built using standard spreadsheet software such as EXCEL. Binomial models can also be easily customized to reflect changing volatility, early decision points, as well as multiple decisions (Copeland, 2004). Another practical advantage is that because the transparency of the model, it could be understood and used by managers without very strong mathematical background. Binomial lattices, compared with close-form solutions, are easy to implement and easy to explain. They are also highly flexible but require significant computing power and lattice steps to obtain good approximation. The process of working through lattices can be cumbersome and less intuitive, which is particularly true for more complex cases to real assets with several coinstantaneous and compound options. It is important to note, however, that in the limit, results obtained through the use of binomial lattices tend to approach those derived from closed-form solutions. The choice of mod els in practice is largely depending on the underlying assets nature of changes. A possible process for deciding upon which model to use is presented below. Identify and Define RO (1) Quantify Activities Related to Changes Related to Changes (2, 3) Choose Solution Method Binomial Model Underlying change is a binomial (discrete) process Black-Scholes Model Underlying change is a lognormal (continuous) process Monte Carlo Simulation When parameter Estimation is needed REAL OPTION ANALYSIS Source: Newbhard H. B., Shi. L, Park .C (2000) Although managers today are facing a more volatile environment, most of them still rest their decisions on deterministic methods such as the discounted cash flow method, which is static in nature (Krychowski and Que ´lin, 2010). RO have problems in the implementation sector and empirical evidence shows that it is little used in practice. Whereas about 75% to 85% of firms use NPV for their investment decisions, only about 6% to 27% of them use RO analysis. Empirical studies on the implementation of RO are still rare, and research remains relatively silent on how to concretely apply RO theory (Krychowski and Que ´lin, 2010). Main Critics of options-based methods to valuing and managing growth opportunities often have two arguments. One is the huge difference between the highly complex real options and relatively simple financial options. The other is that the real option analysis relies itself on some simplified assum ptions. However, just as Copeland (2004) noted, differences do exist but are not unsolvable. Lets take the availability of information as an example. Financial options can be valued based on their underlying assets price such as the stock price. For real options, in some cases the values of their underlying assets can be observed in the same way. A coal company could estimate the value of its reserve coal by checking the expected exploitation costs and the current price of coal. It is true that at most circumstances we dont know the exact value of the underlying asset. Yet by observing comparable assets or making educated guess based on certain assumptions, we can do the estimation. In the end, option models are not the only method that requires assumptions. The main alternative to real-option analysis-discounted cash flow method-does make simplified assumptions such as the pre-committed future cash flows. Conclusion Real Options, as it is remarked by Hall(2005), is one of the most crucial important decision-making tools introduced to managers in the last three or four decades. By utilizing financial theory, economic analysis, management science and econometric modeling, real option analysis can be very useful for investment decision making in the context of uncertain environment. Managers are allowed to make flexible midcourse corrections when adopting RO (Mun, 2006). I began paper by familiarizing the readers with the essential background of RO which includes the classifications of RO and methodologies adopted to value the embedded options. The merits of RO have been discussed via a comparison with the traditional DCF method. Meanwhile, they have also been introduced to several industry applications, ranging from the equity market to manufacturing industry. Then it comes the main part of this thesis-demonstration of the three RO methods, which are the Binomial Approach, the Black and Schol es Model and Monte Carlo Simulation. A case study has been worked out via using the two techniques of the Binomial approach with the details shown on the graphs. Two simplified examples of applications of the other two methods are also included to offer the readers a general sense. Furthermore, in the discussion section, I have compared the three methods with respect to their merits and limitations. A general process of model selection is presented in a flow chart as an illustration. As for the further research, it is suggested that there is a need to find a general approach which integrates at least two models discussed in this paper. At the same time, it might also be an interesting subject to compare the usefulness of RO in different industry settings.