The second limiting factor is the cost to conduct research. Not enough research dollars available to perform a comprehensive analysis of secondary information of all major cities on the perceptual map which may be beneficial due to the lack of supporting data surrounding the initial targeted cities.
In review of the primary research survey tool one can see that the information can be flawed easily due to language barriers. Because India has 24 major languages the ability to conduct a survey that is 100% reliable and valid may be compromised.
Validity and reliability
To prove validity one must establish a confidence level in the data. Confidence in data is achieved through a range of values constructed from sample data so that the population parameter is likely to occur within that range at a specified probability. The specified probability is called the level of confidence (Lind 2004, Ch 9). Due to the lack of data on all cities in India, Coffee Time was not presented with a level of confidence that validates the chosen cities.
In order to stand the test of reliability of the data; one must know the sources and the standard deviations in order to make sound projections. Good research also relies on the Empirical Rule which states, “For a symmetrical, bell-shaped frequency distribution, approximately 68 percent of the observations will lie within plus and minus one standard deviation of the mean; about 95 percent of the observations will lie within plus and minus two standard deviations of the mean; and practically all (99.7 percent) will lie within plus and minus three standard deviations of the mean.” (Lind et al.). The primary research tool that Coffee Time plans to use may lend a higher standard deviation than expected due to the culture and language differences. Finally, the tool was developed without much consideration of the Indian culture evident by the fact that it did not contain specific cultural questions that address the effects of fasting and religious holidays on the coffee market.
Secondary research and Random Sampling
Several issues related to the research and random sampling methodologies need to be addressed in order to make sound business decisions. The first is the culture and behavior of the people of India. Do Indians believe in dining out, or are they opposed to this behavior? What is the repeatability of the customers in India? Is it an occasional behavior or is it their pattern to purchase coffee daily?
Random Sampling
Random sampling is known as a sample selected so that each item or person in the population has the same chance of being included. The sampling process is comprised of several stages: 1) define the population of study 2) specify the sampling frame 3) specify the sampling method for variables or events from the frame 4) determine the sample size 5) implement the sampling plan 6) sample and do data collection and finally 7) review the sampling process. (Need to cite a source?)
Successful statistical practice is based on focused . Typically, companies seek to take action on some in this case the selected cities in India. The selection of the cities Delhi and Mumbai are critical to the sampling. Coffee time will use a sampling frame which has the property in which we can identify every single element and include any in our sample. For example, in an , possible sampling frames include the telephone directory and random customers in any coffee bar in Delhi and Mumbai on any workday morning. Since the sampling frame must be representative of the population. All the above frames omit some people who will purchase coffee at Coffee Time and contain some people who will not. People not in the frame have no prospect of being sampled. In defining the frame, practical, economic, ethical, and technical issues need to be addressed. Having established the frame, the next step is to develop a way of organizing it to improve efficiency and effectiveness. Within any type of frame, a variety of sampling methods can be employed, individually or in combination. Sampling is divided in two categories, the first is probability sampling and the second is non-probability sampling. (Need to cite a source somewhere?)
In a of a given size all subsets of the frame are given an equal probability. Each element of the frame will have an equal probability of selection; if the frame is not subdivided or partitioned the possibility the sample will not be completely random exists. In the Coffee Time case the company could select every 10th name from the telephone directory, which is an example of that is not . For example, every 10th sampling is especially useful for efficient sampling from .
Where the population embraces a number of distinct categories the frame can be organized by categories into separate "strata." A sample is then selected from each "stratum" separately, producing a . In this case we would categorize the age as being between 13-54, and the monthly income of the participants. Typically, the strata or categories should be chosen to have means that are different from one another, and minimize any variance between the strata.
It may be cheaper for us to 'cluster' the sample in some way e.g. by selecting respondents from certain areas only, or certain time-periods only. is an example of '' or '': in the first stage a sample of areas is chosen; in the second stage a sample of respondent within those areas are selected. This can reduce our travel and other administrative costs. It also means that we do not need a for the entire population, but only for the selected clusters.
In quota sampling, the population is first segmented into sub-groups, being Mumbai and Delhi. Then judgment is used to select the subjects or units from each segment based on a specified proportion. For example, we may interview a sample of 200 females and 300 males between the ages of 20-34.In quota sampling the selection of the sample are non-. For example, our interviewers might be tempted to interview those who look more prosperous. The problem is that these samples may be because not everyone gets a chance of selection. (Need to cite sources somewhere?)
Two types of random variables exist: categorical and numerical, we could use Categorical random variables yield responses which will be 'yes' or 'no'. Categorical variables can yield more than two possible responses. For example: 'Which days of the week are customers’ most likely to purchase coffee?' Numerical random variables can indicate what time of the day that they may purchase coffee. Upon review of numerical variables, two types exist: discrete and continuous. Discrete random variables produce numerical responses from a counting process. An example is 'how many times do cusotmers visit the coffee bar in a typical month?' Continuous random variables produce responses from a measuring process and in this case will not be applicable.
In the sampling process we know that good data collection involves the following: following a defined sampling process, keeping the data in time order, noting comments and other events, and finally recording any non-responses. (Need to cite sources?)
After sampling, a review should be held to understand the exact process followed in sampling in order to study any effects that divergences might have on subsequent analysis. At this point we can narrow our decision making process down to whether India is the ideal location for Coffee Time.
Decision Making Strategies
The decision making strategies recommended to the company are based on the secondary data given to Coffee Time. As the Manager for Business Development a method for further data may be required before deciding where to locate Coffee Time outlets in India. One method of obtaining additional data is through a Feasibility Study. A feasibility study is an analysis of an idea and focuses on determining the viability of a project before initiation (Hofstrand and Holz-Clause, 2007).
A feasibility study is usually undertaken following a series of business ideas or scenarios and assists in framing specific business alternatives so that each can be studied in-depth (Hofstrand and Holz-Clause, 2007). In the initial stages of the process the number of business alternatives under consideration is usually reduced rapidly. During the feasibility process companies may investigate a variety of ways of organizing the business and positioning products in the marketplace.
An additional strategy Coffee Time may want to explore is the creation of a test market in the city of Delhi, India. Delhi is highly populated city and diverse in terms of age and culture, with the majority of the in the age bracket between 13-45, and little differences gender percentages (University of Phoenix, 2008). The majority of the income in Delhi is between $5,000-$15,000 Rupees (Rs). Delhi contains a high percentage of educated populace, even though the city has only a small number of students. Delhi has a high number of restaurants and ranked second in malls and mall visits (University of Phoenix, 2007). The competition for Coffee Time in Delhi is half of what the company will face in Mumbai.
The final strategy for Coffee Time to initiate following a successful launch in the city of Delhi will be expansion into the cities of Bangalore and Pune. Coinciding with expansion Coffee Time should develop an in-depth analysis of Indian and Hindu culture. Understanding the Indian and Hindu culture is extremely important to its success in the foreign market. Gathering cultural, social, and economic data will assist Coffee Time in offering the appropriate goods and services and proper product placement that will appeal to Indian clients (Craig and Douglas, 2006). The products and coffee flavors sold at traditional Coffee Time locations in the United States may not appeal to the Indian culture. Gaining information on the coffee brands, foods and snacks consumed with coffee, traditional uses, culture influence, and population that consume coffee are all necessary information needed in determining a location (Lind, Marchal, and Wathen, 2005, Chap. 1, p. 11).
Coffee Time Constraints
In the scenario presented Coffee Time has been faced with several constraints regarding the company’s plan to expand into the market in India. For example, Coffee Time had to look at the size of the market available, the country’s lack of modernism and richness, and the company’s budget of $250,000 imposed by my management. Based on these various constraints, Coffee Time will need to develop a research plan that adheres to all the constraints in order to be successful in the market of India.
Another constraint that Coffee Time is experiencing is due to the limitations of the secondary research provided by Total Access. Important information is missing and not all the angles have been covered. Due to this constraint, Coffee Time will conduct additional primary research in order to determine additional demographics and inferential statistics.
Time has also presented another constraint for Coffee Time. Time is limited and more information is needed before reaching a decision. The secondary data received from Total Access does not provide us with any information regarding possible errors in the data for potentially inaccurate or incomplete data. Although this data will save valuable time, and the results of the questionnaire returned favorable results, an experimental study to validate the findings needs to be conducted and of cause this will also take some time. Since Total Access has experience in performing the task, contracting them to do so will save us time.
Lastly another constraint to Coffee Time's emergence into the Indian coffee market is that it does not have first-mover advantage. They don’t have an establish brand recognition. Through primary research, Coffee Time will discover the brand loyalty to competitors as well as number of competitors each city has which will determine if each of the cities has room for them, or if the market is saturated.
Conclusion
In conclusion, Coffee Time has the tools to emerge as a successful coffee bar enterprise in the Indian market through targeting the middle-age population and encouraging the decisions of teens and young adults to experience the exotic and regular coffee flavors. Utilizing good research skills will result in valid and reliable data. The key to successful market expansion is to identify what the strategy is, collect relevant and reliable data, validate data so that the data is reproducible, examine thoroughly any possible constraints and error in data, and design survey instrument to achieve the most accurate results. Coffee Time can become a global leader in the specialty coffee industry by implementing a successful marketing research design.
References
Cooper, D., & Schindler, P. (2003). Business Research Method. [University of Phoenix
Custom Edition e-text]. NewYork, NY: Prentice Hall. Retrieved November 29,
2008, from University of Phoenix, Resource, MBA 510-Managerial Decision
Making Web site.
Craig, C. S., & Douglas, S. P. (2006). Beyond National Culture: implications of cultural
dynamics for consumer research. International Marketing Review, 23(3), 322.
Retrieved November 28th, 2008, from ProQuest Database.
Hofstrand, D. & Holz-Clause (2007). What is a Feasibility Study? Retrieved November 29, 2008,
from PROQuest database at: http://www.extension.iastate.edu/agdm/wholefarm/html/c5-65.html
Lind, D., Marchal, W., & Wathe, S. (2004). Statistical techniques n business and economics. University of Phoenix Custom edition e-text. New York, NY:McGraw-Hill. Retrieved November 29, 2008, from University of Phoenix,
rEsource, MBA510-Managerial Decision Making Web site.
Terror Attack on Mumbai, retrieved on November 30, 2008 from www.Fox News.com
University Of Phoenix website, Statistics and Research Methods for Managerial
Decisions, retrieved on November 30, 2008 from
University of Phoenix 2008 MBA 510 Managerial Decision Making, Scenario