Abstract
This paper explores how research methodologies can be used to resolve organizational issues. Using Starbucks as the company of focus, this paper discusses the qualities of qualitative and quantitative research and how they can be used for investigation and analysis in an organizational setting. It is hypothesized, for instance, that the decline in Starbucks’ sales as well as the poor performance of some of its stores is due to poor customer service. The concept of customer service, however, is too abstract to measure directly. However, this hypothesis can be determined using qualitative research methods as opposed to the quantitative method. Nevertheless, it does not mean that the qualitative research method is superior compared to quantitative research. In fact, no research method can be categorized as inferior or superior against another. In this context, the paper implies that the success of the research method used is determined by the skill of the researcher in applying these research methods appropriately. Furthermore, the paper also provides a background on regression analysis and how it can be used as a tool to measure customer satisfaction.
Introduction
Starbucks is, unarguably, the most successful coffee and refreshment company in the world. The company currently operates around 19,000 stores in 60 different countries (STARBUCKS COFFEE COMPANY, 2011). Like most success stories, Starbucks started out as a small coffee retailer in Seattle; a business venture of three educators: Zev Siegel, Jerry Baldwin and Gordon Bowker. The trio repacks and sells roasted coffee beans, which they bought from Alfred Peet, a coffee bean importer and enthusiast. As the demand for their products grew, Siegel, Baldwin and Bowker decided to import and roast their own coffee. The modern image of Starbucks, however, did not emerge until Howard Schultz joined the company in 1982. From being a coffee bean retailer, Schultz transitioned Starbucks into coffee bars; a business model that he copied from his experience with coffee bars in Italy. Schultz observed that, just like wine, Italians are very particular on how they enjoy their coffee. Schultz wanted to set up this type of bistro in the United States wherein coffee is meticulously served in a cozy and comfortable setting. Schultz’s business model became an instant success. After acquiring the company in 1987, Starbucks’ growth became phenomenal. At its peak, the company operated 24,000 stores in the United States alone, 60% of which are franchised (Garthwaite, Busse, & Brown, 2012).
The company’s rapid expansion, however, brought about many challenges. In 2007 many of Starbucks stores were closed because of performance issues (Garthwaite et al., 2012). Scholars believe that this decline in sales is caused by customer service issues that plagued the company associated with its rapid growth. Some observers, for instance, criticized the company for deviating from its core values. Accordingly, some stores, particularly those who are far from its distribution centers, are always out of something (Garthwaite et al., 2012). The company has also replaced its meticulous coffee brewing methods with instant coffee making machines in order to meet its self-imposed, ‘3 minute service goal’ (Garthwaite et al., 2012). Many competitors have also threatened the company’s superior position in the coffee beverage industry. Companies such as McDonald's and Dunkin Donuts, for instance, are slowly adopting Starbucks’ business model with significant success. Leveraging on their global presence, these competitors must be chipping away some of Starbucks customers with more affordable, freshly brewed, coffee. In an increasingly competitive environment, these perceived challenges should be carefully analyzed using research methodologies.
The Difference Between Quantitative and Qualitative Research
In order to determine the decline of customer service and its impact on Starbucks sales, several research methodologies can be employed. In general, research studies can be done either quantitatively or qualitatively. There is, however, much controversy regarding the distinction between quantitative and qualitative research. As observed by one scholar, “the presence of substantial overlap between many features of qualitative and quantitative research often makes it difficult to separate qualitative and quantitative research” (Allwood, 2011, p. 1417). One of the major reason for this overlap is the abstract nature of the variables that might be involved, making the distinction between qualitative and quantitative research problematic. Both qualitative and quantitative research measures data, but perhaps the difference between the data that are being measured is what makes the distinction between these two research approach. Some authors, for instance, differentiates quantitative and qualitative research on the nature of data that is being measured. According to Mendenhall et al., A quantitative research, as its name suggests, is a research based on quantifiable variables or variables that can be expressed in numerical terms (Mendenhall, Beaver, & Beaver, 2013, p. 10). Examples of such are price, sales, volume, size, interest rates and many other variables that can be quantified. A qualitative research, on the other hand, considers variables that describes a quality or characteristics. Examples of such are colors, ethnicity, religious affiliations and other qualities that are used to categorize data.
Importance of the Appropriateness of the Research Method Employed
Quantitative research methods are often employed in the natural sciences, particularly when measuring data that are observed during experiments. Social sciences, on the other hand, leans towards qualitative methods, especially in studies that aims to predict complex phenomenon, such as human behavior. With the exception of financial analysis, most organizational variables are abstract. Business success, for instance, is measured under the criteria of the triple-bottom-line, wherein success is not only measured by the organization’s financial success, but also by its environmental and social engagement (Norman & MacDonald, 2003). One of the most common issues facing the organization, for example, is the quality of customer service. The relationship between customer service and revenue is difficult to quantify. However, it is a universally accepted belief among experts that customer service directly impacts business success and sustainability. As an abstract concept, customer service could not be measured quantitatively. However, such concept can be easily measured when categorized under certain parameters. Starbucks, for example, may measure the quality of its customer service in terms of speed of service, cleanliness, courtesy and product quality. In order to determine the quality of the company’s customer service, a qualitative research maybe conducted using the customer service parameters that were mentioned earlier.
Regression Analysis
A common statistical technique in order to determine the relationship between variables is regression analysis (Sykes, n.d., p. 2). Most often, this statistical tool is used when investigating how one particular phenomenon is connected with another. When are researcher, for instance, wants to determine whether decreasing or increasing one aspect could lead to the increase or decrease of another, he or she may use regression analysis in order to establish such relationship. Take for example the relationship earnings and, say, education. It is a common notion that education is directly proportional with earnings so that the higher the level of education an individual achieves, the higher is his or her salary. This relationship between education and earnings can be established using regression analysis. In an organizational setting, regression analysis is also commonly employed to establish the relationship of certain variables in order to help executives in their decision making. The relationship between price and sales, for instance, can be determined using regression. Except for Veblen goods, it is commonly understood that when the price goes up, the sales is inversely affected. Such relationship can be established through regression analysis.
In its simplest, bivariate form, the regression equation can be expressed as: y=B0+B1X+u; where ‘x’ is the independent variable and ‘y’ is the dependent variable (Campbell & Campbell, 2008, p. 3). By inspection, it can be observed that the regression equation is a linear equation in its slope-intercept form wherein the value of the constant,B0, is determined by letting the variable ‘x’ equate to zero. B1, on the other hand, is the slope of the equation while ‘u’ is also a constant that introduces adjustments or margin of error that could not be determined by the slope and the intercept. Simple regression is used when there are only two variable involved. Most often though, in conducting regression analysis, several variables are considered at once. As such, the regression equation can take the form of: y=B0+B1X+B2Z++u.
In the case of Starbucks, a regression analysis maybe conducted using customer service parameters as the independent variable and customer satisfaction as the dependent variable. Say, for example, that the researcher wish to determine how cleanliness impacts customer satisfaction. The researcher may proceed by doing a bivariate regression analysis choosing speed of service as the independent variable and customer satisfaction as the dependent variable. The common methodology that can be employed is to send out questionnaires to random customers. For this particular analysis, the participants may be asked to answer a Likert-type questionnaire wherein they can choose how satisfied they are with the cleanliness of the place. Points such as very satisfied, satisfied, disappointed and very disappointed, can be used as the choices for evaluating cleanliness. These points are then given a corresponding numerical value and measured using bivariate regression analysis.
Conclusion
The growth of Starbucks is phenomenal. Recently, however, this growth was halted by poor sales, which resulted to the closure of a significant number of its stores. The most common hypothesis associated with this decline is poor customer service, which may have resulted to poor customer satisfaction. Customer service, however, is an abstract concept that could not be measured using the usual quantitative techniques. However, such abstract concept can be measured and given a numerical significance using qualitative research methods. One way of measuring the relationship between customer satisfaction and customer service is through regression analysis. Customer service parameters such as speed of service, cleanliness, courtesy, and many others can be given a numerical value through the ingenuity and creativeness of the researcher. These values can then be plugged into the regression equation in order to determine the relationship between the variables involved.
References
Allwood, C. M. (2011). The distinction between qualitative and quantitative research methods is problematic. Retrieved from http://users.polisci.wisc.edu/schatzberg/ps816/Allwood2012.pdf
Campbell, D., & Campbell, S. (2008). Statlab Workshop Introduction to Regression and Data Analysis. Retrieved from http://statlab.stat.yale.edu/workshops/IntroRegression/StatLab-IntroRegressionFa08.pdf
Garthwaite, C., Busse, M., & Brown, J. (2012). Starbucks: A Story of Growth. Retrieved from https://hbr.org/product/starbucks-a-story-of-growth/KEL665-PDF-ENG
Mendenhall, W., Beaver, R. J., & Beaver, B. M. (2013). Introduction to Probability and Statistics. Boston, MA: Cengage Learning.
Norman, W., & MacDonald, C. (2003). Getting to the Bottom of “Triple Bottom Line. Business Ethics Quarterly. Retrieved from http://www.businessethics.ca/3bl/triple-bottom-line.pdf
STARBUCKS COFFEE COMPANY. (2011). The Story of Starbucks. Retrieved from http://globalassets.starbucks.com/assets/BA6185AA2F9440379CE0857D89DE8412.pdf
Sykes, A. O. (n.d.). The Inaugural Coase Lecture. An Introduction to Regression Analysis. Retrieved from http://www.law.uchicago.edu/files/files/20.Sykes_.Regression.pdf
