Bottled Water Case Study

Numerical Results We asked several survey questions to gain a better understanding of the demographic of our participants. A total of 15 individuals in the CLU MBA program were surveyed: 11 male and 4 females. The ages of the students ranged from 24 to 56 years old, with a mean of approximately 34 years of age. Respondents also told us about their annual income which ranged from $5,000 to $135,000 with a mean of $62,500, and a standard deviation of $32,073. Next, we determined the type of water participants drink: store-bought bottled water, home filtered water, or tap water. As depicted in chart A, seven (47%) respondents drink home-filtered water, six (40%) drink bottled water, and the remaining two (13%) drink tap water. An overwhelming
majority of respondents, 13 out of 15, drink either bottled or home filtered water.
Graph A

Later, we asked participants what has a greater impact on your decision to drink filtered (bottled and home filtered) water rather than unfiltered (tap) water?
Six (40%) responded that health concerns weighted heaviest in their decision, three (20%) said availability, two(13%) taste, two (13%) price, one (7%) home filtration system, and one (7%) does not drink bottled or filtered water. As we had anticipated, many more people (2 out of 5) people drink bottled or home filtered water because of health concerns or safety reasons. Our finding are illustrated in
Chart
A.
Chart A

Our hypothesis was based on people’s belief that tap water is unhealthy to drink, so we also ask respondents questions about their health habits. We asked how many times per week he or she participated in a non-sporting form of exercise. The results are displayed in table A. The majority of respondents exercise 3 to 4 times weekly. We also asked if they consider their diet to be healthy. These results can be found in chart B. Again, the majority of respondents (74%) agreed or strongly agreed that they maintain a healthy diet. Do related health concerns and a growing concern for physical health influence peoples decision in drinking water?

Table A Exercise (times per week) | Frequency | Relative Frequency | 0-2 | 3 | 21% | 3-5 | 9 | 64% | 6-8 | 1 | 7% | 9+ | 1 | 7% |

Chart B

Once setting the groundwork for one's choice of drinking water an one's personal health, we asked respondents if they have read information on the health risks of tap water.
Eight (53%) replied yes they have, three (20%) have received information by work or mouth, three (20%) have heard nothing, and one (7%) replied no. About 3 out of 4 respondents have read or heard information on the contamination of tap water. Table B records these findings. We further asked participants to rank their level of knowledge concerning his or her local drinking water system. As displayed in chart C, six (40%) participants said they agree with the statement, one (7%) strongly agreed, five (33%) disagreed, one (7%) strongly disagreed, and 2 (13%) said they have no knowledge. A little less than half of respondents have knowledge about his or her local drinking water system, yet 13 out 15 (or the vast majority) do not drink tap
water.
Table B | Frequency | Relative Frequency | Cumulative Rel. Freq. | Yes | 8 | 53% | 53% | Word of Mouth | 3 | 20% | 73% | I've heard Nothing | 1 | 20% | 93% | No | 0 | 7% | 100% |

Chart C

We wanted to examine if the shift from tap water to bottled or home filtered water was correlated to social status or earning a higher income. Participants were asked how much he or she west willing to pay for a bottled of water. Their answers along with their previously mentioned annual income were used to make a scatter plot to demonstrate the correlation and liner regression of the two (see graph B). Upon viewing the graph, there does not appear to be a correlation between the two variables.
Graph B

Recommendations Although our findings did support our hypothesis, there are several things we will keep in mind for further studies. First, vary the methods of gathering information. We primary asked questions to be answered on a Likert Scale and this did not yield interval or ratio levels of measurement. Thus, we were unable to thoroughly examine the correlation and regression of many variables. We would also sample a larger, more diverse population. This would likely produce results that would more closely mirror our researched reference findings. Instead, our findings were rather skewed and didn't have a strong correlation. We would also have asked follow-up questions and maybe provide space for quantitative answers to verbally explained and vice versa. Many responses were contradicted by a later response and a verbal response would have denoted why.