BUSI600 CASE STATE FARM DISCUSSION 2
1. Identify the various constructs and concepts involved in the study.
Concepts
Concepts are defined as “a bundle of meanings or characteristics associated with certain
concrete, unambiguous events, objects, conditions, or situations” (Schindler, 2022, p. 19, para.
2). They are used to understand and communicate information in research and the success of the
research is dependent on how well the research can create concepts and how well those concepts
are understood by others. Hypotheses and the measurement scales used to test them are designed
using these concepts (Schindler, 2022). In the study by State Farm to identify the most dangerous
intersections, some concepts used include accident rates, traffic volume, and property damage
accident payout.
Constructs
Constructs are defined as abstract ideas that are specifically generated for research
purposes. Constructs are built by combining simpler concepts to convey a message that is not
directly observable (Schindler, 2022). The main construct of the study was the “most dangerous”
title that was earned, which factored in many measured concepts to conclude an aggregate
danger index value. One of the building blocks of the aggregate danger index value was also a
construct. A scale was assigned to levels of personal injury, which is not a directly observable
value.
2. What hypothesis might drive the research of one of the cities on the top 10 dangerous
intersection list?
Constructing a good hypothesis is one of the most important aspects of conducting
research. A hypothesis is a research question that includes the expected result of the research,
which is what differentiates it from just a research question. While research questions are open-
BUSI600 CASE STATE FARM DISCUSSION 3
ended and invite discussion, hypothesis statements are closed and forecast the relationship
between variables (“What is and how to write a good hypothesis in research”, 2023). A proposed
hypothesis for the State Farm Dangerous Intersections case study could be: investing in the
reengineering of identified intersections can reduce the danger index value of said intersection.
Using the danger index would account for a reduction in property damage and personal injury.
Additionally, the hypothesis makes the prediction that State Farm’s investments and the
consequential investment in improvements by the cities will lead to lower levels of danger in
those intersections.
3. Evaluate the methodology for State Farm’s research.
To collect their research, State Farm came up with the idea to review its previously
collected data by mining its database for information on accidents within the United States. What
they initially found, though, was that specific information on intersections did not exist. To fix
this problem, they began requiring adjusters to complete a location field as part of the data in a
claim, launching a longitudinal study for the duration of 1998. The data that State Farm then
used was a census of all of the recorded accidents at intersections throughout the duration of the
study; using a sample would not have been appropriate because all of the intersections were
desired to be ranked. Data was, however, filtered to exclude any accident that occurred on an
access or egress ramp of a highway and any accident where the State Farm insured-driver was
not the one at fault. Since State Farm was the largest auto insurer a the time (Schindler, 2022), it
was appropriate to make a generalization that their data represented the entire population, which
would be defined as all drivers in the United States. The first study ignored accident severity and
did not isolate demographics or geographics. While it did not completely invalidate the study, the
omission of these confounding variables had the potential to alter the perceived relationship of a
BUSI600 CASE STATE FARM DISCUSSION 4
particular intersection and its associated risk. Studies have shown that weather conditions
increase the frequency and severity of car accidents; rain, snow, fog, extremely high or low
temperatures, and lighting conditions have all been shown to amplify the probability of a car
accident (Bruhwiler et al., 2022). In 2001, to improve the study, State Farm created a discrete
measurement scale to classify the severity of property damage and personal injury. What resulted
was the aggregate danger index, which was then used to improve the identification of the most
dangerous intersections (Schindler, 2022).
4. If you were State Farm, how would you address the concerns of transportation
engineers?
One of the main concerns of the transportation engineers about the State Farm study that
was conducted in 1998 was the sampling method. The transportation engineering solution did not
place high validity on the data; they believed that locations with accidents that resulted in
injuries and death should be weighted as more important than those where the accidents were
more minor. This problem was already addressed by State Farm with the inclusion of the
aggregate danger index for each intersection (Schindler, 2022).
Another concern of transportation engineers was that the survey generated a desire for
“immediate solutions, solutions that they often didn’t have budgets to implement” (Schindler,
2022, p. 2, para. 3). The limitations of budgets of various towns and cities is not something that
State Farm has as much control over as the methodology of the study but plays a big part in
whether or not the area would be able to invest in the infrastructure change. According to Bill
Fulton, director of Urban Research at Rice University, “Cities with stagnant tax bases can’t keep
up with infrastructure needs without vastly increasing their property tax revenues” (Ionescu,
2021, para. 2). I see there being two ways that State Farm could reduce outrage for solutions.
BUSI600 CASE STATE FARM DISCUSSION 5
One is that the data could be private and require consultation with the government of the area
with the intersection before releasing data to the public. This would ensure that there could be
solutions in place when the announcement is made, which should appease the public. Another
solution, which maintains the spirit of informing the public on safety matters as soon as possible,
would be to increase the grant aid to the identified communities helping them to make a change.
I would be interested in seeing if an ROI could be calculated that would validate the investment
in the repair of the intersection.
Further investing in the safety of drivers would be costly to State Farm, but even if it did
not return financially, it could be considered an incredibly thoughtful act of service. We are told
in the bible, “and God is able to make all grace abound to you, so that having all sufficiency in
all things at all times, you may abound in every good work” (English Standard Version Bible,
2001/2016, 2 Corinthians 9:8). We are reminded that the generous will prosper because it is the
generous that delight in the heart of the Lord.
5. If you were State Farm, would you use traffic volume counts as part of the 2003 study?
What concerns, other than those expressed by Nepomuceno, do you have?
Nepomuceno expressed concern that the study did not consider traffic volume in the
study (Schindler, 2022). If I were State Farm, I would want to use traffic volume counts in my
next study to normalize the danger indexes for traffic volume. Normalizing data involves scaling
collected data to ensure all points lie on the same scale and consequently have the same
importance (Rogic et al., 2022). Doing a study that finds traffic patterns of all intersections
would be too expensive and time-consuming, so I would resort to using population data of the
towns/cities of each of the intersections. Another concern of myself would be how to factor in
geographical conditions at the time of the accident. A question that I would ask is if weather or
BUSI600 CASE STATE FARM DISCUSSION 7
Bruhwiler, L., Fu, C., Huang, H., Longhi, L., & Weibel, R. (2022, January 31). Predicting
individuals’ car accident risk by trajectory, driving events, and geographical context.
Science Direct. https://www.sciencedirect.com/science/article/pii/
S0198971522000047#bb0170
English Standard Version Bible. (2016). English Standard Version Bible Online.
Ionescu, D. (2021, July 6). Small cities struggling to pay for infrastructure projects. Planetizen
News. https://www.planetizen.com/news/2021/07/113916-small-cities-struggling- pay-
infrastructure-projects
Rogić, S., Kašćelan, L., & Bach, M. P. (2022). Customer Response Model in Direct Marketing:
Solving the Problem of Unbalanced Dataset with a Balanced Support Vector Machine.
Journal of Theoretical and Applied Electronic Commerce Research, 17(3), 1003.
https://doi.org/10.3390/jtaer17030051
Schindler, P. S. (2022). Business research methods (14th ed.). McGraw-Hill.
What is and how to write a good hypothesis in research?. Elsevier Author Services - Articles.
(2023, August 4). https://scientific-publishing.webshop.elsevier.com/ manuscript-
preparation/what-how-write-good-hypothesis-research/
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