State Farm Individual response posts

Instructions Individual response posts The primary goal of Part 2 is to discuss the individual posts by offering analysis and critiques to include specific strengths and weaknesses and other insights for consideration. Ensure the following are met: • Reply to at least 2 different peer individual posts and address at least 1 strength and 1 weakness per reply. • Each response must be supported with at least 2 peer-reviewed sources and include 1 biblical application/integration (no more than 10% of the total response). • Each individual response post must be 450-600 words • Use proper grammar and current APA formatting.Module 2, 4, and 6: Weeks 2, 4, and 6 submit your Part 2 individual responses by 11:59 p.m. (ET) on Sunday of the respective week. 1. Passage 1 State Farm: Dangerous Interactions Gabriel Moriba Identify the various constructs and concepts involved in the study. Constructs are concepts or ideas that one perceives about a phenomenon needed for research. Construct involves, choosing the concept, formulation of hypothesis, variables, are and the steps are undertaken (Bhattacharjee, 2020). The study of State Farm, aimed at researching the safety involvement in auto and appliance design. This research\’s purpose was to prevent losses and ensure safety. What hypothesis might drive the research of one of the cities on the top 10 dangerous intersection list? The principles of intersection design are: • Compact: Effective design is compact. • Effective designs minimize conflicts. • One should try to avoid conflict. • There should be served at all level. • Skewed and multi-level design of intersecting need to be avoided. • One should ensure the intersections are fully accessible (Babbie, 2010). As the study mentions that the intersection geometry or physical layout of intersection can play an influencing role in the intersection. The hypotheses that can put cities in the top 10 danger list would be if the result. Any data from police can be incomplete and thus can create confusion. Until every data is available, the study should not be carried. Evaluate the methodology for State Farm’s research. State Farm followed the initiative by Insurance Corporation of British Columbia, Canada( ICBC) and American Automobile association, Michigan. The State Farm uses complete detailed data about the incident. The methodology for a survey has to be appropriate. Readers should get information about the source of data and how were they interpreted . An unreliable method can produce undesirable results that cannot be relied on. Usually, a research problem can be chosen from a variety of methods. The data collected should be consistent with accepted practice. A research methodology should maintain six standards: • The purpose should be clearly defined. • Research design should be thoroughly planned. • High ethical standards need to be applied. • There is a need for adequate analysis for the need of decision-makers. • Limitations should be revealed • The report should be clear (Babbie, 2010). The State Farm used the Quantitative research method. “Quantitative methods emphasize objective measurements and the statistical, mathematical, or numerical analysis of data collected through polls, questionnaires, and surveys, or by manipulating pre-existing statistical data using computational techniques. Quantitative research focuses on gathering numerical data and generalizing it across groups of people or to explain a particular phenomenon” (Babbie, 2010). A quantitative method allows a wider range of studies that involves a greater number of subjects (Schindler,2019). Such a method helps to give accurate results. If standard data are used, the research can be replicated later. Such researches do not have personal biases as the research and the conclusion is entirely based on data. If you were State Farm, how would you address the concerns of transportation engineers? The engineers need to maximize the efficiency of existing transportation and infrastructure, plan to avoid mishaps, accommodate mobility demand instead of expanding infrastructure, and expand street and highway infrastructure. The engineers need to look at different areas and populations. After that, they need to decide what kind of transport would well suit them. 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? Traffic counts are low at a unit is not always effective. Even though traffic counts make work easy, but it is not counted daily. So, the exact count is not acquired always. The peak hour value is useful for “traffic engineers in estimating the amount of congestion experienced, and shows how near to capacity the highway is operating. Unless otherwise indicated, peak hour values indicate the volume in both directions” (\”Traffic Volumes\”, 2017). Annual average daily traffic is a good way for calculating traffic count. The AADT or annual average daily traffic was divided by 365 days. The traffic counting is calculated by electronic counting instruments (Mallikarjuna et al., 2009). The traffic volume counts are effective. However, the data should be taken regularly and accurately. Nepomuceno expressed that there were reasons for excluding the police reports as varied officers collect varied reports and note down the data. So, it is better to exclude the reports of the police officers. The Case Study said, “the reporting threshold for police filing reports on accidents differs widely from jurisdiction to jurisdiction. Some will only fill out reports when personal injury or criminal behavior is involved. Others will fill them out only when a vehicle is damaged to the degree that it needs to be towed from the scene. Still others fill out such reports on every incident. Traffic volume reports are often prepared infrequently and often by independent sources. Not only may the data quality be questionable, but the time period in which the data was collected may not match our 1998 incident reports in every city involved. Also, when traffic volumes are factored in, low volume roads with relatively few crashes are often deprioritized. Now that we are through with the 2001 study, we are asking ourselves if intersection volume should be factored in, and if so, how it can be included without significantly increasing our effort in data processing.” Other than the issues mentioned, pointing down the data can give different results. So video image processing can help to get better results. References Babbie, R.(2010) The Practice of Social Research. 12th ed. Belmont, CA: Wadsworth Cengage. Bhattacharjee, A. (2020). Social Science Research – Principles, Methods, and Practices. Global Text Project. Denscombe, M.(2014). The Good Research Guide: For Small-Scale Social Research Projects. 5th edition. Buckingham, UK: Open University Press. Mallikarjuna, C., Phanindra, A., & Rao, K. (2009). Traffic Data Collection under Mixed Traffic Conditions Using Video Image Processing. Journal Of Transportation Engineering, 135(4), 174-182. https://doi.org/10.1061/(asce)0733-947x(2009)135:4(174) Schindler, P. (2019). Business Research Methods, 13th ed. McGraw-Hill. Traffic Volumes. Dot.ca.gov. (2017). https://dot.ca.gov/programs/traffic-operations/census/traffic-volumes. 2. Passage 2 1. Identify the various constructs and concepts involved in the study. The State Farm case study involved various concepts and constructs. The main concept the company worked with was the idea of improving public safety by studying the locations of accidents. One of the main constructs the company likely dealt with was traffic safety, and within traffic safety, the concepts of intersection-only roads, State Farm-insured at-fault, and internal data related to the people involved. Companies are increasingly becoming more interested in the various factors beyond the pure empirical data of an event and seeking to understand consumer behavior, utilizing concepts such as service satisfaction, organizational image, and reform support to buoy internal research initiatives (Vigoda-Gadot & Cohen, 2015). 2. What hypothesis might drive the research of one of the cities on the top 10 dangerous intersection list? A hypothesis to drive the research of one of the cities on the top 10 dangerous intersection list could be: intersections with stop signs experience a greater rate of accidents than intersections with traffic lights. The idea here would be to utilize the initial indications of the study and combine that initial information with the knowledge of the city’s layout and nuances of different parts of town to better understand possible contributing factors to accident and damage rates. As mentioned in the study, transportation engineers were faced with an almost immediate problem in that the State Farm study identified a plethora of issues that local municipalities and government were not equipped to handle and address with any kind of speed. Another hypothesis that could drive the research into of these cities could be: intersections with turn lanes that have a dedicated green-only turn instead of a standing yellow light turn have a lower accident rate. Again, there are many avenues researchers could pursue by comparing and contrasting the accident, injury, and property damage rates at various intersections in a city to better understand and identify trends common to safer intersections and other factors affecting intersections that have a higher perceived danger. These studies could go so far as to study variables such as temperature, rainfall, and other items like a study performed in Pakistan (Qamar, Yaseen & Khan, 2020). The study included the effects on fatalities from an accident by having the right density of healthcare workers in a given area. This is an aspect of the motor vehicle accident experience that North American researchers may regularly overlook or take for granted, given the response times by local emergency services and the resources devoted to medical professionals to respond to such incidents. 3. Evaluate the methodology for State Farm’s research. State Farm conducted the study utilizing an exploration strategy for its research. The company utilized its previous study and also made intentional decisions regarding which data it would and would not consider in the study. For example, the company’s first study did not account for accident severity and did not factor in demographic and geographic details that may have been useful in the course of its research. State Farm utilized an immense amount of internal data it had collected over the years and given its market share, was able to utilize the data with maximum effect. Because of the company’s market share and immense amount of data it had available, the company made the decision to not consider other possible data points available through police reports or any public records due to the inconsistency of data quality across jurisdictions. One of the big gaps in the intersection study was not mentioning the effect of pedestrian and bicycle traffic at those intersections. A study conducted in Oslo, Norway, which had established a goal of zero pedestrian and bicycle fatalities in a given year, finally achieved its goal in 2019 after several years of dedicated work to lower the risk and improve the safety for its foot and bicycle-heavy population, a feat not easily attained (Hartmann & Abel, 2020). 4. If you were State Farm, how would you address the concerns of transportation engineers? The transportation engineers need to believe that you, as a company, are on their team and are there with a sincere motive to help in any way possible. The study most certainly stirred up emotions, including embarrassment and frustration from city and community leaders, that only complicate and exacerbate the issues in a given locale. State Farm’s approach to addressing transportation engineer concerns should include, as a part of the studies conducted with the grant funding, studying intersections with certain volume and accident rate data. State Farm’s study, though well-constructed and no doubt effective, would most certainly cause frustration if State Farm offered little cooperation to help remedy the issues it uncovered. Under immense public pressure, transportation engineers are going to need to be empowered to enact quick-win changes that would enhance the safety of an intersection while a greater, comprehensive, or capital-intensive project was undertaken to address other aspects of the items identified in the study. A quick win and a possible item that may not require extensive project planning and capital investment, could be initiatives aimed at items as simple as road marking (Babi? et al, 2020). 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? Traffic volume counts are, in my opinion, one of the biggest shortcomings of the study. It is important to note the dangers of various intersections, regardless of volume, but for the purposes of public safety, traffic volume counts are essential. The traffic volume counts are what take the study from purely academic to practical and actionable intelligence to help save lives. One concern that I would have liked to have seen the study address would be the nature of the accident at the intersection. For example, is there a disparity between left or right-turn accidents? Accidents with one vehicle at zero speed or both vehicles at speed entering the intersection? There was a fascinating study performed in San Marcos, TX, that studied safety performance for displaced left-turn intersections, a newer model for intersection management that could pave the way for improvements in safety (Qu et al, 2020). The State Farm study could have included additional information about the general construct of an intersection by providing additional insight into the fatality rates between different intersection models. References Babi?, D., Fioli?, M., Babi?, D., & Gates, T. (2020). Road Markings and Their Impact on Driver Behaviour and Road Safety: A Systematic Review of Current Findings. Journal of Advanced Transportation, 2020 http://dx.doi.org.ezproxy.liberty.edu/10.1155/2020/7843743 Hartmann, A., & Abel, S. (2020). How Oslo Achieved Zero. Institute of Transportation Engineers. ITE Journal, 90(5), 32-38. com%2Fscholarly-journals%2Fhow-oslo-achieved-zero%2Fdocview%2F2400567457%2Fse-2%3Faccountid%3D12085″ target=”_blank”>http://ezproxy.liberty.edu/login?qurl=https%3A%2F%2Fwww.proquest.com%2Fscholarly-journals%2Fhow-oslo-achieved-zero%2Fdocview%2F2400567457%2Fse-2%3Faccountid%3D12085 Qamar, A., Yaseen, M. R., & Khan Muhammad, T. I. (2020). The impact of temperature, rainfall, and health worker density index on road traffic fatalities in Pakistan. Environmental Science and Pollution Research International, 27(16), 19510-19529. http://dx.doi.org.ezproxy.liberty.edu/10.1007/s11356-020-08233-1 Qu, W., Sun, Q., Zhao, Q., Tao, T., & Qi, Y. (2020). Statistical Analysis of Safety Performance of Displaced Left-Turn Intersections: Case Studies in San Marcos, Texas. International Journal of Environmental Research and Public Health, 17(18), 6446. http://dx.doi.org.ezproxy.liberty.edu/10.3390/ijerph17186446 Vigoda-Gadot, E., & Cohen, H. (2015). Service satisfaction and organizational image: An empirical examination of the relationship with support for NPM-style reforms. Transforming Government: People, Process and Policy, 9(1), 2-16. http://dx.doi.org.ezproxy.liberty.edu/10.1108/TG-02-2014-0004

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