Transportation Facilities Improvement

Transportation Facilities
Transportation Facilities

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Transportation Facilities

Increasing demand for effective travel has prompted transportation projects focused on the improvement of transportation facilities (Cooper, 2012).  The response of the federal government to this demand has been through an enhancement of an ambitious transport program (Bell, 2013). This is because transport usually involves the movement of people and goods from one location to the other, using a variety of modes including road, air, water, rail, air, and pipeline (Alstadt, 2010).

The transportation theory according to its articulation by Cooley (1894) provides an explaination of the contribution of traffic to geographical and mechanical concepts, the relationship between land  and/or waterways and physical situations, as well as the general observations that links transportation to natural conditions. Transportation contribution is also focused on political organization, society organization, economic organization, military organization, the location of cities and town, as well as markets (Tilahun & Levinson, 2010).

The industry of transportation consists of the modes of transportation, physical infrastructure and operations, and plays a crucial role in the facilitation of economic development, particularly through intertrade promotion between regions and persons (Levinson & Huang, 2012).

Transportation infrastructure improvement enhances socio-economic outcomes, especially by increasing earnings arising from opened up consumer goods’ markets and labor markets (Tilahun & Levinson, 2010). Improved transportation infrastructure is associated to socio-economic benefits including increased accessibility of spatial locations and mobility among residents (McDermott, 2010). As a result, transportation is attributed to enhanced quality of life, which ensures there is a link between individuals to occupation, teaching, healthiness, refreshment among other socio-economic activities (Bell, 2013). 

Transportation presents market accessibility by connecting manufactures and consumers to enable transactions.  Without any elaboration, as mentioned in the theory of transportation by Cooley (1894), economic expansion cannot progress in the absence of transport facilities.  In addition, the socio-economic effects are differentially experienced according to demographic parameters such as income level, job level, marital status, and level of education (Gomben et al., 2012). 

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Specifically, with regards to the state of California, the transportation program that exists is not adequate to equate with the predicted economic expansion (Kernohan & Rognlien, 2011; Saunders & Dalziel, 2014). This is because in the State of California the rate of economic expansion has not matched that of transport expansion, necessitating an evaluation of the specific status of the situation which has been affecting commuters (Cooper, 2012).

As such, the literature indicates the need for a more ambitious approach that would involve a far-reaching strategy to develop and improve transport facilities for enhancement of the socio-economic status of California residents (Kernohan & Rognlien, 2011; Levinson & Huang, 2012; Saunders & Dalziel, 2014). The findings of studies by Gonzalez-Guillen (2012) and Bell (2013) showed that transportation influences socio-economic status of a population in various ways including increased connectivity, which enables residents to easily commute from one point to another.

Purpose of the Study    

The purpose of this quantitative, correlational study is to examine the relationship between transportation investment and socio-economic well-being of residents in the State of California. The target population for this study is the members of the communities of California and the sample will be archival data on transportation investment measures retrieved from the California State Transportation Agency website and survey data on measures of the population’s socio-economic status satisfaction.

According to Cohen (1992) and Faul et al. (2009) G*Power is the most appropriate method to determine the sample size for a study. The sample size will include 150 participants randomly drawn within the communities in California with an assumption of a response rate of about 70 per cent (Babbie, 2010).  The sample size was determined using 0.95 as the power of test and 0.05 as the alpha, while the study was one-sided. Considering that California is the place of study, the primary data will be gathered using rating scale analysis survey questionnaires as data collection instrument administered on the randomly selected sample size (Wright & Masters, 1982).

The survey questionnaires will rate responses of research participants in a five-point Likert scale that range from strongly disagree (1) to strongly agree (5). On basis on the above analysis, it is undoubtedly evident that the field of service quality has be extensively researched (Parasuraman, et. al., 1985, 1988, 1991), and this has led to the development of SERVQUAL, used as a measurement of service, which states that the assessment of service quality in overall by customers is determined by the direction and degree of the gap between their perceptions and expectations of actual performance levels.

As a result, they identified five key variables that are associated to service quality including reliability, tangibles, responsiveness, empathy and assurance. They proposed that the service quality perception could be approximated through calculation of the difference between perceptions and expectations of actual performance of service. Hence, this research instrument can be used to examine the relationship between transport investments and socio-economic status perceptions in California.

The sample will be randomly picked from the target population, particularly within communities across California to ensure each of them is appropriately covered in the data collection and analysis process (Coleman 2010; Williamson, Philbin & Sanderson, 2012). The collected primary data will be cleaned subsequent to processing and coding followed by data analysis using SPSS to enable the hypothesis testing. The analytic plan will include regression and correlation analysis for the determination of the direction and strength of variables’ relationships using Pearson r correlation, Kendall rank correlation and Spearman rank correlation statistics.       

Research Questions 

In this study, specific quantitative research questions will be asked to gather primary information essential for hypotheses testing. The questions must be in tandem with research variables/constructs as far as transport infrastructure investment is concerned and how it relates to on socio-economic status of residents. The research questions will ensure the problem statement is addressed to establish whether there is significant relationship between public transportation investment and socio-economic status satisfaction levels among the residents California State.    


Litman, T. (2014). Land use impacts on transport. Considering the impacts, benefits and costs of different land use development patterns. Retrieved from Victoria Transport Policy Institute, Canada, website:

MacKinnon, D., Pine, G. & Gather, M. (2008). Transport and Economic Development. In R. Knowles, J. Shaw and I. Docherty (eds.) Transport Geographies: Mobilities, Flows and Spaces. Oxford: Blackwell, pp. 10-28.

McDermott, P. (2010). Transport, connectivity, and regional development. Logistics & Transport New Zealand, 9, p. 8.

Saunders, C., &Dalziel, P. (2014) Economic development: A review of key themes in the international literature. Retrieved from Ministry of Transport website:  

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