In order to ensure that the quality of the research is of high standard, some measures can be taken. Two prominent criteria within quantitative research are reliability and validity (Bryman & Bell, 2015).
5.5.1 Reliability
Reliability regards whether the results of the study is consistent and repeatable (Bryman & Bell, 2015). In quantitative research reliability is particular concerned in whether a measure is reliable and stable over time, in other words that the results does not fluctuate and provide the exact same results if the study are done at a later time. Evaluating the replicability of the study, the chosen area is
narrow streets and considered a typical “pedestrian zone” with challenging driving conditions. The size of the city and type of construction is similar to other shopping areas in Norwegian cities. This makes it easy to transfer the knowledge and research from this study to similar cases.
In terms of the questionnaires there can be four threats to reliability, which are participant error, participant bias, observer error and observer bias (Saunders, Lewis and Thornhill, 2009; Robson, 2002). The first is participant error, where the time is crucial for when the questionnaire was distributed. This is not something we know, but it is assumable that it was conducted in a week day where the flow of customers were low, so the retailers had time and opportunity to answers the question. Participant bias is concerned with the employees answering what they believe their boss wants them to say. Since most of our recipients are store manager, it is not considered to impact the result. The third is observer error, similar to interview validity, where several people have conducted the interviews.
We know that some error might be present here due to several interviewers with different perspective on the research. Last is observer bias, measuring if the replies from the questionnaires have been interpreted similar. One of the project owners was exclusively responsible for this and therefore no observation bias in the study. The reliability of the study is not crucially affected, but decreases due to the observer errors.
Events that could reduce the reliability are decisions related to closing the area completely for traffic or implement strict restrictions regarding vehicles. If this is done before the local consolidation centre has been established, the results of the study would be completely different. However, the data collected would most likely provide a similar result independent of which day and time it was collected if no events occur, and therefore not considered to fluctuate over time and evaluated consistent. However, many of our calculations are based on assumptions and not accurate numbers, and errors might therefore be found. This undermines the reliability.
5.5.2 Validity
Validity is concerned with the integrity of the study and looks at what has been concluded through the research (Bryman & Bell, 2015). Here it is important that the study has researched what it says it was going to research, and does not measure something completely different. The thesis is based on secondary data that obtained from another source and it is therefore difficult to know if the numbers are accurate. However, the source is considered to have high reliability and the data was gathered on the same premises as this thesis.
Measurement validity primarily refers to quantitative researcher and is concerned with whether or not a measure reflects the actual concept it is supposed represent.
Since some retailers were removed from the data the study does not reflect the whole selection of freight vehicles transporting goods in the area. Hence the validity of the study is weakened.
6 Presenting the data from retailers
The project owners in Stavanger distributed a questionnaire to all retailers located at the first floor within the research area, and the following section presents the data collected from this questionnaire. The collected data was received in an excel file where responses to each of the questions was sorted by business ID. Some figures were assembled by the project owners to illustrate the distribution of answers, but we chose to redo all of these as we wanted to become more familiar with the dataset. We also included some additional figures, which means that all the figures presented below are drafted by us. The only calculations made in the dataset prior to our receival was transformation of data from received goods per week to received goods per day, and standardization of the volumes to freight calculation weight. Questions considered less relevant for our thesis will not be elaborated on, but the questionnaire in its entirety can be found in Appendix 1.
There are 200 representative businesses in the area where 161 were present at the time the questionnaire was distributed. Those who were absent during the distribution were mainly restaurants and bars with opening hours later in the day.
A response rate of approximately 80% was reached, which is quite good especially when comparing it a similar report conducted by the municipalities Stavanger and Sandnes, which only achieved a response rate of 13% (Sandnes og Stavanger Kommune, 2014).
The questionnaire is divided into several categories which is the structure the data will be presented through, starting with some general questions regarding the specific retailer, followed by questions concerning frequency, volume, number of shipments and location. As a conclusion the retailers were asked questions in relation to cost and environmental aspects, and the relationship between the two.
We will also discuss some limitations of the dataset as well as how the data are narrowed down to fit our research model.