Measurement scale analysis

Before the study constructs were used to analyse the relationship between the BRT and the intelligent transport system, it was necessary to evaluate their reliability and validity, ensuring that research instruments (questionnaires) used for this study have internal consistency, stability and are free form random (Alshehri, 2012). In addition, Giannakos (2014) indicates that internal consistency was related to the extent to which participants ‘responses are dependable and steady across construct variables of a single data gathering instrument.

For this reason, the measurement scales used for assessing the study objectives were tested for reliability and validity. The details of such statistical processes and results are given below.

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5.3.1.1. Reliability analysis: Estimating internal consistency

A crucial feature of scientific research is the aspect of validity and reliability which Thiel (2014) mentioned that are closely interrelated. Reliability according to the author is the extent to which research variables are measured accurately using appropriate data capturing instruments; and how methodological approaches in research can be consistently repeated in other researches under similar context to arrive at same results. On the other hand, validity in research concerns the strength of a study both internally and externally. Internal validity indicates how well a researcher measures a purported relationship or effects between variables. Also, research is externally valid when it is possible to generalize its findings.

Cronbach‘s Alpha was used to perform reliability analysis (Cronbach, 1951). Internal consistency reliability analysis is an estimate of internal consistency associated with the scores that can be derived from the scale or composite score. Reliability analysis should be performed before commencing any advanced statistical analysis. It is significant to any study because without performing it, it is impossible to have any validity associated with the scores of the scales. Alshehri (2012) posits that high values of Cronbach‘s Alpha are desirable and signify the reliability of measures. A four-point- Likert scale measure of reliability was suggested by Hair, Black, Babin and Anderson (2014); (0.50 and below) low-reliability, (0.50 and below 0.70) high moderate-reliability (acceptable), (0.70 and below 0.90) high-reliability and excellent-reliability (0.90 and below 1.0).

Hair et al., (2014) view that a Cronbach‘s Alpha score of 0.70 and above is essential for acceptable internal reliability, whereas Pallant (2013) advocates for any internal reliability score value which is above 0.60. Additionally, Nadi (2012:103) recommends that all alpha values above 0.50 (acceptable) should be regarded as a true indicator of convergence and any values below 0.50 are unacceptable and should be discarded. The findings of the study showed that Cronbach‘s Alpha values for all the variables construct ranged between 0.67-0.89, for the questionnaires distributed to BRT stakeholders. A crucial feature of scientific research is the aspect of validity and reliability which Thiel (2014) mentioned that are closely interrelated. Reliability according to the author is the extent to which research variables are measured accurately using appropriate data capturing instruments; and how methodological approaches in research can be consistently repeated in other researches under similar context to arrive at same results. On the other hand, validity in research concerns the strength of a study both internally and externally. Internal validity indicates how well a researcher measures a purported relationship or effects between variables. Also, research is externally valid when it is possible to generalize its findings.

Cronbach‘s Alpha was used to perform reliability analysis (Cronbach, 1951). Internal consistency reliability analysis is an estimate of internal consistency associated with the scores that can be derived from the scale or composite score. Reliability analysis should be performed before commencing any advanced statistical analysis. It is significant to any study because without performing it, it is impossible to have any validity associated with the scores of the scales. Alshehri (2012) posits that high values

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of Cronbach‘s Alpha are desirable and signify the reliability of measures. A four-point- Likert scale measure of reliability was suggested by Hair, Black, Babin and Anderson (2014); (0.50 and below) low-reliability, (0.50 and below 0.70) high moderate-reliability (acceptable), (0.70 and below 0.90) high-reliability and excellent-reliability (0.90 and below 1.0).

Hair et al., (2014) view that a Cronbach‘s Alpha score of 0.70 and above is essential for acceptable internal reliability, whereas Pallant (2013) advocates for any internal reliability score value which is above 0.60. Additionally, Nadi (2012:103) recommends that all alpha values above 0.50 (acceptable) should be regarded as a true indicator of convergence and any values below 0.50 are unacceptable and should be discarded. The findings of the study showed that Cronbach‘s Alpha values for all the variables construct ranged between 0.67-0.89, for the questionnaires distributed to BRT stakeholders.

Research objec tiv es Number

of items Cronbach Alpha Overall comme nt based on (based on Hair et al.’s, (2014) four de grees of reliabilit y scale) To determine the co mple menta rity of ITS capability and Bu siness agility in the South African BRT industry;

0.85 High reliability

To measu re the extent of Intelligent Transpo rt Syste m (ITS) capab ility;

0.67 High moderate reliability (acceptab le)

To exa mine the relationship between Intelligent Transpo rt Syste m (ITS) and Bus Rapid Transit (BRT) agility.

0.87 High reliability

Table 5.1. Cronbach‘s Alpha Reliability results, Source: Author 2019

Thus, overall and in line with Nadis (2012) recommendations, the Cronbach‘s Alpha results for this study indicated that the study instrument for BRT Rea-Vaya commuters was reliable with all the values above 0.50- thus indicating proper internal construct reliability as shown in table 5.24.