APS - Administración del portafolio de servicios de TIC

As mentioned at the beginning of this appendix, before taking any action to improve customers’ overall satisfaction, it is important to determine the criteria that influence and explain customers’ overall satisfaction. These criteria are network coverage, spans of service, frequency, punctuality, travel time, fare, bus comfort, safety, security, stop comfort, stop accessibility, accessibility for disable persons, drivers’ behaviour, seat availability, cleanliness, passenger information. Contribution of these quality attributes to customers’ overall satisfaction is calculated through factor analysis and regression analysis which determines the relative weighting of quality attributes in overall satisfaction.

Establishment of Correlation Matrix

Firstly, correlation analysis is performed in order to understand how the specific service quality attributes relate to overall customer satisfaction. Correlation coefficient among quality attributes are presented in Table B-9.

Appendix B

Table B-9: Correlations among specific quality attributes

Overall satisfaction Q1 Q2 Q3 Q4 Q5 Q6 Q7 Q8 Q9 Q10 Q11 Q12 Q13 Q14 Q15 Q16 1.000 Network coverage Q1 .294 1.000 Span of service Q2 .315 .602 1.000 Frequency Q3 .433 .396 .570 1.000 Punctuality Q4 .429 .155 .205 .464 1.000 Travel time Q5 .458 .088 .030 .254 .640 1.000 Fare Q6 .422 .339 .405 .390 -.018 .031 1.000 Bus comfort Q7 .539 .301 .340 .296 .203 .210 .450 1.000 Safety Q8 .412 .160 .268 .231 .195 .198 .368 .531 1.000 Security Q9 .408 .162 .213 .222 .246 .227 .157 .497 .808 1.000 Stop comfort Q10 .551 .211 .212 .276 .340 .327 .342 .497 .540 .543 1.000

Walking distance and walking environment

Q11 .394 .130 .222 .180 .251 .258 .157 .408 .221 .238 .375 1.000

Accessibility for disabled persons

Q12 .391 .082 .217 .222 .276 .294 .215 .361 .469 .426 .463 .309 1.000

Driver' and conductor's behaviour Q13 .523 .083 .026 .136 .413 .523 .163 .400 .273 .256 .388 .317 .345 1.000 Seating Q14 .530 .242 .258 .304 .331 .386 .374 .479 .310 .245 .338 .402 .290 .475 1.000 Cleanliness Q15 .496 .246 .252 .213 .249 .329 .336 .548 .447 .445 .407 .397 .371 .494 .513 1.000 Passenger information Q16 .588 .262 .304 .372 .282 .272 .314 .461 .304 .251 .293 .300 .240 .341 .383 .409 1.000 Overall satisfaction (Sig. < 0.01)

Appendix B

Table B-9 shows that all specific quality attributes have a significant positive relation with overall satisfaction (p< .001). This means that when satisfaction with a specific service quality attributes increases, overall satisfaction increase too. Passenger information (r = .588, p = .000), stop comfort (r = .551, p = .000), bus comfort (r = .539, p = .000) have the highest correlation to overall satisfaction. In contrast, network coverage (r = .294, p = .000) and span of service (r = .315, p = .000) have the lowest correlation to overall satisfaction.

Factor Analysis

Before doing factor analysis, the KMO and Bartlett’s test analysis are implemented. Table B-10 shows the acceptable results of the standard statistical tests. The analysis found that the measurement of sample adequacy (MSA) KMO is 0.861 more than minimum value (0.5) and that the data suitable for analysis of Principal Component Analysis (PCA). Similarly, Bartlett Sphericity test values are significant (p < 0.001), suggesting that the variables are closely related to each other and suitable for further analysis.

Table B-10: Statistical test in factor analysis

Kaiser-Meyer-Olkin Measure of Sampling Adequacy. .861 Bartlett's Test of

Sphericity

Approx. Chi-Square 2046.441

Df 136

Sig. .000

The Principal Component Analysis (PCA), the values of the scale (loading), eigenvalue and percentage changes shows in Table B-11. Varimax rotation methods were performed to produce the maximum value of the scale factor. The results show that four factors were produced and the value of each item exceeds the value 0.4. These four factors have eigenvalue ≥ 1.0 and explain 65% of the total variability.

The first factor includes six variables: bus comfort, walking distance and walking environment, driver’ and conductor’s behavior, seating, cleanliness, and passenger information. Reliability (Cronbach’s alpha) of this factor is 0.815 more than 0.65 (minimum value).

The second factor consists of four variables: safety, security, stop comfort, and accessibility for disabled persons. This factor has Cronbach’s alpha meets the threshold value (0.820). The third factor also contains four variables: network coverage, span of service, frequency, fare. The Cronbach’s alpha of this factor is 0.765, satisfy with the threshold value.

Appendix B

Table B-11: Factor analysis

Factor

Quality Attributes 1 2 3 4

Factor 1 (Cronbach’s alpha = 0.815)

Bus comfort .613

Walking distance and walking environment .590 Driver' and conductor's behaviour .658

Seating .737

Cleanliness .690

Passenger information .535

Factor 2 (Cronbach’s alpha = 0.820)

Safety .876

Security .892

Stop comfort .649

Accessibility for disabled persons .598

Factor 3 (Cronbach’s alpha = 0.765)

Network coverage .755

Span of service .849

Frequency .752

Fare .520

Factor 4 (Cronbach’s alpha = 0.785)

Punctuality .864

Travel time .787

Regression Model

The regression coefficients for satisfaction model are presented in Table B-12. The analysis found that the F-test show that there is a significant relationship ( p < 0.01) between the dependent variable (overall satisfaction) with the independent variables (factor 1, factor 2, factor 3, factor 4).

The analysis of all variables included F1, F2, F3, F4 has a significant relationship (p < 0.05), with variable overall satisfaction. Factor 1 has a highest influence (β= 0.374) on overall satisfaction, following by factor 2 (β= 0.187) and factor 3 (β= 0.181). Factor 4 has a lowest influence (β= 0.177) on overall satisfaction. In other words, an increase of 10% in customer satisfaction regarding bus comfort, walking distance and walking environment, driver’s and

Appendix B

conductor’s behavior, seating, cleanliness, and passenger information would improve the overall customer satisfaction level to 37.4%. Transport authorities’ efforts could therefore be focused first on these quality attributes.

Value of R2 _{can explain the influences of independent variables on the dependent variable. In}

this model, 67.8% of variation in overall satisfaction to public transport can be explained by the factor 1, factor 2, factor 3, and factor 4.

Table B-12: Coefficient regression model

Model

Unstandardized Coefficients Standardized

Coefficients _{t Sig.} B Std. Error Beta 1 (Constant) 3.130 .021 146.839 .000 Factor 1 .374 .021 .630 17.504 .000 Factor 2 .131 .021 .254 8.454 .000 Factor 3 .127 .021 .249 8.309 .000 Factor 4 .287 .021 .415 8.744 .000 R = 0.824; R2 _{= 0.678; F = 130.838; p < 0.01} Opportunities for Action

In order to define precise and concrete actions to improve customers’ satisfaction with the public transport service, another predictive analysis needs to be performed: the two dimensional analysis.

The aim is to determine:

The areas where the public transport service do not provide well and where actions to change the situation are needed in order to improve customers’ satisfaction;

The areas where the public transport service provide well and where no action is needed.

This is done by mean of a diagram taking into account the following information:

The average satisfaction score given by customers to each criterion related to quality attributes (marked as “satisfaction” on the X-axis of the map)

The weighting or contribution of each criterion to customers’ satisfaction – this weighting presents the extent to which each criterion is important to customers (marked as “importance” on the Y-axis of the map).

The diagram on Figure B-12 shows the areas where priority actions are needed in order to improve customers’ satisfaction with the public transport service.

Cleanliness, behaviour of driver and conductor, punctuality, and accessibility for disabled persons are four priority areas for the transport authorities. These four items are of high importance to customers (they make a considerable contribution to overall

Appendix B

satisfaction) whereas they obtain low satisfaction scores (compared to the average). An action in these four areas would have the greatest effect on customer satisfaction. On the other hand, customers are satisfied with bus comfort, walking distance and walking environment, seating, and passenger information as these items obtained satisfaction scores above the average. These two items correspond to an ideal situation as they play an important role in customer satisfaction. No action is required in these areas.

Speed, safety, security, stop comfort, network coverage, span of service, frequency, and fare has the satisfaction score above the average. For the moment, these items are of less importance (it does not contribute much to the overall satisfaction). Communication in this area should raise customer awareness of the importance of these items.

Figure B-12: Two-dimensional analysis for public transport service Importance (+) S at is fa ct io n ( -)

Priority actions Ideal situation

S at is fa ct io n ( + )

Driver’s and conductor’ behaviour Cleanliness

Punctuality

Accessibility for disabled persons

Bus comfort

Walking distance and walking environment Seating

Passenger information

Low importance area Long term actions

Travel time Safety Security Stop comfort Network coverage Span of service Frequency Fare Importance (-)