Description
The PPT discuss about ATVM Feasibility and it contains topics like research methodology of mumbai suburban smartcard service, sample size, data, data analysis, conclusion, limitation, recommendation,
Research Methodology
Mumbai Suburban Railways’: ATVM Smartcard Service
Presented By:Abhishek Gite (M1013) Sandesh Babar (P1004) Kalpesh Patil (M1032)
Ashish Khadse (P1023)
Introduction
Enables commuter to buy ticket through ATVM, thus save time
Service is available and valid on Western and Central Suburban Railways
More than 980 ATVM on western line and nearly 600 ATVM on central line Card have inbuilt microprocessor and flash memory to store data
Research Objective
To study the feasibility of ATVM Smart Card Service To understand commuters perception towards the service
Methodology
Questionnaire method
Step-I: Response from 200 commuters
Step-II: Data analysis and testing of hypothesis
Research Design
Designed to gauge acceptability and popularity of the service
Convenient sampling plan with ordinal scaling
Considered related aspects like awareness, convenience, availability and features
Sample Design
Target Population: Suburban Railway Commuters
Sample Size: 200
Sampling Method Used: Chi-Square
Source of Data
Primary Data: Through Questionnaire
Secondary Data: IRCTC Website, Indian Rail Website, www.wikipedia.org
Data Analysis
Demographic Analysis
Majority of the respondents (94%) are in age group of 21-30 years
Data Analysis
Demographic Analysis
Majority of the respondents (80.5%) are male
Data Analysis
Demographic Analysis
Nearly 60% of respondents travel daily
Data Analysis
Demographic Analysis
51% of the respondents travel by second class and 47.5% travel by first class
Data Analysis
Demographic Analysis
Income5lac=26%, Between 1-5lac=33%
Data Analysis
Awareness
Almost all the respondents are aware of the facility
Data Analysis
Usability
The total number of respondents who are aware of ATVM Smart Card Service, only 53.5% actually use the service
Data Analysis
Satisfaction Analysis
1-Extremely Poor----------------5-Extremely Good
Most of Commuters are satisfied with almost all the parameters
Data Analysis
Hypothesis Analysis:
Hypothesis I: Null Hypothesis Ho: There is no relationship between frequency of travel and awareness of ATVM Smart Card Service. Alternate Hypothesis H1: There is a relationship between frequency of travel and awareness of ATVM Smart Card Service.
Chi-Square Tests Value Pearson Chi-Square Likelihood Ratio N of Valid Cases 1.873a 2.865 200 df 2 2 Asymp. Sig. (2-sided) .392 .239
a. 3 cells (50.0%) have expected count less than 5. The minimum expected count is 1.05.
Since Pearson Chi-Square Sig. is > 0.05, therefore null hypothesis is accepted. There is no relationship between frequency of travel and awareness of ATVM Smart Card Service
Data Analysis
Hypothesis Analysis:
Hypothesis II: Null Hypothesis Ho: There is no relationship between class of travel and awareness of ATVM Smart Card Service. Alternate Hypothesis H1: There is a relationship between class of travel and awareness of ATVM Smart Card Service.
Chi-Square Tests Value Pearson Chi-Square Likelihood Ratio N of Valid Cases .950a 1.039 200 df 2 2 Asymp. Sig. (2-sided) .622 .595
a. 4 cells (66.7%) have expected count less than 5. The minimum expected count is .09.
Since Pearson Chi-Square Sig. is > 0.05, therefore null hypothesis is accepted. There is no relationship between class of travel and awareness of ATVM Smart Card Service
Data Analysis
Hypothesis Analysis:
Hypothesis III: Null Hypothesis Ho: There is no relationship between monthly expense on railways tickets and usability of ATVM Smart Card Service. Alternate Hypothesis H1: There is relationship between monthly expense on railways tickets and usability of ATVM Smart Card Service.
Chi-Square Tests Value Pearson Chi-Square Likelihood Ratio Linear-by-Linear Association N of Valid Cases 6.213a 6.257 1.711 200 df 3 3 1 Asymp. Sig. (2-sided) .102 .100 .191
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 7.74.
Since Pearson Chi-Square Sig. is > 0.05, therefore null hypothesis is accepted. There is no relationship between monthly expense on railways tickets and usability of ATVM Smart Card Service
Data Analysis
Hypothesis Analysis:
Hypothesis IV: Null Hypothesis Ho: There is no relation between awareness and usability of ATVM Smart Card Service. Alternate Hypothesis H1 : There is relation between awareness and usability of ATVM Smart Card Service.
Chi-Square Tests Asymp. Sig. Value Pearson Chi-Square Continuity Correctionb Likelihood Ratio Fisher's Exact Test Linear-by-Linear Association N of Valid Cases 3.553 200 1 .059 3.570a 2.171 3.789 df 1 1 1 (2-sided) .059 .141 .052 .094 .070 Exact Sig. (2-sided) Exact Sig. (1-sided)
a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 2.73.
b. Computed only for a 2x2 table
Since Pearson Chi-Square Sig. is > 0.05, therefore null hypothesis is accepted
There is no relationship between awareness and usability of ATVM Smart Card Service
Conclusion
Most of the commuters (97%) are aware of ATVM smartcard service
Only half of them use this facility
Customers are overall satisfied with the various parameters related to the service There is no relationship between frequency of travel and class of travel with awareness of ATVM service. There is no relationship between monthly expense and awareness with usability of ATVM service.
Recommendations
Machines should be available at more locations and the touchscreens should be more user friendly
Recharge facility should be available online similar to mobile recharge
Facility of journey extension should be incorporated in ATVM Smart Card Service The Indian Railways websites should be more informative
Limitation
Non-availability of information from the railways authorities
Sample size of 200 is not sufficient enough to draw a substantial conclusion Some of our respondents were daily commuters who either have a monthly or quarterly pass and don’t use ATVM Smart Card to a large extent
doc_787898591.pptx
The PPT discuss about ATVM Feasibility and it contains topics like research methodology of mumbai suburban smartcard service, sample size, data, data analysis, conclusion, limitation, recommendation,
Research Methodology
Mumbai Suburban Railways’: ATVM Smartcard Service
Presented By:Abhishek Gite (M1013) Sandesh Babar (P1004) Kalpesh Patil (M1032)
Ashish Khadse (P1023)
Introduction
Enables commuter to buy ticket through ATVM, thus save time
Service is available and valid on Western and Central Suburban Railways
More than 980 ATVM on western line and nearly 600 ATVM on central line Card have inbuilt microprocessor and flash memory to store data
Research Objective
To study the feasibility of ATVM Smart Card Service To understand commuters perception towards the service
Methodology
Questionnaire method
Step-I: Response from 200 commuters
Step-II: Data analysis and testing of hypothesis
Research Design
Designed to gauge acceptability and popularity of the service
Convenient sampling plan with ordinal scaling
Considered related aspects like awareness, convenience, availability and features
Sample Design
Target Population: Suburban Railway Commuters
Sample Size: 200
Sampling Method Used: Chi-Square
Source of Data
Primary Data: Through Questionnaire
Secondary Data: IRCTC Website, Indian Rail Website, www.wikipedia.org
Data Analysis
Demographic Analysis
Majority of the respondents (94%) are in age group of 21-30 years
Data Analysis
Demographic Analysis
Majority of the respondents (80.5%) are male
Data Analysis
Demographic Analysis
Nearly 60% of respondents travel daily
Data Analysis
Demographic Analysis
51% of the respondents travel by second class and 47.5% travel by first class
Data Analysis
Demographic Analysis
Income5lac=26%, Between 1-5lac=33%
Data Analysis
Awareness
Almost all the respondents are aware of the facility
Data Analysis
Usability
The total number of respondents who are aware of ATVM Smart Card Service, only 53.5% actually use the service
Data Analysis
Satisfaction Analysis
1-Extremely Poor----------------5-Extremely Good
Most of Commuters are satisfied with almost all the parameters
Data Analysis
Hypothesis Analysis:
Hypothesis I: Null Hypothesis Ho: There is no relationship between frequency of travel and awareness of ATVM Smart Card Service. Alternate Hypothesis H1: There is a relationship between frequency of travel and awareness of ATVM Smart Card Service.
Chi-Square Tests Value Pearson Chi-Square Likelihood Ratio N of Valid Cases 1.873a 2.865 200 df 2 2 Asymp. Sig. (2-sided) .392 .239
a. 3 cells (50.0%) have expected count less than 5. The minimum expected count is 1.05.
Since Pearson Chi-Square Sig. is > 0.05, therefore null hypothesis is accepted. There is no relationship between frequency of travel and awareness of ATVM Smart Card Service
Data Analysis
Hypothesis Analysis:
Hypothesis II: Null Hypothesis Ho: There is no relationship between class of travel and awareness of ATVM Smart Card Service. Alternate Hypothesis H1: There is a relationship between class of travel and awareness of ATVM Smart Card Service.
Chi-Square Tests Value Pearson Chi-Square Likelihood Ratio N of Valid Cases .950a 1.039 200 df 2 2 Asymp. Sig. (2-sided) .622 .595
a. 4 cells (66.7%) have expected count less than 5. The minimum expected count is .09.
Since Pearson Chi-Square Sig. is > 0.05, therefore null hypothesis is accepted. There is no relationship between class of travel and awareness of ATVM Smart Card Service
Data Analysis
Hypothesis Analysis:
Hypothesis III: Null Hypothesis Ho: There is no relationship between monthly expense on railways tickets and usability of ATVM Smart Card Service. Alternate Hypothesis H1: There is relationship between monthly expense on railways tickets and usability of ATVM Smart Card Service.
Chi-Square Tests Value Pearson Chi-Square Likelihood Ratio Linear-by-Linear Association N of Valid Cases 6.213a 6.257 1.711 200 df 3 3 1 Asymp. Sig. (2-sided) .102 .100 .191
a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 7.74.
Since Pearson Chi-Square Sig. is > 0.05, therefore null hypothesis is accepted. There is no relationship between monthly expense on railways tickets and usability of ATVM Smart Card Service
Data Analysis
Hypothesis Analysis:
Hypothesis IV: Null Hypothesis Ho: There is no relation between awareness and usability of ATVM Smart Card Service. Alternate Hypothesis H1 : There is relation between awareness and usability of ATVM Smart Card Service.
Chi-Square Tests Asymp. Sig. Value Pearson Chi-Square Continuity Correctionb Likelihood Ratio Fisher's Exact Test Linear-by-Linear Association N of Valid Cases 3.553 200 1 .059 3.570a 2.171 3.789 df 1 1 1 (2-sided) .059 .141 .052 .094 .070 Exact Sig. (2-sided) Exact Sig. (1-sided)
a. 2 cells (50.0%) have expected count less than 5. The minimum expected count is 2.73.
b. Computed only for a 2x2 table
Since Pearson Chi-Square Sig. is > 0.05, therefore null hypothesis is accepted
There is no relationship between awareness and usability of ATVM Smart Card Service
Conclusion
Most of the commuters (97%) are aware of ATVM smartcard service
Only half of them use this facility
Customers are overall satisfied with the various parameters related to the service There is no relationship between frequency of travel and class of travel with awareness of ATVM service. There is no relationship between monthly expense and awareness with usability of ATVM service.
Recommendations
Machines should be available at more locations and the touchscreens should be more user friendly
Recharge facility should be available online similar to mobile recharge
Facility of journey extension should be incorporated in ATVM Smart Card Service The Indian Railways websites should be more informative
Limitation
Non-availability of information from the railways authorities
Sample size of 200 is not sufficient enough to draw a substantial conclusion Some of our respondents were daily commuters who either have a monthly or quarterly pass and don’t use ATVM Smart Card to a large extent
doc_787898591.pptx