Factors Affecting eProcurement Performance in Indian Scenario

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Dr. Kalyan Kr. Bhattacharjee from the Indian Institute of Technology Delhi conducted a study on factors influencing eProcurement performance in India. An online questionnaire survey was conducted with 800 users, out of which 310 responses were received and 293 were deemed usable for analysis using SPSS version 20. The descriptive summary of respondents highlighted various user groups and their turnovers. The study also analyzed the statistical position of different variables such as cost-saving, competitiveness, and transparency, among others. Graphical presentations of user responses were used to visualize feedback on aspects like cost-saving, competitiveness, and data security. The rotated component matrix identified key components affecting competitiveness, transparency, success rate, and other factors.


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  1. Factors effecting eProcurement performance in Indian scenario Dr. Kalyan Kr. Bhattacharjee Indian Institute of Technology Delhi

  2. On-line Questionnaire based Survey was conducted to measure the usefulness and acceptance of the application Survey : Google Form Email : 800 users Total Responses received : 310 Usable responses : 293 Analysis : SPSS (version 20)

  3. Descriptive Summary of respondents User_Group Specialization Tot Turnover < 50 lakhs Govt 17 PUC 4 Private 17 Munic 1 Univ 1 Manuf Service 5 IT 1 Educ 3 Legal 3 28 40 50-100 Lakhs 19 5 22 0 1 19 19 7 0 2 47 1-5 crore 24 3 39 0 2 32 25 8 0 3 68 5-10 Crore 10 6 30 0 0 13 26 6 0 1 46 > 10 Crore 19 9 54 1 9 48 23 13 2 6 92 Total 89 27 162 2 13 117 121 35 5 15 293

  4. Basic statistical position of all variables under the study Cron Alpha Attributes Cost_Saving Competitiveness Transparency N Mean 1.74 1.90 1.87 Std. Div .820 .914 .941 Skewness 1.413 1.196 1.190 Kurtosis 2.800 1.595 1.239 293 292 287 .883 .882 .881 No Data Tampering 288 2.05 .934 .724 -.017 .880 High Success Rate 290 2.32 .962 .767 .399 .882 Overall Cronbach's Alpha (reliability) : .885 TimeSaving 288 1.92 1.051 1.139 .451 .878 Reduces_Cycle_Time 288 2.20 .941 .723 .254 .881 Location_independent 288 1.57 .752 1.776 4.562 .880 Reduces_Bidding_Errors 292 2.10 .940 .870 .434 .880 No Unauthorized View Remote_Bid_Opening 290 288 2.03 1.90 .802 .789 .761 .957 .702 1.459 .879 .879 Capturing_bidders_potential 284 2.00 .804 .938 1.328 .879 Bid_submission_convenience 284 1.96 .856 1.510 3.325 .879 Bids Preparation Utility 285 1.89 .802 1.016 1.724 .878 Amendment_of_Bids 285 1.82 .700 .814 1.597 .879

  5. Graphical presentation of Users responses Response Summary Cost Saving 300 Hand holding support Competitiveness 250 Email support Transparency 200 Help Desk Support Data Security 150 100 Multiple Bid Opener Success 50 Agree Neutral 0 Disagree BoQ useful Time Saving Fin View Location independence Tech View Data Viewing Bid Management Remote Access convenience

  6. Rotated Component Matrixa Component 1 2 3 4 Competitiveness Transparency High Success Rate Cost_Saving Reduces_Cycle_Time Tech_Eval_viewability Fin_eval_viewability Capturing_bidders_potential No Data Tampering No Unauthorized View Remote_Bid_Opening Location_independent Bids Preparation Utility Help Desk Support Email_Support Digital_certificate_registration .729 .685 .653 .644 .596 F_Efficiency .763 .761 .499 F_Transparency .765 .732 .601 .530 .486 F_Agility .883 .875F_Flexibility .633 Extraction Method: Principal Component Analysis. Rotation Method: Varimax with Kaiser Normalization. a. Rotation converged in 6 iterations.

  7. Graphical presentation of the inter-relationship between the factors and other variables. .510 Competitiveness .391 Transparency Efficiency Factor .356 Cycle Time -.185 -.108 Remote Bid Opening .130 .089 Financial Viewability .422 Transparency Factor Technical Viewability .382 .112 Bidders Potential .202 Data Security .455 Agility Factor .364 Unauthorized View .149 Location Independence .075 Utility for Bids Preparation Digital Certificate Registration .291 Flexibility Factor E-mail Support .344 Help Desk Support .470

  8. Reduction of Purchase Cycle time (from 2013 to 2016) Processing year Time 350.00 2006 244.59 300.00 2007 261.51 2008 267.96 250.00 2009 296.94 200.00 2010 308.01 2011 307.60 150.00 2012 327.83 100.00 2013 256.29 2014 213.76 50.00 2015 197.45 0.00 2016 123.96

  9. Growth of RTI applications in different Public Authorities of Govt. of India (Source: CIC Annual Report 2015-16, Table 2.4) 976,679.00 834,183.00 811,350.00 755,247.00 629,960.00 437,744.00 2010-11 2011-12 2012-13 2013-14 2014-15 2015-16

  10. Processing of RTI Applications at IIT Delhi 450 397 400 336 350 327 326 326 300 300 234 250 200 150 100 45 36 50 31 27 23 23 22 5 2 2 2 2 1 0 0 2010-2011 234 2011-2012 327 2012-2013 326 2013-2014 397 2014-2015 336 2015-2016 300 2016-2017 326 RTI Applications Received First Appeals Received 45 36 27 23 31 23 22 Second Appeals to CIC 5 2 0 2 2 1 2

  11. Conclusions Four factors have influencing e-procurement practice in Indian context has been identified. Brings high level of satisfaction in terms of cost saving, flexibility and agility. Overall purchase-cycle time has reduced. IIT Delhi s initiative to go for E-procurement helped the institute to march towards transparency and efficiency. There has been a decline in RTI applications at IIT Delhi for the last three years.

  12. For IIT Delhi, it is a case of successful migration Dr. Kalyan Bhattacharjee Indian Institute of Technology Delhi kalyan@admin.iitd.ac.in Mobile No. 09810152691

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