Research — Doctoral thesisSri Satya Sai University of Technology & Medical Sciences

Execution of TQM Facilitator & IT Resources in Indian Industry

Seventeen variables (nine TQM facilitators and eight IT resources), named from 116 studies and ranked by a 21-member expert panel with Interpretive Structural Modelling and MICMAC, then tested on 319 ICT professionals with factor analysis and structural equation modelling. Both TQM facilitators and IT resources relate significantly to customer satisfaction; top-management commitment and electronic data interchange play the major role.

Degree: Ph.D., Computer Application
Conferred: 15 March 2021
University: SSSUTMS, Sehore
Method: ISM · MICMAC · EFA · CFA · SEM · ANOVA

Full thesis (PDF)Summary (PDF)Degree certificate

01 — QuestionObjectives as stated in the thesis

What the research set out to prove.

319 usable responses from ICT professionals (managers and engineers), from a frame of 801 NASSCOM-listed companies across IT, software development, BPO and telecom.

Name the TQM facilitators and IT resources in the ICT industry of India.
Grade and categorise them, and develop the contextual relationships between them.
Understand awareness of TQM and IT programmes in the industry.
Examine the degree to which the facilitators and resources are executed.
Examine the relationship among the named facilitators and resources.

02 — MICMACTables 4.5 & 4.6 · final reachability matrices

Drivers versus dependents.

Each variable is plotted by how many others it drives (y) against how many drive it (x). The dashed lines split the field into autonomous, dependent, linkage and driver quadrants. Positions are the thesis’s own matrix sums; coincident points are offset slightly so both stay visible.

MICMAC variables with driving and dependence power, from thesis Tables 4.5 and 4.6
Var.	Name	Group · ISM level	Drv	Dep
TMCS	Top Management Commitment & Support	TQM · LVI	9	1
TW	Teamwork	TQM · LV	8	4
CT	Continuous Training	TQM · LV	7	4
CC	Culture Change	TQM · LV	7	7
EMPW	Empowerment	TQM · LIV	5	4
TEI	Total Employee Involvement	TQM · LIV	5	6
DMS	Democratic Management Style	TQM · LIII	4	5
CI	Continuous Improvement	TQM · LII	2	8
CS	Customer Satisfaction	TQM · LI	1	9
SPSS	Statistical Packages for Social Sciences	IT · LVI	8	1
CAD	Computer Aided Design	IT · LV	5	3
CAM	Computer Aided Manufacturing	IT · LV	5	3
ERP	Enterprise Resource Planning	IT · LIV	4	2
CAPP	Computer Aided Process Planning	IT · LIII	3	5
CAE	Computer Aided Engineering	IT · LII	2	6
SEM	Structural Equation Modelling	IT · LII	2	2
EDI	Electronic Data Interchange	IT · LI	1	8

Fig. R2 — Driving (y) vs dependence (x), from thesis Tables 4.5 and 4.6. Two notes from the source: SEM’s matrix sums (2, 2) fall in the autonomous quadrant while the text classes it as dependent, and ERP (4, 2) sits on the IT midline; the text classes it as a driver.

03 — FindingsFrom the thesis conclusions

What it found.

Top Management Commitment & Support forms the base of the TQM hierarchy (ISM level VI) and Customer Satisfaction sits at the top (level I); for IT, SPSS is the base and EDI the top.
MICMAC: TMCS (driving 9) and SPSS (driving 8) are the strongest drivers; Customer Satisfaction (dependence 9) and EDI (dependence 8) are the most dependent. Culture Change and Total Employee Involvement are the only linkage variables.
Measurement model: Cronbach’s alpha 0.764–0.892; EFA (KMO 0.777) extracted 17 factors explaining 64.04% of variance.
Structural model: 9 of 16 paths to customer satisfaction are significant: TMCS, CI, TW, EDI, CAD, ERP, CAE, SPSS and SEM.
Both TQM facilitators and IT resources relate significantly to customer satisfaction (p < .001).
Conclusion: top-management commitment and electronic data interchange have a major role in the successful execution of TQM and IT.

04 — Publications3 papers · ISSN 2320-3714

Peer-reviewed papers.

Dec 2016: Study of Software Retrieval Based on Semantic Properties and Its Benefits. Maps how concept relevance varies within a text to separate major from minor themes, then builds a semantic map so users can find relevant resources by navigating semantic proximity instead of keywords. Airo Int. Research Journal · Vol. 8, Issue 4 · pp. 148–158 · with Dr. Suresh Chand Tyagi; PDF
Jan 2017: Effect of Energy Security in the Cloud Prepared by the Loading Algorithm. Load balancing and efficient resource use to cut cloud energy consumption without degrading performance, using genetic algorithms to place virtual machines across servers. Airo Int. Research Journal · Vol. 9 · pp. 201–208 · with Dr. Suresh Chand Tyagi; PDF
2017: Manage Energy Management Resources Effectively in Cloud Computing. Meeting cloud service-level agreements through effective resource management: balancing load so no host is overloaded, alongside VM migration, server consolidation and energy management. pp. 346–358 · with Dr. Suresh Chand Tyagi; PDF

05 — PresentationsPaper presentations, 2017

Presented in 2017.

5 Feb 2017: An Study On Energy Efficient Cloud Computing. Comprehensive Facts and Major Outcomes of Research Recently Done in Arts, Science and Engineering. Airo Journals · IRC Gwalior; Gwalior
21 Jun 2017: Impact of Software Retrievals Based On Semantic Properties and Its Benefits. Scientific and Innovative Approach of Research in Interdisciplinary Streams. CIIS Mumbai · IRC Gwalior; Mumbai
8 Oct 2017: Study of Power Management in Cloud Computing Using Green Algorithm. Technical & Scientific Approach of Innovative Research. Airo Publication · CIIS Mumbai; Gwalior