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The integration of TQM and Technology /R&Din Management quality and innovation Performance.

Presented by:Dinesh Parashar 2010 SMN6869Aishwarya Kumar 2010SMN6938Rajnish Jain 2010SMN6949Akash Grover 2010SMN6953Samrat Banerjee 2010SMN6883

Ashok K Thakur 2010SMN6922Robinson 2010SMN6928Anurag Sharma 2010SMN6880Sanjeev Bhatnagar 2010SMN6885

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Content

Section1 Introduction. Section2 Review of Literature. Section3 Research Frame work.

Section4 Empirical research design Section5. Quantities analysis Section6 Research Findings Conclusion

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This Study Contributes in

research in following ways. The study is important when viewed in today's highly

competitive environment .

The study is important in bridging the area of qualitymanagement and innovation management.

The study add to the literature by investigating theintegration of TQM and Technology/R&D management.

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TQM

TQM is associated with incremental exploitationcapabilities particularly in relation to two processes:

Process managementFocussed on incremental improvement by increasedproficiency through repetition of organizational activities

Customer focus

Principles on better understanding and satisfying existingcustomers

TQM is less concerned with Technology, it is consideredmore as an administrative or managerial innovation;

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TIM

Plays a key role in creating a new Product orProcess or changing the rules of competition

by destroying an existing market and creatingnew.

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Need for Integrating TQM and

TIM

Technological:New solutions

to existing

problems

Complex:Technology and

Market

co-evolve

Differentiated:Compete on quality

and features

Architectural:Novel combinations

of existingtechnologies

Low

Low

High

High

Novelty ofTechnology

Fig: Technological and market maturity determines marketstrategy.

Novelty of markets

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Integration between TQM and TIM in

determining Performance TQM can be aligned with other resources to build competencies. Integration of TQM and TIM in Predicting Quality and Innovation

Performance.

What CustomerNeeds:- Meeting current Requirement: ----This could be achieved

by intensive R&D Process Management:- Technology Management.

Technology Management:- Broaden the perspective ofOrganisation in serving customer needs through productinnovation.

Innovation is no longer strictly confined to R&D, It should be part ofOrganization Daily work and culture.

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Research framework

Purpose of Research frameworko Integration between TQM and TIMo Determination of quality performance and innovation

performance What is research framework: Linear model of

independent and dependent variables Independent variable

o TQM: Leadership, strategic planning, customer focus,

information analysis, people management, processmanagement

Dependent variableo TIM: Technology management, R&D

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Research Instruments

TQM measures Technology management

Research & Development (R&D) Quality performance management Innovation performance management Source of empirical data (Market survey)

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Data Analysis

Data analysis for this study involved two major steps

The data reduction process

The data reduction process aimed to reduce the number of variables andparameters in the research model to a manageable number in terms of the ratiobetween sample size and parameters estimated in the Structural Equation Modeling(SEM).

The structural relationship analysisThe structural relationship analysis was used to examine the simultaneousrelationship between TQM and product quality performance, product innovationperformance, and process innovation performance, as well as assessing therelationships among those three performance variables.

The data reduction process was conducted in order to collapse the nine constructseach consisting offourto six items employed in this study into composite variables.

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Data Analysis

The data reduction process contd

These nine constructs were subjected to validity and reliability tests.Confirmatory Factor Analysis (CFA) using LISREL 8.30 was employed for examiningconstruct validity of each scale by assessing how well the individual item measured

the scale.

Six constructs constitute TQM latent variablesLeadershipStrategic planningCustomer focusInformation and analysis

People managementProcess management

Three constructs constitute three organizational performanceProduct qualityProduct innovationProcess innovation

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Data Analysis

The data reduction process contd The final results of construct validity and reliability tests of the eleven constructs are reportedin Table 1.

The Goodness of Fit Indices (GFI) of the eleven constructs exceeded the 0.9 criterionsuggested by Kelloway, hence, establishing the construct validity.The reliability analysis was conducted by calculating the Cronbachs alpha for each scale.The result shows that the Cronbachs alpha measures for the eleven constructs surpass thethreshold point of 0.7 suggested by Nunnally.

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Data Analysis

The data reduction process contd Another test is conducted at the differences of the variables incorporated in thisstudy based on the position of the respondents in the organization.

The responses were classified into three categories:

Quality managers and production/operations managers that are directlyinvolved in daily operations of the companyManagers in other areas than production/operations and quality (e.g. finance,marketing, human resources, and other administrative areas)Senior managers that include managing directors and general managers.

One-way ANOVA test was used to test the mean differences of the elevenvariables used in this study with respect to these three categories.

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Data Analysis

The data reduction process contd

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Data Analysis

The data reduction process contd The result, as presented in Table 2, indicates significant gaps between the thirdgroup of respondents and the first group with respects to several variables.These gaps reflect variation of perceptions on organizational practices andperformance amongst people working in different levels of organizationalstructure/position.

Bivariate correlations :Both TQM and TIM variables show a strong and positive correlation with all thethree performance measures.As evident from Table 3, all correlations are positive and relatively strong. This

indicates that firms that excel in one area are also likely to excel in other areas.The six TQM practices have strong correlations amongst themselves.

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Data Analysis

Bivariate correlations contd

Table 3

Bivariate correlations amongvariables V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11

Leadership (lead) 1

Strategic planning (plan) 0.642 1

Customer focus (cust) 0.541 0.552 1

Information & analysis (info) 0.597 0.684 0.510 1

People management (peop) 0.723 0.650 0.562 0.653 1

Process management (proc) 0.607 0.613 0.653 0.699 0.692 1

Technology management (tech) 0.518 0.403 0.383 0.416 0.516 0.458 1

Research & development (r&d) 0.289 0.268 0.273 0.297 0.267 0.309 0.561 1

Product quality (qual) 0.428 0.351 0.478 0.352 0.437 0.483 0.442 0.249 1

Product innovation (pdin) 0.366 0.260 0.258 0.328 0.420 0.336 0.521 0.454 0.333 1

Process innovation (pcin) 0.433 0.276 0.260 0.329 0.362 0.332 0.561 0.309 0.568 0.547 1Significant atp

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Data Analysis

Structural equation modeling :In this study, SEM was used for model generation purposes.

When an initial model does not fit the data, it can be modified by deleting, adding,and/or modifying paths in the model, then re-tested using the same data set.

Modifications were only made on the paths relationship between exogenous variables(TQM and TIM) and endogenous variables (product quality/QUAL, productinnovation/PDIN, and process innovation/PCIN) by deleting the insignificant paths. Thebest competing model is presented in Fig. 3.

The GFI is above 0.95, the RMSEA value is well below 0.08, and the SRMR is well

below 0.05.

The loading factor of R&D appears to be lower than that for technology, however, stillfalls in the acceptable range (above 0.5). The result also shows that the correlationbetween TQM and TIM is positive, significant, and strong (0.535 at p

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Data Analysis

Structural equation modeling contd

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Data AnalysisStructural equation modeling contd

When combined with the results of the bivariate correlation, we can conclude thatfirms that undertake TQM efforts are also likely to invest in R&D and technologyactivities. Therefore, the result suggests that TQM can be integrated with TIM asorganizational resources.The relationships between organizational practices and performancevariablesIt can be concluded that TIM has a greater explanatory power in predictinginnovation performance than TQM.The overall impact of the combination of TQM and TIM was cross-validated byusing the multiple regression analysis (MRA) method.The results presented in Table 4 indicate the inclusion of TIM increased themultiple R2 values of the three performance variables, particularly for product

innovation and process innovation.Overall the findings indicate that the combination of TQM and TIM create asynergy in enhancing both quality and innovation performance as compared to thecase if organizations solely employed either of TQM as TIM their resources.

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Data AnalysisStructural equation modeling contd

SEM presented above has produced three major findings.

First, there is a strong and positive correlation between TQM and TIM which therefore supports the compatibility of TQM withtechnology and R&D management.

Second, the findings also demonstrate the distinctive role of TQM and TIM in predicting different types of organizationalperformance, with TQM being related to quality performance, whilst TIM being related to both quality and innovationperformance although this strength of the relationship is higher toward innovation.

Third, there are significant relationships between product quality and process innovation and between product innovation and

process innovation.

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The Relationship between Performance Variable

TQM did not specifically relate quality management toproduct Innovation, they insisted on continuous improvementof quality to meet customer expectation needs and

expectation. Study suggest that we can not negate the relationshipbetween Product quality and Product Innovation.

Do not negate the possibility of a company achieving a highconformance level of quality and at the same time producingradical Innovation.

Product Quality can have indirect effect on ProductInnovation Performance through Process Innovation.

Process Innovation has significant relationship with bothProduct quality and Product Innovation.

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Conclusion

Issues1. TQM can be implemented with TIM2. TQM & TIM produces greater explanatory power in terms of :

product quality, product innovation and process innovation

1. Cross fertilization amongst performance e variables with processinnovation and product quality and product innovation

TQM and TIM distinct as well as unique in predicting performancebetween quality and performance

Effectiveness :o TQM more effective in downstream process (e.g/ shop floor)o TIM more effective in upstream design process (e.g. R& D &

radical innovation) TQM concepts & techniques- difficult to apply ( Zaire) Time lags between TQM and R& D technology TQM and TIM can be implemented in harmony with each other