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ABSTRACT The importance of information technology (IT) in total quality management (TQM) has been described widely in the literature. However, empirical evidence for such a claim is still not well established. This paper has empirically explored the use of IT to support TQM processes in the Malaysian public sector. The findings reveal that the level of IT usage varies among the nine dimensions of TQM. Important innovations and information and analysis exhibit high levels of IT usage whereas quality results and supplier quality assurance are associated with significantly lower level.
Introduction
Total quality management (TQM) and the use of information technology (IT) have both been extensively researched over recent years. The importance of IT in TQM has also been described widely in the literature (e.g. Aiken et al., 1996; Cortada, 1995; Goodman & Darr, 1996; Kathuria & Igbaria, 1997; Khalil, 1996; Kock & McQueen, 1997; Murray, 1991; Zadrozny & Ferrazzi, 1992). According to Pearson et al. (1995) and Matta et al. (1998), IT responsive to the needs of TQM is a critical success factor in the implementation of such an information-intensive management system. Significant benefits can be achieved from the integration of IT and TQM in the form of lowered manufacturing costs, improved profitability and improved customer satisfaction.
Even though there exist substantial examples and anecdotal evidence to illustrate the critical role of IT in the success of TQM (e.g. Collins, 1994; Matta et al., 1998), quantitative, empirical evidence for confirming such a claim is still lacking. Nevertheless, there are some notable exceptions. Forza (1995) and Burgess and Gules (1998) found that IT and quality management, especially the quality assurance aspect of TQM, were associated. Both studies were conducted in the manufacturing sector. Ngai and Cheng (1998), on the other hand, examined the use of IT in support of quality among a range of organizations. Their study found that the use of IT in TQM was low even though the usage level in general office operations was relatively high.
The link between IT and TQM is not empirically established in the literature. To ascertain the role of IT, especially in the non-manufacturing sector, which can illustrate the importance or otherwise of IT for TQM, this paper attempts to investigate the extent to which IT is used to support various aspects of TQM quantitatively.
The remainder of the paper describes how the key aspects of TQM practices were identified and the measurement instrument developed. This is followed by an explanation of the research methodology adopted, a statement of the research findings and discussion of the implications of the results.
Research methodology
To gain knowledge about a research problem, McGrath (1982) argues that there is no one best methodological strategy. The use of a combination of multiple strategies (not within one study, but over studies within a programme) to gain information about a given problem through multiple means that do not share the same weaknesses is highly recommended. Past work on the role of IT in supporting TQM is summarized in Table 1. It showed that the link between IT and TQM was mostly demonstrated by quoting particular application examples or deduced practice from theory. Quantitative, empirical techniques were hardly involved. This study takes the suggestion of Straub and Carlson (1989) to tackle the problem quantitatively, undertaking rigorous instrument validation as well as quantitative analysis to establish greater confidence in the research and its findings.
Domain identification
The purpose of this study is to investigate the extent to which IT has been used to support TQM in Malaysian public agencies in order to ascertain the role of IT in TQM. The emphasis was on how IT supported TQM processes rather than on TQM performance. As no suitable instrument was readily available, an instrument had to be developed.
To determine the domain of TQM, an extensive review of the theoretical, empirical and practitioner literature was undertaken. A framework based on the literature of TQM (e.g. Flynn et al., 1994; Garvin, 1991; Kanji & Asher 1993; Oakland, 1993; Saraph et al., 1989) has been derived and used as the basis for the fieldwork content agenda to determine the use of IT in TQM. The content can be classified into the following nine dimensions of TQM:
leadership;
strategic planning process;
output quality assurance;
supplier quality assurance;
important innovations;
information and analysis;
human resource utilization;
customer satisfaction;
quality results.
Leadership
Crosby, Deming and Juran unanimously consider top management commitment to quality as a top priority (Waldman, 1994). The importance of top management support and their leadership in TQM is repeatedly emphasized in the theoretical and empirical quality literature (Cullen, 1992; Dale et al., 1997; Garvin, 1991; Oakland, 1993; Ryan, 1996; Terziovski et al., 1996; Thiagarajan & Zairi, 1997a). Besides developing a clear quality vision and putting in place elements of TQM structures, top management has to `walk the talk’ (Cullen, 1992; Thiagarajan & Zairi, 1997a). The actual rime and energy spent by senior managers in daily quality activities are far more important than lip service and are regarded highly by judges of the Baldrige Award (Garvin, 1991). Top management involvement includes activities such as communicating company’s quality values, reinforcing quality messages, meeting with the workforce and customers, giving formal and informal recognition, receiving training and training others.
Strategic planning process
Quality does not happen on its own; it has to be planned and managed. Strategic quality plans are the glue that holds a company’s quality effort together (Garvin, 1991). The plans have to be focused, concrete, integrated and aligned with other business plans. Quality gurus and writers of TQM are unanimous in stressing the importance of a strategic planning process (e.g. Deming, 1986; Kanji & Asher, 1993; Oakland, 1993). The process of the planning itself enables an organization to identify its customers, prioritize their requirements, make employees understand and become committed to the quality goals of the organization (Harrington, 1997; Kanji & Asher, 1993; Thiagarajan & Zairi, 1997a).
Output quality assurance
The activity of checking to ensure the output is of the desired quality is known as quality assurance. It is the prevention of quality problems through planned and systematic activities (Oakland, 1993). Implementation of a formal quality assurance system has been identified as a critical factor of success (Terziovski et al., 1996). Quality assurance is a framework that encapsulates four principles of control, i.e. setting standards, appraising conformance to these standards, acting to ensure standards are met and planning for improvement in standards, to provide an integrated system for managing all functions within an organization (Lin, 1991). Although numerous quality assurance techniques and tools are available (e.g. statistical process control, Pareto charts), the emphasis is on a sound approach that produces verifiable, repeatable, controllable results that meet customers’ needs (Dale et al., 1997; Garvin, 1991; Oakland, 1993; Thiagarajan & Zairi, 1997b; Woodruff, 1995-96).
Supplier quality assurance
Supplier quality has a great effect on an organization’s quality performance (Flynn et al., 1994; Saraph et al., 1989). World-class companies such as Toyota, Nissan and ICL Product Distribution UK view suppliers as an integral part of their organization’s operation (Thiagarajan & Zairi, 1997b). This is because they recognize that a major source of quality product/process problems is defective in-coming supplies. These companies have adopted various supplier management programmes in their pursuit of continuous quality improvement.
Important innovations
The quest for quality requires reduced unwanted variation in products or services, and adherence to predetermined standards. However, there should be a balance between innovation and standardization (Oakland, 1993) as TQM means continuous improvement. Pursuit of new technology for strategic advantage, whether by designing and introducing new products or services, or by creating innovative work processes, is critical for TQM success (Terziovski et al., 1996).
Information and analysis
TQM is an information-intensive management system (Matta et al., 1998). Information plays a vital role as all quality improvement activities are based on informed decision-making (Flynn et al., 1994; Garvin, 1991; Lin, 1991). A company’s database must be comprehensive and cover all critical areas such as customers, suppliers, employees and projects/processes (Atkinson, 1991; Kyte, 1991; Zahedi, 1998). As managing quality generates a great deal of data, it is important to determine what data types are worth keeping and how to organize them into an easily accessible structure. The databases must be able to facilitate different data manipulation and in-depth analysis to fulfil information requirements of each level (strategic, tactical and operational) of decision-making activities (Collins, 1994; Lin, 1991; Miller, 1996).
Human resource utilization
Many of the problems faced in implementing and sustaining TQM are to do with employees’ involvement and commitment to achieving quality goals (Dale et al., 1997). In TQM interventions, the workforce should be informed and empowered in order to perform their responsibility fully (Flynn et al., 1994; Scully, 1996; Thiagarajan & Zairi, 1997a) and be actively involved in teamwork (Kanji & Asher, 1993; Oakland, 1993). Besides pooling expertise and resources to tackle various quality problems, teamwork also boosts employees’ morale and increases productivity (Atkinson, 1991; McCafferty & Laight, 1997; Woodruff, 1995-96; Wythe, 1991). However, employees must be given the relevant training and education to ensure they have the theory and tools needed to function as part of an organization dedicated to quality principles (Ryan, 1996; Scully, 1996; Siegel & Seidler, 1996; Terziovski et al., 1996; Wythe, 1991). At the same time, to realize employees’ full potential and involvement they have to be motivated by suitably relevant reward mechanisms. Their contribution should be given due recognition (Keck, 1996; Memmott, 1992; Thompson, 1998; Wythe, 1991).
Customer satisfaction
Quality is meeting the customer requirements. To satisfy customers, an organization has to know its customers and be aware of their needs (Adam et al., 1997; Garvin, 1991; Oakland, 1993, Terziovski et al., 1996). Quality-oriented organizations constantly collect customer information from a wide range of sources and use a variety of quantitative techniques to measure their satisfaction (Evans, 1991; Garvin, 1991; Oakland, 1993; Thiagarajan & Zairi, 1997b) in order to exceed customers’ expectations and anticipate needs.
Quality results
All activities performed by an organization should be measured in order to sustain improvement, to meet customer requirements, to justify the use of resources and to detect quality problems (Oakland, 1993; Ryan, 1996; Ward, 1996). Hence, quality results should include product and service quality, productivity, waste reduction and elimination, customer and employee satisfaction (Oakland, 1993; Woodruff, 1995-96).
Instrument development
Using the previously mentioned key TQM processes found in the literature, a set of items was selected for each dimension, operationalized as the extent to which IT has been used to support the processes (see the Appendix for this operationalization). A seven-point Likert scale was used to measure each of the dimensions identified. They were anchored at the ends with `not at all’ and `maximum feasible amount’. A definition of IT was given at the beginning of the questionnaire to ensure that respondents shared a common understanding of IT.
After developing an initial measurement instrument, pre-testing was carried out to ensure completeness and precision. Personal interviews were conducted with nine participants in order to improve the instrument progressively in terms of both content and construct validity (Churchill, 1979; Nunnally, 1978; Straub & Carlson, 1989). The selection of the participants was designed to get maximum feedback from academic and practitioner experts in the fields of TQM and IT. The instrument was continuously modified for the successive interviews. The process was complete when the last two participants made no recommendation for any significant changes.
The final version of the questionnaire was then pilot-tested with six university administrative officers in Malaysia who were actively involved in quality programmes. The questionnaires were completed in the presence of the researchers. Minor modifications were again made and the questionnaire was finalized.
Data source
The research sample consisted of 110 public agencies that have been candidates for the Malaysian Prime Minister’s Quality Award. The list was obtained from the Malaysian Administrative Modernization and Management Planning Unit, which is responsible for the administration of the award. These agencies were selected because they have had extensive documentation to substantiate the implementation of TQM. Therefore, they potentially offer an informed view on the use of IT to support TQM.
Personalized survey instruments were mailed to quality managers of the public agencies. They were first identified via telephone contact. Of the 110 questionnaires mailed, 47 were returned and used for analysis. The response rate (43%) is compatible with studies of this nature (King & Teo, 1994; Ngai & Cheng, 1998).
A profile of the responding organizations and respondents is illustrated in Tables 2-4.
Non-response bias was tested by comparing the early-late responses and also by other sample characteristics. These were organization size (chi2 = 3.53, df = 1, p = 0.06), location (chi2 = 0.47, df = 1, p = 0.49) and current TQM practice (chi2 = 0.09, df = 1, p = 0.76). The chi-square tests indicated that the non-response bias was unlikely to be a significant issue in this study.
Instrument validation
Prior to any formal data analysis, the instrument was thoroughly validated (Table 5). The reliability coefficients (Cronbach’s alpha) of all the nine constructs were well above 0.75. Construct validity of the measurement instrument for the nine dimensions of TQM was evaluated by factor analysing the measurement items of each dimension separately. The nine constructs individually loaded as a single distinct factor with eigenvalue ranging from 1.61 (supplier quality assurance) to 8.38 (human resource utilization). The unifactorial constructs accounted for 65.5-94.5% of the total variance of each respective dimension, indicating appropriate construct validity. Finally, the combined set of the nine constructs has a significant 0.54 correlation with the criterion-variable of IT impact, providing evidence of predictive validity (Hair et al., 1995; Nunnally, 1978).
Findings
On the whole, the use of IT in support of TQM along the nine dimensions exceeded the moderate level, i.e. above four on a seven-point scale (Table 6). Over 85% of the organizations reported that they have used a moderate to maximum feasible amount of IT to support the `important innovations’ (number of respondents = 41) and the `information and analysis’ (40). Only about 20% of them indicated having used IT less than the moderate level to perform the `leadership’ (9), the `human resource utilization’ (10) and the `output quality assurance’ (11) dimensions of quality management. As for both the `customer satisfaction’ (33) and the `strategic planning process’ (33), about 70% of the organizations said that the measure of IT use was 4 or above. In contrast, only about half of the responding organizations used IT more than 4 on the scale, in the `quality results’ (23) and about 30% in the `supplier quality assurance’ (8) (there were only 28 valid observations for the’ supplier quality assurance’). The `important innovations’ has the highest level of IT use (5.09) followed closely by the `information and analysis’ (5.06). The `supplier quality assurance’ has the lowest mean of IT use (4.09). Table 6 summarizes the extent of IT use on all nine dimensions of TQM.
The normality test suggested that the distribution of the use of IT for each of the nine dimensions was approximately normal, with Kolmogorov-Smirnov (Lilliefors) statistics ranging from 0.05 to 0.11. Their observed significance levels are above a lower bound of the true significance, i.e. p 0.20 (Norusis, 1997, p. 224).
Table 6 also shows that the overall use of IT to support TQM is 4.66. The distribution of the overall IT use was found to have a kurtosis of 0.32 and a slight negative skew (- 0.27). The Kolmogorov-Smirnov (Lilliefors) statistic is 0.05, with the significance level sufficiently large to assume a normal distribution (p > 0.20).
Repeated ANOVA measures showed a significant difference in the extent of IT use among the nine dimensions of TQM (F8,216 = 7.89, p < 0.01). Duncan’s range test showed that the mean use of IT on the `information and analysis’ and the `important innovations’ differed from the `strategic planning process’, the `customer satisfaction’, the `quality results’ and the `supplier quality assurance’. Differences were also found between the `leadership’ and the `quality results’ as well as between the `supplier quality assurance’ and the `leadership’, the `output quality assurance’ and the `human resource utilization’ at the 0.05 significance level.
Discussion and conclusions
The study provided empirical findings to supplement anecdotal and case evidence on the role of IT in TQM environments. The survey results supported the claims of the authors listed in Table 1 that IT benefits TQM implementation in the `important innovations’, the `information and analysis’, the `output quality assurance’ and `human resource utilization’. Although past work has given examples to demonstrate how IT can be deployed to support the `customer satisfaction’ and `quality results’, this study found that the IT usage level of these two dimensions was only moderate.
When comparing the findings of this study to the few empirical results reported in Table 1, the high level of IT usage in providing quality information and analysis supported Forza’s (1995) work, which found that flows of information strongly and positively influenced the achievement of quality performance. However, this study did not support the findings of Burgess and Gules (1998), whose research was conducted in an automobile manufacturing sector. The difference in the context of the study may account for the variation in the results.
The finding of the study also is not consistent with the work of Lloyd-Walker and Cheung (1998) in the Australian banking industry, who found quality customer services and product issues most strongly influence IT planning, but not IT applications, that support innovations. One possible explanation for the difference in the results is that the banking industry, being profit-oriented, emphasizes customer-focused technologies to ensure a return on investment, whereas the public agencies in Malaysia concentrate more on innovative applications to improve efficiency and effectiveness of service delivery. This is because IT has been singled out to help improve service quality and productivity in the Malaysian public sector (Maarof, 1996), and innovative use of IT has been encouraged, especially to improve efficiency by creating effective work processes and to realize `one-stop shopping’ for citizens (MAMPU, 1999). (The phrase `one-stop shopping’ is used to describe a situation where a citizen goes to a single location for multiple government services or information about the services, such as veterans benefits, unemployment insurance, housing allowances and medical insurance reimbursement (McDonough & Buckholtz, 1992, p. 32).)
The usage of IT in the public sector is expected to increase as the government has doubled the funds allocated to IT-related programmes and projects, in particular Electronic Government projects, from RM2 billion to RM4 billion (around US$1.1 billion, using the exchange rate in 1999) under the mid-term review of the seventh Malaysia Plan 1996-2000 (Allocation for IT projects doubled to RM4b, 1999).
The results of this study as well as past work (Table 1) suggest that managers seeking help from IT to implement TQM could start with the `important innovations’ and the `information and analysis’ dimensions. IT could be deployed to modify work processes to improve productivity and quality of services. IT could also be used to maintain a comprehensive database of customer, supplier, employee and project/process. This could certainly improve the quality of information, which is essential for TQM (Zadrozny & Ferrazzi, 1992). As suitable software to support TQM has been reported lacking (Ngai & Cheng, 1998), this study helps to provide directions to software developers to focus their attention on developing software applications along these dimensions to cater for the immediate demand. The discrepancy between past work and this study on the use of IT to support the `customer satisfaction’ and the `quality results’ may indicate a potential for IT exploitation.
Lastly, this study focused on the use of IT to support TQM processes in the Malaysian public agencies that have been candidates for the Prime Minister’s Quality Award. It is acknowledged that these `highly regarded’ agencies may not be considered representative of all TQM implementing organizations. The difference in sample selection may itself account for the contradicting findings reported by Ngai and Cheng (1998). As this present study was undertaken in a rather narrow field, there may be concern as to the generalizability of the findings, especially to a wider profit-oriented community. This very much depends on how an organization views TQM. Garvin (1991) has pointed out that TQM does not guarantee instant financial success, but rather the long-term survival and future profitability of an organization in the competitive market. It is possible that in the private sector, the quality programmes are viewed very differently. Similarly, if IT is regarded as a tool to generate short-term return on investment, its usage in supporting quality programmes will not be prioritized. If so, then the level of IT usage in supporting TQM would be difficult to establish.
The Malaysian public sector has decisively adopted TQM to support the delivery of public services that satisfy customers (Chiu, 1997). The government has also singled out IT for achieving the goal to be a world-class public service provider (Maarof, 1996). Our sample found IT to be supportive of TQM implementation. If the profit-oriented sector shares that view, then our findings suggest there exists a strong relationship between IT and TQM. On the other hand, if the same relationship does not hold true, more work needs to be done, especially to examine whether our findings are extendible to the other sectors.
Table 1. Summary of the literature on the role of IT in TQM
Legend for Chart:

A – Dimension
B – Source
C – Technique

A

B C

Leadership

Collins, 1994 Example

Cortada, 1995 Example

Strategic planning process

Lin, 1991 Example

Output quality assurance

Zadrozny & Ferrazzi, 1992 Example

Collins, 1994 Example

Quinn & Baily, 1994 Case study

Cortada, 1995 Example
Forza, 1995 Survey

Kathuria & Igbaria, 1997 Example

Matta et al., 1998 Example

Zahedi, 1998 Theory

Supplier quality assurance

Burgess & Gules, 1998 Survey

Matta et al., 1998 Example

Important innovations

Murray, 1991 Example

Quinn & Baily, 1994 Case study

Matta et al., 1998 Example

Lloyd-Walker & Cheung, 1998 Survey

Information and analysis

Lin, 1991 Example

Zadrozny & Ferrazzi, 1992 Example

Collins, 1994 Example

Quinn & Baily, 1994 Case study

Cortada, 1995 Example

Matta et al., 1998 Example

Tan, 1998 Example

Zahedi, 1998 Theory

Human resource utilization

Zadrozny & Ferrazzi, 1992 Example

Collins, 1994 Example

Quinn & Baily, 1994 Case study

Cortada, 1995 Example

Khalil, 1996 Example

Goodman & Darr, 1996 Example

Kock & McQueen, 1997 Example

Matta et al., 1998 Example

Customer satisfaction

Lin, 1991 Example

Zadrozny & Ferrazzi, 1992 Example

Cortada, 1995 Example

Matta et al., 1998 Example

Quality results

Zadrozny & Ferrazzi, 1992 Example

Collins, 1994 Example

Cortada, 1995 Example

Kaplan, 1996 Example

Matta et al., 1998 Example

Zahedi, 1998 Theory
Table 2. Organization size
No. of staff Frequency Percentage

<50 4 9

50-149 8 17

150-299 10 21

300-500 9 19

>500 16 34
Table 3. Respondents’ length of service with the organizations (in years)
Length of service Frequency Percentage

<6 21 45

6-10 4 9
11-15 8 17

>15 11 23

No response 3 6
Table 4. Respondents’ job title
Job title Frequency Percentage

Head or deputy 23 49

Admin. or executive officer 8 17

IT manager or assistant 8 17

Other IT personnel 5 11

No response 3 6
Table 5. Reliability and construct validity
Legend for Chart:

A – Dimension
B – No. of items
C – Alpha
D – Eigenvalue
E – % variance[a]

A B C D
E

Leadership 7 0.92 4.95
70.07

Strategic planning process 5 0.96 4.29
85.9

Output quality assurance 6 0.97 4.06
67.9

Supplier quality assurance 2 0.76 1.61
80.4

Important innovations 2 0.94 1.89
94.5

Information and analysis 11 0.94 7.20
65.5

Human resource utilization 12 0.96 8.38
71.5

Customer satisfaction 4 0.97 3.68
91.9

Quality results 5 0.94 4.03
80.7
a Percentage of variance explained by Factor 1.
Table 6. Extent of IT use along the nine dimensions of TQM
Legend for Chart:

A – Dimension[a]
B – Mean
C – SD
D – Min.
E – Max.

A B C D
E

Important innovations 5.09 1.27 1.50
7.00

Information and analysis 5.06 1.03 2.45
7.00

Leadership 4.88 1.10 2.00
6.86

Output quality assurance 4.82 1.08 1.17
6.67

Human resource utilization 4.80 1.10 2.00
6.86

Strategic planning process 4.40 1.43 1.60
7.00

Customer satisfaction 4.35 1.45 1.00
7.00

Quality results 4.28 1.31 1.80
6.60

Supplier quality assurance 4.09 1.17 1.00
6.50

Overall IT use in TQM: 4.66 1.02 1.74
6.78
a Measured on a seven-point scale.

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