Linking soft and hard total quality management practices: evidence

Int. J. Business Excellence, Vol. X, No. Y, xxxx

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Linking soft and hard total quality management practices: evidence from Jordan Rawan Ali Saleh, Rateb J. Sweis* and Firas I. Mahmoud Saleh Department of Business Administration, The University of Jordan, 11942, Amman, Jordan Email: [email protected] Email: [email protected] Email: [email protected] *Corresponding author

Adel Mohammed Sarea Department of Business Administration, Ahlyah University of Bahrain, Building 41, Road 18, Al-Hoora 310, P.O. Box 10878, Manama, Bahrain Email: [email protected]

Islam Mahmoud Sharaf Eldin Department of Industrial Engineering, Zagazig University, 44519, Al Sharkia, Egypt Email: [email protected]

Disreen Nader Obeid Department of Pharmacy, The University of Jordan, 11942, Amman, Jordan Email: [email protected] Abstract: The purpose of this study is to describe the relationship between the two aspects of total quality management (TQM), soft TQM practices and hard TQM practices in manufacturing organisations. A research project was carried out in Jordanian manufacturing organisations, using questionnaire survey. The relationships between the practices were examined through Pearson correlation and simple linear regression analyses. The results showed that the relationship between soft and hard TQM practices is significant. Customer focus has a significant relationship with statistical process control (SPC), while education and training has two significant relationships (SPC and continuous improvement). Top management leadership has three significant relationships (SPC, continuous improvement and product design). Finally, supplier Copyright © 20XX Inderscience Enterprises Ltd.

Comment [v1]: Author: Please confirm if the amended address is correct.

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A.R. Saleh et al. relationship has significant relationships with all hard practices except process management practice. Hence, managers of manufacturing companies should realise the important role of hard practices in implementing soft TQM practices successfully. Keywords: total quality management; TQM; hard practices; soft practices; manufacturing organisations; Jordan. Reference to this paper should be made as follows: Saleh, R.A., Sweis, R.J., Mahmoud Saleh, F.I., Sarea, A.M., Sharaf Eldin, I.M. and Obeid, D.N. (xxxx) ‘Linking soft and hard total quality management practices: evidence from Jordan’, Int. J. Business Excellence, Vol. X, No. Y, pp.000–000. Biographical notes: Rawan Ali Saleh worked as a Quality Engineer in a leading Jordanian pharmaceutical organisation. She holds a Master in Quality Management from Jordan University. She has a Bachelor degree in Chemical Engineering and three years experience in the pharmaceutical industry. She does professional training in the area of quality management. Rateb J. Sweis is a Professor of Project Management at the University of Jordan/Department of Business Administration. He served as the Vice Dean of the Jordan Institute of Diplomacy, an Advisor to the Minister of Finance and is currently a faculty member in the Department of Business Management at the Jordan University. He has many published articles in the areas of quality management, project management and productivity. He also has five published books in operations management, project management and communications management. Firas I. Mahmoud Saleh is a Manager of Quality in CARE International and PMO Manager in Jordan River Foundation. He holds a Master in Quality Management and Bachelor degree in Computer Science. He has more than 18 years of experience in the fields of quality management and project management. He worked as Projects Management Office Director, Project and Program Manager as well as M&E Manager for several for-profit, non-profit and governmental organisations. He has PMP certification and is the author of a published book in the field of project management and has several published articles in the field of quality management. Adel Mohammed Sarea is an Assistant Professor and MBA program Director. He has special interest in quality management and well published in the field of accounting and business administration. Islam Mahmoud Sharaf Eldin works as a Teaching Assistant at Zagazig University. He has special interest in quality management. Disreen Nader Obied holds a Master in Pharmacy. He is interested in quality management.

Linking soft and hard total quality management practices

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Introduction

Traditionally, organisations all over the world focus on efficiency, share price, revenues, market share or profit to success, but recently, the focus was shifted to improve quality, to gain all these competences and to grow in the future, as delivering high quality goods and services become essential for organisation’s survival (Gupta et al., 2016). Organisations urge to survive in the immensely competitive globalise market and their attempts to aggrandisement their profit gave birth of total quality management (TQM) concept (Saljoughian et al., 2014). In the literature arena, a widespread confusion about the components of TQM was found among the authors. This makes the implementation of TQM practices more difficult and the need for investigating the relationships between them essential. Many studies have tried to make the abstract TQM philosophy much easier to understand by parcelling the practices according to their work area, especially the studies that split the TQM practices into soft and hard, infrastructure and core, organic and mechanistic, supportive and core, etc. Where (soft, infrastructure, organic and supportive) practices related to behavioural factors, meanwhile (hard, core, mechanistic) practices related to more technical factor (measurement and analysis). Despite the difference between authors regarding which practices should be considered as soft and which one as hard, the majority supported the use of the integrated framework to implement TQM correctly such as Al-Khalili and Subari (2013). The implementing of multidimensional framework needs much attention for the role of each practice and the interrelatedness of practices, especially for developing countries where TQM implementation is still in its preliminary stages. Few research papers investigated the interconnection between the two aspects of TQM in developing economy and none were found in Jordan. The majority of soft and hard TQM studies were conducted in developed countries (Abdallah, 2013; Al-Khalili and Subari, 2013). For this reason, this study came to surface to describe the relationships between soft and hard TQM practices, also to clarify how soft and hard TQM practices function when they are combined with each other in Jordanian manufacturing organisations, which can help quality managers on how to plan, organise, carry out, and report TQM system. This study can also serve as a basic reference on soft and hard TQM practices for any manager who may lack substantial background in the subject. Thus, the main goal of this research is to answer the following question: “Is there a relationship between soft TQM practices and hard TQM practices in Jordanian manufacturing organisations”. The next section describes how the concept of TQM arose and how the practices changed over time influenced by the dynamic marketplace needs and competition, starting from the adoption of statistical process control (SPC) as a hard practice to reach the umbrella philosophy of soft and hard TQM.

1.1 TQM history TQM philosophy evolved throughout history, starting from the birth of modern SPC until reaching today’s modern management practices.

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The birth of modern SPC was attributed to Walter Shewhart (the father of SPC) in 1924. A small number of Japanese manufacturing organisations used SPC until 1940’s (Harrington, 2000). But, the wind didn’t go as ships crave, at that time, Japan’s industrial system had a widely held reputation for poor quality, and their goods were avoided by international markets. This led Japanese organisations to explore new ways of thinking about quality. Japan recognised the problem and adopted a notable quality guru’s philosophy, such as Juran, Deming and Feigenbaum (Charantimath, 2011). The origin of efforts for introducing TQM can be traced to 1949, the Union of Japanese Scientists and Engineers (JUSE) after World War II. JUSE devoted to improve their productivity and enhance their quality of life by forming a committee of scholars, engineers, and government officials. Influenced by Deming and Juran, the committee continued their progress by developing a course on SPC, followed by extensive statistical training and deployment of the Deming philosophy among Japanese manufacturers (Powell, 1995). Then, the Japanese adopted the idea of American gurus Deming and Juran, by focusing on organisational process through people who used the process rather than inspection (Charantimath, 2011). The Japanese made a significant progress in the field of quality and penetrated the USA markets (Fotopoulos and Psomas, 2009). After that, Feigenbaum introduced the term ‘total quality’, in the first international conference for quality control which was held in Tokyo in 1969. Issues covered were planning, organisation and management responsibility. At the same conference, Ishikawa presented a paper that explained how total quality control in Japan was performed, and described how all employees, from top management to the workers had to study and participate in quality control for the process to be effective (Charantimath, 2011). Later, in 1974, quality assurance system came to the surface when the British Standard Institute (BSI) initiated the guide to the operation and evaluation of quality assurance system (BS 5179) that consisted of three parts: final inspection system, comprehensive inspection system, and comprehensive quality control. Five years later, in 1979, BS 5179 standards were converted into BS5750 (Bird, 2002), the aim of this system was to increase the attention about the importance of quality for competitiveness and survival in the world market (Charantimath, 2011). In 1980, the National Broadcasting Company (NBC) television produced a program entitled “If Japan Can. Why Can’t We?” that became famous program and revealed Dr. Edwards Deming’s key role in the development of Japanese quality (Samson and Terziovski, 1999). Seven years later, the USA government recognised the need to compete with Japan and the importance of quality to a nation’s economic health as it became a widespread aspect, and established the Malcolm Baldrige National Quality Award (MBNQA) to provide quality leadership (Samson and Terziovski, 1999). In the same year Motorola Company came in with more powerful version of TQM called six sigma (Goetsch and Davis, 2013). International Organization for Standardization (ISO) 9000 was published for the first time in 1987, and it has become the internationally recognised standard for quality management system. It consisted of a number of standards that determine the requirements for documentation, implementation and maintenance of the quality system (Charantimath, 2011). In the same year, Europe relied that quality is a weapon for facing of competition so it brought out European Quality Award (EQA) to encourage European organisations to


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implement quality practices that produce high quality of service, product and processes (Thandapani et al., 2013). Thereafter, in 1990, Toyota introduced lean manufacturing concept. Ten years later, ISO 9000 was revised to incorporate the TQM concept (Goetsch and Davis, 2013). Since then the TQM was acknowledged as an organisation-wide philosophy that seeks to continuously improving the quality of products, services and processes by focusing on customers to satisfy or exceed customers’ needs and expectations and to enhance organisational performance (Sadikoglu and Olcay, 2014). TQM directed the attention toward involvement, commitment, learning, internal cooperation and teamwork (Prajogo and Sohal, 2004). It can be noticed that, throughout history, TQM practices played a crucial role in protecting competitive advantage of manufacturing organisations. Organisations continuously seize the winner, practices to win the completion in a competitive marketplace. No consensus was found on the winner practices as the new challenge arises and the demand of new practice becomes inevitable. Also, TQM history indicated that widespread practices have been implemented to build TQM system as a part of commitment to improve effectiveness, a shared mindset which is characterised by sense of urgency was created to survive in the market and maintain superior position. It also indicated that the danger associated with TQM practices implementation was skipping the best practices, and misunderstanding of how those practices react internally to provide the whole macro image of organisation effectiveness. So, manager should allocate their limited resources to those practices which have significantly positive influence on organisations and help public to understand the role of each quality management practices with ultimate aim of contributing utilisation improvement (Brkić et al., 2016). This may lead to address issues and questions that are not directly relevant to the management process and wasting precious time. One of the best ways to avoid this problem is to use well defined winner practices and to understand how they interact with each other.

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Literature review and hypotheses

2.1 Soft and hard TQM practices Soft and hard TQM practices have been classified by researchers in different ways; some practices were considered as soft practices by some researchers and hard by others. In this context, different empirical research investigated different relationships. Some researchers investigated the combined and separate effect of TQM practices on quality performance, organisational performance, quality management results, key business results, competitive advantage, innovation, total preventive maintenance (TPM) and other variables. However, few of researchers focused on the interrelationships between the two dimensions, soft and hard, of TQM practices. The appendix at the end of this study reveals soft and hard TQM practice models of various studies in different contexts. Based on the reviewed literature in the appendix, the following practices were considered in the proposed research model:

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A.R. Saleh et al. The soft TQM practices included:

1

customer focus

2

education and training

3

top management leadership

4

supplier relationship.

The hard TQM practices included: 1

continuous improvement

2

SPC

3

process management

4

quality tools and techniques

5

product design.

These specific TQM practices were selected according to their frequency of use by reviewed TQM studies.

2.2 The relationships between soft and hard TQM practices According to Azam et al. (2012) core quality practices are professional technical parameters that directed to achieve the best outcomes while supportive (soft practices) practice are all efforts support core practices. The effect of supportive quality practices on core quality practices can be positive or restrictive in nature but both practices must function in synergy and acting in tandem to achieve positive outcomes. While Wu (2015) findings supported the indirect relation between infrastructure practices and performance via core practices. The following discussion clarifies in details the relationships between each soft practice with each hard TQM practice according to previous studies.

2.2.1 The relationships between customer focus and continuous improvement, SPC, process management, quality tools and techniques and product design According to Anderson et al. (1994), effective continuous improvement enhances organisations products or services to meet and satisfy changing customer needs. Also, organisations can understand the specifications by analysing quality data and building a solid cooperation with customers (Kim et al., 2012). Forza and Filippini (1998) reported a positive relationship between quality data and customer focus. Likewise, the results of Al-Khalili and Subari (2013) proved that the relationship between customer focus and process control and improvement was significant and positive. Sisnuhadi (2014) found that mutually beneficial supplier relationship, customer focus, continuous improvement, and leadership support the application of the process approach. Salah et al. (2013, p.176) stated that “Quality is the result of reliable processes and it is better to build quality upstream in the process, than to try to control quality downstream.


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Also, processes should be looked at from the perspective of the customer and there should be equal attention given to the process, the people and the results”. The results of Al-Khalili and Subari (2013) showed different associations between customer focus and different types of TQM tools and techniques. For example, the relationship between customer focus and TQM tools and techniques/purchasing and TQM tools and techniques/customer service were significant and positive. On the other hand, they found no significant and positive relationship between customer focus and TQM tools and techniques/production and TQM tools and techniques/sales. According to Prajogo and Sohal (2003), organisations can search for new customers’ needs and expectations by introducing new products to the market. Also, product features and serviceability can be promoted by encouraging customers to get involved in the product design process, which will help in providing a product that meets the needs of customers and influences customers’ ease of use (Flynn et al., 1995, Ho et al., 1999) and produce efficient process management (Ahire and Ravichandran, 2001; Kim et al., 2012). Al-Khalili and Subari (2013), found a significant and positive relationship between customer focus and product design. Moreover, Kaynak (2003) found that managing quality data provides an opportunity to establish relationships with customers, design new products and improve processes. While according to Flynn et al. (1995), product design had weak relation with customer relationship.

2.2.2 The relationships between education and training and continuous improvement, SPC, process management, quality tools and techniques and product design Ho et al. (2001) stated that employees should agree and accept the initiative of continuous improvement because without their agreement it is doubtful that any core TQM practices can be effective. Therefore, it is essential to provide employees with proper education and training to facilitate TQM success. No significant and positive relationship between education and training and process control and improvement was found by Al-Khalili and Subari (2013). Also, employees and managers need advanced SPC tool training in order to gain quality maturity (Das et al., 2000). Al-Khalili and Subari (2013), showed that there were no significant and positive relationship between education and training and TQM tools and techniques/purchasing, TQM tools and techniques/ production and TQM tools and techniques/sales, but education and training had a significant and positive relationship with TQM tools and techniques/ customer service. Generally, education and training efforts can reduce manufacturing costs through better process and product design optimisations and through empowerment (Salah et al., 2013). Ho et al. (1999) showed that, training supported other TQM practices such as, product design, and quality data and reporting, while there was no relationship between training and process management. Similarly, Al-Khalili and Subari (2013) found no significant and positive relationship between education and training and product design. While Kaynak (2003) found that training was directly related to quality data and reporting and indirectly related to process management, and product/service design through quality data and reporting.

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2.2.3 The relationships between top management leadership and continuous improvement, SPC, process management, quality tools and techniques and product design Organisation leadership plays a great deal by emphasising on continuous improvement throughout the organisation (Flynn et al., 1994). Flynn et al. (1995) found that top management affected all TQM practices, but the relationship between top management and core quality management practices were considered weak (Flynn et al., 1995; Ho et al., 1999). Also, top management focuses on continuous improvement, but did not relate to product design, process management and quality data and reporting (Ho et al., 1999). Moreover, leadership plays a major role in setting organisational strategic direction and developing new opportunities (Hossain and. Prybutok, 2014). Al-Khalili and Subari (2013) found no significant and positive relationship between leadership and process control and improvement. Also, Flynn et al. (1995) showed that SPC had an indirect relationship with top management support. Flynn et al. (1995) found that process flow management is a function of top management support. Furthermore, process flow can be encouraged by top management through providing rewards for process flow improvements instead of the use of shortterm output measures. Also Saljoughian et al. (2014) found that process improvement highly related to leadership. Al-Khalili and Subari (2013) showed that leadership had a significant and positive relationship with TQM tools and techniques/purchasing and TQM tools and techniques/ production, but it had no significant and positive relationship with TQM tools and techniques/sales and TQM tools and techniques/customer service. Top management encourages the purchasing department to use suitable tools to assess supplier quality levels. Also, top managements encourage their employees to use SPC by asking them to record key information about the process, and then top managements must act immediately on the information they received and encourage all managers and supervisors to do the same (Flynn et al., 1995). Kaynak (2003) found that leadership was directly related to product design and indirectly related to process management and quality data and reporting. Also, according to Flynn et al. (1995), product design had two determinants; supplier relationship and top management support, with a very strong direct and indirect relation with top management support through the mediation of the supplier relationship.

2.2.4 The relationships between supplier relationship and continuous improvement, SPC, process management, quality tools and techniques and product design The TQM approach is oriented towards quality to produce continuous improvement, this attention should be considered at all functions in the organisation, since the responsibility for quality is not limited to a single function or department as the whole process that creates services or products cuts across different functions (Forza and Filippini, 1998; Ho el al., 1999). TQM can be characterised by many aspects starting from dedication of resources in the design stage, forming of the inter-functional design team, selection of suppliers on the basis of quality to problem prevention (Flynn et al., 1994). According to Rahman and


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Bullock (2005), continuous improvement was significantly related to supplier relations and personnel training, but it had no significant relation with a customer focus. The results of Kaynak (2003) and Baird et al. (2011) revealed that quality data was positively related to supplier quality management and product or service design. Suppliers contribute to the product design process through their participation in product design team and providing input information about the capabilities of materials and parts (Flynn et al., 1995). Managing the input materials that are coming from suppliers could eliminate input variance, this increases the efficiency of SPC as the focus will be shifted from external variables to internal variables; such as machines and workforce (Carter et al., 1998; Baird et al., 2011). Gupta et al. (2016) stated that all quality matters, depends on manufacturing units own quality and on the quality and reliability of raw material and that on time delivery of the product can help the buyer to use the resources most effectively. Supplier certifications help in providing assertion about the quality of input materials and parts and conveying a manufacturers’ quality expectation to suppliers (Flynn et al., 1995). Trust and commitment between manufacturer and supplier help organisations to gain essential insights about satisfaction and their relationship depends on manufacturer satisfaction with supplier (Rindell et al., 2014). Also, providing information about purchasing materials and components can insure the quality of internal production and external customer needs resulted in better process management (Baird et al., 2011; Carter et al., 1998). Supplier relation is expected to be directly related to process management, this is because the input materials and parts are the main source of process variability (Flynn et al., 1995; Baird et al., 2011). Supplier quality management was directly and positively associated with product design and process management (Kaynak, 2003; Baird et al., 2011). Based on the literature review, three important issues were clearly observed: 1

no agreement was found among the researches on adequate theoretical model regarding soft and hard TQM practices

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there were differences in identifying and separating soft from hard practices.

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there were differences in the resulting linkages among soft and hard TQM practices.

Accordingly the following hypothesis was proposed: H1

There is a significant relationship between soft TQM practices and hard TQM practices in Jordanian manufacturing organisations.

The main hypothesis was divided into the following sub-hypotheses: H1a

There is a significant relationship between customer focus and continuous improvement, SPC, process management, quality tools and techniques and product design.

H1b

There is a significant relationship between education and training and continuous improvement, SPC, process management, quality tools and techniques and product design.

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H1c

There is a significant relationship between top management leadership and continuous improvement, SPC, process management, quality tools and techniques and product design.

H1d

There is a significant relationship between supplier relationship and continuous improvement, SPC, process management, quality tools and techniques, and product design.

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Research framework

This study makes a contribution in proposing a theoretical framework showing the network of the relationships between soft TQM practices and hard TQM practices. The soft TQM practices that were adopted included: customer focus, education and training, top management leadership, and supplier relationship. Whereas, the hard TQM practices that were adopted in the model included: continuous improvement, SPC, process management, quality tools and techniques and product design. This study examines the interactions among soft and hard TQM practices considering soft TQM practices as dependent and hard TQM practices as independent ones. The model of the framework is illustrated in Figure 1. Figure 1

The research model of the relationship between soft and hard TQM practices Soft-TQM Practices:

Hard-TQM Practices: • • • • •

Continuous improvement Statistical process control Process management Quality tools and techniques Product design

H1

• • • •

Customer focus Education and training Top management leadership Supplier relationship

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Methodology

4.1 Survey instrument This study used two methods for collecting data from respondents; mail questionnaire and personally administered questionnaire. All questionnaire measures were adopted from the study of Abdallah (2013), since this study measures were validated in Jordanian manufacturing organisations, except product design practice measures. They were adopted from Al-Khalili and Subari (2013) as their study has the same core objective of this study. Three quality management academics, two quality managers and three quality engineers were asked to review the questionnaire statements. Then, the questionnaire was pre-tested and modified before being sent to the respondents.


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The objective of this test was to confirm that the items were clearly understandable and unambiguous. The feedback from the respondents was favourable and used to produce a final version of the questionnaire. The final instrument has 54 statements measuring soft and hard TQM practices distributed as follows; six statements for customer focus, five statements for education and training, six statements for top management leadership, and seven statements for supplier relationship, five statements for continuous improvement, five statements for SPC, six statements for process management, eight statements for quality tools and techniques and six statements for product design. The five-point Likert scale was used for all questionnaire statements.

4.2 Study population In this study 170 ISO 9001-certified Jordanian manufacturing organisations were asked to join a questionnaire survey on four decision making areas: 1

quality management

2

production management

3

research and development management

4

supply chain management.

The unit of analysis consists of a respondent from management area who played an active role in decisions or enjoyed extensive decision making autonomy. The number of certified ISO 9001 manufacturing organisations was developed based on data collected from the main ISO 9001 consultant and donor bodies operating in Jordan during the research period. However, to achieve a fair level of representation, the sample spanned over a variety of industries covering; pharmaceutical industry and medical supply, hygienic paper industry, food and beverage industries, construction industry, plastic and rubber industries, wood and furniture industries, chemical industries and cosmetic preparations and engineering industry. Thus, reflecting a high degree of heterogeneity. The companies covered under this survey differed in size; large and medium size. The survey yielded valid responses from 40 Jordanian manufacturing organisations generating a response rate of (23.5%).

4.3 Operational definitions Tables 1 and 2 demonstrate the operational definitions of the research variables. Table 1

The operational definitions of hard TQM practices Measures of hard TQM practices

Measures of continuous improvement Your organisation continuously improves all aspects of business so that its performance is made a moving target which is difficult to attack. Your organisation is a dynamic entity, continually search for new room for more incremental improvement to better serve its customer.

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A.R. Saleh et al. The operational definitions of hard TQM practices (continued) Measures of hard TQM practices

Measures of SPC Your organisation designed its processes in a way that ensure achieving the desired specifications ‘foolproof’. Your organisation monitors their processes and reduces the variance related to process performance in the shop floor using SPC methods. Your organisation uses charts to determine whether their processes in control. Measures of process management Your organisation focuses on managing the process rather than people performing the process in order to minimise the errors. Your organisation focuses on improving its production process as this will improve their overall quality performance. Measures of quality tools and techniques Your organisation uses cause and effect diagram Your organisation uses scatter diagram Your organisation uses affinity diagram Your organisation uses relations diagram Your organisation uses force-field analysis Your organisation uses run chart Your organisation uses control charts Your organisation uses quality function deployment Measures of product design The design engineers in your organisation are required to have some shop floor experiences. The design engineers in your origination are required to have some marketing experiences. Your organisation is thoroughly considering customer requirements in new product design. Employees from various departments participate in new product development in your organisation. New product designs are thoroughly reviewed before production in your organisation. Cost is emphasised in the product design process in your organisation. Table 2

The operational definitions of soft TQM practices Measures of soft TQM practices

Measures of customer focus Your organisation depends on customers to identify their wants and needs. Your organisation considers customer satisfaction is essential to long term performance. Your organisation satisfies or exceeds the requirements and expectations of the customers. Measures of education and training Your organisation provides training and education on quality management methods and tools for most employees. Your organisation allocates the required resources for training and education activities. Your organisation considers their employees as a valuable, long term resources worthy of receiving education and training throughout their career.

Linking soft and hard total quality management practices Table 2

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The operational definitions of soft TQM practices (continued) Measures of soft TQM practices

Measures of top management leadership Your organisation’s top management involved in developing a strategy focuses on quality improvement. Your organisation’s top management is personally involved in quality improvement projects. Your organisation’s top management encourages involvement of employees in improving the quality of products and processes. Measures of supplier relationship Your organisation establishes long term relationships with suppliers. Your organisation encourages the participation of suppliers in a new product development process. Your organisation selects suppliers based on quality. Your organisation actively engages suppliers in its quality improvement efforts.

4.4 Checking the outliers Outliers should be detected and excluded before starting the analysis journey, as outliers harm the results and mislead the researcher. The method of (5%) trimmed mean was used to check the outliers as shown in Table 3. It was clear from (5%) trimmed mean values that no outliers were detected (no extreme differences between original mean and 5% values trimmed mean were found). Table 3

The values of original mean and 5% trimmed mean

Variables Customer focus (CF) Education and training (ET) Top management leadership (TML) Supplier relationship (SR) All soft TQM practices Continuous improvement (CI) SPC Process management (PM) Quality tools and techniques (QTT) Product design (PD) All hard TQM practices

Original mean

5% Trimmed mean

3.516 3.915 4.188 3.975 3.898 4.220 3.795 3.017 3.406 3.879 3.663

3.519 3.950 4.190 3.988 3.892 4.244 3.811 3.009 3.406 3.903 3.676

4.5 Assessing normality According to Field (2007), the data is said to be normal if the absolute value of Z-score is greater than (1.96) at (P < 0.05). Table 4 shows that none of Z-score values of the research variables are found beyond the critical limit except the value of Z-score for ‘education and training’ variable. It deviates by 0.005 from 1.96 which is not considered a significant deviation from the criteria. In sum the data is not deviated extremely from the normal distribution.

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Table 4

The values of skewness and kurtosis and Z-scores Standard error

Skewness

Standard error

CF

0.144

0.374

0.385

–0.790

0.733

–1.078

ET

–0.735

0.374

–1.965

–0.582

0.733

–0.794

Variables

ZSkewness

Kurtosis

ZKurtosis

TML

–0.173

0.374

–0.462

–0.890

0.733

–1.214

SR

–0.311

0.374

–0.831

–0.747

0.733

–1.019 –1.510

All soft TQM practices

0.017

0.374

0.045

–1.107

0.733

CI

–0.482

0.374

–1.289

–0.212

0.733

–0.289

SPC

–0.302

0.374

–0.807

–0.580

0.733

–0.791

PM

0.058

0.374

0.424

0.648

0.733

0.578

QTT

–0.048

0.374

–0.128

–0.614

0.733

–0.838

PD

–0.612

0.374

–1.64

–0.085

0.733

–0.116

All hard TQM practices

–0.224

0.374

–0.599

–0.233

0.733

–0.318

4.6 Validity of the survey instrument 4.6.1 Content validity As illustrated in the previous section, the research instrument statements were adopted from previous studies of Abdallah (2013) and Al-Khalili and Subari (2013) and reviewed by managers, academics and engineers so it is considered to have content validity.

4.6.2 Construct validity To measure the extent to which the statements represent all facets of the instrument, principal component factor analysis (PCFA) was used. However, this test cannot be done unless the values of Kaiser-Meyer-Olkin (KMO) are above 0.5 and the significant (sig.) values of Bartlett’s test are 0 (Kaiser, 1974). Table 5 shows that the two previously mentioned conditions are met so the next step is to evaluate PCFA. Table 5

The results of KMO and Bartlett’s tests

Variables

KMO test

Bartlett’s test Sig.

CF

0.652

0.000

ET

0.763

0.000

TML

0.721

0.000

SR

0.675

0.000

CI

0.762

0.000

SPC

0.824

0.000

PM

0.623

0.000

QTT

0.771

0.000

PD

0.657

0.000

All variables

0.735

0.000


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As illustrated in Table 6, factor loading values of the instrument are distributed closer to each other in the same variable, thus the construct validity is accepted.

4.7 Reliability of the survey instrument Regarding reliability, the criteria of Cronbach’s alpha coefficient (α ≥ 0.6) was used to check the construct reliability (Sekaran and Bougie, 2010). Cronbach’s alpha coefficient for the whole instrument consisted of nine variables was 0.894, and none of Cronbach’s alpha coefficients for the measured variables exceed the criteria, so the reliability of the instrument was supported. SPC was found to be highly reliable (five statements; α = 0.874), while product design has the least reliability among other variables (six statements; α = 0.700) (Table 6). Table 6 Construct CF1 CF2 CF3 CF4 CF5 CF6 ET1 ET2 ET3 ET4 ET5 TML1 TML2 TML3 TML4 TML5 TML6 SR1 SR2 SR3 SR4 SR5 SR6 SR7 CI1 CI2 CI3 CI4 CI5

The results of PCFA and Cronbach’s alpha coefficient Factor loading

Cronbach’s alpha coefficient

0.886 0.930 0.731 0.935 0.783 0.738 0.779 0.855 0.766 0.846 0.775 0.906 0.841 0.906 0.707 0.851 0.858 0.805 0.831 0.878 0.775 0.822 0.686 0.763 0.874 0.873 0.861 0.913 0.773

0.710

0.844

0.788

0.812

0.854

16

A.R. Saleh et al.

Table 6

The results of PCFA and Cronbach’s alpha coefficient (continued) Factor loading

Cronbach’s alpha coefficient

SPC1

Construct

0.851

0.874

SPC2

0.852

SPC3

0.907

SPC4

0.909

SPC5

0.895

PM1

0.804

PM2

0.875

PM3

0.667

PM4

0.797

PM5

0.885

PM6

0.908

QTT1

0.897

QTT2

0.850

QTT3

0.879

QTT4

0.759

QTT5

0.827

QTT6

0.837

QTT7

0.818

QTT8

0.800

PD1

0.841

PD2

0.849

PD3

0.790

PD4

0.902

PD5

0.839

PD6

0.900

5

0.708

0.844

0.700

Results

5.1 Descriptive statistics The summary of the studied variables descriptive statistics is shown in Table 7. All variables mean values are greater than 3, and standard deviation (SD) less than 1. For TQM variables, continuous improvement is ranked first with a mean value of (m = 4.220) and standard deviation of (SD = 0.551). While process management is ranked last with a mean value of (m = 3.017) and standard deviation of (SD = 0.573). This result indicates that among the nine TQM variables top management leadership and continuous improvement are favoured by manufacturing organisations.

Linking soft and hard total quality management practices Table 7

17

The descriptive statistics for TQM practices for sample size (40) M

SD

CF

Variables

3.517

0.606

ET

3.915

0.720

TML

4.183

0.500

SR

3.975

0.585

All soft TQM practices

3.988

0.386

CI

4.220

0.551

SPC

3.795

0.745

PM

3.017

0.573

QTT

3.406

0.709

PD

3.879

0.496

All hard TQM practices

3.663

0.377

5.2 Answering the research question As illustrated in Table 8, the Karl Pearson correlation coefficient showed that: Customer focus has weak, positive, but not significant association with continuous improvement (r = 0.045, p > 0.05), while it has moderate, negative and significant correlation with SPC (r = –0.360, p < 0.05). Whereas the correlations between customer focus and process management, quality tools and techniques and product design are weak, negative and not significant (r = –0.249, p > 0.05), (r = –0.262, p > 0.05) and (r = – 0.029, p > 0.5) respectively. Education and training practice has a strong, positive and significant correlations with continuous improvement and SPC (r = 0.602, p < 0.01) and (r = 0.607, p < 0.01) respectively. On the other hand, it has weak, positive and not significant correlations with process management and quality tools and techniques (r = 0.107, p > 0.05) and (r = 0.263, p > 0.05) respectively. Finally, it has a moderate, positive and not significant association with product design (r = 0.305, p > 0.05). Top management leadership has a moderate, positive and significant association with continuous improvement (r = 0.418, p < 0.01). But it has a strong, positive and significant association with SPC (r = 0.716, p < 0.01). While it has a weak, positive and not significant correlations with process management and quality tools and techniques (r = 0.004, p > 0.05) and (r = 0.263, p > 0.05) respectively. Finally, it has a moderate positive and significant correlation with product design (r = 0.438, p < 0.01). Supplier relationship has a moderate, positive and significant correlation with continuous improvement, SPC and quality tools and techniques (r = 0.477, p < 0.01), (r = 0.457, p < 0.01) and (r = 0.364, p < 0.05) respectively. Whereas, it has a weak, positive and not significant association with process management (r = 0.016, p > 0.05). Finally, it has a strong, positive and significant correlation with product design (r = 0.530, p < 0.01). It is also noticed that all soft TQM practices as one variable has a strong positive and significant association with all hard TQM practices as one variable (r = 0.600, p < 0.01).

–0.029 0.861 0.232 0.149 –0.311 0.051

Sig. (two -tailed) Pearson correlation Sig. (two -tailed) Pearson correlation Sig. (two -tailed)

0.102

Sig. (two -tailed) Pearson correlation

–0.262

0.122

Pearson correlation

–0.249

Sig. (two -tailed)

0.023


–0.360*

0.782


0.045

0.463

Pearson correlation

–0.119

Sig. (two -tailed)

0.503

Pearson correlation

–0.109

Sig. (two -tailed)

0.292

Pearson correlation

Sig. (two -tailed)

0.000

0.627**

0.000

0.786**

0.055

0.305

0.102

0.263

0.511

0.107

0.000

0.607**

0.000

0.602**

0.007

0.417**

0.000

0.704**

1

ET

Notes: *Correlation is significant at the 0.05 level (two-tailed) **Correlation is significant at the 0.01 level (two-tailed)

Hard TQM

Soft TQM

PD

QTT

PM

SPC

CI

SR

TML

–0.171

Pearson correlation

Sig. (two-tailed)

1

0.000

0.620**

0.000

0.831**

0.005

0.438**

0.101

0.263

0.981

0.004

0.000

0.716**

0.007

0.418**

0.000

0.583**

1

TML

0.000

0.601**

0.000

0.717**

0.000

0.530**

0.021

0.364*

0.923

0.016

0.003

0.457**

0.002

0.477**

1

SR

0.000

0.588**

0.000

0.615**

0.032

0.341*

0.079

0.281

0.834

0.034

0.157

0.228

1

CI

0.000

0.675**

0.000

0.548**

0.044

0.320*

0.028

0.349*

0.972

–0.006

1

SPC

0.027

0.349*

0.804

–0.041

0.913

–0.018

0.493

0.112

1

PM

0.000

0.751**

0.131

0.243

0.003

0.460**

1

QTT

0.000

0.657**

0.002

0.474**

1

PD

0.000

0.600**

1

1

Soft TQM Hard TQM

Table 8

ET

CI

CI

Pearson correlation

Variables

18 A.R. Saleh et al.

Pearson correlation coefficient of the relationship between soft TQM practices and hard TQM practices


19

5.3 Hypotheses testing To test the main hypothesis, simple linear regression was used for the mean values of all soft TQM practices, and the mean values of all hard TQM practices then simple linear regression was used to test the sub-hypotheses.

5.3.1 Hypothesis1: there is a significant relationship between soft TQM practices and hard TQM practices in Jordanian manufacturing organisations Investigating the relationship of all TQM practices as one variable against all hard TQM practices as one variable using simple linear regression is shown in Table 9. The calculated t-value is bigger than the tabulated t-value of the relationship between soft TQM practices and hard TQM practices at significance level (α = 0.05) (4.624 > 2.0244). Also, the significant value is smaller than the significance level (sig. = 0.000 < 0.05). Thus, the H1 is accepted for the relationship between soft TQM practices and hard TQM practices. It is clear from the Table 9 that hard TQM practices explained (36%) of the variance in the soft TQM practices (R2 = 0.36).

5.3.2 Hypothesis1a: there is a significant relationship between customer focus and continuous improvement, SPC, process management, quality tools and techniques and product design Examining the sub hypothesis H1a is illustrated in Table 10. The calculated t-values are smaller than tabulated t-values of the relationships between customer focus and continuous improvement, process management, quality tools and techniques and product design at significance level (α = 0.05) (0.287 < 2.0244), (1.584 < 2.0244), (1.675 < 2.0244) and (0.177 < 2.0244) respectively. Also, the significant values for the four above mentioned variables are bigger than the significance level (0.782 > 0.05), (0.122 > 0.05), (0.102 > 0.05) and (0.861 > 0.05) respectively. Thus, the hypothesis (H1a) is rejected for the relationships between customer focus and continuous improvement, process management, quality tools and techniques and product design. On the other hand, the calculated t-value is bigger than the tabulated t-value for SPC at significance level (α = 0.05) (2.375 > 2.0244) and the significant value is smaller than the significance level (sig = 0.023 < 0.05). So, the hypothesis H1a is accepted for the relationship between SPC and customer focus. In addition, it can be noticed that SPC explained (12.9%) of the variance in the customer focus (R2 = 0.129) which is the greatest value compared with the other (R2) values for the remaining variables.

2.088 3.711 5.799

Regression Residual Total

Sum of squares

Note: Dependent variable: soft TQM practices

Hard TQM practices

Statistic

39

38

1

Degree of freedom 0.600

R 0.360

R2 1.649

β constant 0.614

β 4.624

\t\ calculated

2.0244

t tabulated

0.000

Sig.

Table 9

Independent variable


The results of simple linear regression analysis for testing H1

Note: Dependent variable: CF

PD

QTT

PM

SPC

CI

14.310 14.322

Residual Total

14.322

Total 0.012

13.337

Residual

Regression

0.985

14.322

Total Regression

0.887 13.435

Residual

14.322

Total Regression

1.852 12.471

Residual

14.322

Total Regression

0.029 14.293

Residual

Sum of squares

Regression

Statistic

39

38

1

39

38

1

39

38

1

39

38

1

39

38

1

Degree of freedom

0.029

0.262

0.249

0.360

0.045

R

0.001

0.069

0.062

0.129

0.002

R2

3.652

4.280

4.310

4.627

3.307

β constant

–0.035

–0.224

–0.263

–0.293

0.050

β

0.177

1.675

1.584

2.375

0.278

\t\ calculated

2.0244

2.0244

2.0244

2.0244

2.0244

t tabulated

0.861

0.102

0.122

0.023

0.782

Sig.

Table 10


Linking soft and hard total quality management practices 21

The results of simple linear regression analysis for testing H1a

22

A.R. Saleh et al.

5.3.3 Hypothesis1b: there is a significant relationship between education and training and continuous improvement, SPC, process management, quality tools and techniques and product design Testing the sub hypothesis H1b is illustrated in Table 11. The calculated t-values are smaller than tabulated t-values of the relationships between education and training and process management, quality tools and techniques and product design at significance level (α = 0.05) (0.663 < 2.0244), (1.678 < 2.0244) and (1.976 < 2.0244) respectively. Also, the significant values for process management, quality tools and techniques and product design are bigger than the significance level (0.511 > 0.05), (0.102 > 0.05) and (0.055 > 0.05), respectively. Accordingly, the hypothesis H1b is rejected for the relationship between education and training and process management, quality tools and techniques and product design. For the other two variables; continuous improvement and SPC, the calculated t-values are bigger than tabulated t-values at significance level (α = 0.05) (4.645 > 2.0244) and (4.710 > 2.0244), respectively. Also, the significant values are smaller than the significance level (sig = 0.000 < 0.05) and (sig = 0.000 < 0.05) respectively. Thus, the hypothesis H1b is supported for the relationship between education and training and continuous improvement and SPC. Moreover, as shown in Table 11, SPC explained (36.9%) of the variance in the education and training (R2 = 0.369) which is the greatest value compared with the remaining variables, followed by continuous improvement which explained (36.2%) of the variance, product design (9.3%), quality tools and techniques (6.9%) and process management (1.1%) respectively.

5.3.4 Hypothesis1c: there is a significant relationship between top management leadership and continuous improvement, SPC, process management, quality tools and techniques and product design Exploring the sub hypothesis H1c is illustrated in Table 12, the calculated t-values are bigger than tabulated t-values of the relationships between top management leadership and continuous improvement, SPC and product design at significance level (α = 0.05), (2.832 > 2.0244), (6.316 > 2.0244) and (3.007 > 2.0244) respectively. Also, the significant values for the three above mentioned variables are smaller than the significance level (sig. = 0.007 < 0.05), (sig. = 0.000 < 0.05) and (sig. = 0.005 < 0.05) respectively. Thus the hypothesis H1c is accepted for the relationships between top management leadership and continuous improvement, SPC and product design. While the calculated t-values are smaller than tabulated t-values of the relationships between top management leadership and process management and quality tool and techniques at significance level (α = 0.05) (0.024 < 2.0244) and (1.683 < 2.0244) respectively. Also, the significant values are bigger than the significance level (sig. = 0.981 > 0.05) and (sig. = 0.101 > 0.05), respectively. So, the hypothesis H1c is rejected for the relationships between top management leadership and process management and quality tool and techniques. Regarding the explained variance, SPC explained (51.2%) of the variance in the top management leadership (R2 = 0.512), followed by product design (19.2%), continuous improvement (17.4%), quality tools and techniques (6.9%) and process management (0.002%) respectively.

18.346 20.231

Residual Total

20.231

Total 1.885

18.836

Residual

Regression

1.395

20.231

Total Regression

0.232 19.999

Residual

20.231

Total Regression

7.457 12.774

Residual

20.231

Total Regression

7.327 12.904

Residual

Sum of squares

Regression

Note: Dependent variable: ET

PD

QTT

PM

SPC

CI

Statistic

39

38

1

39

38

1

39

38

1

39

38

1

39

38

1

Degree of freedom

0.305

0.263

0.107

0.607

0.602

R

0.093

0.069

0.011

0.369

0.362

R2

2.197

3.007

3.510

1.687

0.593

β constant

0.443

0.267

0.134

0.587

0.787

β

1.976

1.678

0.663

4.710

4.645

\t\ calculated

2.0244

2.0244

2.0244

2.0244

2.0244

t tabulated

0.055

0.102

0.511

0.000

0.000

Sig.

Table 11


Linking soft and hard total quality management practices 23

The results of simple linear regression analysis for testing H1b

1.877 7.890 9.767

Residual Total

9.767

Total Regression

9.089

Residual

9.767

Total 0.678

9.767

Regression

0.000

9.767

Total

Residual

4.765

Regression

5.002

9.767

Total

Residual

8.064

Regression

1.702

Residual

Sum of squares

Regression

Note: Dependent variable: TML

PD

QTT

PM

SPC

CI

Statistic

39

38

1

39

38

1

39

38

1

39

38

1

39

38

1

Degree of freedom

0.438

0.263

0.004

0.716

0.418

R

0.192

0.069

0.00002

0.512

0.174

R2

2.469

3.550

4.173

2.359

2.582

β constant

0.442

0.186

0.003

0.481

0.379

β

3.007

1.683

0.024

6.316

2.832

\t\ calculated

2.0244

2.0244

2.0244

2.0244

2.0244

t tabulated

0.005

0.101

0.981

0.000

0.007

Sig.

Table 12



The results of simple linear regression analysis for testing H1c


25

5.3.5 Hypothesis1d: there is a significant relationship between supplier relationship and continuous improvement, SPC, process management, quality tools and techniques, and product design Examining the sub hypothesis H1d is illustrated in Table 13. The calculated t-values are bigger than tabulated t-values of the relationships between supplier relationship and continuous improvement, SPC, quality tools and techniques and product design at significance level (α = 0.05) (3.346 > 2.0244), (3.168 > 2.0244) (2.409 > 2.0244) and (3.850 > 2.0244) respectively. Also, the significant values are smaller than the significance level (sig. = 0.002 < 0.05), (sig. = 0.003 < 0.05), (sig. = 0.021 < 0.05) and (sig. = 0.000 < 0.05) respectively. Thus, the hypothesis H1d is accepted for the relationships between supplier relationship and continuous improvement, SPC, quality tools and techniques and product design. While, the calculated t-value is smaller than the tabulated t-value of the relationship between supplier relationship and process management at significance level (α = 0.05) (0.098 < 2.0244) and the significant value is bigger than the significance level (sig. = 0.923 > 0.05). Accordingly, the hypothesis H1d is rejected for the relationship between supplier relationship and process management. SPC explained the most variance in the three previous soft variables, but different result is found here. Product design explained (28.1%) of the variance in the supplier relationship (R2 = 0.281) which is the greatest value of R2, followed by continuous improvement (22.8%), SPC (20.9%), quality tools and techniques (13.2%) and process management (0.03%) respectively. In sum, the results of regression and correlation can be summarised in the following matrix (Figure 2). Figure 2

Soft and hard TQM practices significance/correlation strength matrix CF

ET CI and SPC

Correlation

Strong Moderate

TML

SPC

PD CI, PM, QTT and PD

Weak

Significant

Not significant

SPC

PD

CI and PD

CI, SPC and QTT

PM and QTT Significant

Not significant

SR

PM and QTT Significant

Relation significance

Not significant

PM

Significant

Not significant

9.599 13.342

Residual Total

13.342

Total 3.744

11.575

Residual

Regression

1.767

13.342

Total Regression

0.003 13.339

Residual

13.342

Total Regression

2.787 10.555

Residual

13.342

Total Regression

3.036 10.306

Residual

Sum of squares

Regression

Note: Dependent variable: SR

PD

QTT

PM

SPC

CI

Statistic

39

38

1

39

38

1

39

38

1

39

38

1

39

38

1

Degree of freedom

0.530

0.364

0.016

0.457

0.477

R

0.281

0.132

0.0003

0.209

0.228

R2

1.554

2.953

3.926

2.613

1.837

β constant

0.624

0.300

0.016

0.359

0.507

β

3.850

2.409

0.098

3.168

3.346

\t\ calculated

2.0244

2.0244

2.0244

2.0244

2.0244

t tabulated

0.000

0.021

0.923

0.003

0.002

Sig.

Table 13



The results of simple linear regression analysis for testing H0-1d


6

27

Discussion

The results showed that there were no significant relationships between customer focus and continuous improvement, process management, quality tools and techniques and product design, and it had only a unique significant relationship with SPC. These results can be attributed to the presence of the reversed question or negatively keyed question, which confound most respondents in differentiating between using engineers’ specifications or relying on customer needs and wants. The respondents deviated from the research operational definition of customer focus ‘your organisation depends on customers to identify their wants and needs’, and thereby customer focus connected with the engineering design of the process to achieve the desired specification ‘foolproof’ and using SPC in the shop floor to reduce variance and control the process. The results also showed that there were no significant relationships between education and training and process management, quality tools and techniques and product design, and it had significant relationships with continuous improvement and SPC. These results can be linked with the fact that people initiate continuous improvement. Education and training on quality management methods and tools provides employees with up to date skills that are essential for continuous improvement, creates a learning organisation that can facilitate the adoption of change, or being the first mover organisation that better serves its customers. Moreover, education and training can facilitate the use of SPC by providing the required training and knowledge. The relationship between education and training and SPC was supported by Ho et al. (1999) and Kaynak (2003). Regarding top management leadership, the results illustrated that there were no significant relationships between top management leadership and process management and quality tools and techniques, while top management leadership had significant relationships with continuous improvement, SPC and product design. These results can be explained by the fact that this research considered top management responsible for developing strategies that focus on quality improvement, themselves involved in quality improvement projects and encourages employees’ involvement in improvement activities, leaving the TQM initiatives in the process and using of quality tools and techniques to the middle and lower level managers. These results were supported by Flynn et al. (1995) and Ho et al. (1999). Top management encourages employees to use SPC in order to have timely information regarding the problems to prevent their recurrence and to monitor processes. Also, top management frequently meets with customers to understand their wants and needs to reflect this data in new product development, providing design engineers the desired information from production and marketing departments and encourages employees’ involvement in new product design from various departments. The relationship between SPC and top management leadership was supported by Flynn et al. (1995), while the relationship between product design and top management leadership was supported by Kaynak (2003). Finally, the results supported the notion that, supplier relationship had significant relationships with continuous improvement, SPC, quality tools and techniques and product design, while it had no significant relation with process management. Finding no association between supplier relationship and process management was really confusing result, that is inconsistent with Flynn et al. (1995) and Baird et al. (2011). This result can be justified by the presence of two reversed questions. The respondents deviated from the operational definition of the process management ‘the process rather than the people who

28

A.R. Saleh et al.

perform the process is the source of errors’ and they considered most problems result from the lack of motivation. On the other hand, it was clear that, establishing long term relationship with suppliers can facilitate the exchange of information that are essential for continuous improvement and monitoring process through reducing the variation in the input materials that thereby shift the focus from external variables to the process variation. Also, involving suppliers in new product design can facilitate the product design process, by providing them with input information about the required materials and parts that enhance a long term relationship. The relationship between product design and supplier relationship was supported by Flynn et al. (1995) and Baird et al. (2011). In sum, all soft TQM practices showed strong, positive and significant relationship with all hard TQM practices and hard practices as one variable explained 36% of the variance in all soft practices as one variable.

7

Conclusions and practical implications

A review of the literature implies a gab regarding the relationship between soft and hard TQM practices in manufacturing organisations, more specifically the interconnections of soft and hard TQM practices. Based on this gap, Al-Khalili and Subari (2013) encouraged other researcher to study the interconnections of soft and hard TQM practices in developing countries. This motivated the authors to conduct this research. In doing this research, this study can contribute to prior literature. It can help in better understanding of the specific issues that are manifest in managing soft and hard TQM practices in manufacturing organisations. Setting and maintaining TQM practices can be daunting if an organisation tries to embark on any successful model of another context, skipping the need to test the validity of their own success model. For this reason this study provides a genuine and rational dialogue to implement TQM for any Jordanian organisation that intents to do so. This study can be seen as a compendium resource for many reasons; it provided an overview for TQM history, and TQM model in different contexts which may consider as a good starting point for any manager or individual interested in TQM scope or lake background, it used the most frequent soft and hard TQM practices to study their relationships. Valuable information can be gleaned from this study; it showed that soft and hard TQM practices had a significant relationship, and hard TQM practices explain 36% of soft practices which indicated that all hard TQM practices have a good degree of relatedness with soft TQM practices. Add to this, descriptive statistic results revealed that top management leadership was considered as the most soft TQM practices that dominate other practices in manufacturing organisations which is consistent with the descriptive statistic results of Sweis et al. (2016) study and ISO 9001 core practices. Taking into consideration that Sweis et al. (2016) study targeted one of the service organisations in Jordan, may lead to an important conclusion that both service and manufacturing organisations in Jordan consider top management leadership as the dominant TQM practice. This may afford an opportunity to initiate TQM easily; as initiating TQM will inevitably provoke change in the way people think, work and live. So building a profound quality culture from the top is a precondition of inclusion of such practices with the aim of making it truly inclusion.


29

Also the matrix in Figure 2 provides evidence from the perspective of manufacturing organisations that the success of all soft TQM practices significantly related to SPC practice. Meanwhile, process management has no significant relationship with all soft TQM practices which indicated that other factors may mediate the relationship between process management and soft TQM practices. Finally, product design affects supplier relationship significantly with strong correlation. This may take a strategic side, to encourage managers in manufacturing organisation to consider the necessity of SPC practice to implement customer focus, education and training, top management leadership and supplier relationship successfully. Finally, dividing TQM for two categories and screening the relationships between the categories can build a robust understanding of TQM approach.

8

Limitations and future research recommendations

Some limitations in this study may affect the study findings generalisability and should be carefully considered. A small study sample of the Jordanian manufacturing organisations diminishes the response rate and prevents the authors to use structural equation modelling for testing the relationships. Add to this, the study based on subject evidence solicited from managers in manufacturing organisations. Studying direct and indirect relationship using different analytical methods with larger study sample and comparing Jordan case results with other countries results to build comprehensive soft and hard TQM model will be the future lines for this study.

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Appendix Summary of soft and hard TQM models of published empirical studies Study

TQM practices

Study background

(1) Studies that focused on soft and hard TQM practices and both quality performance and competitive advantage.

Flynn et al. (1995)

Soft TQM

Hard TQM practices

Customer relationship, supplier relationship, work attitudes, workforce management, and top management support.

Process flow management, product design process, and statistical control/ feedback.

Flynn et al. (1995) studied the direct and indirect effect of infrastructure and core quality management practices on quality performance and competitive advantage. They carried out their investigation on 45 world class manufacturers in the US.

(2) Studies that focused on soft and hard TQM practices and both quality performance and innovation. Prajogo and Sohal (2004)

Leadership and people management

Customer focus, process management, strategic planning and information and analysis.

Prajogo and Sohal (2004) used Samson and Terziovski (1999) framework to investigate this relationship. Prajogo and Sohal (2004) used a sample of ISO 9000-certified Australian organisations included manufacturing and non-manufacturing sectors, while Feng et al. (2006) extended the study of Prajogo and Sohal (2004) to include organisations from Australia and Singapore certified with ISO 9000 or engaged in a quality program, with the purpose to compare the experience of TQM in both countries.

Small group problem solving, employee suggestion, and task related training of employees.

Process management, and quality information.

Zeng et al. (2015) used data collected from 283 manufacturing plants in eight countries, which are: US, Japan, Italy, Sweden, Austria, Korea, Germany and Finland.

Feng et al. (2006) Zeng et al. (2015)

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Summary of soft and hard TQM models of published empirical studies (continued) Study

TQM practices

Study background

(3) Studies that focused on soft and hard TQM practices and quality performance. Dow et al. (1999)

Workforce commitment, shared vision, customer focus, use of teams and personnel training.

Cooperative supplier relations, use of benchmarking, advanced manufacturing systems and use of JIT principles.

Dow et al. (1999) in their study that was conducted using a mail survey on manufacturing sites that registered with (Australian Bureau of Statistics and Statistics New Zealand in 1993) investigated the relationship between quality management practices and product quality.

Ho et al. (1999)

Role of top management, the role of the quality department, training, and employee relations

Product design, process management, quality data and reporting and supplier quality management.

Using a sample of 25 electronic manufacturing organisations in Hong Kong, they investigated the relationship between core and infrastructure TQM practices, quality performance and customer satisfaction.

Ho et al. (2001)

Role of top management, the role of quality department, employee relations and training.

Product design, process management, quality data and reporting and supplier quality management

They used 25 electronics organisations in Hong Kong to investigate the effect of TQM practices on quality performance using various approaches.

Kaynak (2003)

Top management leadership, training and employee relations.

Quality data and reporting, supplier quality management, product/service design and process management

She used a large sample of 214 US organisations that implemented TQM and just-in-time purchasing (JITP) to study the relationship between TQM practices and quality, inventory management, financial and market performance.

Zu (2009)

Top management support, customer relationship, supplier relationship and workforce management.

Quality information, product/service design and process management.

She adopted Flynn et al. (1995) framework to study the direct and indirect effect of core and infrastructure quality management practices on quality performance. Zu (2009) study was conducted on 226 manufacturing plants in the USA.

Wu (2015)

Top management support, training, and teamwork.

Internal quality practices and external quality practices.

This study used a sample of 397 manufacturing organisations in China to empirically test the path from quality culture to infrastructure practices, core practices, and finally to quality performance using structural equation modelling.


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TQM practices

Study background

(4) Studies that focused on soft and hard TQM practices and organisational performance Rahman and Workforce Bullock (2005) commitment, shared vision, customer focus, use of teams, personnel training, and cooperative supplier relation.

Computer-based technologies, JIT principle, technology utilisation, and continuous improvement enablers.

They investigated the direct and indirect relationship between soft and hard TQM practices and organisational performance on 261 Australian manufacturing sites.

Gadenne and Sharma (2009)

Top management philosophy and supplier support, employee and customer involvement, and employee training.

Benchmarking and quality measurement, continuous improvement, and efficiency improvement.

Their study was carried out on Australian small and medium size enterprise (SMEs) from manufacturing, service and construction industries that adopted ISO 9000 or TQM system or both.

Garcia (2011)

Employee involvement, employee commitment, customer focus, top management support and continuous improvement.

Quality control, quality improvement, quality assurance, technology utilisation and planning for quality.

He studied the effect of soft TQM practices and hard TQM practices on organisational performance using a sample of different countries included: Philippines, Singapore, Indonesia, and the US.

Abdullah and Tari Guill (2012)

Management commitment, customer focus, employee involvement, training and education, reward and recognition and supplier relationship.

Feedback, interfunctional design, new product quality, process control and process management.

They used a wide range of quality management practices to study the direct and indirect influence of soft and hard quality management practices on organisational performance. Their study was carried on electrical and electronic manufacturing organisations in West Malaysia.

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TQM practices

Study background

(5) Studies that focused on soft and hard TQM practices and organisational outcomes, included: quality results, business results and quality management benefits. Fotopoulos and Top management Psomas (2009) commitment, strategic quality planning, employee involvement, supplier management, customer focus, process orientation, continuous improvement, facts-based decision making, and human resource development.

Quality tools and techniques included: cause and effect diagram, scatter diagram, affinity diagram, relations diagram, forcefield analysis, run chart, control charts, quality function deployment, and failure mode and effect analysis

They investigated the relationship between soft and hard TQM practices and quality results on 370 ISO 9001:2000-certiﬁed Greek companies (manufacturing, service and commercial) using questionnaire survey.

Calvo-Mora et al. (2014)

Management and human resources.

Process management and strategic management of partnerships and resources.

They studied the relationship between soft and hard TQM practices and key business results. They identified the soft and hard element of the European Foundation for Quality Management (EFQM) model. Their analysis was carried out in 116 private Spanish firms including both SMEs and large firms.

Psomas et al. (2014)

Continuous improvement, top management commitment, customer focus, human resource development, factbased decision making, strategic quality planning, process focus, employee involvement and supplier involvement.

Quality tools/techniques included: run chart, relations diagram, quality function deployment, failure mode and effect analysis, stem and leaf diagram, control charts, scatter diagram, cause and effect diagram and benchmarking.

They conducted an exploratory study to examine the direct and indirect impact of soft TQM practices and hard TQM practices on the quality management benefits using a sample of ISO 9001-certified Greek food companies.


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TQM practices

Study background

(6) Studies that focused on soft and hard TQM practices and organisational learning. Sisnuhadi (2014)

Customer focus, leadership, involvement of people, continual improvement and mutually beneficial supplier relationship.

Process approach, systems approach to management, and factual approach to decision-making.

He discussed the relationship between soft and hard TQM practices and organisational learning. He used a sample of 217 ISO 9001-certified Indonesian manufacturing organisations.

(7) Studies that focused on soft and hard TQM practices and TPM. Abdallah (2013)

Considered customer focus, training, top management leadership, workforce management and supplier relationship.

Continuous improvement, information feedback, SPC, process management and tools and techniques

He studied the influence of soft and hard TQM practices on TPM using a sample of 119 private manufacturing organisations in Jordan.

(8) Studies that focused on the interrelationships between soft and hard TQM practices. Al-Khalili and Subari (2013)

Leadership, vision and plan statement, evaluation, employee participation, recognition and reward, education and training and customer focus.

Supplier quality management, process control and improvement, product design, quality system improvement, and TQM tools and techniques usage in case of purchasing/ production/sales/c ustomer service.

They studied the interrelatedness between the binary dimensions of TQM practices their study was conducted using a sample of 79 ISO 9000-certified Malaysian manufacturing companies.

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TQM practices

Study background

(9) Study that focused on the adoption and implementation of TQM Chin et al. (2002)

Organising included: strategic planning, leadership, education and training and top management commitment. Culture and people included: existing organisational culture, culture change, employee involvement and human resource development.

Systems and techniques included: tools and techniques, quality system, process analysis and improvement and supplier chain management. Measurement and feedback included: internal performance measurement, external performance measurement, communication and recognition and rewards.

Their study was conducted on state-owned enterprises (SOEs) and foreign joint ventures (FJVs) in China with particular reference to the Shanghai manufacturing industries.