Providing a Framework for Performance Evaluation

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1. Introduction

In the present era of globalization and competitive environment, quality plays a key role in the organization’s success and survival. Recent studies showed that assuring quality through controlling the tolerance levels is no more applicable. Rather, the organization is emphasising on changing the mind set of the people from “errors are inevitable” to “doing the things right the first time and every time.” Therefore, in order to compete globally, the organizations must embrace total quality management concept and its practices and incorporate them into all of their activities effectively [1]. Total quality management is both a philosophy as well as a set of guiding principles and practices that addresses continuous improvement in quality and customer satisfaction through management of quality [2].

The past two decades has witnessed a widespread acceptance of total quality management as a means of gaining and maintaining competitive advantage in the global market. Total quality management now has become a worldwide topic in the twenty-first century. From the last two decades, it has also been observed that total quality management has become a way of life in production and services sector. Services sector accounts for more than two-third’s of total gross domestic product (GDP) and work force in developed countries such as the USA, UK, Germany, Canada, and Australia; with a rapid growth rate [3], total quality management is widely used in different production and services organizations, namely, information technology, hospitality, healthcare, education, banking, and recreation facilities to improve customer satisfaction and still been an ongoing effort. These measures have met with considerable success in them. The strength of total quality management implementation in production and services organization lies on its best practices. There is a substantial body of literature that provides support for the notion that quality practices improve organization performance and customer satisfaction [4–7] as well as it leads to successful total quality management implementation in the organization.

Similarly, the works of Karuppusami and Gandhinathan [8], Duggirala et al. [9], Gustafsson et al. [5], Kureshi et al. [10], and other studies focused on the relationship between quality practices, quality performance, and business performance. The extent review of literature further identified some common practices that are responsible to successful total quality management implementation, namely, top-management commitment and leadership, strategic planning, resource management, customer focus, process management, supplier management, information and analysis, continuous improvement, teamwork, and social and environmental issues [11–17].

Organizations face enormous pressure due to market climate and changing customers’ demands; one of the ways to respond to these pressures is drawing on the concept of management and enhanced flexibility [18]. One aspect of agility is flexibility. Creating an organization with agility requires the coordination and cooperation of knowledge-seeking staff. The five-facet nature of knowledge management in implementing agility has attracted the attention of researchers. Therefore, in the age of knowledge-based economy, organizations have gained an appropriate and important opportunity to achieve the goals and strategies that have been created for them through applying knowledge management within themselves, monitoring and evaluating the organization according to knowledge management components; this is a prerequisite for planning and implementing agility in the organization. There is also a positive convergence between knowledge management and organizational agility, so that organizational agility is achieved when knowledge management is in a state of equilibrium in every way [19]. It should also be noted that efforts to make manufacturing and service organizations agile have sometimes led to fatal mistakes such as neglecting quality in the organizational acceleration process. The category of quality has entered the field of competition in the previous decades; it has established itself as a permanent element in all efforts aimed at promoting organizations and neglecting it can nullify any success theory in organizations. Nevertheless, the agility of organizations should be considered in the terms of quality and its components. Therefore, in order to compete globally, the organisations must embrace TQM concept and its practices and incorporate them in all of their activities effectively [1]. Total quality management is both a philosophy as well as a set of guiding principles and practices. Through continuous improvement in quality and customer satisfaction with management of quality [2], the previous researches showed the relationship between knowledge management and organizational agility and TQM. Much research has been done on the performance appraisal based on each of the approaches described. However, despite the impact of these categories on each other, the simultaneous and combined evaluation of these three approaches has received less attention in the literature.

In the present study, in addition to evaluating the performance of organizations based on the success factors of TQM, we seek to identify the influential factors and success factors of each of the three areas of knowledge management, organizational agility, and TQM; then, the impact of the two areas of knowledge management and organizational agility on the success factors of TQM is evaluated.

To express the above-given relationship, group ISM techniques were applied to rank the components of each domain. The purpose is to classify the factors and identify the relationships between the criteria. Also, the use was made of the MICMAC (impact matrix cross-reference multiplication applied to a classification) technique for analysing variables to separate them into independent, dependent, interface, and linking ones for use in the next step. Furthermore, FQFD technique was applied to find the weight and relationship of the three mentioned domains by examining the independent and interface variables of the previous step and interface variables of the previous step, and fuzzy method has been used for better and more comprehensive collection of survey results. Finally, the weights obtained from the two-stage house of quality have been used as the weights for designing a two-stage DEA model by the weight control method. Finally, the above-given factors have been studied in knowledge-based companies located in Khorramabad Science and Technology Park, and the results have been stated. In the following, the theoretical foundations of research in three areas have been described. Research implementation phases are shown in Figure 1.

[figure(s) omitted; refer to PDF]

2. Literature Review

Now, to show the study gap, a number of articles in the abovegiven areas have been discussed here. As stated previously, the relationship between total quality management and knowledge management is conceptualized in different ways. From one perspective, knowledge management is determined as an enabler for total quality management. Stewart and Waddell [20] expressed that widening the concept of quality, from product/service specification to rapid response to customer needs, clears the relationship between knowledge management and total quality management. Also, knowledge acquiring and disseminating it provides a quality culture that leads to effective quality management implementation. Barber et al. [21] argued that the role of knowledge management systems in supporting continuous improvement and knowledge management system enables continuous improvement by utilization of available data already held within the company’s management databases. Hung et al. [22] empirically examined the relationship between knowledge management, total quality management, and innovation. The results of this study revealed that there is a significant association between knowledge management and total quality management. In addition, knowledge management contributes to innovation through total quality management. In other words, knowledge management is an antecedent for total quality management and innovation. The other approach supposes that total quality management is a supporter for knowledge management. Choo et al. [23] showed a conceptual framework based on quality programs and knowledge management. Based on this study, quality programs are effective enablers of knowledge management. Jayawarna and Holt [24] introduced and analysed the relationship between knowledge creation and transformation in the R & D context. Based on their case study research, they concluded that total quality management practices improve knowledge creation and transformation. Molina et al. in the study of [25] showed the relationship between total quality management practices and knowledge transfer is examined. They indicated that there is a significant and positive association between total quality management and knowledge transfer. The criterion of this paper is performance and the finding of the study shows that total quality management contributes to performance through knowledge transfer. For example, Frank and Ribei [26] expressed that encouragement from leaders will encourage the knowledge transfer among employees. Benchmarking also can be used as measures of knowledge management by comparing organizational knowledge management structures, knowledge management practices, and knowledge-based strategies with a benchmarking partner [27].

Convergence of knowledge management and organizational agility is also expressed in the articles, showing that organizational agility is achieved when knowledge management is in a state of balance in every way. TQM has also been introduced in response to the highly competitive challenges of Japanese companies; it is now recognized as a competitive advantage around the world, and quality management should not be neglected due to the acceleration of organizational agility. Lou and Rezaeenour [28] also expressed the impact of knowledge management processes on the organizational agility in a foundry company. On the other hand, through structural analysis, the relationship between TQM and knowledge management is expressed. Furthermore, Honarpour et al. [29] and Garcia [30] have shown the relationship between knowledge management and TQM. Iqbal et al. [31] and Zelbst et al. [32] also explained the relationship between organizational agility and TQM in the Pakistani garment industry. Abbas and Kumari [33] express that a positive correlation existed between TQM and KM, and organizational performance also positively influence on firm operational and financial performance and partially mediates the relationship between TQM and corporate performance [34]. Soares and Rios-Zaruma [35] sought to identify which are the relationships between knowledge management and quality management in organizational performance. The data survey was carried out in Web of Science, Scopus, and SciELO databases. The searches took place in October 2020, and also in the paper, it is showed that knowledge management and quality management have a positive relationship in the performance of organizations and express the use of only two variables can help in the identification of relationships between areas. Ong and Cheng [36] examine the link among agility, knowledge management practices, and firm performance, and Ong and Tan [37] study the organizational performance improvement with the alignment of KM, soft TQM, and agility. Kamoun [38] research the impact of knowledge management and TQM on staff efficiency and on the performance of the company Barua et al. The authors of [39] research the effect of TQM on organizational performance considering the mediating role of knowledge creation process. And finally, Talib et al., [40] in their article, presented an ISM interpretive structural modelling approach for modelling total quality management practices in the service sector [40]. Table 1 shows a brief review on research literature.

Table 1

A brief review on research literature.

Row nos	Writer(s)	Year	Tool(s)	Subject	Research attitude
Row nos	Writer(s)	Year	Tool(s)	Subject	KM⁵	OA⁶	TQM
1	Stewart and Waddell	2008	Statistics	To consider the connection between KM and TQM	✓		✓
2	Barber et al.	2006	Statistics	Argued that the role of knowledge management systems in supporting continuous improvement and knowledge management system enables continuous improvement by utilization of available data already held within the company’s management databases	✓
3	Hung et al.	2010	Structural equation modelling	Empirically examined the relationship between knowledge management, total quality management, and innovation. The results of this study revealed that there is a significant association between knowledge management and total quality management. In addition, knowledge management contributes to innovation through total quality management. In other words, knowledge management is an antecedent for total quality management and innovation. The other approach supposes that total quality management is a supporter for knowledge management	✓		✓
4	Choo et al.	2007	Statistics	Showed a conceptual framework based on quality programs and knowledge management. Based on this study, quality programs are effective enablers of knowledge management	✓		✓
5	Jayawarna and Holt	2009	Statistics	Introduced and analyzed the relationship between knowledge creation and transformation in the R & D context. Based on their case study research, they concluded that total quality management practices improve knowledge creation and transformation	✓		✓
6	Molina et al.	2007	Statistics	Showed the relationship between total quality management practices and knowledge transfer is examined. They indicated that there is a significant and positive association between total quality management and knowledge transfer	✓		✓
7	Frank and Ribeiro	2014	Statistics	Convergence of knowledge management and organizational agility is also expressed in the articles, showing that organizational agility is achieved when knowledge management is in a state of balance in every way	✓	✓
8	Lou et al.	2016	Structural analysis	Expressed the impact of knowledge management processes on the organizational agility in a foundry company. On the other hand, through structural analysis, it is expressed that the relationship between TQM and knowledge management	✓	✓	✓
9	Honarpour et al.	2017	Statistics	To research the reciprocal relationship between KM and TQM	✓		✓
10	García	2011	Statistics	Enhance the organizational performance with the combination of management orientations: KM, soft TQM, and hard TQM	✓		✓
11	Iqbal et al.	2018	Statistics	To investigate agile manufacturing and its connection with TQM, JIT, and firm performance		✓	✓
12	Pamela et al.	2010	Statistics	To study the relationship among market orientation, JIT, TQM, agility, industrial management, and data systems		✓	✓
13	Abbas et al.	2021	Statistics	Express that a positive correlation existed between TQM and KM, and organizational performance also positively influence on firm operational and financial performance and partially mediates the relationship between TQM and corporate performance	✓		✓
14	Soares et al.	2021	Statistics	In the study, it is showed that knowledge management and quality management have a positive relationship in the performance of organizations	✓		✓
15	Ong and Tan	2021	Statistics	To examine the link among agility, knowledge management practices and firm performance	✓	✓
16	Ong and Tan	2022	Statistics	To study the organizational performance improvement with the alignment of KM, soft TQM and agility	✓	✓	✓
17	Kamoun	2022	BSC⁷	To research the impact of knowledge management and TQM on staff efficiency and on the performance of the company	✓		✓
18	Barua et al.	2022	Descriptive statistics Regression	To research the effect of TQM on organizational performance considering the mediating role of knowledge creation process	✓		✓
19	Talib et al.	2011	ISM	In this research, an ISM interpretive structural modeling approach is presented for modeling total quality management practices in the service sector			✓

⁵Knowledge management. ⁶Organizational agility. ⁷Balanced score card.

As Table 1 demonstrates and previous researches have highly emphasized on, each of managerial attitude can have a great impact on the organizational performance. Among the management orientations TQM which makes the firm to commit to the customers’ requirements is important to be appraised. On the other side to gain the customer satisfaction, in a competitive world of the business, it would tremendously be influential to have the power of adaption with the environmental change and changing customers’ needs. Thereby, a knowledge-based company which provides the knowledge infrastructures would have basic but paramount foundation to increasingly keep the organizational performance improved. Hence, reviewing the research literature, it can be found out that these three managerial attitudes and their impact on the organizational performance has rarely been researched. Besides, applying a precise tool, to consider the attitudes with the controlled weights and also consideration of the efficiency numbers of the organization helps the managers to provide a policy map on the basis of the principle attitudes of the management while even the details of the indicators identification, indicators’ weights calculation, and efficiency numbers are precisely studied.

2.1. Theoretical Foundations of Research

Because the three areas are examined in this article, first, each of them is defined separately according to the experts’ opinions.

2.2. Total Quality Management

The term total or comprehensive quality management (TQM) is one of the most common terms that have been recently used in the business field. Total management is regarded as improvements made in the traditional methods of doing business; it has been technically proved to ensure survival in the today’s competitive world. Total quality management is the art of managing all sections to get the best; the main focus is on quality according to TQM. This included the quality of work and processes. Thus, TQM is contrasted with result-oriented management, which only pays more attention to the outcomes and production. In general, the important principles governing this view are the commitment of senior management to the customer-centred evaluation and decision-making based on facts, participation and collaboration, training, and continuous improvement [41]. TQM is an intelligent, peaceful, and continuous activity that also has an energetic effect on meeting the goals of the organization, ultimately leading to the customer’s satisfaction, increased efficiency, and enhanced competitiveness in the market. TQM can be regarded as an effective cost management system for continuous efforts to make improvement at all levels [6].

2.3. Total Quality Management Success Factors

Almost after the initial design of TQM, the factors affecting it have been discussed; over the years, many researchers have completed these factors and introduced them as the keys for success in TQM. Table2 lists the success factors of TQM according to the researchers.

Table 2

Critical success factor of organizational agility [42].

No.2	Critical success factors	Literature review
1	Organizational flexibility	Dubey and Gunasekaran [43], Yusuf et al. [44], and Dove [45]
2	Data analysis	Yusuf et al. [44] and Al-Tahat et al. [46]
3	Workforce flexibility	Yusuf et al. [44] and Al-Tahat et al. [46]
4	Easy flow of information and communication	Dubey and Gunasekaran [43], Yusuf et al. [44], and Al-Tahat et al. [46]
5	Indoor data	Yusuf et al. [44] and Al-Tahat et al. [46]
6	Business process flexibility	Dubey and Gunasekaran [43], Yusuf et al. [44], Dove [45], and Al-Tahat et al. [46]
7	Organizational attitude to participation	Yusuf et al. [44], Dove [45], and Al-Tahat et al. [46]
8	Positive attitude to change, ideas	Yusuf et al. [44], Dove [45], and Al-Tahat et al. [46]
9	Manager support for innovation	Yusuf et al. [44], Dove [45], and Al-Tahat et al. [46]
10	Continuous improvement of staff training	Dubey and Gunasekaran [43], Yusuf et al. [44], and Al-Tahat et al. [46]
11	Change management	Yusuf et al. [44] and Al-Tahat et al. [46]
12	Easy of change process	Yusuf et al. [44] and Al-Tahat et al. [46]

2.4. Knowledge Management

Economy is moving from the era of competitive advantage based on information to the era of competitive advantage based on knowledge creation. The world is experiencing an age of knowledge in which knowledge is a basic commodity and knowledge flows are considered as the most important factor in the economy. Knowledge is assumed to be a strategic asset that can help organizations to maintain their competitiveness in a turbulent environment [47]. Knowledge management is a more important category than knowledge itself and organizations are seeking it. It explains how to transform individual and organizational information and knowledge into individual and group knowledge and skills. Knowledge management is an approach to create an organization whose members can acquire, share, and create knowledge or use it for decision-making activities [3].

2.5. Critical Success Factors in Knowledge Management

A wide range of factors can affect the successful implementation of knowledge management. For example, cultural factors, information technology, and leadership are important considerations in implementing knowledge management. Determining an appropriate set of key success factors will help organizations to consider the important issues they face when designing and implementing knowledge management [48]. To express this using management language, knowledge refers to the factors of success, activities, and measures necessary to succeed in knowledge management. If these factors do not exist in the organization, they must be created and if they exist, they must be nurtured and developed. External factors such as environmental impacts are not considered, because organizations have no control over them in the implementation of knowledge management [48]. Table 3 shows the success factors of knowledge management according to researchers.

Table 3

Critical success factor of knowledge management [47].

No.1	Critical success factor (CSF)	Literature review
1	Management support	O’dell and Grayson [49], Valmohamadi and Ahmadi [47], Moffett et al. [50], Chong and Choi [51], Hung et al. [52], Kanagasabapathy et al. [53], and Chourides et al. [54]
2	Organizational culture	O’dell and Grayson [49], Moffett et al. [50], Chong and Choi [51], Nelson and Middleton [55], Valmohamadi and Ahmadi [47], and Kanagasabapathy et al. [53]
3	IT	Valmohamadi and Ahmadi [47], O’dell and Grayson [49], Hung et al. [52], Kanagasabapathy et al. [53], and Akhavan et al. [56]
4	Employee motivation	Valmohamadi and Ahmadi [47], O’dell and Grayson [49]
5	Structure	Valmohamadi and Ahmadi [47], Chong and Choi [51], Chourides et al. [54], Nelson and Middleton [55], and Akhavan et al. [56]
6	Employee educational and training	Moffett et al. [50], Chong and Choi [51], Kanagasabapathy et al. [53], Valmohamadi and Ahmadi [47], Akhavan et al. [56], and Wong [57]
7	Measurement	O’dell et al. [49], Chong and Choi [51], Hung et al. [52], Kanagasabapathy et al. [53], Akhavan et al. [56], Karabage [58], Valmohamadi and Ahmadi [47], and Wong [57]
8	Team working	Moffett et al. [50], Hung et al. [52], Kanagasabapathy et al. [53]
9	Strategy and goals	Akhavan et al. [56], and Karabage [58], Valmohamadi and Ahmadi [47]

2.6. Agility

The word agility means the ability to move quickly and easily and to be able to think fast and in a smart way. There are many definitions for agility, but none of them contradicts or opposes the others. These definitions generally reflect the idea of speed and change in the workplace. However, given the novelty of the agility issue, there is no one-size-fits-all definition. In fact, agility is the ability of an organization to (1) discover new opportunities for competitive advantage, (2) use assets, knowledge, and relationships to seize these opportunities, and (3) adapt to sudden changes in the business environment [42].

2.7. Research Implementation Algorithm

In this part, the stages of conducting research are described; in each phase, the general description of it is presented; also, in regard to the steps, the necessary stages to achieve the goals of each phase are stated. The stages involved in conducting this research are in 5 phases and 14 steps, which are as follows.

2.7.1. Phase 1: Identifying Indicators

In the first phase, performance indicators are identified; this is carried out during three steps. These three steps include a comprehensive review of the research literature through field study, respectively.

Step 1.

Extracting and identifying the success factors of knowledge management

Step 2.

Extracting and identifying the components of agility indicators

Step 3.

Extracting and identifying the success factors of TQM implementation

2.7.2. Phase 2: Classification of Indicators

In the second phase, the indicators are ranked and the purpose is to classify the factors and identify the relationships between the criteria. This phase also takes place during three steps, as brought here.

Step 4.

Classifying and identifying the relationships between the indicators of knowledge management success factors using ISM

Step 5.

Classifying and identifying the relationships between agility indicators using ISM

Step 6.

Classifying and identifying the relationships between TQM implementation success factors using ISM

2.7.3. Phase 3: Analysis Based on Permeation Power and Dependency

The third phase deals with the MICMAC analysis based on the permeation power (influence) and the degree of dependence (effectiveness) of each variable, allowing further study of the range of each variable. In this analysis, the variables are divided into four groups: independent, dependent, interface, and linking.

Step 7.

MICMAC analysis on knowledge management success factors

Step 8.

MICMAC analysis on organizational agility factors

Step 9.

MICMAC analysis on TQM success factors

2.7.4. Phase 4: Prioritization and Weighting of Indicators Using FQFD

In the fourth phase, according to the results of the previous step, those variables that are in the group of independent and interface variables are selected. The reason for choosing independent and interface variables for all three domains is that the variables with more importance and effectiveness can be selected in all three domains because these variables have a high guiding power for the effectiveness of their domains. Then, the prioritization and weighting of indicators are carried out using FQFD; this phase takes place in two steps; first, a questionnaire is used to fill in the tables related to houses of quality and the tables are filled without considering the specific industry and service. The results obtained can be generalized to all industries and services. This section includes the following two steps, respectively:

Step 10.

Forming the first-stage fuzzy house of quality, weighting, and prioritizing the indicators and knowledge management success factors with agility indexes using FQFD and filling the house of quality by university experts

Step 11.

Establishing a second-stage fuzzy house of quality, weighting, and prioritizing the indicators of agility with the success factors of TQM using FQFD and filling the house of quality by academic experts, as shown in Figure 2.

It should be noted that the weight results obtained from the house of quality are finally defuzzified for use in the next stage and the relative weight of all indicators is calculated and specified.

[figure(s) omitted; refer to PDF]

2.7.5. Phase 5: Design of Two-Stage Data Envelopment Analysis Model and Implementation in a Case Study

Step 12.

Designing a two-stage data envelopment analysis model by weight control method; this is carried out in this step by using weights obtained from two houses of quality.

In fact, at this step, the two-stage DEA model is designed with weights controlled from the results obtained by the two-stage house of quality.Here, we have n units under hypothetical evaluation, each of which has a network like the structure in Figure 2; here, X_j = (X_1j, X_2j,…, X_mj) is the input of stage 1 of the j^th unit with output Z_j = (Z_1j, Z_2j,…, Z_mj) and z plays the role of the input of Step 2 of the j^th unit, which leads to the output Y_j = (Y_1j, Y_2j,…, Y_mj) in Figure 3.

The inputs of this model are the success factors of knowledge management in the organization; the weight assigned to it is represented by $v$ and the intermediate values are the indicators of organizational agility; they are weighed with $w$ , and the output values are the success factors of TQM, which are marked by the weight u.

Weights obtained from fuzzy house of quality by the weight control method are then used in the two-stage DEA model. By applying some restrictions, no zero weight is given to the parameters; also, weight is assigned to each parameter according to its importance. This level of importance is determined by the relative importance achieved in both stages of the house of quality.

Also, it is worth mentioning that the results obtained from the fuzzy house of quality are obtained from the fuzzy state and become crisp; then, they are written using the formula $v_{i}$ ≥ ${d v}_{j}$ in the form of weight constraints for the knowledge management field in each of the parameters related to it. They are compared with each other in terms of importance; also, by using the formula $w i$ ≥ $d_{w j}$ , the weight constraints for organizational agility and finally, the formula ui ≥ $d_{u j}$ , the weight constraints for quality management success factors are obtained for each parameter. The importance of the parameters is compared and finally added to the two-stage DEA model in the form of constraints.

[figure(s) omitted; refer to PDF]

Step 13.

Designing a questionnaire according to the selected indicators in the third phase and determining the performance of the studied organizations in each parameter according to the opinion of managers and experts of the units

Step 14.

Evaluating the performance of the studied organizations using two-stage data envelopment analysis

As stated, the stages involved in conducting this research are in 5 phases which are summarized in Figure 1. To better express the steps of the article, the reason for using each method and the relationship between each phase and the previous phase is stated in Table 4.

Table 4

Research implementation phases.

Phases	Phase title	The relation between phases	Motivation of using a method
Phase 1	Identifying indicators: critical success factor	Start	A wide range of factors can affect the successful implementation of KM, AM, and TQM. Determining an appropriate set of key success factors will help organizations to consider the important issues they face when designing and implementing. Therefore, success factors are very important for implementing the success of these fields. If these factors do not exist in the organization, they must be created and if they exist, they must be nurtured and developed. External factors are not considered, because organizations have no control over them in the implementation
Phase 2	Classification of indicators: ISM method	Critical success factor in all three domains have been used as inputs to form the ism matrix	The purpose is to classify the factors and identify the relationships between the criteria. The results of determination of the level of variables by using the ISM method for each of the abovegiven areas are presented; then, in each stage, according to the results obtained from the previous step, the network of interactions for each of the above three areas is drawn to represent the relationship between the parameters and the placement levels of each parameter. In general, the main advantages of this modeling method are:(i) Understandable for a wide range of users(ii) A tool to integrate different perceptions of experts(iii) Ability to use it in the study of complex and diverse systems
Phase 3	Analysis based on permeation power and dependency: MICMAC analysis	The results of the final received matrix of the last step of the ism method have been used to form the MICMAC matrix	The reason for choosing independent and interface variables and MICMAC analysis for all three domains is that the variables with more importance and effectiveness are selected in all these domains because these variables have a high driving force in the effectiveness of their domains
Phase 4	Prioritization and weighting of indicators using FQFD: FQFD	Success factors of knowledge management, which are, in fact, independent and interface elements obtained from MICMAC analysis, are taken as the input of the first-stage house of quality; as well, independent and interface elements and the organizational agility, as also obtained from MICMAC analysis, are considered as the output of the first stage. Further, weights obtained from the first house of quality for organizational agility parameters are considered as the second stage inputs and the independent and interface parameters of the TQM success factors obtained from the MICMAC analysis are considered as the output of the second-stage fuzzy house of quality	The FQFD method has been used to calculate the weight of indicators and relationship of the three mentioned domains by examining the independent and interface variables of the previous step and fuzzy method has been used for better and more comprehensive collection of survey results
Phase 5	Design of two-stage data envelopment analysis model and implementation in a case study: two-stage data	The weights obtained from the two-stage house of quality have been used as the weights for designing a two-stage DEA model by the weight control method. The inputs of this model are the success factors of knowledge management in the organization, and the intermediate values are the indicators of organizational agility, and the output values are the success factors of TQM. Weights obtained from fuzzy house of quality by the weight control method are then used in the two-stage DEA model	The reason for using DEA method: The data envelopment analysis method is a management method that measures the efficiency of units relatively. Also, a two-step method is used to examine all three areas and its effect on the TQM and evaluate performance of the organization. This method is more generalizable and expandable than other methods, and using it in one unit for one topic can provide the basis for future work. It is not sensitive to units of measurement and inputs and outputs can have different units

2.8. Implementation of the Research Algorithm

Now, according to the algorithm proposed in the previous step, each of the steps and phases are performed and the results of the algorithm are expressed. It is worth mentioning that the results are expressed separately for each phase.

It should be noted in this research that all of numerical results cases were questioned, studied, and examined using a questionnaire filled by 40 university experts who had studied in the above field. The criteria for selecting those experts included having a doctorate in industrial engineering and management, being a faculty member and also having published at least one article in the field of TQM, knowledge management, or organizational agility; it was filled without considering the specific industry and service. Therefore, the obtained results do not depend on a specific industry and can be implemented in production and service organizations. Also, in the case study phase, a questionnaire was used to examine 20 knowledge-based companies located in Khorramabad Science and Technology Park. The information was completed by the managers and experts of the company.

2.8.1. Phase 1: Identifying Indicators

In this phase, the success factors of knowledge management, TQM, and organizational agility are identified; this is carried out according to field studies conducted in all three specific areas.

The results of studies in the field above and compares the selected parameters in each area during the three Tables 3–5 have been reported. In the table, you can see the articles in which the selected parameter is mentioned.

Table 5

Success factors for total quality management (TQM) [59].

No.3	Critical success factor (CSF)	Literature review
1	Top management commitment	Valmohammadi [60], Bani et al. [61], Sengar et al. [62], Anil and Satish [63]
2	Customer focused	Valmohammadi [60], Bani et al. [61], Sengar et al. [62], Sadikoglu and Olcay [64], Gupta and Belokar [65]
3	Training and education	Sengar et al. [62], Anil and Sathish [63], Sadikoglu Olcay [64], Gupta Belokar [65]
4	Continuous improvement an innovation	Anil and Sathish [63], Talib et al. [66], Fotopoulos and Psomas [67], Sharma and Kodali [68]
5	Supplier management	Gupta and Belokar [65], Talib et al. [66], Fotopoulos and Psomas [67], Sharma and Kodali [68], Salaheldin [69]
6	Employee involvement	Anil and Sathish [63], Talib et al. [66]
7	Information and analysis	Bani et al. [61], Sengar et al. [62], Anil and Sathish [63], Talib et al. [66], Fotopoulos and Psomas [67], Miyagawa and Yoshida [70]
8	Process management	Sengar et al. [62], Sadikoglu and Olcay [64], Gupta and Belokar [65], Anil and Sathish [63], Gulbarga et al. [71], Talib et al. [66], Fotopoulos and Psomas [67], Sharma and Kodali [68], Salaheldin [69]
9	Quality system	Bani et al. [61], Anil and Sathish [63], Sadikoglu and Olcay [64], Gupta and Belokar [65], Talib et al. [66]
10	Benchmarking	Bani et al. [61], Sengar et al. [62], Gulbarga et al. [71], Talib et al. [66], Salaheldin [69], Ooi et al. [72]
11	Quality culture	Bani et al. [61], Sengar et al. [62], Anil and Sathish [63], Talib et al. [66], Fotopoulos and Psomas [67], Salaheldin [69], Ooi et al. [72]
12	Human resource management	Talib et al. [66], Sharma and Kodali [68], Salaheldin [69], Miyagawa and Yoshida [70]
13	Strategic planning	Valmohamadi and Ahmadi [47], Anil and Sathish [63], Talib et al. [66], Fotopoulos and Psomas [67], Miyagawa and Yoshida [70], Gulbarga et al. [71]
14	Employee encouragement	Anil and Sathish [63], Talib et al. [66]
15	Team work	Bani et al. [61], Anil and Sathish [63], Sadikoglu and Olcay [64], Gupta and Belokar [65], Gulbarga et al. [71], Talib et al. [66]
16	Product and service design	Salaheldin [69], Miyagawa and Yoshida [70]
17	Communication	Gulbarga et al. [71]

2.8.2. Phase 2: Implementing the ISM Method

In this section, the results of determination of the level of variables by using the ISM method for each of the above-given areas are presented; then, in each stage, according to the results obtained from the previous step, the network of interactions for each of the above-given three areas is drawn to represent the relationship between the parameters and the placement levels of each parameter.

(1) Investigating the Success Factors of Knowledge Management Using ISM Method. The results of examining the parameters of knowledge management success factors by ISM method are described in Table 6.

Table 6

Results of determining the level of interpretive structural modelling (ISM) variables of knowledge management success factors.

CSF no	Reachable set	Antecedent set	Intersection set	Level
2	1, 2, 4, 6, 7, 8, 9	1, 2, 4, 6, 7, 8, 9	1, 2, 4, 6, 7, 8, 9	1
4	1, 2, 4, 9	1, 2, 4, 6, 7, 8, 9	1, 2, 4, 9	1
5	5	1, 5, 9	5	1
1	1, 8, 9	1, 8, 9	1, 8, 9	4
3	3, 7	1, 3, 7, 8, 9	3, 7	3
6	1, 6, 8	1, 3, 6, 7, 8, 9	1, 6, 8	2
7	3, 7	1, 3, 7, 8, 9	3, 7	3
8	1, 8	1, 8, 9	1, 8	4
9	1, 9	1, 9	1, 9	5

Also, Figure 4 represents the ranking of the network diagram of the interactions of the knowledge management success factors as obtained from the results of the table brought above.

[figure(s) omitted; refer to PDF]

As can be seen, the elements are at 5 levels.

(2) Assessing the Organizational Agility by ISM. The results of the study of organizational agility parameters by ISM are described in Table 7.

Table 7

Results of determining the level of interpretive structural modelling (ISM) variables for organizational agility factors.

Agile nos.	Reachability set	Antecedent set	Intersection set	Level
1	1	1, 2, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19	1	8
2	1, 2, 9, 10, 11	2, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19	2, 9, 11	7
3	3	3, 4, 5, 6, 7, 8, 12, 17, 18, 19	3	5
4	1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19	4, 7, 12, 18, 19	4, 7, 12, 19	2
5	1, 2, 3, 5, 6, 9, 10, 11, 13, 14, 15, 16	4, 5, 6, 7, 8, 12, 17, 18, 19	5, 6	4
6	1, 2, 3, 5, 6, 9, 10, 11, 13, 14, 15, 16	4, 5, 6, 7, 8, 12, 17, 18, 19	5, 6	4
7	1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19	4, 7, 12, 18, 19	4, 7, 12, 19	2
8	1, 2, 3, 5, 6, 8, 9, 10, 11, 13, 14, 15, 16	4, 7, 8, 12, 17, 18, 19	8	3
9	1, 2, 9, 10, 11	2, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19	2, 9, 11	7
10	10	2, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17, 18, 19	10	8
11	1, 2, 9, 10, 11	2, 4, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 16, 17, 18, 19	2, 9, 11	7
12	1, 2, 3, 4, 5, 67, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19	4, 7, 12, 18, 19	4, 7, 12, 19	2
13	1, 2, 9, 10, 11, 13, 15, 16	4, 5, 6, 7, 8, 12, 13, 14, 15, 16, 17, 18, 19	13, 15, 16	6
14	1, 2, 9, 10, 11, 13, 14, 15, 16	4, 5, 6, 7, 8, 12, 14, 17, 18, 19	14	5
15	1, 2, 9, 10, 11, 13, 15, 16	4, 5, 6, 7, 8, 12, 13, 14, 15, 16, 17, 18, 19	13, 15, 16	6
16	1, 2, 9, 10, 11, 13, 15, 16	4, 5, 6, 7, 8, 12, 13, 14, 15, 16, 17, 18, 19	13, 15, 16	6
17	1, 2, 3, 5, 6, 8, 9, 10, 11, 13, 14, 15, 16, 17	17	17	1
18	1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 18, 19	18	18	1
19	1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 19	4, 7, 12, 18, 19	4, 7, 12, 19	2

Figure 5 shows the ranking diagram of the network of the interactions of the organization’s agility factors obtained from the results of Table 7.

[figure(s) omitted; refer to PDF]

As can be seen, the elements are arranged at eight levels.

(3) Assessing the Success Factors of TQM by ISM. The results of examining the parameters of TQM success factors by ISM are described in Table 8.

Table 8

Results of determining the level of the interpretive structural modelling (ISM) variables of TQM success factors.

CSF nos.	Reachability set	Antecedent set	Intersection set	Level
2	2	1, 2, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17	2	1
4	4, 10	1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17	4, 10	2
10	4, 10	1, 3, 4, 6, 7, 8, 9, 10, 11, 12, 13, 14, 15, 16, 17	4, 10	2
16	16	1, 3, 5, 6, 7, 8, 9, 11, 12, 13, 15, 16, 17	16	3
8	8, 9	1, 3, 5, 6, 7, 8, 9, 11, 12, 13, 14, 15, 17	8, 9	4
9	8, 9	1, 3, 5, 7, 8, 9, 11, 12, 13, 15, 17	8, 9	4
12	12	1, 3, 5, 6, 7, 11, 12, 13, 14, 15	12	5
3	3, 6, 14	1, 3, 5, 6, 7, 11, 13, 14, 15	3, 6, 14	6
6	3, 6, 14	1, 3, 5, 6, 7, 11, 13, 14, 15, 17	3, 6, 14	6
14	3, 6, 14	1, 3, 6, 7, 11, 13, 14, 15, 17	3, 6, 14	6
15	15	1, 5, 7, 11, 13, 15, 17	15	7
5	5	1, 5, 13, 17	5	8
7	7	1, 7, 17	7	8
11	11	1, 11, 17	11	8
13	13	1, 13, 17	13	8
17	17	1, 17	17	9

Figure 6 shows the ranking diagram of the network of the interactions of TQM success factors resulting from the results of the above tables.

[figure(s) omitted; refer to PDF]

2.8.3. Third Phase: MICMAC Analysis

After ranking the variables, in this step, the results of the analysis of variables are expressed using the MICMAC method; the parameters are divided into four categories or groups: autonomous, dependent, linking, and independent. This division is based on the permeation power (influence) and the degree of dependence (effectiveness) of each variable.

In this section, the MICMAC analysis graph is drawn, as shown in Figure 7, to examine the success factors of knowledge management.

[figure(s) omitted; refer to PDF]

In this graph, the index number 9 is independent and indices 1, 2, 6, 7, and 8 are interface, index 5 is autonomous, and indices 3 and 4 are dependent. Also, the diagram obtained from MICMAC analysis is drawn, as described in Figure 8, to examine the factors of organizational agility.

[figure(s) omitted; refer to PDF]

In the diagram brought in Figure 6, the indices 1, 2, 3, 9, 10, 11, 13, 15, and 16 are independent, the indices 5, 6, and 14 are interface, and 4, 7, 7, 8, 12, 17, 18, and 19 are dependent. Also, MICMAC analysis diagram is drawn, as shown in Figure 9, to examine the TQM success factors.

[figure(s) omitted; refer to PDF]

In the diagram brought in Figure 9, the indices 1, 5, 7, 13, 15, and 17 are independent, the indices 3, 6, and 11 are interface, and the indices 2, 4, 8, 8, 9, 10, 12, 14, and 16 are dependent.

2.8.4. Phase 4: Fuzzy House of Quality

Now, according to the results obtained from the MICMAC analysis and the identification of independent and dependent factors for each of the studied areas, in this section, to examine the relationship between the proposed areas, the two-stage fuzzy house of quality is used. Success factors of knowledge management, which are, in fact, independent and interface elements obtained from MICMAC analysis, are taken as the input of the first-stage house of quality; as well, independent and interface elements and the organizational agility, as also obtained from MICMAC analysis, are considered as the output of the first stage. Furthermore, weights obtained from the first house of quality for organizational agility parameters are considered as the second stage inputs and the independent and interface parameters of the TQM success factors obtained from the MICMAC analysis are considered as the output of the second-stage fuzzy house of quality. The reason for choosing independent and interface variables for all three domains is that the variables with more importance and effectiveness are selected in all these domains because these variables have a high driving force in the effectiveness of their domains.

Also, the two stages of the fuzzy house of quality consisted of asking 40 university experts who were available; the criteria for selecting those experts included having a doctorate in industrial engineering and management, being a faculty member and also having published at least one article in the field of TQM, knowledge management, or organizational agility; it was filled without considering the specific industry and service. The results obtained could be generalized to all industries and services, as can be seen in Tables 9 and 10.

Table 9

House of quality stage 1.

What is

Weights

Organizational flexibility

Data analysis

Workforces flexibility

Easy flow of information and communication

Indoor data

Business process flexibility

Organizational attitude to participation

Positive attitude to change. Idea

Manager support to innovation

Continuous of staff training

Change management

Easy of change process

Strategy and goals

(0.52; 0.78; 0.88)

(0.55; 0.8; 0.86)

(0.32; 0.51; 0.69)

(0.13; 0.12; 0.44)

(0.32; 0.51; 0.69)

(0.13; 0.12; 0.44)

(0.55; 0.8; 0.86)

(0.54; 0.8; 0.87)

(0.55; 0.8; 0.86)

(0.12; 0.2, 0.5)

(0.16; 0.25; 0.48)

(0.51; 0.75; 0.8 3)

(0.16; 0.25; 0.48)

Management support

(0.56; 0.79; 0.91)

(0.54; 0.8; 0.87)

(0.16; 0.25; 0.48)

(0.12; 0.2, 0.45)

(0.13; 0.12; 0.44)

(0.54; 0.8; 0.87)

(0.51; 0.75; 0.83)

(0.54; 0.8; 0.87)

(0.51; 0.75; 0.83)

(0.55; 0.8; 0.86)

(0.51; 0.75; 0.83)

Team working

(0.43; 0.65; 0.88)

(0.51; 0.75; 0.83)

(0.16; 0.25; 0.48)

(0.51; 0.75; 0.83)

(0.16; 0.25; 0.48)

(0.51; 0.75; 0.83)

(0.55; 0.8; 0.86)

(0.32; 0.51; 0.69)

(0.36; 0.56; 0.72)

(0.32; 0.51; 0.69)

(0.37; 058; 074)

(0.16; 0.25; 0.48)

Measurement

(0.46; 0.67; 0.1)

(0.12; 0.2, 0.45)

(0.55; 0.8; 0.86)

(0.13; 0.12; 0.44)

(0.51; 0.75; 0.83)

(0.54; 0.8; 0.87)

(0.12; 0.2, 0.45)

(0.13; 0.12; 0.44)

(0.12; 0.2, 0.45)

Employee motivation

(0.45; 0.65; 0.91)

(0.37; 0.58; 074)

(0.13; 0.12; 0.44)

(0.51; 0.75; 0.83)

(0.12; 0.2, 0.45)

(0.13; 0.12; 0.44)

(0.36; 0.56; 0.72)

(0.32; 0.51; 0.69)

(0.37; 0.58; 074)

(0.36; 0.56; 0.72)

(0.55; 0.8; 0.86)

(0.13; 0.12; 0.44)

Organizational culture

(0.43; 0.65; 0.88)

(0.51; 0.75; 0.83)

(0.16; 0.25; 0.48)

(0.51; 0.75; 0.83)

(0.16; 0.25; 0.48)

(0.51; 0.75; 0.83)

(0.55; 0.8; 0.86)

(0.32; 0.51; 0.69)

(0.36; 0.56; 0.72)

(0.32; 0.51; 0.69)

(0.37; 058; 074)

(0.16; 0.25; 0.48)

Weight of the HOW

Absolute weight fuzzy

(0.2, 6.67, 11.73)

(0.11, 0.25, 0.38)

(0.13, 0.29, 0.50)

(0.10, 0.23, 0.38)

(0.09, 0.18, 0.34)

(0.20, 0.44, 0.61)

(0.20, 0.45, 0.61)

(0.17, 6.60, 11.68)

(0.14, 0.31, 0.52)

(0.15, 0.33, 0.53)

(0.15, 6.57, 11.28)

(0.10, 0.21, 0.40)

Absolute weight·defuzzy

9.66

0.38

0.46

0.36

0.30

0.65

0.66

9.57

0.49

0.51

9.44

0.35

Relative weight

0.2943

0.0115

0.0140

0.0109

0.0090

0.0199

0.0201

0.2917

0.0148

0.0156

0.2877

0.0105

Ranking

Table 10

House of quality stage 2.

What is	Weights	Top management commitment	Communication	Information and analysis	Quality culture	Strategic planning	Supplier management	Team work	Training and education	Employee encouragement
Organizational flexibility	(0.2, 6.67, 11.73)	(0.32; 0.51; 0.69)	(0.55; 0.8; 0.86)	(0.13; 0.12; 0.44)	(0.36; 0.56; 0.72)	(0.36; 0.56; 0.72)	(0.12; 0.2, 0.45)	(0.32; 0.51; 0.69)	(0.12; 0.2, 0.45)	(0.16; 0.25; 0.48)
Data analysis	(0.11, 0.25, 0.38)	(0.36; 0.56; 0.72)	(0.36; 0.56; 0.72)	(0.54; 0.8; 0.87)	(0.36; 0.56; 0.72)	(0.32; 0.51; 0.69)	(0.13; 0.12; 0.44)	(0.16; 0.25; 0.48)	(0.13; 0.12; 0.44)	(0.16; 0.25; 0.48)
Workforce flexibility	(0.13, 0.29, 0.50)	(0.37; 058; 074)	(0.32; 0.51; 0.69)	(0.16; 0.25; 0.48)	(0.37; 058; 074)	(0.16; 0.25; 0.48)	(0.16; 0.25; 0.48)	(0.51; 0.75; 0.83)	(0.55; 0.8; 0.86)	(0.51; 0.75; 0.83)
Easy flow of information and communication	(0.10, 0.23, 0.38)	(0.32; 0.51; 0.69)	(0.51; 0.75; 0.83)	(0.55; 0.8; 0.86)	(0.13; 0.12; 0.44)	(0.12; 0.2, 0.45)	(0.51; 0.75; 0.83)	(0.37; 058; 074)	(0.16; 0.25; 0.48)	(0.13; 0.12; 0.44)
Indoor data	(0.09, 0.18, 0.34)	(0.37; 058; 074)	(0.36; 0.56; 0.72)	(0.51; 0.75; 0.83)	(0.12; 0.2, 0.45)	(0.32; 0.51; 0.69)	(0.16; 0.25; 0.48)	(0.12; 0.2, 0.45)	(0.12; 0.2, 0.45)	(0.12; 0.2, 0.45)
Business process flexibility	(0.20, 0.44, 0.61)	(0.55; 0.8; 0.86)	(0.51; 0.75; 0.83)	(0.12; 0.2, 0.45)	(0.16; 0.25; 0.48)	(0.36; 0.56; 0.72)	(0.55; 0.8; 0.86)	(0.32; 0.51; 0.69)	(0.13; 0.12; 0.44)	(0.12; 0.2, 0.45)
Organizational attitude to participation	(0.20, 0.45, 0.61)	(0.51; 0.75; 0.83)	(0.55; 0.8; 0.86)	(0.13; 0.12; 0.44)	(0.12; 0.2, 0.45)	(0.36; 0.56; 0.72)	(0.54; 0.8; 0.87)	(0.36; 0.56; 0.72)	(0.16; 0.25; 0.48)	(0.12; 0.2, 0.45)
Positive attitude to change, ideas	(0.17, 6.60, 11.68)	(0.54; 0.8; 0.87)	(0.51; 0.75; 0.83)	(0.12; 0.2, 0.45)	(0.32; 0.51; 0.69)	(0.36; 0.56; 0.72)	(0.16; 0.25; 0.48)	(0.37; 058; 074)	(0.37; 058; 074)	(0.13; 0.12; 0.44)
Manager support for innovation	(0.14, 0.31, 0.52)	(0.55; 0.8; 0.86)	(0.37; 058; 074)	(0.13; 0.12; 0.44)	(0.37; 058; 074)	(0.32; 0.51; 0.69)	(0.12; 0.2, 0.45)	(0.32; 0.51; 0.69)	(0.37; 058; 074)	(0.32; 0.51; 0.69)
Continuous improvement of staff training	(0.15, 0.33, 0.53)	(0.36; 0.56; 0.72)	(0.32; 0.51; 0.69)	(0.16; 0.25; 0.48)	(0.37; 058; 074)	(0.36; 0.56; 0.72)	(0.16; 0.25; 0.48)	(0.37; 058; 074)	(0.55; 0.8; 0.86)	(0.37; 058; 074)
Change management	(0.15, 6.57, 11.28)	(0.51; 0.75; 0.83)	(0.36; 0.56; 0.72)	(0.12; 0.2, 0.45)	(0.32; 0.51; 0.69)	(0.37; 058; 074)	(0.55; 0.8; 0.86)	(0.16; 0.25; 0.48)	(0.16; 0.25; 0.48)	(0.16; 0.25; 0.48)
Easy of change process	(0.10, 0.21, 0.40)	(0.32; 0.51; 0.69)	(0.32; 0.51; 0.69)	(0.12; 0.2, 0.45)	(0.36; 0.56; 0.72)	(0.32; 0.51; 0.69)	(0.16; 0.25; 0.48)	(0.13; 0.12; 0.44)	(0.16; 0.25; 0.48)	(0.13; 0.12; 0.44)
Weight of the HOW	Absolute weight fuzzy	(0.06, 1.28, 2.51)	(0.06, 1.3, 5.27)	(0.02, 0.36, 1.49)	(0.04, 0.96, 2.24)	(0.04, 1, 1.82)	(0.04, 0.48, 1.93)	(0.04, 2.47, 2.08)	(0.03, 0.65, 1.82)	(0.02, 0.41, 1.55)
	Absolute weight defuzzy	1.30	1.76	0.50	1.02	0.98	0.65	2.00	0.75	0.54
	Relative weight	0.14	0.19	0.05	0.11	0.10	0.07	0.21	0.08	0.06
	Ranking	3	2	9	4	5	7	1	6	8

2.8.5. Phase 5: Implementing a Two-Stage DEA Model in a Case Study

Knowledge as an asset must be exchangeable between human beings and can grow. On the other hand, organizations are in an environment full of change and transformation; to survive and continue their activities, they need to increase their knowledge and awareness of their employees and personnel.

Therefore, any constructive mechanism that provides such an opportunity for individuals to increase their knowledge and awareness will naturally contribute to the efficiency and effectiveness of the organization, helping the survival and continuity of the activity, as well as competition, in that organization. For this reason, knowledge-based companies were established to make a better use of knowledge in the field. Knowledge-based companies are those that employ university graduates; its main structure consists of specialists and the main factor in generating income in them is knowledge.

In this research, knowledge-based companies located in Khorramabad Science and Technology Park have been evaluated. Three questionnaires were designed in accordance with the final indices obtained from the previous stages of research in all three areas; the level of performance in each of the three areas was completed by asking the managers and experts of the companies under each unit; then, according to the two-stage data envelopment analysis method, the performance of the mentioned organizations has been evaluated. The results of the study of knowledge-based organizations are described in Table 11.

Table 11

Results of the performance of knowledge-based companies.

DMU	First stage efficiency	Second stage efficiency	Efficiency
DMU1	1	1	1
DMU2	1	1	1
DMU3	0.996	0.824	0.820704
DMU4	1	1	1
DMU5	1	1	1
DMU6	1	1	1
DMU7	1	1	1
DMU8	1	1	1
DMU9	0.929	1	0.929
DMU10	1	1	1
DMU11	0.952	0.999	0.951048
DMU12	1	1	1
DMU13	1	1	1
DMU14	1	1	1
DMU15	1	1	1
DMU16	1	1	1
DMU17	1	1	1
DMU18	0.952	0.824	0.784448
DMU19	1	1	1
DMU20	1	1	1

The results, as shown, revealed that 4 companies out of 20 surveyed had less than one efficiency; in other words, they were inefficient, and the remaining 16 companies could be recognized as efficient.

After evaluating the weak companies, the factors that have reduced their score were extracted and suggestions for improvement according to Table 12, were proposed to the managers of the companies.

Table 12

The cause of the organization’s inefficiency.

DMU	Efficiency⁸	The cause of the organization’s inefficiency	Management suggestion
DMU3	0.820704	The reason for the inefficiency of the unit is due to the lack of attention to the flexibility of the organizational structure, the lack of attention to change management and the flexibility of the business process. That is, the main problem is the lack of agility of the organization in order to implement TQM in the organization	As it is shown in column of inefficiency analysis and for each of inefficient units, the points of weakness can be extracted from the efficiency analysis. As a managerial suggestion, the indicators should be strengthened trough a plan and organizational road map must include the policies that assist the organization to be improved. However, it shouldn’t be neglected to have a plan in order to keep and improve the strength points. The indicators that are focused to be improved should be precisely considered by managers and should be evaluated in the signified periods of time
DMU9	0.929	The reason for the inefficiency of the unit is due to the specialization and independent functioning of the units, which was clearly seen in the organization. In fact, the units did not follow teamwork in any of the areas. If so, participation, flexibility and teamwork are the pillars of successful TQM implementation
DMU11	0.951048	Three indicators of the ease of the change process, information and analysis, easy flow of information and communication and data of the internal environment, as well as team work, have received low scores, which caused the inefficiency of the investigated unit
DMU18	0.784448	Indicators such as employee capability and training, continuous improvement and training of employees, training and retraining, and employee participation have been performed poorly and have caused the unit to become inefficient

⁸Efficiency numbers are obtained from Table 10.

Due to the knowledge-based nature of the organizations under study, young specialized staff, as well as up-to-date knowledge, the use of advanced and flexible technologies today can be the reason for this observation; the results also showed that most of the companies in question could use the three areas under study appropriately; this high efficiency has led to the successful implementation of TQM in the organizations under study.

3. Discussion, Managerial Implications, and Conclusions

3.1. Discussion

In this article, the relationship between the knowledge management success factors and organizational agility on the one hand, and the success factors of total quality management on the other was investigated. To this aim, first, each of these areas was surveyed; finally, the relation between these three areas was addressed using Group ISM, MICMAC, and FQFD.

Therefore, first, success factors of TQM and organizational agility were surveyed; then, the ISM method was used for screening; as Figure 4 shows strategy and goals are located at the basic level and organizational culture, structure, and employee motivation are located at the top. Figure 5 demonstrates organizational agility variables ranking. Among agility variables, the flexibility of organizational structure and data analysis form the basic level while the ability to answer environmental issues and the ability to change business goals are shown at the top and of TQM success factors ranking results are depicted in Figure 6. Top management commitment is located at the basic level and customer focus is located at the top. The basic or the lowest location of variables is dedicated to those which are the most paramount from the aspect of dependency of the other variables to them. It should be mentioned that they are the most influential variables of each attitude. After that, the MICMAC method was applied to select the factors that were independent and had the greatest impact on the successful implementation of each of the mentioned areas. MICMAC analysis is formed on the basis of the permutation power and dependency level (being affected) and the method provides the further possibility to consider each variable in its range. Figures 7–9 show the analysis results which include pendant and independent indices. They can be signified from their location in the MICMAC graph. In the next phase, the FQFD method was used in two steps.

In the first house of quality, the success factors of knowledge management have been selected as “whats” and weighted by experts. In the “hows” section, the agility of the organization has been placed. After solving the first fuzzy house of quality, the weight of organizational agility factors was determined and ranked in terms of their importance. In the second fuzzy house of quality, agility factors were considered as “whats” and total quality management success factors were classified as “hows;” finally, in the second house of quality, total quality success factors were weighed and ranked in terms of importance. The outcomes of this phase are the indicators’ weights that are applied as the controlled weights in the two step DEA approach. Eventually, in the fifth phase, the two step DEA approach is used to appraise the organizations’ performance in successfully implementing TQM, based on knowledge management approach and organizational agility.

It should be noted that all of the abovegiven cases were questioned, studied, and examined using a questionnaire filled by 40 university experts who had studied in the abovegiven field. Therefore, the obtained results do not depend on a specific industry and can be implemented in production and service organizations; then, by using the results obtained from the house of quality, the two-stage DEA model was designed by applying the weight control method.

3.2. Managerial and Policy Implications

Given that TQM, knowledge management, and organizational agility are three paramount attitudes which has a key role in organizational improvement. TQM as a management system says that being committed to the customers’ requirements leads to organizational improvement. On the other hand, a knowledge-based organization is a firm which counts knowledge as an asset and tries to implement the knowledge process based on the knowledge management infrastructures. To gain customer satisfaction as the eventual aim of each company, needs to committedly recognize and manage the customers’ needs. Besides, in the modern world of business, organizations should adjust quickly and revitalize the system, structure and policies in response to a rapidly-changing, uncertain, and chaotic environment. Thus, performance evaluation is a solution and also a tool that assists managers to have a perspective from the strengths and points of weakness. The results of assessing the organizational performance on the basis of the TQM which considers the knowledge management infrastructures and agile performance of the company can help the managers to draw the road map based on the customer needs, adaption to the environmental change and finally have the aimed quality to gain the customer satisfaction. So the proposed approach states that mathematical tools can appraise the organizational performance on the basis of TQM considering knowledge management approach and organizational agility.

3.3. Limitations

Undoubtedly, researchers face limitations in the way they conduct their work, and these may affect the results. Recognition of these limitations can lead to a better interpretation of research results and also, improvement of the quality of future research. The present study also faced some limitations discussed below. Using only the questionnaire tool to collect data can be problematic, as for more in-depth studies and a better understanding of variables and their relationships, other methods such as interviews, especially focused ones, could be used. It should also be noted that in addition to the factors affecting the success of TQM, knowledge management and organizational agility, other factors may also influence these two variables; these were considered in this study.

Given these limitations, in addition to the success factors of TQM, there may be other factors affecting these two variables, which were not addressed in this study. The suggestion is, therefore, that other researchers try to identify and measure other factors affecting them. Also, the structural equations method should be determined in relation to the correlation between factors; if there are other factors, the degree of correlation with the mentioned factors should be determined by structural equations.

There were some other limits, however, in this research; these include the lack of an integrated data collection system for the organizations and the unavailability of the integrated measurement of the efficiency of organizations. In this proposed model, the parameters are considered controllable. Therefore, it is suggested that the mentioned limitations are considered in future studies and more components are used in the structure of performance evaluation. Given the importance of evaluating, the use of the proposed model can have more effective results in the decision of managers in evaluating the performance of the organizations in successfully implementing TQM, based on knowledge management approach and organizational agility.

3.4. Case Study Conclusion

In the case study phase, a questionnaire was used to examine 20 knowledge-based companies located in Khorramabad Science and Technology Park. The information was completed by the managers and experts of the company. The obtained results were examined according to the two-stage DEA model and the efficient units were distinguished from the inefficient ones; the obtained results were provided to the managers of the companies. The factors that caused to decrease in the score of weak companies were identified and suggestions for improving the performance according to Table 11 were proposed.

3.5. Conclusion

Considering that TQM, knowledge management, and organizational agility are important factors in improving the performance of the organization. In this research, all three filed were considered and the influence of the factors of each filed was evaluated based on the proposed method. In this study, experts’ opinions were considered as the inputs and outputs, and the intermediate data were taken in the two-stage data envelopment analysis model, the results of this model are important for the managers of different companies in order to formulate and implement TQM, knowledge management, and organizational agility in order to improve business performance. Since organizations need to regularly and continuously improve their processes and products; so by increasing innovation which can be one of the aspects of knowledge management, they have better chances of survival and growth. These organizations should also seek to take advantage of new opportunities to improve their performance, which requires them to be agile to easily adapt to changes. The management of such organizations must also ensure the implementation of all aspects of TQM, knowledge management, and organizational agility. Therefore, the three factors of management support, team working, and organisational flexibility can be mentioned as the most effective success factors based on the proposed model. Since, in this research, the performance of the success factors of TQM, knowledge management, and organizational agility was studied only from the perspective of a number of managers, supervisors, and experts of the studied organizations, it is suggested that other employees of these organizations be surveyed and evaluated in the future studies.

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Abstract

Nowadays, any organization, in order to be aware of the desirability and quality of its activities, especially in dynamic environments, urgently needs an evaluation system to assess its system’s performance and efficiency. In this study, the performance of production and service organizations has been evaluated according to the effect of knowledge management success factors and organizational agility on the success factors of total quality management (TQM (total quality management)). Considering that the two areas of knowledge management and organizational agility are among those influential on TQM and each has been examined separately in the previous studies in relation to it, none of the previous studies has focused on all these three areas together. Therefore, in the present study, in addition to evaluating the performance of organizations based on the success factors of TQM, we seek to identify the influential factors and success factors of each of the three areas of knowledge management, organizational agility, and TQM; then, the impact of knowledge management and organizational agility on the success factors of TQM is evaluated. To express the above-given relationship, group interpretive structural modelling (ISM (interpretive structural modelling)) techniques have been used to rank the components of each domain; also, fuzzy quality function deployment (FQFD (fuzzy quality function deployment)) technique has been applied to find the weight and relationship of the three mentioned domains by examining the independent and interface variables of the previous step. The weights resulting from two-stage house of quality have been used as the weights for the design of the two-stage data envelope analysis (DEA) model by the weight control method. Finally, the above-given factors in knowledge-based companies located in Khorramabad Science and Technology Park have been studied and the results have been expressed.

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Title

Providing a Framework for Performance Evaluation of Organizations in Successfully Implementing TQM, Based on Knowledge Management Approach and Organizational Agility

Author

Irannejad, Neda¹; Shirouyehzad, Hadi¹

; Shahin, Arash²

¹ Department of Industrial Engineering, Najafabad Branch, Islamic Azad University, Najafabad, Iran
² Department of Management, University of Isfahan, Isfahan, Iran

Editor

Mojtaba Ahmadieh Khanesar

Publication year

2023

Publication date

2023

Publisher

John Wiley & Sons, Inc.

ISSN

10762787

e-ISSN

10990526

Source type

Scholarly Journal

Language of publication

English

DOI

https://doi.org/10.1155/2023/1857596

ProQuest document ID

2816620237

Providing a Framework for Performance Evaluation of Organizations in Successfully Implementing TQM, Based on Knowledge Management Approach and Organizational Agility

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