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

organization, in order to be aware of the desirability and quality of its activities,


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 frst time and every time." Terefore, in order to compete globally, the organizations must embrace total quality management concept and its practices and incorporate them into all of their activities efectively [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].
Te 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-frst 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 diferent production and services organizations, namely, information technology, hospitality, healthcare, education, banking, and recreation facilities to improve customer satisfaction and still been an ongoing efort. Tese measures have met with considerable success in them. Te strength of total quality management implementation in production and services organization lies on its best practices. Tere is a substantial body of literature that provides support for the notion that quality practices improve organization performance and customer satisfaction [4][5][6][7] as well as it leads to successful total quality management implementation in the organization.
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 fexibility [18]. One aspect of agility is fexibility. Creating an organization with agility requires the coordination and cooperation of knowledgeseeking staf. Te fve-facet nature of knowledge management in implementing agility has attracted the attention of researchers. Terefore, 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. Tere 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 eforts to make manufacturing and service organizations agile have sometimes led to fatal mistakes such as neglecting quality in the organizational acceleration process. Te category of quality has entered the feld of competition in the previous decades; it has established itself as a permanent element in all eforts 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. Terefore, in order to compete globally, the organisations must embrace TQM concept and its practices and incorporate them in all of their activities efectively [1]. Total quality management is both a philosophy as well as a set of guiding principles and practices. Trough 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 infuential 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. Te 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 classifcation) 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 fnd 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 twostage 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.

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 diferent 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 specifcation 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 efective 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 2 Complexity 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. Te results of this study revealed that there is a signifcant 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. Te 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 efective 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. Tey indicated that there is a signifcant and positive association between total quality management and knowledge transfer. Te criterion of this paper is performance and the fnding 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 infuence on frm operational and fnancial 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. Te data survey was carried out in Web of Science, Scopus, and SciELO databases. Te 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 identifcation of relationships between areas. Ong and Cheng [36] examine the link among agility, knowledge  Complexity management practices, and frm 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 staf efciency and on the performance of the company Barua et al. Te authors of [39] research the efect of TQM on organizational performance considering the mediating role of knowledge creation process. And fnally, 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. 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 frm 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 infuential to have the power of adaption with the environmental change and changing customers' needs. Tereby, 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 efciency 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 identifcation, indicators' weights calculation, and efciency numbers are precisely studied.

Teoretical Foundations of Research.
Because the three areas are examined in this article, frst, each of them is defned separately according to the experts' opinions.

Total Quality Management.
Te term total or comprehensive quality management (TQM) is one of the most common terms that have been recently used in the business feld. 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. Tis included the quality of work and processes. Tus, 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 decisionmaking based on facts, participation and collaboration, training, and continuous improvement [41]. TQM is an intelligent, peaceful, and continuous activity that also has an energetic efect on meeting the goals of the organization, ultimately leading to the customer's satisfaction, increased efciency, and enhanced competitiveness in the market. TQM can be regarded as an efective cost management system for continuous eforts to make improvement at all levels [6].

Total Quality Management Success Factors.
Almost after the initial design of TQM, the factors afecting 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.

Knowledge Management.
Economy is moving from the era of competitive advantage based on information to the era of competitive advantage based on knowledge creation. Te world is experiencing an age of knowledge in which knowledge is a basic commodity and knowledge fows 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 decisionmaking activities [3].

Critical Success Factors in Knowledge Management.
A wide range of factors can afect 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.
2.6. Agility. Te word agility means the ability to move quickly and easily and to be able to think fast and in a smart way. Tere are many defnitions for agility, but none of them contradicts or opposes the others. Tese defnitions generally refect the idea of speed and change in the workplace. However, given the novelty of the agility issue, there is no one-size-fts-all defnition. In fact, agility is the ability of an organization to (1) discover new opportunities for

2010
Structural equation modelling Empirically examined the relationship between knowledge management, total quality management, and innovation. Te results of this study revealed that there is a signifcant 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. Te other approach supposes that total quality management is a supporter for knowledge management  Knowledge management. 6 Organizational agility. 7 Balanced score card.
6 Complexity competitive advantage, (2) use assets, knowledge, and relationships to seize these opportunities, and (3) adapt to sudden changes in the business environment [42].

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. Te stages involved in conducting this research are in 5 phases and 14 steps, which are as follows.

Phase 1: Identifying Indicators.
In the frst phase, performance indicators are identifed; this is carried out during three steps. Tese three steps include a comprehensive review of the research literature through feld 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

Phase 2: Classifcation 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. Tis 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  Strategy and goals Akhavan et al. [56], and Karabage [58], Valmohamadi and Ahmadi [47] Step 6. Classifying and identifying the relationships between TQM implementation success factors using ISM

Phase 3: Analysis Based on Permeation Power and
Dependency. Te third phase deals with the MICMAC analysis based on the permeation power (infuence) and the degree of dependence (efectiveness) 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

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. Te reason for choosing independent and interface variables for all three domains is that the variables with more importance and efectiveness can be selected in all three domains because these variables have a high guiding power for the efectiveness of their domains. Ten, the prioritization and weighting of indicators are carried out using FQFD; this phase takes place in two steps; frst, a questionnaire is used to fll in the tables related to houses of quality and the tables are flled without considering the specifc industry and service. Te results obtained can be generalized to all industries and services. Tis section includes the following two steps, respectively: Step 10. Forming the frst-stage fuzzy house of quality, weighting, and prioritizing the indicators and knowledge management success factors with agility indexes using FQFD and flling 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 flling 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 fnally defuzzifed for use in the next stage and the relative weight of all indicators is calculated and specifed.

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.
Te 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. Tis 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 ≥ dv j in the form of weight constraints for the knowledge management feld in each of the parameters related to it. Tey are compared with each other in terms of importance; also, by using the formula wi ≥ d wj , the weight constraints for organizational agility and fnally, the formula ui ≥ d uj , the weight constraints for quality management success factors are obtained for each parameter. Te importance of the parameters is compared and fnally added to the two-stage DEA model in the form of constraints.
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. It should be noted in this research that all of numerical results cases were questioned, studied, and examined using a questionnaire flled by 40 university experts who had studied in the above feld. Te 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 feld of TQM, 8 Complexity knowledge management, or organizational agility; it was flled without considering the specifc industry and service. Terefore, the obtained results do not depend on a specifc 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. Te information was completed by the managers and experts of the company.

Phase 1: Identifying Indicators.
In this phase, the success factors of knowledge management, TQM, and organizational agility are identifed; this is carried out according to feld studies conducted in all three specifc areas.
Te results of studies in the feld 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.

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.  Table 6.
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.
As can be seen, the elements are at 5 levels.
(2) Assessing the Organizational Agility by ISM. Te results of the study of organizational agility parameters by ISM are described in Table 7. 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.
As can be seen, the elements are arranged at eight levels.
(3) Assessing the Success Factors of TQM by ISM. Te results of examining the parameters of TQM success factors by ISM are described in Table 8. Figure 6 shows the ranking diagram of the network of the interactions of TQM success factors resulting from the results of the above tables.

Tird 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. Tis division is based on the permeation power (infuence) and the degree of dependence (efectiveness) 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.
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.

Phase 4: Fuzzy
House of Quality. Now, according to the results obtained from the MICMAC analysis and the identifcation 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 frst-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 frst stage. Furthermore, weights obtained from the frst 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. Te reason for choosing independent and interface variables for all three domains is that the variables with more importance and efectiveness are selected in all these domains because these variables have a high driving force in the efectiveness 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  1, 9 1, 9 1, 9 5 12 Complexity a faculty member and also having published at least one article in the feld of TQM, knowledge management, or organizational agility; it was flled without considering the specifc industry and service. Te results obtained could be generalized to all industries and services, as can be seen in Tables 9 and 10.

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. Terefore, any constructive mechanism that provides such an opportunity for individuals to increase their knowledge and awareness will naturally contribute to the efciency and efectiveness 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 feld. 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. Tree questionnaires were designed in accordance with the fnal 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. Te results of the study of knowledgebased organizations are described in Table 11.
Te results, as shown, revealed that 4 companies out of 20 surveyed had less than one efciency; in other words, they were inefcient, and the remaining 16 companies could be recognized as efcient.
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.
Due to the knowledge-based nature of the organizations under study, young specialized staf, as well as up-to-date knowledge, the use of advanced and fexible 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 efciency has led to the successful implementation of TQM in the organizations under study.

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, frst, each of these areas was surveyed; fnally, the relation between these three areas was addressed using Group ISM, MICMAC, and FQFD. Terefore, frst, 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 fexibility of organizational structure and data analysis form the basic level while the ability to answer environmental issues and the ability to   Figure 6. Top management commitment is located at the basic level and customer focus is located at the top. Te 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 infuential 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 afected) 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. Tey can be signifed from their location in the MICMAC graph. In the next phase, the FQFD method was used in two steps.
In the frst 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 frst 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 classifed as "hows;" fnally, in the second house of quality, total quality success factors were weighed and ranked in terms of importance. Te outcomes of this phase are the indicators' weights that are applied as the controlled weights in the two step DEA approach. Eventually, in the ffth 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 flled by 40 university experts who had studied in the abovegiven feld. Terefore, the obtained results do not depend on a specifc 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.

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 knowledgebased organization is a frm 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. Tus, performance evaluation is a solution and also a tool that assists managers to have a perspective from the strengths and points of weakness. Te 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 fnally 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.

Limitations.
Undoubtedly, researchers face limitations in the way they conduct their work, and these may afect the results. Recognition of these limitations can lead to a better interpretation of research results and also, improvement of the quality of future research. Te 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 afecting the success of TQM, knowledge management and organizational agility, other factors may also infuence 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 afecting these two variables, which were not addressed in this study. Te suggestion is, therefore, that other researchers try to identify and measure other factors afecting 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.
Tere 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 efciency of organizations. In this proposed model, the parameters are considered controllable. Terefore, 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 efective 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.

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. Te information was completed by the managers and experts of the company. Te obtained results were examined according to the two-stage DEA model and the efcient units were distinguished from the inefcient ones; the obtained results were provided to the managers of the companies. Te factors that caused to decrease in the score of weak companies were identifed and suggestions for improving the performance according to Table 11 were proposed.

Conclusion.
Considering that TQM, knowledge management, and organizational agility are important factors in improving the performance of the organization. In this research, all three fled were considered and the infuence of the factors of each fled 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. Tese organizations should  DMU3 0.820704 Te reason for the inefciency of the unit is due to the lack of attention to the fexibility of the organizational structure, the lack of attention to change management and the fexibility of the business process. Tat 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 inefciency analysis and for each of inefcient units, the points of weakness can be extracted from the efciency 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. Te indicators that are focused to be improved should be precisely considered by managers and should be evaluated in the signifed periods of time DMU9 0.929 Te reason for the inefciency 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, fexibility and teamwork are the pillars of successful TQM implementation DMU11 0.951048 Tree indicators of the ease of the change process, information and analysis, easy fow of information and communication and data of the internal environment, as well as team work, have received low scores, which caused the inefciency 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 inefcient also seek to take advantage of new opportunities to improve their performance, which requires them to be agile to easily adapt to changes. Te management of such organizations must also ensure the implementation of all aspects of TQM, knowledge management, and organizational agility. Terefore, the three factors of management support, team working, and organisational fexibility can be mentioned as the most efective 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.

Data Availability
Te data used to support the study are included in the paper.

Conflicts of Interest
Te authors declare that they have no conficts of interest.