Excellence management practices, knowledge management and key business results in large organisations and SMEs: A multi-group analysis

Depósito de Investigación de la Universidad de Sevilla https://idus.us.es/ This is an Accepted Manuscript of an article published by Elsevier in European Management Journal, 2016 Volume 34, Issue 6, on December, available at: https://doi.org/10.1016/j.emj.2016.06.005 Copyright 2016 Elsevier. En idUS Licencia Creative Commons CC BY-NC-ND EXCELLENCE MANAGEMENT PRACTICES, KNOWLEDGE MANAGEMENT AND KEY BUSINESS RESULTS IN LARGE ORGANISATIONS AND SMEs: A MULTI-GROUP ANALYSIS ABSTRACT Following the Total Quality Management (TQM) philosophy and the knowledge management (KM) approach, this contribution aims to study the influence of process methodology and partner management on knowledge management, and the relationships between this variable with key business results. We also analyse the moderating role of organisational size on these previous relationships. The hypotheses proposed in our research model are tested on a sample of 225 Spanish companies with experience in TQM through evaluations by means of the EFQM Excellence Model. The partial least squares structural equations modelling (PLS-SEM) approach was used to test the research model. In order to assess the moderating effects of organisational size, we adopt a multi-group approach using two subsamples with large firms and small and medium-sized enterprises (SMEs). Our findings indicate that the use of process methodology and the involvement of partners are key factors for KM to have a significant impact on the key results of the business, both strategic and operational. Moreover, the organisational size is determinant when analysing the effect of process methodology and partner management on KM. In this sense, process methodology has a greater effect on KM in the SMEs. On the contrary, the relationship between partner management and KM is more intense in large firms. Finally, it is corroborated that KM can be effective and improve the key business results independently of the size of the organisation. Key words: Knowledge management, TQM, EFQM Model, organisational size, PLS-SEM, multi-group analysis, moderating effects. 1. INTRODUCTION The literature contributes evidence of relationships and synergies between total quality management (TQM) practices and knowledge management (KM). In this sense, the more studied topics refer to how quality management favours knowledge creation (Asif et al., 2013; Linderman et al., 2004), knowledge transfer (Molina et al., the 2007) and the complete process of creation, transfer, sharing and application of knowledge (Ooi, 2009). In addition, research shows how the integration of both management approaches can strengthen learning (Choo et al., 2007; Loke et al., 2012), innovation (Honarpour et al., 2012), as well as affect other variables related more directly to organisational performance such as customer satisfaction, revenue growth, employee productivity or profit growth (Tarí and García-Fernandez, 2013). Various studies (Bou-Llusar et al., 2009; Calvo-Mora et al., 2014; Kim et al, 2010) show how excellence models offer a suitable reference framework for the implementation of TQM. Although, as Gómez et al. (2015) indicate, Excellence Models and TQM are not the same frameworks, but follow a similar path, and it can be expected that a company with high scores in Excellence Models will have high odds of being a TQM company. Both systems provide a means to improve performance and to guarantee continuous improvement and competitiveness. With time, Excellence Models have become more complete management frameworks, with increasingly greater scope. In addition to aspects typical of TQM philosophy, they approach other aspects such as corporate social responsibility, knowledge management, human resources management and strategic planning. Benavides and Quintana (2005), Martín-Castilla and Rodriguez-Ruiz (2008) and Westerveld (2003) maintain that similarities exist between KM activities and the evaluation criteria of the EFQM Model or other Excellence Models. Thus, Benavides and Quintana (2005) make a theoretical proposal, on how the ‘agents’ criteria of the EFQM Model favour the KM process, and how the ‘results’ criteria enable the evaluation of this process. In addition, they conclude how the EFQM Model constitutes an ideal instrument of support to KM, explicitly recognising that to reach maximum performance, organisations need to manage and to share their knowledge in the context of a culture, oriented towards learning, innovation and continuous improvement. Martín-Castilla and Rodriguez-Ruiz (2008) try to show how the EFQM Model offers a strategic framework for knowledge management and innovation, which focuses on a conceptual analysis of the relationships between excellence and intellectual capital. The study shows that intellectual capital is taken into account in the overarching framework of the EFQM Model. In this regard it is possible to define relationships between each component of the intellectual capital navigators, and those coming from the model. The authors consider that the intellectual capital perspective is a key element that runs horizontally across the criteria of the EFQM Model. Westerveld (2003) maintains that the EFQM model constitutes an element of stimulus and fundamental support to KM, and that important correspondences exist, between the activities of KM, and the fundamental concepts and criteria of the EFQM model. However, there is a lack research that empirically analyses the suitability of the EFQM Model as a reference framework for a KM implementation in SMEs and large organizations and how it can positively influence the key results of the organisation. Research studies that use a horizontal reading of the EFQM Model to analyse questions related to TQM and KM. The horizontal reading of the EFQM Model through the transverse axes is a powerful tool for analysing important concepts of the organisation (Fernández-Santos, et al., 2010), although it is not as obvious as the traditional through the criteria and the sub-criteria. Thus, the EFQM Model is not a set of unconnected criteria. On the contrary, it presents a series of inter-related practices that offer greater continuity and coherence (Martín-Castilla and Rodriguez-Ruiz, 2008). The interpretation of the relationships between the criteria and sub-criteria lies in the so-called transverse axes, or horizontal reading of the model, as opposed to its traditional vertical reading. The existence of these axes implies adopting a systemic approach to management (Rusjan, 2005). This is to say, we will not be able to reach global improvements in the organisation, if we do not simultaneously approach the different aspects of the criteria of the model as interdependent elements (Calvo-Mora et al., 2015). In this study, the transverse analysis of the EFQM Model allows KM to be analysed in those organisations which have been subjected to the assessment process, taking into account that KM is not contemplated in any specific criterion of the model. On the contrary, the aspects related to knowledge are considered in different sub-criteria throughout the EFQM Model. More specifically, it will be attempted to analyse two important aspects for the effectiveness of KM: process management methodology (Asif et al., 2013; Hsu and Shen, 2005) and the management of partners (Ju et al., 2006). In this regard, the value of products and services for the customers should be optimised, through process management methodology. Thus, documented information (procedures, technical instructions and records) is generated, which is a way of systematising the what, who, how and when, etc., of what is done in the organisation (a formalisation of the organisational report). In addition, this documented information constitutes a means of contributing evidence of the results that are being reached. This source of information and knowledge must be known by the management to improve the decision making process and by the workers to undertake their work more efficiently (internal knowledge). On the other hand, the management of partners is crucial to obtain a sustainable profit; more specifically, we refer to the need to establish networks to identify opportunities for potential alliances with partners. This type of knowledge is also necessary to compete, which is why it is necessary to favour the transfer of knowledge between organisations. In addition, the effectiveness of KM will be analysed through its impact on the key results of the business. The results are a basic element of the knowledge accumulated in the organisation, which not only serve to mark the state, speed and course reached by the continuous improvement of the quality in the organisation, but also, and even more importantly, guides us towards the desired future or destination in permanent adaptation to the context of each moment. Finally, the previous practices and results can be seen to have been conditioned by the size of the organisation. Thus, the organisational characteristics of SMEs, such as informal processes, person-to-person contact, limited human resources, limited financial assets, limited access to technology or shortage of time, could encourage the management of their knowledge (Durst and Edvardsson, 2012; McAdam and Reid, 2001). Desouza and Awazu (2006), Hutchinson and Quintas (2008) and Wong and Aspinwall (2005) identify a series of peculiarities of KM in SMEs: (1) Predominance of socialisation activity within the process of knowledge creation. In SMEs, most of the knowledge is held in the mind of the proprietor and some key employees, instead of storing it formally. In addition, management and employees maintain more direct and constant contact with each other, which facilitates knowledge transfer; (2) In the SMEs, their members have broad and deep levels of common knowledge. It is knowledge that is assumed and interiorised by the employees and management. It helps mark the behaviour in the workplace and provides a common reference framework that ensures communication, transfer and application of the knowledge; (3) The companies must acquire and apply new knowledge with the purpose of reaching a sustainable competitive advantage. A form of obtaining it is to create, generate, develop and construct the knowledge internally. However, most of the SMEs present limitations when putting these types of processes into practice. Therefore, the alternative is to capture the knowledge from external sources, working directly and co-operating with the customers, suppliers, competitors, professional associations and partners; (4) In environments of high competitiveness and mobility of employees, the loss of knowledge can be a serious problem. However, in SMEs this is not seen as a real problem, due to their high flexibility, their common knowledge base or to their capacity to retain employees, thanks to the close social bonds between them; (5) In SMEs, KM is carried out through work meetings, observation, in training courses or informal meetings, which is to say, that they manage knowledge from a more person-focused approach than a technological aspect. In this way they are able to save time and resources. For that reason, the present research attempts to reach the following objectives: 1. To verify the reliability and validity of the horizontal reading of the EFQM Model to study key aspects of quality management and KM. 2. To analyse the relationships between three transverse axes of the EFQM model (process management methodology, partner management and knowledge management) with key business results. 3. To study the moderating effect that organisational size can play between the relationships that exist between the previous variables. In order to answer the proposed questions, this paper is organised as follows. Firstly, the literature on QM and KM is analysed. Secondly, the research model and the hypotheses are presented. This is followed by the research method and results. Finally, the conclusions are presented and the limitations and future research of the study are described. 2. THEORETICAL FRAMEWORK 2.1. Total quality management and knowledge management Total quality management is a comprehensive management philosophy oriented towards achieving excellent results in relation to stakeholders (Prajogo and McDermott, 2005). The principles and practices for TQM to produce the desired effects on an organisation’s performance are called critical factors. Among those most studied in the literature are: leadership and top management commitment, strategic planning, continuous improvement, customer focus, data-based management, human resources management, process management and control and supplier management (Sila and Ebrahimpour, 2003). Moreover, there is evidence in the literature on the positive effect of this management philosophy on organisational performance (Flynn et al., 1995; Kaynak, 2003; Prajogo and Sohal, 2006; Rahman and Bullock, 2005; Sila, 2007). Bou-Llusar et al. (2009), Calvo-Mora et al. (2014) and Kim et al. (2010) show how excellence models offer a suitable reference framework that facilitates the implementation and improvement of TQM. In Europe, the EFQM model is the best-known and most widespread reference when introducing and improving a TQM system. Bou-Llusar et al. (2009) and Gómez et al. (2015) point out how the use of the EFQM model guarantees that the TQM practices employed, form a coherent system. With respect to KM, it has been gaining importance in the field of strategic management. According to the knowledge based approach, it is the most important strategic resource of companies. This is because the knowledge based resources are generally difficult to imitate and socially complex (Denford and Chan, 2011; Helfat and Winter, 2011; Teece, 2014). This approach suggests companies exist to create, share and receive benefit from their knowledge (Ipe, 2003). Thus, companies that are successful are those that can identify, value, create and develop their knowledge assets (Spender and Scherer, 2007; Kiessling et al., 2009). In the same way that knowledge is considered a strategic resource, knowledge management is considered a critical capacity for organizational success (Chou, 2005; Chen and Huang, 2009; Van den Hooff and Huysman, 2009). This fact has meant taking a qualitative and quantitative step in the management of organisations, which see the need to implement knowledge management systems to increase their competitive capacity. The knowledge management systems are a set of infrastructures and tools that support the activities of knowledge management (Alavi and Leidner, 2001), that is to say, they provide a context that facilitates the creation, storage, transfer and application of knowledge. Meso and Smith (2000) differentiate between technical infrastructure (information technologies) and that of a social and cognitive nature (leadership, organisational structure, human resources and the culture). In addition, there is not one sole valid model for managing knowledge, but it depends on the theoretical vision adopted and the context in which it is applied. In agreement with existing literature, TQM and KM share factors considered as key for the success in the implementation of both management approaches. For example, motivated workers (Alazmi and Zairi, 2003; Davenport et al., 1998), employee training, involvement and empowerment, teamwork (Moffett et al., 2003; Ryan and Prybutok, 2001), leadership and senior management support and commitment (Conelly and Kelloway, 2003; Davenport et al., 1998; Moffett et al., 2003; Yeh et al., 2006), friendly and open organisational culture (Moffett et al., 2003; Ryan and Prybutok, 2001; Yeh et al., 2006), processes and performance measurement (Alazmi and Zairi, 2003; Hung et al., 2005), benchmarking (Hung et al., 2005; Moffett et al., 2003) and information systems structure (Alazmi and Zairi, 2003; Hung et al., 2005). Linderman et al. (2004) go further, by considering that TQM and KM seek the same objective: to create and use tacit and explicit knowledge more efficiently, at individual and collective level, to continuously improve and to obtain better results. Molina et al. (2007) emphasise the importance of technical and social aspects of quality and KM so that the knowledge transfer process is efficient. Asif et al. (2013) show how a series of TQM practices (continuous improvement, statistical control of quality, management of client satisfaction, process improvement techniques, individual learning and the methods of new product development) favours the process of knowledge creation. In short, knowledge management processes do not make sense if they are not developed systematically. To be competitive, organisations need continuously to generate and assimilate knowledge and new capabilities. Therefore, TQM as a management philosophy based on continuous improvement, innovation and learning can serve as a context and support for the start-up and later development of a knowledge management process. 2.2. Vertical and horizontal interpretation of the EFQM model The aim of the EFQM Model is to support organisations to achieve business excellence through continuous improvement, learning and innovation. The model presents a non-prescriptive working framework which analyses the relationships between what an organisation does and the results that it is able to attain, assuming that there are different approaches to attaining excellence (EFQM, 2013). The EFQM Model sets out the management of excellence from a conceptual structure, based on a series of Fundamental Principles of Excellence upon which all the later development of the elements of the Model is based. Nevertheless, when making a detailed description of the implications of excellent management, the Model considers three levels of detail:  Criteria (Enablers and Results): These represent essential constructs to be able to describe the actions and consequences that must derive from an authentic excellent management in a comprehensible manner and adjusted to the reality of the organisations. These criteria are leadership, policy and strategy, partnerships and resources, people and process, and the four remaining criteria reflect the results which the organisation attains, concerning their customers, employees, society and other key results.  Sub-criteria: In each criterion, the Model sets out a series of sub-criteria which detail the elements that shape the construct on which they depend. Their purpose is to provide a more specific and practical guide that translates what each criterion defines at more operational levels. If we understand that a criterion represents an important construct in management terms, the sub-criteria can be understood as components of the said construct which allow a greater applicability of the proposals of the Model.  Elements to consider: In its maximum level of detail, the Model gives examples, without pretensions of being exhaustive, of what each criterion and its corresponding sub-criteria mean in very specific terms of actions or consequences that should be seen if we were observing an organisation which applies an excellent management. Two immediate conclusions can be drawn from the description of the general structure of the Model: Firstly, the criteria, on which the development of the Model is based, cannot be considered in a compartmentalised manner, and it should certainly not be understood that a description of the full complexity involved in the management of an organisation could be made solely with those criteria. Only those best suited to serve as a conceptual framework for the description of excellence are considered. It could be said that these 9 criteria, represent “a vertical” perspective from which to approach excellence in management. Secondly, the consideration of other possible constructs important for management oblige a horizontal reading of the Model, based on the meaning of each of its 32 sub-criteria. Each of these horizontal readings (“transverse axes”) allows the consideration of new factors that allow management excellence to be approached from other perspectives (Fernández-Santos et al., 2010). In comparative terms, the vertical structure of the model would be the equivalent of that used to describe an organisation on the basis of its organisational units or departments. On the contrary, the analysis of other possible management components, through axes, would be equivalent to the processes executed daily in an organisation and which connect the activities or functions of departments. Thus, it is easy to fall into the simplification of seeing the Model as the sum of nine criteria without apparent connection between them. Nevertheless, it is impossible to approach the whole complexity of management without analysing other constructs or axes (Martín-Castilla and Rodriguez-Ruiz, 2008). These axes involve a more refined reading of the different sub-criteria, seeking in each those ideas that could be extracted for a better knowledge of the components of the construct that is attempted to be approached. Figure 1 shows three of these axes: knowledge management, process management methodology and partner management. ---------------------- Figure 1 --------------------- If we assumed that the consideration of each and every one of the possible elements involved in excellent management would be unapproachable, we must conclude that the analysis of the Model on the basis of transverse axes supposes a creative research work that obliges a response to the following questions: (a) In each case, which sub-criteria of the model relate to the new construct to be studied (axis), and what knowledge is contributed with respect to that question? (b) For a more correct understanding of the new construct under study, how is each of these sub-criteria interconnected with the others? 2.3. Using transverse axes of the EFQM model for knowledge management Benavides and Quintana (2005), Calvo-Mora et al. (2015), Martín-Castilla and Rodríguez-Ruiz (2008) and Westerveld (2003) maintain that the EFQM Model constitutes an element of stimulus and fundamental support to KM, and that there are important relationships between the fundamental activities of KM and the fundamental concepts of excellence and criteria and sub-criteria of the EFQM Model (Table 1). ---------------------- Table 1 --------------------- Nevertheless, there is no criterion that approaches KM through the vertical reading of the Model, although a transverse axis can be identified for KM. In addition, other axes can be found, such as communication, social responsibility, creativity and innovation, human resources, process management methodology or partner management (EFQM, 2003). Indeed, these last two axes (process management methodology and partner management) are practices characteristic of excellent management that can favour and strengthen the effect of knowledge management on the results (Calvo-Mora et al., 2015). Process management methodology (PMM) is a critical factor of KM, because the knowledge of the organisation becomes formalised and more explicit through processes, which favours its creation, transfer and diffusion (Asif et al., 2013; Hsu and Shen, 2005; Molina et al., 2007; Ooi, 2009). Partner management (PM), apart from the information derived from the internal processes, the management of the information and knowledge which comes from them is increasingly important (Ju et al., 2006; Molina et al., 2007). These two axes contemplate different aspects, although complementary to the Process and Partnerships and Resources criteria. Thus, the Process criterion makes two essential statements for the description of excellent management: (1) independently of the departmental structure of an organisation, the identification and management of their processes become key elements for excellence; (2) within the whole spectrum of processes that unfold daily in an organisation, those that have direct involvement with the products and services provided to the customers must have special attention, as they are considered to be key processes. However, there is no exhaustive description of the complete development of all the activities for an excellent process management in the Process criterion itself, but it is extended to others. For example, if referring to the establishment of owners (leaders) as an essential phase of process management, this activity appears among the sub-criteria of the Leadership criterion. In short, for a complete analysis of process management, an axes based analysis becomes necessary, that is to say, apart from considering some sub-criteria of the Process criterion (those of a more general character), it is also necessary to consider others included in different criteria of the model, such as in the case mentioned for “Leadership”. On the other hand, criterion 4 (Partnerships and Resources) shows that, when using the term “Resources” with excellence criteria, we must extend our field of vision to understand that not only must the tangible elements linked to the activity of the organisation have space within the construct, but also those of an immaterial character, fundamentally those associated with information and the bonds, contacts, influences or formal alliances with third parties. Both elements need excellent management in consonance with the strategy and policies of the organisation. Although most of the questions related to the excellent management of the material resources of an organisation are included in the sub-criteria of criterion 4, there are many which concern immaterial elements and, especially the theme of alliances, are dispersed through the remaining criteria of the Model. 3. RESEARCH MODEL AND HYPOTHESES The research model is based on the extent to which the organisation can improve its key business result (KBR) through KM, for which it will have to apply PMM, as well as having the participation and involvement in the process of its strategic suppliers and partners (PM). The KBR are analysed as a dependent variable. This variable attempts to determine what benefits the organisation is reaching in relation to the planned economic-financial, market and process results and the efficiency in the management of the tangible and intangible resources. Moreover, the relationship between these variables may be affected by organisational size. ---------------------- Figure 2 measurement invariance”. ---------------------- Table 5 --------------------- Table 6 shows the results of the structural model assessment. Consistent with Hair et al., (2013), bootstrapping (5000 resamples; one-tailed Student t distribution with (n-1) degrees of freedom) was used to generate standard errors, t-statistics, and percentile 95% confidence intervals. This analysis was carried out both for the total sample and for the two subsamples. The three main paths are significant, except for the PMM and KM relationship in the large companies subsample. The endogenous constructs achieve R2 values between 0.392 and 0.536 for KBR, considering those values of moderate character (Chin, 2010). In the case of the knowledge factor, R2 varies between 0.785 and 0.848. In this case, this is higher than the substantial level indicated by Chin (2010). For the three considered models (total sample, SMEs and large companies), the results reflect that neither the sector, nor the ownership, have a direct significant effect on KBR, thus confirming the robustness of the proposed model and the solidity of the obtained results (Table 6). The predictive relevance of the theoretical/structural model is assessed with the cross-validated redundancy index (Q2) for endogenous constructs. Since all Q2 values are greater than 0, evidence was found that our model has predictive relevance (Chin, 2010). In addition, Table 6 shows the amount of variance that each antecedent variable explains on each dependent variable, the greater value being obtained in the case of the suppliers/partners variable when explaining the explained variance of the KBR (67%). ---------------------- Table 6 --------------------- Also, Table 6 shows that the indirect effects are significant for the whole sample, with significant differences being generated, according to the size of the company, in the effect generated by PMM on KBR through KM. Therefore, in small companies, designing a good PMM from the point of view of the application of the EFQM model can be vital for knowledge generation and obtaining good results. In the PM-KM-KBR relationship, the size did not generate significant differences (Table 6). Once the metric invariance was guaranteed in the measurement model and the structural model tested, the multi-group analyses were performed for the hypotheses 4–6, allowing the testing of the moderating role of organisational size on the relationships included in the research model. For this, the permutation test was mainly used (5,000 permutation run; two-tailed 0.05 significance level), showing the existence of significant differences (p-value<0.05) generated by the size in the PMM-KM (H4) and PM-KM (H5) relationships, there being no significance in the KM-KBR (H6) relationship (Table 7). Also, and in a complementary manner, a parametric approach is applied. The moderating effect is examined using a t-test with pooled standard errors. This approach requires the data to be distributed normally and/or that the variances of the two samples are not too different from one another (tParam {EV}). In the case of assuming there are different variances for the two samples, a Welch-Satterthwait test (tParam{NEV}) can be applied (Sarstedt et al., 2011). Both tests have been applied in the comparison, obtaining similar results (Table 7). ---------------------- Table 7 --------------------- The same result is derived from the application of the non-parametric approaches (the bias –correct 95% confidence intervals). In this case, if the parameter estimate for a path relationship of one group (Table 6) does not fall within the corresponding confidence interval of another group (Table 7) and vice versa, there exists no overlap and it can be assumed that the group-specific path coefficients are significantly different with regard to a significance level α (Sarstedt et al., 2011). This condition is fulfilled for H4 and H5, but not confirmed for H6. Finally, the overall model was measured through standardized root mean square residual (SRMR) composite factor model (Henseler et al., 2014). Thus, the values obtained for the complete model (0.075) for large companies model (0.073) and SMEs model (0.079) give below the limit recommended value of 0.08 (Hu and Bentler, 1999). 6. DISCUSSION AND CONCLUSIONS The results support the reliability and validity of the measurement model (Tables 2 and 3), both for the model that represents the whole sample of companies and for the subsamples that represent the SMEs and the large companies. In addition, the property of metric invariance is verified, that is to say, the measurement model does not change when dividing the original sample into two subsamples (Tables 4 and 5). This result supports the universal character of the Excellence Models that can be used as reference for evaluation and improvement by both large organisations and by SMEs (EFQM, 2013). Moreover, the results confirm the high predictive power (R2) and high predictive validity (Q2) of the EFQM model as a framework for the implementation and integration of TQM and KM practices. As can be seen in Table 6, the KM and KBR variables display substantial R2 values (R2 > 0.67) according to Chin (2010), both for the whole sample and for the two subsamples representing the SMEs and large companies. Moreover, the endogenous variables present Q2 coefficient values above 0, specifically, they display values of Q2 > 0.34. With respect to the direct effects represented by the H1, H2 and H3 hypotheses, firstly it is highlighted (Table 6) that PMM plays a central role in the complete model, and in that representing the SMEs, where there is a significant direct effect on KM (H1). In addition, PMM is used with more intensity in the SMEs (0.344) than in large organisations (0.113). In this sense, in the model that represents large companies, the relationship between PMM and KM, although positive, is not statistically significant. In addition, this causes the indirect effect between PMM, KM and KBR to lack statistical significance. This may be due to PMM being focused mainly on the key processes, which are those that have a direct involvement with the products and services supplied to the customers. Thus, the SMEs have greater proximity, contact and knowledge with customers, which is why their effect on KM will be stronger and more direct than in the large companies (Desouza and Awazu, 2006; Wong and Aspinwall, 2005), Moreover, this result may be due to greater collaboration and cooperation between employees in the SMEs when putting key processes into practice (Durst and Edvardsson, 2012), and because the SMEs are more focused on continuous improvement in their activities and processes. In this regard, large companies can dedicate more resources to product innovation, services, processes or technology than the SMEs (McAdam and Reid, 2001). Continuous improvement is based on the human factor and supposes small but constant changes that do not require heavy investments or monetary expenditure. On the other hand, innovation involves drastic changes in the processes and activities of the organisation, which requires time and an important amount of resources, which is more feasible for large organisations. The importance of this factor is also reflected in the high percentages of variance (R2) of the KM variable in both the complete model (20.4%) and in that representing the SMEs (28.28%). Secondly, the management of the main partners of the organisations is also a critical variable for KM within the framework of the EFQM model. Thus, the direct effect between PM and KM (H2) is statistically significant both in the model that represents all the companies and in the models segmented according to size (Table 6). In addition, management in large companies emphasises the importance of PM for KM (0.826). This value is far beyond that obtained for this same relationship in the SMEs (0.581). For that reason the indirect effect between these variables and KBR is statistically significant (Table 6). This crucial role in the model is also observed when analysing the percentage of variance accounted for by the endogenous KM variable in the complete sample (54.13%), as well as in those of SMEs (46.71%) and large companies (67.65%). Thirdly, it is necessary to emphasize how the specific efforts that companies make to manage their knowledge have a direct and significant effect on the KBR (H3). This effect is confirmed both for the whole sample and for the subsamples that represent the SMEs and large companies (Table 6). In addition, no important differences exist in the values of the indirect effects in this case (PMMKMKBR and PMKMKBR), although the relationship between KM and KBR is more intense in the SMEs (0.722) than in large companies (0.611), explaining up to 52.13% of the variance of the KBR variable. Finally, if the results of the moderating effect that the size variable exerts on the direct relationships between the variables of the model are analysed, it is seen that there are significant differences (Table 7) in the relationships between PMM and KM (H4) and between PM and KM (H5). These differences corroborate that indicated in the literature on the distinctive features presented by the management of SMEs with respect to large companies. More specifically, PMM has a greater effect on KM in the SMEs. This may be due to the smaller size and the lower level of specialisation of the workforce, causing a greater probability of collaboration and cooperation between the employees, which to a large extent favours the processes of creation, transfer and application of knowledge. In addition, as noted previously, the SMEs are more focused on continuous improvement through processes and not as much towards technological innovation (McAdam and Reid, 2001). On the contrary, the relationship between PM and KM is more intense in large companies. In this sense, the large companies have greater negotiating power over their main partners (Gray and Mabey, 2005) and have more financial means to know the movements and actions of competitors and other stakeholders. Finally, it is corroborated that KM can be effective and improve the KBR independently of the size of the organisation, when there are no significant differences between both samples. Managerial and practical implications Organisations can use the vertical reading of the EFQM Model with the objective of identifying areas of improvement in each of the nine established criteria. Nevertheless, this is not the excellence management philosophy of the EFQM Model. On the contrary, we can identify the existence of an obvious first horizontal reading among the agents' criteria and the results criteria. For example, when we analysed the People criterion, we must simultaneously analyse the Results in the people criterion. Nevertheless, there are many other horizontal readings, which are not so obvious, and which establish relationships between the subcriteria of the Model (transverse axes). From the point of view of management, the use of the axes can be considered a powerful management and improvement tool, as it allows us to analyse important concepts for excellent management using different sub-criteria of the criteria that compose the EFQM Model. Thus, if an organisation tries to analyse how it is managing its knowledge, in the context of an excellent management, it must study three axes: the methodology of processes, the management of partners and the management of knowledge. In addition, the horizontal reading of the Model allows an analysis from the perspectives of leadership, policy and strategy, people, alliances and resources and processes (Figure 1). Specifically, we will be able to identify the areas of improvement of knowledge management, with respect to concrete aspects (sub-criteria) of policy and strategy (2b), people (3b), and the alliances and resources of the organisation (4e). With respect to process management methodology, we must analyse the areas of improvement in leadership (1b), policy and strategy (2b), and processes (5a and 5b). In order to identify the areas of improvement in Partner Management, we must focus our attention on leadership (1c), policy and strategy (2a and 2c) and the alliances and resources (4a). Finally, the proposed model adds the relationships and synergies between these three key elements of excellent management and results, that is to say, we can also analyse the effectiveness of the actions undertaken. In addition, the multi-group analysis allows us to orient the KM based on whether the organisation is small, medium or large in size. Thus, in both types of organisations (SMEs and large), the development of alliances and cooperation with partners is important for KM, although this aspect is more determinant in large companies. Nevertheless, in the SMEs, the management of internal knowledge (PMM) is more important than in large companies. Finally, suitable KM is going to have a positive and significant effect on the operational and strategic results of the organisation, independently of the size of the organisation. Limitations and future research lines The interpretation of the results and conclusions of this study are subject to a series of limitations, principally of a methodological character. The first limitation is due to the technique used for the proposed model: structural equation modelling, which assumes the linearity of relationships between the latent variables. The second is related to the notion of causality. Our study considered a soft modelling approach oriented more towards prediction than causality. The third, due to the eclectic nature of knowledge, its management is affected by a multitude of factors, and not all of them could have been considered in the research. The fourth is that, when interpreting the results, it is necessary to take into account that the sample corresponds to Spanish companies, to a specific culture of excellence and knowledge management, and therefore cannot be generalised. Finally, the research design is cross-sectional instead of longitudinal. In this case, with a longitudinal study it would be possible to analyse the effects of excellence practices and knowledge management on the results in more detail. Some of these limitations allow us to open future lines of research: (1) To introduce new relationships between the excellence practices in the conceptual model, as well as between those and the results; (2) To analyse the influence of other possible transverse axes of the EFQM Model, such as communication, creativity and innovation, human resources or corporate governance on knowledge management; (3) To study the possible relationship of excellence practices and knowledge management in other types of results, for example related to people, customers or the company; (4) To analyse, according to company size, the influence of KM on the different types of results (operational and strategic), that form the KBR construct. REFERENCES Afonso, A., Roldán, J.L., Sánchez-Franco, M.J., & González, M. (2012). The moderator role of Gender in the Unified Theory of Acceptance and Use of Technology (UTAUT): A study on users of Electronic Document Management Systems. 7th International Conference on Partial Least Squares and Related Methods, At Houston, Texas, USA Alavi, M., & Leidner, D.E. (2001). Review: Knowledge management and Knowledge management systems: conceptual foundations and research issues. MIS Quarterly, 25 (1), 107-136. Alazmi, M. & zairi, M. (2003). Knowledge management critical success factors. Total Quality Management, 14(2), 199-204. Aragón-Sánchez, A. & Rubio-Bañon, A. (2005). Factores asociados con el éxito competitivo de las PYMES industriales en España. Universia Business Review, cuarto primestre, 36-49. Asif, M., de Vries, H.J., & Ahmad, N. (2013). Knowledge creation through quality management. Total Quality Management & Business Excellence, 24 (5-6), 664-677. Benavides, C., & Quintana, C. (2005). Procesos y sistemas organizativos para la gestión del conocimiento. El papel de la calidad total. Boletín Económico del ICE. 2838, 37-52. Bou-Llusar, J.C., Escrig-Tena, A.B., Roca-Puig, V., & Beltrán-Martín, I. (2009). An empirical assessment of the EFQM Excellence Model: Evaluation as a TQM framework relative to the MBNQA Model. Journal of Operations Management, 27 (1), 1-22. Calvo-Mora, A. Picón, A. Ruíz, C. & Cauzo, L. (2014). The relationships between soft-hard TQM factors and key business results. International Journal of Operations & Production Management, 34 (1), 115-143. Calvo-Mora, A., Navarro-García, A., & Periañez-Cristobal, R. (2015). Project to improve knowledge management and key business results through the EFQM excellence model. International Journal of Project Management, 33(8), 1638-1651. Chen, C.-J. & Huang, J.-W. (2009). Strategic human resource practices and innovation performance-The mediating role of knowledge management capacity. Journal of Business Research, 62(1), 104-114. Chin, W.W. (2000). Multi-group analysis with PLS. Retrieved from http://disc-nt.cba.uh.edu. Chin, W.W. (2010). How to write up and report PLS analyses. In Esposito Vinzi, V., Chin, W.W., Henseler, J., & Wang, H. (Eds.), Handbook of partial least squares: Concepts, methods and applications (pp. 655–690). Berlin, Germany: Springer-Verlag. chin/plsfaq/multigroup.htm. Chin, W. W., Mills, A. M., Steel, D. J., & Schwarz, A. (2012, May). Multi-group invariance testing: An illustrative comparison of PLS permutation and covariance-based SEM invariance analysis. In 7th International Conference on Partial Least Squares and Related Methods. Choo, A. S., Linderman, K. W., & Schroeder, R. G. (2007). Method and context perspective on learning and knowledge creation in quality management. Journal of Operations Management, 25, 918-931. Chou, S.-W. (2005). Knowledge creation: absorptive capacity, organizational mechanisms, and knowledge storage/retrieval capabilities. Journal of Information Science, 31(6), 453-465. Daft, R.L. (2010). Organisation Theory and Design, Tenth Edition. South-Western, Cengage Learning. OH: USA. Davenport, T.H., & Prusak, L. (1998). Working knowledge, Harvard Business School Press, Boston, MA. Davenport, T.H., De Long, D.W. & Beers, M.C. (1998). Successful knowledge management projects. Sloan Management Review, 39 (2), 43-57. Denford, J.S. & Chan, Y.E. (2011). Knowledge strategy typologies: defining dimensions and relationships. Knowledge Management Research & Practice, 9(2), 102-119. Desouza, K.C., & Awazu, Y. (2006). Knowledge management at SMEs: Five peculiarities. Journal of Knowledge Management, 10(1), 32–43. Durst, S., & Runar Edvardsson, I. (2012). Knowledge management in SMEs: a literature review. Journal of Knowledge Management, 16(6), 879-903. EFQM. 2003. EFQM Excellence Model. European Foundation for Quality Management, Brussels, Belgium. EFQM. 2013. EFQM Excellence Model. European Foundation for Quality Management, Brussels, Belgium. Fawcett, S. E., Wallin, C., Allred, C., Fawcett, A. M., & Magnan, G. M. (2011). Information technology as an enabler of supply chain collaboration: a dynamic‐capabilities perspective. Journal of Supply Chain Management, 47(1), 38-59. Fernández-Santos, J., Lorenzo-Martínez, S., Navarro-Royo, C., Alguacil-Pau, A.I., Morón-Merchante, J., & Pardo-Hernández, A. (2010). Utilización de los ejes transversales del modelo EFQM en el ámbito sanitario público. Revista de Calidad Asistencial, 25 (3), 120-128. Flynn, B.B., Schroeder, R. G., & Sakakibara, S. (1995). The impact of quality management practices on performance and competitive advantage. Decision Sciences, 26(5), 659-691. Fornell, C., & Larcker, D.F. (1981). Structural equation models with unobservable variables and measurement error: Algebra and statistics. Journal of Marketing Research, 382-388. Gómez Gómez, J., Mártinez Costa, M. & Martínez Lorente, A.R. (2015). EFQM Excellence Model and TQM: an empirical comparison. Total Quality Management & Business Excellence, doi.org/10.1080/14783363.2015.1050167. Gray, C., & Mabey, C. (2005). Management Development Key Differences between Small and Large Businesses in Europe. International Small Business Journal, 23 (5), 467-485. Hair Jr, J.F., Hult, G. T. M., Ringle, C., & Sarstedt, M., (2013). A primer on partial least squares structural equation modeling (PLS-SEM). Thousand Oaks, CA: SAGE Publications, Incorporated. Hair, J. F., Sarstedt, M., Ringle, C.M., & Mena, J.A. (2012). An assessment of the use of partial least squares structural equation modeling in marketing research. Journal of the Academy of Marketing Science, 40(3), 414-433. Helfat, C.E. & Winter, S.G. (2011). Untangling dynamic and operational capabilities: strategy for the (n)ever-changing world. Strategic Management Journal, 32(11), 1243-1250. Henseler, J. (2014). Common factor models, composite models, and formative measurement: Their nature, application, and testing. Lecture at University of Seville, November 20. Henseler, J., & Fassott, G. (2010). Testing moderating effects in PLS path models: An illustration of available procedures. In Handbook of partial least squares (pp. 713-735). Springer Berlin Heidelberg. Henseler, J., Dijkstra, T. K., Sarstedt, M., Ringle, C.M., Diamantopoulos, A., Straub, D.W., Ketchen, D.J., Jr., Hair, J.F., Hult, G., Tomas M., & Calantone, R J. (2014). Common beliefs and reality about PLS: Comments on Rönkkö & Evermann (2013), Organisational Research Methods, 17 (2), 182-209. Henseler, J., Ringle, C.M., & Sarstedt, M. (2015). A new criterion for assessing discriminant validity in variance-based structural equation modeling. Journal of the Academy of Marketing Science, 43 (1), 115-135. Henseler, J.; Ringle, C. M.; & Sarstedt, M. (2016). Testing measurement invariance of composites using partial least squares. International Marketing Review. Forthcoming. Henseler, J., Ringle, C.M., & Sinkovics, R.R. (2009). The use of partial least squares path modeling in international marketing. Advances in International Marketing, 20, 277–320. Honarpour, A., Jusoh, A., & Nor, K.M. (2012). Knowledge management, total quality management and innovation: a new look. Journal of Technology Management & Innovation, 7 (3), 22-31. Hsu, S.H., & Shen, H.P. (2005). Knowledge management and its relationship with TQM. Total Quality Management, 16 (3), 351–361. Hu, L.T., & Bentler, P.M. (1999). Cutoff criteria for fit indexes in covariance structure analysis: Conventional criteria versus new alternatives. Structural Equation Modeling: A Multidisciplinary Journal, 6 (1), 1-55. Huang, P.S., & Shih, L.H. (2009). Effective environmental management through environmental knowledge management. International Journal of Environmental Science and Technology, 6 (1), 35-50. Hung, Y.C., Huang, S.M., Lin, Q.P., & Tsai, M.L. (2005). Critical factors in adopting a knowledge management system for the pharmaceutical industry. Industrial Management & Data Systems, 105(2), 164- 183. Hutchison, V., & Quintas, P. (2008). Do SMEs do knowledge management? Or simply manage what they know? International Small Business Journal, 26, 131-151. Ipe, M. (2003). Knowledge sharing on organizations: a conceptual framework. Human Resource Development Review, 2(4), 337-359. Ju, T.L., Lin, B., Lin, C., & Kuo, H.J. (2006). TQM critical factors and KM value chain activities. Total Quality Management & Business Excellence, 17 (3), 373-393. Kaynak, H. (2003). The relationship between total quality management practices and their effects on firm performance. Journal of Operations Management, 21(4), 405-435. Kiessling, T.S., Richey, R.G., Meng, J. & Dabic, M. (2009). Exploring knowledge management to organizational performance outcomes in a transitional economy. Journal of World Business, 44(4), 421-433. Kim, D., Kumar, V., & Murphy, S.A. (2010). European foundation for quality management business excellence model: an integrative review and research agenda. International Journal of Quality & Reliability Management, 27 (6), 684-701. Laforet, S. (2013). Organisational innovation outcomes in SMEs: Effects of age, size, and sector. Journal of World business, 48 (4), 490-502. Lee, H., & Choi, B. (2003). Knowledge management enablers, processes and organisational performance: an integrative view and empirical examination. Journal of Management Information Systems, 20 (1), 179-228. Linderman, K., Schroeder, R.G., Zaheer, S., Liedtke, C., & Choo, A.S. (2004). Integrating quality management practices with knowledge creation processes. Journal of Operations Management, 22 (6), 589- 607. Loke, S.P., Downe, A.G., Sambasivan, M., & Khalid, K. (2012). A structural approach to integrating total quality management and knowledge management with supply chain learning. Journal of Business Economics and Management, 13 (4), 776-800. Martín-Castilla, J.I., & Rodríguez-Ruiz, O. (2008). EFQM model: knowledge governance and competitive advantage. Journal of Intellectual Capital, 9 (1), 133-156. McAdam, R., & Reid, R. (2001). SME and large organisation perceptions of knowledge management: comparisons and contrasts. Journal of Knowledge Management, 5 (3), 231-241. Meso, P. & Smith, R. (2000). A resource-based view of organizational knowledge management systems. Journal of Knowledge Management, 4(3), 224-234. Moffett, S., McAdam, R. & Parkinson, S. (2003). An empirical analysis of knowledge management applications. Journal of Knowledge Management. 7 (3), 6-26. Molina, L.M., Lloréns-Montes, J., & Ruiz-Moreno, A. (2007). Relationship between quality management practices and knowledge transfer. Journal of Operations Management, 25 (3), 682-701. Ooi, K.B. (2009). TQM and knowledge management: literature review and proposed framework. African Journal of Business Management, 3 (11), 633-643. Pannirselvam, G.P., & Ferguson, L.A. (2001). A study of the relationships between the Baldrige categories. International Journal of Quality & Reliability Management, 18(1), 14-37. Prajogo, D.I., & McDermott, C.M. (2005). The relationship between total quality management practices and organisational culture. International Journal of Operations & Production Management, 25 (11), 1101-1122. Prajogo, D.I., & Sohal, A.S. (2006). The relationship between organization strategy, total quality management (TQM), and organization performance––the mediating role of TQM. European Journal of Operational Research, 168(1), 35-50. Rahman, S.U., & Bullock, P. (2005). Soft TQM, hard TQM, and organisational performance relationships: an empirical investigation. Omega, 33(1), 73-83. Riege, A. (2005). Three-dozen knowledge-sharing barriers managers must consider. Journal of Knowledge Management, 9(3), 18-35. Ringle, C.M., Wende, S. & Becker, J-M. (2015). SmartPLS, 3. SmartPLS GmbH. Boenningstedt, Germany. URL: www.smartpls.com Roldán, J.L., & Sánchez-Franco, M.J. (2012). Variance-based structural equation modeling: guidelines for using partial least squares in information systems research. In M. Mora, O. Gelman, A. Steenkamp, & M. Raisinghani (Eds.), Research Methodologies, Innovations and Philosophies in Software Systems Engineering and Information Systems (pp. 193-221). Rusjan, B. (2005). Usefulness of the EFQM excellence model: Theoretical explanation of some conceptual and methodological issues. Total Quality Management & Business Excellence, 16(3), 363-380. Ryan, S.D. & Prybutok, V.R. (2001). Factors affecting knowledge management technologies: a discriminative approach. Journal of Computer Information Systems, 41 (3), 31-7. Saeed, K. A., & Abdinnour-Helm, S. (2008). Examining the effects of information system characteristics and perceived usefulness on post adoption usage of information systems. Information & Management, 45(6), 376-386. Sarstedt, M., Henseler, J., & Ringle, C.M. (2011). Multigroup analysis in partial least squares (PLS) path modeling: Alternative methods and empirical results. Advances in International Marketing, 22 (1), 195-218. Sila, I. (2007). Examining the effects of contextual factors on TQM and performance through the lens of organizational theories: An empirical study. Journal of Operations management, 25(1), 83-109. Sila, I., & Ebrahimpour, M. (2003). Examination and comparison of the critical factors of total quality management (TQM) across countries. International Journal of Production Research, 41 (2), 235-268. Simonin, B., 1997. The Importance of Collaborative Know-how: An Empirical Test of the Learning Organisation. Academy of Management Journal, 40 (5), 509-533. Spekman, R.E., Spear, J., & Kamauff, J. (2002). Supply chain competency: learning as a key component. Supply Chain Management: An International Journal, 7( 1), 41-55. Spender, J.C. & Scherer, A.G. (2007). The philosophical foundations of knowledge management: editors' introduction. Organization, 14(1), 5-28. Tang, J. & Tong, J.Y. (2007). A two-phase Knowledge management system for the quality standard ISO 9001. International Journal of Management, 24 (1), 184-197. Tanriverdi, H. (2005). Information technology relatedness, knowledge management capability. MIS Quarterly, 29 (2), 311-334. Tarí, J.J., & García Fernández, M. (2013). ¿Puede la gestión del conocimiento influir en los resultados empresariales? Cuadernos de Gestión, 13(1), 151-176. Teece, D.J. (2014). The foundations of enterprise performance: dynamic and ordinary capabilities in an (economic) theory of firms. Academy of Management Perspectives, 28 (4), 328-352. Van den Hooff, B. & Huysman, M. (2009). Managing knowledge sharing: emergent and engineering approaches. Information & Management, 46(1), 1-8. Weske, M. (2007). Business Process management- Concepts, Languages, Architectures. Springer-Verlag, Berlin Heidelberg. Westerveld, E., (2003). The Project Excellence Model®: linking success criteria and critical success factors. International Journal of Project Management, 21, 411–418. Wong, K.Y., & Aspinwall, E. (2005). An empirical study of the important factors for knowledge-management adoption in the SME sector. Journal of Knowledge Management, 9(3), 64-82. Yeh, Y.J., Lai, S.Q. & Ho, C.T. (2006). Knowledge management enablers: a case study. Industrial Management & Data Systems, 106 (6), 793-810. Zack, M., McKeen, J., & Singh, S. (2009). Knowledge management and organisational performance: an exploratory analysis. Journal of Knowledge Management, 13 (6), 392-409. Zárraga-Rodríguez, M., & Álvarez, M.J. (2014). Does the EFQM model identify and reinforce information capability? Procedia-Social and Behavioral Sciences, 109, 716-721. Table 1. EFQM Model and knowledge management issues. Source: Own production. Fundamental Concepts of Excellence KM issues Development and involvement of people Excellent organisations recognise the increasing importance of the intellectual capital of those who comprise them and use their knowledge to the benefit of the whole organisation Continuous process of learning, innovation and improvement Excellent organisations, through benchmarking activities, must continuously learn, and gather and share the knowledge of the people who comprise them, to maximise the learning in the whole organisation Development of alliances Partners must work together to reach common objectives, each helping the others with their experience, resources and knowledge EFQM Criteria KM issues Leadership Refers to practices that help knowledge creation: the promotion of empowerment, creativity and innovation, or establishing incentives so people and groups participate in improvement activities. Policy and strategy Refers to the need to base policy and strategy upon information on performance indicators, research and learning. People It is necessary to assess: (1) How the knowledge and the competences of the personnel are identified, classified and adapted to the needs of the organisation. (2) How training and development plans are developed and implemented which contribute to guaranteeing that the abilities of the personnel are adjusted to the present and future needs of the organisation. (3) How learning opportunities are designed and promoted at the individual, group and organisational level. Partnerships and Resources It analyses how the organisation: (1) Manages information and knowledge in support of policy, strategy and objectives. (2) Identifies the current information and knowledge. (3) Provides suitable access to important information and knowledge. (4) Uses information technology to support internal communication and information and knowledge management. (5) Cultivates, develops and protects the intellectual property to maximise its value for the customer. (6) Tries to acquire, increase and use knowledge effectively. (7) Generates a climate of innovation and creativity in the organisation by means of suitable information and knowledge resources. Process management Identifies aspects related to the application of knowledge when the need is mentioned to manage the information that comes from the customers for the development of new products and services.