There are many definitions of quality. However, most of them have the following commonalities: (1) the fulfilment of requirements, in particular customer needs, (2) the focus on specific products, services or processes, (3) improved organisational performance, and (4) the absence of errors (Sila & Maling 2003). This concept is not, therefore, limited to products but also includes processes and other potentially important factors, such as technical and personal resources (Hietschold et al. 2014).

Quality management has, over the last few decades, evolved from being a result-orientated quality control to being an integrated company-wide approach. Researchers refer to this approach as TQM, which is a set of philosophies and methods used by an organisation to guide it in its continual improvement in all aspects of its business (Boon, Arumugam & Hwa 2005; Short & Rahim 1995).

According to many researchers, TQM produces value through a variety of benefits (Kaynak 2003; Lee & Lee 2015; O’Neill, Sohal & Teng 2016; Valmohammadi & Roshanzamir 2015; Zairi, Letza & Oakland 1994). With TQM, it is possible to achieve an improved understanding of customers’ needs; improved customer satisfaction; better problem-solving, improved internal communication; stronger relationships with suppliers; reduced waste; greater employee commitment and motivation; and fewer errors. A resource-based analysis supports this conclusion, suggesting that TQM is not readily imitable owing to time compression diseconomies, causal ambiguity, connectedness of resources and social complexity. The success of TQM depends not only on adopting the TQM attributes, but also on complementary factors that are apparently unrelated to TQM but that are more difficult to imitate than TQM itself. This appears to require a culture that is receptive to change, leadership qualities and the motivation to improve (Kaynak 2003; Powell 1995). Without these tacit, intangible and difficult to imitate complementary resources, TQM programmes have no foundation for success (Anderson & Sohal 1999; Aquilani et al. 2017; Bouranta, Psomas & Pantouvakis 2017; Samson & Terziovski 1999).

At the core of TQM’s ability to create value is its power to bring about an efficient creation and utilisation of valuable specific knowledge at all levels of the organisation. This contribution to knowledge creation leads to improvements in certain distinctive competencies, such as managerial competencies, employee know-how, external cooperation skills, the creation of a collective mind, organisational commitment, stimulation of the organisational learning process, speed and flexibility in the design of new products or services, and reputation (Bowen & Lawler 1992; Escrig, Bou & Roca 2001; Lemak & Reed 1997; Rao, Solis & Raghunathan 1999; Watson & Korukonda 1995; Webley & Cartwright 1996; Wruck & Jensen 1998; Youssef, Boyd & Williams 1996).

The term ‘intellectual capital’ is used as a synonym for intangible or knowledge assets (Stewart 1991). Its emergence in the context of business administration was first addressed in the early 1990s. ‘Intellectual capital’ is defined in several ways, and there is no common platform regarding these definitions, as discussed in the following.

Some of the definitions converge at the same point: the difference between the company’s market value and the cost of replacing its assets. Some empirical works highlight a persistent gap between market value and book value, and intangible assets or intellectual capital could, perhaps, explain some of these gaps (Bontis 1996; Edvinsson & Malone 1997).

Stewart (1998) defines ‘intellectual capital’ as the intellectual material, including information, knowledge, intellectual property, experience and so on that can be put to use to create wealth. Subramaniam and Youndt (2005) conceptualise intellectual capital as the sum of all knowledge and knowing capabilities that can be utilised to give a company a competitive advantage.

As can be seen from some of the definitions, three key characteristics of the intellectual capital construct can be described as follows: its intangibility, its potential to create value and the growth effect of collective practice and synergies (Martín et al. 2010).

Having discussed the term ‘intellectual capital’, in the following we review the current body of knowledge regarding its dimensions.

Evans (1992) states that TQM has a total systemic role; that is, it influences the whole workforce of a company. Furthermore, human resources are one of the most important factors contributing to the long-term success of quality management in a firm (e.g. Shafiq, Lasrado & Hafeez 2017). In this respect, intensive and continuous training is an essential component of quality management. Maintaining high levels of quality depends on the best use of the abilities and talents of a firm’s entire workforce (Rao et al. 1999).

Training is a prerequisite for the effectiveness of quality improvement activities. The usage of workers’ knowledge is so important that training has become a fundamental requirement in all companies. It is one of the TQM dimensions, and having the management support and the necessary resources makes it possible to achieve the appropriate level of HC (Das, Paul & Swierczek 2008; Partlow 1996).

In this research, these lines of reasoning will be employed as a basis on which to test the following hypothesis:

There are some dimensions of TQM that lead to an improvement in SC. Firstly, it is management that creates a work environment that is conducive to employee involvement and that encourages and facilitates open communication (Anderson et al. 1995; Wilson & Collier 2000). Involving employees requires communicating a clear quality improvement strategy to them (Kaynak 2003). Secondly, in the context of TQM practices, work teams are said to facilitate information sharing, problem-solving and to develop the employees’ responsibility for managing quality performance. Teamwork is seen to promote communication between employees and management and also promotes communication and cooperation between employees in different areas of the organisation (Cooney & Sohal 2004; Cordery 1996; Coyle-Shapiro 1995). Thirdly, in the area of the relation between the firm and its environment, TQM drives the practice of cooperation with both customers and suppliers (Samson & Terziovski 1999; Zylfijaj & Pira 2017). TQM increases the organisation’s capacity to transfer knowledge, and according to Molina, Lloréns and Ruiz (2007), the results indicate that both internal knowledge transfers and those from suppliers and customers are related to the firm’s performance. Therefore, considering all of these contributions, we think that TQM practices facilitate networks of people and knowledge in groups, which leads to an improvement in SC.

These lines of reasoning will be employed as a basis on which to test the following hypothesis:

Hietschold et al. (2014) conduct a structured review of empirical studies in order to discover critical success factors when introducing TQM. They state that nearly all studies include process management, in addition to employee participation, teamwork and top management commitment. Internal operations and information processes represent a key part of the quality management infrastructure. If organisations are to maintain and continuously improve quality, they require a persistent flow of reliable information. In addition, it is not only the availability of information that is important to organisations but also its adequate usage by management and employees (Rao et al. 1999). The company is, therefore, able to maintain documented processes through the use of quality practices such as process management, and as a result, to increase the level of OC, that is, the knowledge stored in patents, manuals, databases, routines, structures and so on (Teece 1998).

Tóth and Jonás (2012), upon considering the European Foundation for Quality Management (EFQM) Excellence Model, state that excellent models are directly related to intellectual capital models. In this respect, they point out that processes include all knowledge assets accumulated by the organisation from its relationships with other stakeholders that interact in the organisational environment. They attain similar conclusions as regards the consideration of quality dimensions such as leadership and strategy, thus supporting H.1 and H.2.

These lines of reasoning will be employed as a basis on which to test the following hypothesis:

After offering a research model and related hypotheses, the following section describes the research methodology and explains the findings of our study.

The sample used in our research was developed by choosing some companies from the SABI¹ database. Sampling was carried out on companies from Castilla–La Mancha (Spain) with at least 25 employees and belonging to different industrial sectors and services. Inactive companies were excluded; thus the final sample was made up of 876 firms. The data were collected through a questionnaire survey (see Appendix 1) carried out by mail, first in October and later in November 2016, and more responses were, in some cases, also obtained by means of personal and telephone interviews.

The questionnaires of our research were sent to the chief officer or coordinator of the Human Resources Department and Quality Department. Of the 876 questionnaires distributed, 142 were returned. However, some of them were incomplete; we eventually obtained 129 usable questionnaires, yielding a response rate of 14.7%.

Analysing the sample, the companies’ employees had a mean age of 25.56 years (SD = 22.60) and the companies had a mean size of 74.97 (number of employees, SD = 127.20). We compared the sample with the rest of the firms in the population, analysing variables such as age and size. There were no significant differences between the sample and the population.

Harman’s one-factor test and confirmatory factor analysis were conducted to test the presence of a common method effect. This single factor test examines the unrotated factor solution to determine the number of factors that are necessary to account for the variance in the variables. If a single factor emerges or one general factor accounts for the majority of the covariance among the measures, then it is concluded that a substantial amount of common method variance is present (Podsakoff & Organ 1986). We developed a principal components factor analysis with varimax rotation using the items from the questionnaire. There are five factors with an eigenvalue of over one, which explain 69.67% of the variance (16.94% of the variance for the first factor). We can, therefore, state that a substantial amount of common method variance is not present.

The questionnaire employed a five-point scale from one (strongly disagree) to five (strongly agree). That is, the questions reflected the level of agreement with some statements related to TQM and intellectual capital (see Appendix 1 for a detailed listing of the items).

The hypotheses were tested using SEM, which permits a simultaneous test of the causal relationships among multiple variables in a model and provides techniques with which to correct for measurement errors, which are potential problems in behavioural research.

In order to carry out a SEM analysis, it is necessary to choose between two statistical methods (Hair, Ringle & Sarstedt 2013): methods based on covariance analysis or methods based on variance such as Partial Least Squares (PLS). We chose PLS-SEM because it has fewer restrictions in relation to the size of the sample. In this respect, authors such as Reinartz, Haenlein and Henseler (2009) state that PLS-SEM is the most appropriate method when there are fewer than 250 cases. We introduced two control variables into the structural model – the company’s age and the company’s size (number of employees) – but we eventually decided not to consider these variables because they did not show significant effects.