INTRODUCTION

According to a study by Gottfredson et al. (2008), carried out in order to identify the problems faced by the 500 most important companies in the world in the last 50 years, 87% of business crises are caused by internal factors, including failures to innovate and lack of management of the organization's resources. This has led to the suggestion that innovation and quality contribute significantly to improving the performance of organizations, making them more competitive in the market (Saloner et al., 2005b; Schumpeter, 1967; Thompson et al., 2012). Although both elements contribute to the better performance of organizations, there is ample scope for discussion about the relationship between the two variables.

Quality, innovation, and their relationship

In the case of standardization in Mexico, the Quality Infrastructure Law, in its section of the National Quality and Innovation System, states that the application of standards contributes to innovation in products and services (Secretaría de Economía, 2020). Similarly, other international models such as the quality ladder model point out that quality, research, and development (R+D) and innovation are interrelated tools that allow companies to be more competitive(Grossman & Helpman, 1991; Klette & Griliches, 1997).

Although this relationship has been studied in many areas, there is still a long way to go to reach more accurate conclusions. Delving into the literature, it can be observed that this relationship has been approached in two ways. One where the quality-innovation relationship is observed as positive and the other, where innovation is negatively affected by quality. Before discussing these two perspectives, both concepts are briefly addressed, suggesting that while quality is doing things better, innovation involves doing things differently (Zeng et al., 2017).

In companies, management staff are continually trying to improve their products and services to generate wealth and profits. This gives meaning to the term perpetual innovation, which is based on Schumpeter's creative destruction, which describes the consistency and speed with which new technologies replace previous ones (Hitt et al., 2008). To be considered an innovation, an idea initially proposed must be accompanied by its commercial implementation(Schumpeter, 1967). An example of this phenomenon was the development of automobiles, which in turn reduced the demand for bicycles and made carriages obsolete.

An innovation can be "the result of a series of minor improvements that result in a significant difference, the difference between being or not, is subjective because it is relative to the context, capabilities and requirements of each company". Under this definition, many activities can be considered as innovation (OECD, 2018, p.79).Thus, the literature shows studies that classify innovations according to their impact at a given time. This explains why, while some innovations can be developed by modifications made in work practice, by exchanges and combinations of professional experience, others can be more elaborate. It is also worth mentioning that innovations are not only related to the development of new technologies, but innovation can also involve changes in the behavior and organization of companies to manage knowledge and other resources.

On the other hand, quality, according to Ishikawa, involves designing, producing, and offering a product or service that is useful, at the best price, and that always satisfies the needs of the customer (San Miguel, 2007). For his part, the creator of the Zero Defects concept, P. Crosby, defined quality as doing what was agreed at the agreed time(Munch, 2016). Whereas, for the International Organization for Standardization (ISO) it represents "the degree to which the characteristics of an object comply with the requirements of the customer, legal, regulatory or self-imposed by the organization"(ISO TC/176, 2015). In the usual terminology of the production sector, quality is linked to excellence and being at the forefront in order to obtain and maintain a competitive advantage. In the U.S., about 92% of manufacturing companies and 69% of service companies have implemented some form of quality management (Wheelen& Hunger, 2007). The rise and importance of quality in organizations worldwide has led to the creation and implementation of multiple tools for quality management such as quality circles, Total Quality Management (TQM), six sigma and management systems based on the ISO 9000 standard.

However, we mentioned earlier that it is possible to identify in the literature different studies that have addressed the relationship between quality and innovation that present different results. A first perspective asserts that the relationship between quality and innovation is positive(Dean Jr & Bowen, 1994; Kanji, 1996; Prajogo & Sohal, 2003; Roffe, 1999; Tang, 1998; Zeng et al., 2015, 2017). However, quality does not affect different types of innovation in the same way. Authors such as Gotzamani&Tsiotras (2002) and Terziovski& Guerrero (2014) point out that, given the focus of ISO 9001, which focuses on process control, the positive relationship between quality and innovation has a greater impact on process innovation than on product innovation.

A second perspective presents a position where innovation is negatively affected by quality processes. Studies suggest that quality processes can include mechanistic routinization and standardized business processes, thus restricting creativity and innovation(Glynn, 1996; Kanter, 1983; Liao et al., 2010; Perdomo-Ortiz et al., 2009a), situations that lead organizations to concentrate inwards, becoming rigid and difficult to recognize and introduce innovations tags (Saloner et al., 2005a; Christensen, 1997).

In view of these divergent perspectives, the construction of a model that relates both variables are presented, as well as its application that allows evaluating this relationship in the context of the agricultural machinery industry.

Construction of the quality-innovation model

To identify the relationship between the variable’s quality and innovation, a model was constructed that relates the dimensions of both variables. This model makes it possible to weigh the degree of maturity of each variable in an organization and then analyze the relationship between the quality components and the innovation results of that organization. The four stages of model construction are described below.

Stage 1. Identification of components in the quality and innovation variables

The study of the quality variable allowed us to identify that it is composed of elements that together promote learning processes, which result in useful knowledge for the improvement of performance, products and services and increase customer satisfaction. Figure 1 presents the proposed components and elements of the quality variable.

Likewise, several elements that help to characterize the innovation variable were identified. Figure 2 shows how innovation can be characterized by considering two main aspects: its type (e.g., product and services, business processes) and its degree of significance (radical innovation, incremental innovation, and improvement).

Stage 2. Identification of the relationship between the components of the quality variable and innovation.

After the identification of the components of the variables studied, an argument was made about the potential relationship between the components of quality and innovation results. Table 1 shows the relationship and the arguments that support this relationship (See Relationship with Innovation column).

3. Identification of the intermediate variable between quality and innovation.

During the previous stages of the construction of the relationship model and the data that were collected in a first stage, it was identified that quality does not directly provide results in innovation. This led us to delve deeper and analyze the link that mediates this relationship. As a result of this research, it was identified that the interaction and presence of the components of the quality variable led to the appearance of a variable that was called the intermediate vairbale to promote innovation. This variable affects the company's decisions to adopt new technologies, its access to new knowledge and its ability to assimilate it; aspects that together allow the organization to remain at the same level as its competitors or gain a certain advantage. This variable is divided into two components: a) input and b) process, proposing that the resulting outputs are, in effect, the results in innovation. Thus, Figure 3 shows that the components of the intermediate variable of driving innovation enable the relationship between the quality components and the results in innovation, while Table 2 presents the description of the components and elements that make it up.

Stage 4. Operationalization of the model

Based on the above, it is suggested that the quality variable, through its components, has a relationship with the intermediate variable that drives innovation, which in turn generates results in innovation. Once the three variables of the model have been determined, Table 3 presents the structure of the designed measuring instrument, whose reagents allow the evaluation of the components and elements of the three variables in question. Each item was given a quantitative weighting to identify the degree of maturity of each variable. Regarding the measurement of each component of the three variables, Tables 4, 5 and 6 show the way in which it was evaluated. It is worth mentioning that this same questionnaire has been applied to other companies, the results of which are declared in other works that were in the process of evaluation at the time of submission of this work.

It should be noted that in the case of the laboratory testing component, the product, which provides relevant information for manufacturers in terms of compliance with technical and safety specifications, was evaluated through documentary review and interviews with the source of information.

Application of the model and results

The results of the application of the relationship model are presented in Table 7 and Figure 4, applied to an agricultural machinery manufacturing company located in Mexico, considered a large company due to its number of employees that exceeds half a million.

Derived from the application of the model to study the relationship between quality and innovation, mediated by the intermediate variable of impulse to innovation, it was found that the robustness of the components of the variable quality related to the design, development, and manufacture of the product, contribute to the strengthening of the intermediate variable of impulse to innovation.

Likewise, it is observed that the quality variable has a maturity percentage of 80%, which shows its strength and contribution to the constant delivery of compliant products and high customer satisfaction. This strength of the quality variable is largely due to the global vision, the follow-up of warranty claims and the lessons they generate, as well as the continuous efforts to maintain five certifications in management systems (quality, environmental, occupational health, energy, and laboratory tests). Likewise, the solidity of the quality variable is largely due to the large databases that allow the company to manage the knowledge generated within it, as well as to the implementation of Kaizen and other analysis tools. In the same vein, efforts to maintain collaborative relations abroad with subsidiaries, importers, suppliers, government, etc., are very useful in strengthening the quality variable.

On the other hand, the model also made it possible to identify positive results with respect to the intermediate variable of driving innovation, obtaining a 76% maturity rate. This percentage is due, on the one hand, to the culture of experimentation and risk aversion, which leads the company to experiment once it has the greatest of the controlled parameters, once these have already been evaluated in other contexts. On the other hand, the exploitation of knowledge contributes to the strengthening of the intermediate variable thanks to the efforts made with respect to industrial secrets and patent registrations, which has allowed the company not to seek the purchase of developments patented by other organizations.

The strength of the intermediate variable of driving innovation has allowed the company to integrate six new products into the market that include new functional developments, considered to have a degree of incremental international regional innovation. This has allowed the substitution of its product portfolio, the improvement of product quality, an increase in market share, the increase in developments of precision agriculture services and new markets in the industry.

Finally, in relation to the limitations presented by the company, it pointed out the difficulties they face in terms of current regulations, as well as the lack of public support for innovation and R+D in the Mexican STI ecosystem. Taken together, these situations make it difficult for the company to deal with the excessive risk of potential losses associated with the high costs involved in innovation. As a whole, the proposed model and its application allow us to observe that the elements of quality such as attention to complaints and guarantees, laboratory tests, process control and documented information contribute to the exploitation of knowledge component of the intermediate variable of impulse to innovation and that, in turn, this knowledge can be used to strengthen the components of adaptability of business processes and generation of innovative projects.

In addition, the quality components of process management, quality information, and product and service design contribute to the generation of development into more robust products and processes, while the monitoring and evaluation component allows for innovation in the way problems are solved and customer expectations are exceeded.

CONCLUSIONS

The study of the relationship model shows that the components of the quality variable have a direct relationship with the intermediate variable that drives innovation, and that this, in turn, strengthens the foundations for the development of innovative products, processes and services. This is since the components of the intermediate variable of impulse to innovation allow structuring and strengthening the activities and stages of development, through the generation of new knowledge that can be incorporated into innovative developments.

Given that the company indicated that it has limited budgets and deadlines for each project, the proposed model shows that quality promotes incremental innovation to a greater extent than radical innovation. This is because quality drives rational innovation, as it considers the viability of innovative projects.

Regarding the limitations of the study, one of the most relevant is the difficulty of access to information. This is because on some occasions the company hesitated whether to provide information, since, even though such information did not put the company or its projects at risk, there is no culture of providing information openly. This problem was especially present when issues related to the variables of impulse to innovation and their results in innovation were addressed. This situation, on the other hand, reflects the level of business distrust in the context in which it is located.

Finally, it is also worth mentioning that the results of this research are derived from the study of a company in the agricultural machinery industry, so it is suggested to validate the proposed model in other agricultural machinery companies, as well as in companies in other industries.

REFERENCES

Abrahamson, E. (1996). Fashion management. Academy of Management Review, 21(1), 254–285. https://doi.org/10.5465/AMR.1996.9602161572

Christensen, C. M. (1997). The Innovator's Dilemma. Harvard Business School Press. Boston, MA.

Dean Jr, J. W., & Bowen, D. E. (1994). Management theory and total quality: improving research and practice through theory development. Academy of Management Review, 19(3), 392–418.

Deming, W. E., & Medina, J. N. (1989). Quality, productivity and competitiveness: the way out of the crisis. EdicionesDíaz de Santos.

Glynn, M. A. (1996). Innovative genius: A framework for relating individual and organizational intelligences to innovation. Academy of Management Review, 21(4), 1081–1111.

Gottfredson, M., Schaubert, S., & Saenz, H. (2008). The New Leader's Guide to Diagnosing the Business. Harvart Business Review.

Gotzamani, K. D., &Tsiotras, G. D. (2002). The true motives behind ISO 9000 certification. International Journal of Quality & Reliability Management.

Grint, K. (1997). TQM, BPR, JIT, BSCs and TLAs: managerial waves or drownings? Management Decision, 35(10), 731–738. https://doi.org/10.1108/00251749710192048

Grossman, G. M., &Helpman, E. (1991). Quality ladders in the theory of growth. The Review of Economic Studies, 58(1), 43–61.

Hitt, M., Ireland, R. D., Hoskisson, R., Benjamin, E., &Fincowsky, F. (2008). Strategic management. Competitiveness and globalization.

ISO TC/176. (2015). ISO 9001:2015 Quality Management Systems - Requirements.

Kanji, G. K. (1996). Can total quality management help innovation? Total Quality Management, 7(1), 3–10.

Kanter, R. M. (1983). The change masters: innovation for productivity in the American mode. Simon and schuster.

Klette, T. J., &Griliches, Z. (1997). Empirical Patterns of Firm Growth and R&D Investment: A Quality Ladder Model Interpretation. In 26 S.https://doi.org/10.3386/w5945

Liao, S. H., Chang, W. J., & Wu, C. C. (2010). Exploring TQM-innovation relationship in continuing education: A system architecture and propositions. Total Quality Management and Business Excellence, 21(11), 1121–1139. https://doi.org/10.1080/14783363.2010.529330

Munch, L. (2016). Techniques and procedures for continuous improvement. Trails.

OECD. (2018). Oslo manual 2018: guidelines for collecting and interpreting innovation data on innovation.

Perdomo-Ortiz, J., González-Benito, J., &Galende, J. (2009a). An analysis of the relationship between total quality management-based human resource management practices and innovation. International Journal of Human Resource Management, 20(5), 1191–1218. https://doi.org/10.1080/09585190902850372

Perdomo-Ortiz, J., González-Benito, J., &Galende, J. (2009b). The intervening effect of business innovation capability on the relationship between Total Quality Management and technological innovation. International Journal of Production Research, 47(18), 5087–5107. https://doi.org/10.1080/00207540802070934

Prajogo, D. I., &Sohal, A. S. (2003). The relationship between TQM practices, quality performance, and innovation performance: An empirical examination. International Journal of Quality and Reliability Management, 20(8), 901–918. https://doi.org/10.1108/02656710310493625

Roffe, I. (1999). Innovation and creativity in organisations: a review of the implications for training and development. Journal of European Industrial Training.

Saloner, G., Shepard, A., &Podolny, J. (2005a). Strategic management in a dynamic environment. In Strategic Management.

Saloner, G., Shepard, A., &Podolny, J. (2005b). Business strategy. In Strategic Management.

San Miguel, P. A. (2007). Quality. Editorial Paraninfo.

Schumpeter, J. (1967). Theory of Economic Development: An Inquiry into Profits, Capital, Credit, Interest, and the Business Cycle.

Secretaría de Economía. (2020). Proyecto de Ley de Infraestructura de la Calidad.

Tang, H. K. (1998). An inventory of organizational innovativeness. Technovation, 19(1), 41–51.

Terziovski, M., & Guerrero, J. L. (2014). ISO 9000 quality system certification and its impact on product and process innovation performance. International Journal of Production Economics. https://doi.org/10.1016/j.ijpe.2014.08.011

Thomas, P. (2003). The recontextualization of management: A discourse-based approach to analysing the development of management thinking. Journal of Management Studies, 40(4), 775–801. https://doi.org/10.1111/1467-6486.00360

Thompson, A. A., Gamble, J. E., &Peteraf, M. A. (2012). Strategic Management - Theory and Cases (18th edic.). McGraw-HILL.

Wheelen, T., & Hunger, D. (2007). Strategic Management and Business Policy: Concepts and Cases.

Zeng, J., Anh Phan, C., & Matsui, Y. (2015). The impact of hard and soft quality management on quality and innovation performance: An empirical study. International Journal of Production Economics, 162, 216–226. https://doi.org/10.1016/j.ijpe.2014.07.006

Zeng, J., Zhang, W., Matsui, Y., & Zhao, X. (2017). The impact of organizational context on hard and soft quality management and innovation performance. International Journal of Production Economics, 185, 240–251. https://doi.org/10.1016/j.ijpe.2016.12.031

Información adicional

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