Theoretical basis

The concept of engagement, proposed by ^{Kahn in 1990}, is defined as the use of organizational members to achieve business objectives, personal self-fulfillment and emotional stability of individuals. Over time, various researchers have expanded and enriched this definition. ^{Huan et al. (2022)}, Khan (1990) and ^{Sun and Bunchapattanasakda (2019)} have added the Cognitive, Emotional and Psychic Theory of Engagement. ^{Rameshkumar (2020)} highlighted the importance of including emotions and behavior in the conceptualization of engagement. On the other hand, ^{Kosaka and Sato (2020)} have described it as a combination of commitment, loyalty and productivity, while ^{Chanana and Sangeeta (2021)} propose a different approach that includes cognition, emotion and behavior. ^{Borst et al. (2020)} emphasize employee engagement at work in cognitive, physiological and emotional terms. In turn, ^{Huan et al. (2022)} express that engagement is a term that encompasses different types of engagements, such as trait, behavioral and psychological. Additionally, ^{Koprivitsa (2020)} defines it as energy, participation and effectiveness, considering it as the opposite of burnout and stress. Despite these varied definitions, engagement is conditioned by the individual's work and personal factors, as well as by the reward they may receive for performing their job efficiently.

The job demands-resources model (JD- R model) states that job and personal factors, both independently and jointly, have the ability to predict employee engagement. Specifically, when high levels of job demands are required, these factors have a more positive impact on employee engagement. In this sense, ^{Vargas and Estrada (2020)} claim that job resources can mitigate the impact of job demands, facilitate the achievement of professional goals and stimulate growth, learning and personal development. Albertcht et al. (2021) support this idea by stating that available job factors are the main predictors of engagement. A study conducted by ^{Bakker and De Vries (2021)} shows that certain job factors, such as financial profitability, team atmosphere and participation in decision making, have a positive influence on employee engagement.

In addition, cross-cultural theory is used to explain the differences in personal factors that influence engagement. Engaged employees, according to ^{Carolina (2019)}, ^{Hughes et al. (2018)} and ^{Pidduck et al. (2020)}, are characterized by optimism, self-efficacy, good self-esteem, resilience and a positive attitude to face challenges. These personal resources enable committed employees to effectively control and influence their work environment. ^{Teekens et al. (2021)} supports this approach by finding that resilience is an individual resource that promotes engagement.

The reward system constitutes a part of the brain responsible for indicating a person if situations are positive and, when repeated, generate greater satisfaction. According to ^{Sutikno (2019)}, the aversion system indicates to the brain those situations that should be avoided because they generate anger, depression, listlessness, among others. ^{Salameh and Zamil (2020)} define reward as a benefit granted by employers in the form of money, benefits or promotions, generating job satisfaction. ^{Kebels (2022)} found in his study that an organization that provides recognition to its employees, along with training and other benefits, manages to develop their commitment to the company. Similarly, ^{Ntanos et al. (2020)} revealed that an effective reward system is directly related to employee motivation and satisfaction, showing that this strategy can have positive effects on the organization.

Intrinsic rewards, derived from the activity performed, can improve mood and contribute to the well-being of others (^{Bozzo, 2019}). ^{Araujo et al. (2021)} point out that intrinsic rewards at work, such as reputation empowerment, autonomy and trust, are fundamental to maximize employee commitment, motivation and participation. ^{Pinho et al. (2018)} claim that these rewards also enhance organizational support and employee satisfaction, influencing positively affective commitment and work engagement. In contrast, extrinsic rewards are external to the job and include tangible benefits such as bonuses, job security, private offices, promotions, social climate, salary increase, vacation pay and paid leave (^{Araujo et al., 2021}). Employees who prefer extrinsic rewards tend to show higher performance and contribute to the achievement of organizational goals when they receive tangible rewards (^{Abad, 2019}). Since these rewards generate reciprocal results, upon receiving them, employees are satisfied, which enhances their performance and benefits the organization (De Souza and Alves, 2021).

^{Montalván et al. (2020)} emphasize that scientific production is the form in which knowledge is expressed, not necessarily associated with the academic field. Mohabad et al. (2020) and ^{Carvajal and Rodríguez (2019)} claim that it is the result of intellectual work, characterized by being published and unpublished, in order to contribute to the development of science. ^{Lopera et al. (2021)} point out that scientific production includes tangible materials susceptible of being quantified, such as books, articles, patents and their variants in printed and digital media (^{Alcalá and Parra, 2021}).

Human capital theory suggests that educational level, experience and individual skills are determinants, as educated and trained researchers are likely to conduct research (^{Montalván et al., 2020}). Social capital theory highlights the importance of social networks, interactions and collaborations with other scientists, both nationally and internationally. These connections facilitate the exchange of knowledge, experiences, resources and opportunities (^{Falla et al., 2022}). In this regard, life-cycle theory suggests that scientific productivity undergoes variations throughout a researcher's career, following an upward and positive trend according to the professional development achieved (^{Carvajal and Rodriguez, 2019}).

Levels of engagement and scientific production

As shown in Table 1, in regard to the levels of engagement and scientific production, 64.42% of the teachers surveyed reported a high level of engagement, 33.65% reported a medium level, and only 1.92% reported a low level. Regarding scientific production, 57.69% reported a low level, which includes the production of patents and others. On the other hand, 34.62% indicated a high level, focused on the publication of scientific articles in indexed journals such as Scopus, Scielo, Latindex, among others. Likewise, 7.69% mentioned a medium level in the publication of books or book chapters and conference papers.

These results coincide with ^{Moquillaza (2019)}, who suggests the need to improve engagement to increase scientific production, proposing strategies that are based on the reality of the institution and motivate teachers to conduct research. Similarly, ^{Falla et al. (2022)} point out that the level of engagement is reflected in enthusiasm, dedication and commitment to work, aspects that, when properly developed, have a positive impact on the quality of work and translate into high levels of scientific production.

Table 2 shows the frequencies and percentages of the levels of the dimensions of engagement. Regarding organizational culture, 58.7% of teachers indicated a high level, suggesting a relationship or predisposition towards research and scientific production. On the other hand, 41.3% stated a low level, showing the need for efforts to improve engagement levels. This result is in line with the statement of ^{Pedraza (2020)} who highlighted that organizational culture, responsibility, positive emotions and commitment are key requirements to improve engagement.

In the dimension of work factors, 59% stated a high level, coinciding with the studies of ^{Bakker and De Vries (2021)}, who showed that certain work factors such as financial profitability, organizational climate and decision making have a positive impact on employee commitment. 40.4% indicated a low level, suggesting that there is still low commitment on the part of teachers. This finding supports the claim of Albertcht et al. (2021), who stated that work factors are the main predictors of commitment.

In the personal factors dimension, 79.8% indicated a high level, evidencing energy and involvement to improve their knowledge and research capacity. This result is consistent with cross-cultural theory, which explains that personal factors, such as optimism, self-esteem, and resilience influence the ability of dedicated employees to positively influence their work environment (^{Carolina, 2019}; ^{Hughes et al., 2018}; ^{Pidduck et al., 2020}). 20.2% expressed a medium level.

In the reward system, 48.1% indicated a high level, 43.3% a medium level and 8.7% a low level. These results suggest the need to improve employee benefits, supporting the idea of ^{Salameh and Zamil (2020)}, who stated that reward is a benefit that generates job satisfaction. To improve these results, ^{Ntanos et al. (2020)} recommended that an effective reward system should be directly related to the levels of motivation and personal satisfaction. This implies implementing strategies that generate positive effects, leading to effective results where engagement levels reach the expectations of the organizations.

Regarding the types of scientific production, 34.62% corresponds to the publication of scientific articles in indexed journals such as Scopus, Web of Science, Scielo, Latindex, among others. In addition, 6.73% corresponds to the publication of books or book chapters, while 0.96% is attributed to utility patents. A significant percentage is related to other types of scientific production, such as conference papers, participation in congresses and research thesis advising.

The results obtained indicate a low percentage of teachers dedicated to scientific production, being the writing of scientific articles the main activity. It is crucial to improve this indicator, since the evaluation of the researcher is made through research results, which contribute to their qualification within the scientific community, as pointed out by Esteban et al. (2021). This result also finds support in the life-cycle theory, which suggests that scientific productivity varies according to a researcher's career, presenting an upward and positive trend as a function of their professional development (^{Carvajal and Rodriguez, 2019}).

It is essential that teachers maintain production levels in various types of scientific products, such as the creation of patents, writing of book chapters and publication in scientific articles with Q1 and Q2 indexing, in order to ensure a solid professional development in the scientific community.

Inferential results

A significance level of p = 0.05 was established and Kendall's Tau b test statistic was used to test the research hypotheses since transformations in three categories were used for both variables (low, medium and high).

The following study hypotheses were proposed:

General hypothesis

H0: Engagement is not related to scientific production

Hi: Engagement is related to scientific production at universities in Peru.

As shown in table 4, results show a positive and significant correlation between the variables, evidenced by a Spearman's rho coefficient of 0.195. This value indicates a low correlation, but the significance obtained was 0.039, which is less than the established significance level of 0.05. Consequently, the null hypothesis is rejected while the research hypothesis is accepted, with a confidence level of 95%.

According to the results of the dimension contrasts, it is observed that there is only a positive and significant correlation between work factors and scientific production (correlation coefficient = 0.190 and Sig. = 0.047 < 0.05), as well as between personal factors and scientific production (correlation coefficient = 0.211 and Sig. = 0.028 < 0.05). In contrast, no correlation was found between organizational culture, reward system and scientific production, since the significances in both cases were greater than 0.05.

These results suggest that it is necessary to address and improve both the organizational culture and the reward system to generate greater motivation and initiative on the part of teachers in the field of research. ^{Kebels (2022)} and ^{Pinho et al. (2018)}) highlighted in their studies that an organization that offers recognition to its collaborators, along with providing training and other benefits, manages to develop their commitment to the company, improving organizational support and employee satisfaction.