## 2 Literature Review
The main findings, starting from the application of 460 participants from 150 small and medium enterprises, demonstrated the importance of relating digital transformation and business performance. The HORSE Project--where BPM was applied--investigated several of the new technologies to find novel ways to improve flexibility. The purpose was to develop a system integrating these new technologies to support efficient and flexible manufacturing based on the application and extension of BPM to manage dynamic manufacturing processes [24]. On the other hand, [PERSON] et al. [25] used a modeling process for intelligent enterprises starting from understanding strategic topics to observe future behavior and trends. Their main findings show that the Business Process Model and Notation (BPMN), Unified Modeling Language (UML), and Petri Net are the most relevant languages for smart manufacturing. The authors highlighted the need for developing new languages capable of representing the dynamics, interoperability, and multiple technologies to be considered. A study developed in Germany by [PERSON] et al. [26] was based on BPM, where a particular process was modeled in a business to measure its dependence on the inflexibility of the traditional chart models, which has been considered as the main source of process rigidity. One of the studies related to operational performance (OP) and the use of Lean Management (LM) techniques for the development of small and medium enterprises is that set out by [PERSON] and [PERSON] [27], who applied and analyzed 268 surveys; among their main findings were that the association of lean manufacturing techniques have a positive effect in operational performance. However, the effect of technical LM on both types of innovation was not significant. In addition, process and management innovations positively mediated the social LM-OP relationship. Empirical studies have been developed with system dynamics related to the case study. For example, [PERSON] and [PERSON] [28] improved an assemblage line of front car seats. They considered modification in quantity and distribution of human talent and operations using a simulation model that represented and identified two improvement strategies. The first one, with almost null investment, increased line productivity by 12% and reduced the idle time by 44%. The second one, called \"integration of work centers\", broke production paradigms and allowed for obtaining still greater benefits [28]. From another perspective, [PERSON], [PERSON], and [PERSON] [29] analyzed the complexity associated with the production systems to improve process yield through the Six Sigma philosophy, using a dynamic model; the results showed an improvement in process yield by increasing the Sigma level that allowed for validating the proposed approach. The work of [PERSON] and [PERSON] [30] simulated the behavior of the main agribusiness productive chains that belong to the Department of Bolivar. The authors found different scenarios that were set out to determine the sensitivity and how these changes affected the productivity, employment, and usefulness of the actors. When 10% of increases and decreases showed in the participation percentages of the hectares harvested, all the actors experienced similar variations, either profits and/or losses. Indeed, an informatics model conducted by [PERSON] et al. [31] allowed for simulating the effect of Knowledge Management on the corn production industry. The result achieved was due to the application of Knowledge Management production that increased through system stability. Another recommendation is to perform the same study with the same methodology but applied to other agribusiness environments. Several works have focused--as is this research--on the study of the agri-food supply chain, such as [PERSON] and [PERSON] [32], who identified the implementation dynamics of traceability technologies in the fruit chain.