1. Introduction

Competitiveness is critical to an organization’s survival, profit generation, and contribution to the state’s economic, social, and political development [1,2]. Consequently, organizations strive to enhance their competitiveness through internal means or government assistance. A German government initiative – initially designed to increase the competitiveness of two of Germany’s most important industrial sectors and called Industry 4.0 - had a significant global impact [3].

The core concept of Industry 4.0 is digitizing the entire production chain, from suppliers to the end customer, minimizing human intervention throughout the value chain. Under these conditions, the goal is to combine production with high-quality services and intelligent monitoring and decision-making processes in a real-time environment. This self-organized production integrates people, machines, systems, products, and logistics through direct communication to make the entire organizational value chain more efficient [4,5].

Colombian organizations are aware that Industry 4.0 will affect them in some way, either positively by gaining more competitiveness through implementing Industry 4.0 elements or negatively by not doing so. The National Business Association of Colombia (ANDI) has been conducting surveys to estimate the state of Colombian organizations in implementing Industry 4.0 in the national territory. In their 2019 survey, 63.5% of their affiliates have a digital transformation strategy. 88.2% of organizations are familiar with the concept of Industry 4.0, and likewise, they are aware that the impact extends across the entire organization and not just a specific area (93.2%). However, this survey does not specify or evaluate the results of implementing Industry 4.0 initiatives in Colombian organizations. It is, therefore, essential to determine whether these initiatives have substantially impacted organizational results and whether their objectives have been achieved. Since Industry 4.0 encompasses a universe of possible initiatives to improve organizational results, this study focuses on determining the impact of additive technologies on strategies and changes in production processes to increase operational effectiveness. Deficient infrastructure, the Colombian topography, and the inherent potential for decentralized production in small batches through additive technologies generate advantages that Colombian organizations should exploit.

At the heart of Industry 4.0 lies the digitization of the entire production chain, from suppliers to end customers, with minimal human intervention. This transformation integrates intelligent monitoring, decision-making in real-time, and the seamless communication of people, machines, systems, and logistics throughout the value chain. The ultimate objective is to achieve a self-organized production system that optimizes efficiency, reduces waste, and improves product and service quality. As Industry 4.0 becomes a cornerstone of competitive strategy, it underscores the need for organizations to adapt and innovate to meet the demands of an increasingly interconnected and technology-driven world [6,7].

Integrating Industry 4.0 concepts, characterized by the seamless interplay of digital technologies, automation, and data exchange, is pivotal in enhancing competitiveness within the manufacturing landscape. In this transformative paradigm, additive technologies emerge as a critical enabler, fostering agility and innovation [8]. Industry 4.0-driven smart factories leverage additive manufacturing to facilitate on-demand production, rapid prototyping, and intricate customization, responding swiftly to dynamic market demands. The convergence of these technologies empowers organizations to achieve heightened operational efficiency, reduced lead times, and enhanced product quality [9]. Furthermore, the real-time data analytics inherent in Industry 4.0 enable predictive maintenance, optimizing the performance of additive manufacturing equipment. The synergy between Industry 4.0 and additive technologies elevates production capabilities and positions companies at the forefront of global competitiveness by fostering adaptive, cost-effective, and highly responsive manufacturing ecosystems [10].

Additive manufacturing (AM) has also revolutionized the aerospace industry by offering unprecedented design freedom, efficiency, and cost-effectiveness. Unlike traditional manufacturing methods, AM builds components layer by layer, enabling the creation of complex, lightweight structures that are critical for aerospace applications. This technology is particularly advantageous for producing intricate parts, such as turbine blades, fuel nozzles, and satellite components (such as antenna and communication devices), which require precision and reliability under extreme conditions. By minimizing material waste and allowing for the use of advanced materials like titanium alloys and high-performance polymers, AM significantly reduces production costs and environmental impact. Furthermore, the ability to rapidly prototype and customize designs facilitates innovation and accelerates development timelines, ensuring that aerospace manufacturers can meet evolving demands. AM also supports the concept of on-demand manufacturing, which is particularly beneficial for remote operations, such as space missions, where spare parts can be produced in situ. As the aerospace industry continues to prioritize efficiency, sustainability, and performance, additive manufacturing is set to remain a cornerstone of its innovation strategy. Consequently, the integration of additive manufacturing into antenna and communication system production not only drives innovation and cost-effectiveness in the aerospace sector but also addresses critical challenges in scalability, performance, and adaptability [11–14].

Many studies focus on the impact of strategies on the implementation of new technologies and the organization’s processes [15–17]. Nevertheless, the impact of process changes and innovation on organizational strategy still requires a more profound understanding [18,19].

The findings of this research are expected to contribute to both theoretical and practical understanding. Theoretically, the study aims to bridge gaps in the literature by exploring the dynamic interplay between additive technologies, strategy, and process innovation in the context of developing economies. Practically, it provides actionable recommendations for Colombian organizations seeking to enhance their competitiveness through Industry 4.0 initiatives. By identifying the conditions under which additive technologies contribute to operational effectiveness, the study offers a roadmap for leveraging these innovations to achieve sustainable growth.

Consequently, the research question for this study is: “What impact do factors such as innovation strategies and process innovation have on the relationship between additive technologies and operational effectiveness? Additionally, this question will be answered using two samples, one from the manufacturing industry and the other from the aerospace industry. This question will be answered using structural equation methodology, with input from collaborators from various Colombian organizations.

The remainder of the article is structured as follows. The conceptual framework for developing hypotheses and presenting the conceptual model of the relationship between the suggested variables is provided in Section 2, and the research methodology is presented in Section 3. The most significant observations and outcomes are presented in the fourth part. The used measurement items are shown in Section 5. Finally, in Section 6, the study’s conclusions, limitations, and potential directions for future research are reviewed.

2. Theoretical framework

2.4. Process innovation

Innovation is fundamental to any organizational strategy [57,58]. Industry 4.0 is a transformative innovation in managing production or offering services and is considered the fourth industrial revolution. It is necessary to generate, promote, and manage innovation adequately within the organization [59,60]. Therefore, innovation is considered the main driver of an organization’s competitiveness. Innovation management and innovative culture within an organization enable the improvement of process efficiency, market conquest, and the generation of innovative products and services, and, in general, support the organization’s survival over time and in markets [61,62]. Beyond managing an innovation process within the organization as something additional or not to be taken seriously, Industry 4.0 obliges organizations to rethink their business model, their way of managing their product and service offerings, and how to reach the customer, that is, to make innovative changes within the organization that improve its efficiency [5,63].

Depending on the context, the concept of innovation has different definitions. For Evangelista & Vezzani [64], innovation is any process that generates knowledge for the organization and its application within the organization. The Organization for Economic Cooperation and Development (OECD) extends the concept to include technological innovations and organizational innovations that involve changes from the organization’s structure to changes in procedures, routines, processes, and activities. Another definition considers innovation as any process or adaptation to improve the organization’s competitiveness [65,66]. The approach to innovation can be defined from the perspective of a result, a process, and a mindset of change. Considering these approaches, innovation, as a result, encompasses all changes in products, supply chains, the design of novel products or services, processes, and activities, or, in general, all results of the organization’s business model.

Similarly, innovation can also be considered a process, as it defines and designs organizational activities, processes, and routines to achieve the results of innovation initiatives. Finally, an innovative mindset within the organization is necessary, an innovative culture that allows for changes, experimentation, and acceptance that, in some cases, failure may occur [67,68]. Therefore, innovation is pervasive throughout the organization and cannot only be managed by a few individuals or departments. Constant support is required from management and all employees at all organizational levels.

Tidd & Bessant’s [28] model has been widely discussed as part of an organizational innovation model [69]. Tidd & Bessant [28] suggest an innovation space within which organizations can be located according to their way of innovating (radical or incremental) or in which organizational aspect they are innovating (product, position, processes, or paradigmatic). Industry 4.0 initiatives are primarily located in the process innovation space, as they modify the ways of producing and offering products and services to customers, even if the product or service remains the same. The product may be the same, but how it is produced and delivered to the customer changes to a more efficient, faster, and effective process [63,70]. Since additive technologies are an innovation that affects organizational processes to improve efficiency, the fourth hypothesis proposes a direct relationship between additive technologies and process innovation:

If an organization changes its processes due to the inclusion of new technologies, these changes also affect its strategy and vice-versa [46]. Process innovation means a change in capabilities and competencies, and consequently, it opens up a new strategic horizon for the organization [71]. In this sense, the organization can redefine or refine its strategy depending on the process changes. These changes could improve the organization’s efficiency in production processes or the generation of services. A second possibility is that process innovation facilitates individualizing products or services to differentiate them from the competition and gain a competitive advantage [72,73]. Many studies analyze the impact of strategy on changes in organizational processes but also process changes can define and enhance organizational strategies [71,74]. Process innovation introduces new ways of working, which often expand an organization’s operational capabilities. Additionally, organizations that innovate processes are better equipped to adapt to changing market conditions. For instance, supply chain process innovations, such as just-in-time inventory management or blockchain for transparency, enable firms to respond swiftly to disruptions. These process improvements can redefine organizational strategies by emphasizing agility, risk management, and resilience in a dynamic global environment. Finally, process innovation can transform how organizations deliver value to their customers. For instance, innovations in digital payment systems or customer service automation redefine strategies by focusing on customer experience and convenience. These changes not only enhance operational efficiency but also align the organization’s strategic goals with evolving customer expectations [72,75–77].

Therefore, the following hypothesis proposes that:

One of the main objectives of making organizational changes, such as process innovation, is to improve the company’s results through more efficient processes and routines or by producing new products or services. These changes can be planned as part of a change in organizational strategies or improving production resources. Alternatively, they can respond to changes in the organization’s environment, such as changes in legislation, consumer preferences, or new technologies, among others [34,78]. Therefore, we propose the following hypothesis:

Based on the literature review, we propose the following hypothesized model (Fig 1).

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Fig 1. Hypothetical model.

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3. Methodology

This study adopts an exploratory approach. There is a scarcity of research on additive technologies as part of Industry 4.0 initiatives and their relationship with operational effectiveness, strategies, and process innovation in developing economies [39,56]. Exploratory studies are conducted when there is little to no existing evidence regarding the phenomenon under investigation, and the existing literature only provides an imprecise general idea related to the problem [79,80]. Exploratory research allows therefore for a deeper investigation into complex phenomena where existing theoretical frameworks provide limited guidance. By focusing on the aerospace and manufacturing sectors, this methodology captures a diverse range of industrial contexts, each with unique challenges and opportunities, thereby enriching the study’s findings and offering broader implications for Industry 4.0 adoption.

This study’s initial phase involves defining the critical variables to be considered and addressing issues in implementing Industry 4.0 that affect many Colombian organizations through an extensive literature review. A questionnaire assessed perceptions based on the variables of interest identified in the first phase. The survey instrument was meticulously designed, drawing on established frameworks, including Tidd & Bessant’s innovation model [28], Santa et al.’s operational effectiveness framework [81], and Porter’s strategic models[82] and concepts related to additive technologies and Industry 4.0 from Haleem & Javaid [39], Horst et al. [35], and Steenhuis & Pretorius [83] (13 questions).. Each model was selected to align with the study’s objectives, ensuring the robustness of the constructs measured. The Likert-style questionnaire encompassed 37 items across key dimensions such as additive technologies, strategies, process innovation, and operational effectiveness, enabling a comprehensive analysis of the interrelationships among these variables. Care was taken to validate the content of the survey through expert reviews and pilot testing, ensuring clarity and relevance to the industrial contexts under investigation. The Likert-style questionnaire (from strongly disagree to strongly agree) presented different statements based on the variables. Additionally, the questionnaire includes a demographic section to characterize the organization and the sector in which the surveyed individuals operate. This questionnaire was administered virtually due to the ongoing pandemic in the country, which made conducting in-person surveys complex. Additionally, leveraging the benefits of online surveys was considered [84,85]. Data collection started on July 2022 and finished in December 2023. At the beginning of the questionnaire, a paragraph is included to inform participants that by continuing to answer, they consent to the collection of their data. Participants are made aware that they can withdraw from the questionnaire at any point, despite their initial agreement to data collection by proceeding with the survey. The questionnaire was distributed to various organizational stakeholders, including managers, technologists, administrative personnel, and operational staff, as these individuals may have differing perceptions of the phenomenon under study [86,87]. The survey was approved by the Ethics committee of Colegio de Estudios Superiores de Administración – CESA.

Of the 994 collected surveys, 945 (95%) were deemed usable. Most of these surveys were from the manufacturing sector (N =  423), followed by surveys collected from the aerospace industry (N =  522). Due to the significant interest of the aerospace sector in this study, the results of the two sectors are compared. By including a mix of stakeholders—ranging from managers to operational staff—the study captures a holistic perspective on additive technologies’ impact. The decision to focus on both the aerospace and manufacturing industries reflects their strategic importance in Colombia’s economy and their differing adoption patterns of Industry 4.0 initiatives. The aerospace sector’s emphasis on precision and high-quality standards contrasts with the broader manufacturing sector’s varied operational objectives, making this comparative analysis particularly valuable. Fig 2 shows the percentage of respondents working in the aerospacee or manufacturing sector.

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Fig 2. Sector of the respondent.

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Likewise, more than half of the respondents (54.6%) work in organizations with more than 251 employees, while only 8% work in organizations with 101 to 250 employees; meanwhile, 37.4% work in organizations with 100 or fewer employees (Fig 3).

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Fig 3. Organization size of the respondent.

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The software packages SPSS and AMOS were employed to conduct the statistical or multivariate analysis. These programs were used for confirmatory factor analysis and structural equation modeling to measure the model’s robustness and the impact of the variables in the established model. Confirmatory factor analysis (CFA) was employed to validate the robustness of the model following the guidelines of Hair et al. [80] and Byrne [88]. The Cronbach’s Alpha indicator was evaluated following established parameters, and since all values exceed 0.7, it can be affirmed that internal consistency within the model is achieved [89,90]. The choice of these tools underscores the study’s methodological rigor, allowing for robust testing of hypotheses and the reliability of constructs. Lastly, the comparative analysis between the aerospace and manufacturing sectors adds depth to the methodology. By identifying sector-specific differences in the impact of additive technologies, strategies, and process innovation, the study offers nuanced insights into Industry 4.0 adoption. For instance, the aerospace sector’s reliance on high precision and stringent quality controls influences its strategic priorities differently than the broader manufacturing sector. This comparative perspective underscores the study’s contribution to understanding how industrial context shapes the outcomes of technological innovation.

Initially, the dataset was divided into two distinct groups: one comprising data from the aerospace industry and the other from non-aerospace industries. Subsequently, statistical analyses were conducted for each group separately to calculate Cronbach’s Alpha, ensuring the reliability of the constructs, and to evaluate model fit indices, thereby validating the robustness of the measurement models for both sectors. The model robustness indicators provide the following information:

In addition to assessing internal consistency through Cronbach’s alpha, this study employed Confirmatory Factor Analysis (CFA) to ensure the validity and reliability of the constructs. CFA was used to validate the measurement model by testing the relationships between observed variables and their underlying latent constructs. Fit indices such as the Comparative Fit Index (CFI), Tucker-Lewis Index (TLI), Normed Fit Index (NFI), and Root Mean Square Error of Approximation (RMSEA) were evaluated to confirm the robustness of the model. The results demonstrated strong model fit for both the aerospace and general manufacturing sectors, with CFI and TLI values exceeding 0.9 and RMSEA values below 0.08. These results indicate that the constructs were appropriately measured and aligned with the theoretical framework [91,92].

Considering the presented indicators (Tables 1 and 2), both models are robust and valid for conducting path diagram analysis within structural equation modeling to determine the impact and interrelation of the variables of interest.

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Table 1. Cronbach’s alpha.

https://doi.org/10.1371/journal.pone.0318339.t001

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Table 2. Robustness indicators.

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4. Results

4.1. Results for the industry in general

According to these results (Table 3 and Fig 4), only hypothesis 1 proposed in the theoretical framework is rejected. In this regard, additive technologies do not impact operational effectiveness (Hypothesis 1, β =  0.1; P =  0.05). According to the statistical analysis, there is a strong relationship between additive technologies and process innovation (Hypothesis 4, β =  0.76; P <  0.001), between process innovation and operational effectiveness (β =  0.52; P <  0.001), and between process innovation and organizational strategies (Hypothesis 5, β =  0.68; P <  0.001). Meanwhile, there is a moderate relationship between strategy and operational effectiveness (Hypothesis 3, β =  0.34; P <  0.001) and a weak relationship between additive technologies and strategies (Hypothesis 2, β =  0.22; P <  0.001).

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Table 3. SEM results.

https://doi.org/10.1371/journal.pone.0318339.t003

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Fig 4. Structural model for the manufacturing sector (except Aerospace).

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4.2. Results for the aerospace sector

According to the results (Table 4 and Fig 5), only hypothesis 6 proposed is rejected. Process innovation has no significant relationship with operational effectiveness (Hypothesis 6, β =  0.14; P =  0.008). Meanwhile, the relationship between additive technologies and process innovation is strong (Hypothesis 4, β =  0.67; P <  0.001), as is the relationship between strategies and operational effectiveness (Hypothesis 3, β =  0.54; P <  0.001), and the relationship between process innovation and strategies (Hypothesis 5, β =  0.53; P <  0.001). The relationship between additive technologies and strategies is weak (Hypothesis 2, β =  0.25; P <  0.001), as well as the relationship between additive technologies and operational effectiveness (Hypothesis 1, β =  0.31; P <  0.001).

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Table 4. SEM results for the aerospace sector.

https://doi.org/10.1371/journal.pone.0318339.t004

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Fig 5. Structural model for the Aerospace sector.

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5. Discussion

The comparison (Table 5) between the β of the industry in general and the aerospace sector shows the following results:

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Table 5. Comparison of SEM results.

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For the Aerospace sector, only hypothesis 6 was rejected. Process innovation has no significant relationship with operational effectiveness (β =  0.14; P =  0.008). Meanwhile, there is a strong and close relationship between additive technologies and process innovation (β =  0.67; P <  0.001), confirming the proposals by Steenhuis & Pretorius [83] and Baumers & Holweg [93]. These authors suggest that additive technologies represent an innovation in the organization, affecting its processes incrementally in some industries and radically in others. The results, both for the industry in general and the aerospace sector, indicate that organizations understand the importance of additive technologies in driving innovations in their processes and routines and that these changes are necessary.

On the other hand, changes in organizational processes have consequences for organizational strategies because these changes, aimed at improving competitive positioning and addressing environmental changes, generate shifts in the organization’s capabilities and competencies, thus expanding the strategic horizon [67]. The results of this study confirm this view, as process innovation has a significant impact on strategies, which is valid not only for organizations across all sectors but also for the aerospace sector.

Interestingly, additive technologies have little impact on operational effectiveness and organizational strategies in the aerospace sector. For organizations in other manufacturing sectors, the impact of additive technologies on strategy is low, and there is no impact on operational effectiveness. These results contradict the literature in which additive technologies significantly boost organizational productivity and competitive advantage [38,94]. The reasons for this situation can be manifold. Firstly, Colombian organizations have limited knowledge of this new technology and its benefits, resulting in inadequate processes for implementing such innovations and, consequently, a lack of impact on strategies. Secondly, the initial cost of implementing additive technologies may be too high for organizations, thus having a low impact on operational effectiveness. This result also indicates the low importance of this innovative technology. Another possible cause could be that it is considered a significant change in organizational processes, changes that the organization is not willing to face. In this regard, organizational culture and a rigid, inflexible hierarchy hinder organizational innovation [95,96]. Since additive technologies do not significantly change organizational strategies, they cannot generate the expected impact even if this innovative technology is implemented adequately.

For the manufacturing industry in general, process innovation has a moderate impact on operational effectiveness, as do strategies. In this regard, organizations seem to not capitalize on innovations’ benefits. Although strategies impact operational effectiveness, the results suggest that strategies are focused on only a part of the organization or are not adequately communicated within the organization. The literature suggests a properly implemented strategy significantly increases operational effectiveness and organizational results [97,98]. Similarly, process innovation aims to enhance the organization’s competitive position and, thus, improve results [53,99]. However, it seems that Colombian organizations are not achieving these objectives.

It is also interesting to note that process innovation does not impact operational effectiveness in the aerospace industry. Innovation and change require internal and external components, and innovation becomes challenging with only internal resources [100]. The difference may lie in the fact that the aerospace industry depends mainly on a) connections between various organizations in the aerospace sector and b) conditions imposed by different governments [101]. In Colombia, cooperation with foreign and local organizations may be hindered by the high degree of regulation in the sector. Similarly, the necessary controls on suppliers hinder changes within the organization, and organizations thus remain relatively static in their processes that have worked [102]. Therefore, it is unsurprising that aerospace sector organizations have difficulties changing processes and routines, thus improving their operational efficiency. On the other hand, process innovation also impacts aerospace organizations’ strategies, although this impact is not very strong.

Another result is that the impact of strategies on operational effectiveness in the aerospace industry is more significant than in the manufacturing industry as a whole. The aerospace industry demands a high degree of product and process safety. From the five performance objectives of operational effectiveness (flexibility, costs, reliability, quality, and speed), quality and reliability are particularly significant in this industry, as a failure could result in the loss of human lives. Consequently, organizations in the Aerospace sector define strategies to increase operational effectiveness. These strategies may include Big Data analysis, standardized processes and routines, stringent quality controls, and the design of reliable and durable products [103–105]. In this manner, organizations in the sector ensure that the products they offer meet the requirements of their customers and that customers can receive a quality, reliable product that meets their needs. Hence, the standardization of processes and routines is essential, given the increasing complexity and costs of aerospace systems, and process innovations are carefully planned and executed [106]. Due to lower risks and investments, organizations may be more inclined to implement innovations in their processes and routines in other industries.

The differing SEM results for the aerospace and non-aerospace sectors in this study highlight the distinct dynamics and operational realities of these industries. In the aerospace sector, additive technologies show a more significant direct impact on operational effectiveness compared to the manufacturing sector. This stronger relationship is likely due to the aerospace industry’s reliance on advanced materials and precision engineering, which align closely with the capabilities of additive manufacturing. The ability to produce lightweight, intricate, and high-performance components makes additive technologies a critical innovation in Aerospace, where weight savings directly translate to fuel efficiency and cost reductions. Conversely, in the general manufacturing sector, additive technologies do not directly impact operational effectiveness. This discrepancy can be attributed to the sector’s broader range of products and processes, many of which do not require the level of precision and material efficiency that additive manufacturing offers. Additionally, traditional manufacturing methods may already be optimized for mass production, reducing the relative advantage of adopting additive technologies.

Process innovation also plays a contrasting role in these sectors. In the general manufacturing sector, process innovation significantly impacts operational effectiveness, indicating that manufacturers are leveraging new processes to improve efficiency, reduce costs, and enhance product quality. This reflects a readiness to adapt and innovate within existing frameworks, utilizing process improvements as a pathway to competitive advantage. However, in the aerospace sector, process innovation does not significantly impact on operational effectiveness. This outcome may stem from the stringent safety and quality requirements in Aerospace, where process changes must undergo rigorous validation and are often implemented cautiously. The high stakes associated with failure in Aerospace make organizations less likely to adopt radical process innovations, focusing instead on incremental improvements that prioritize reliability over efficiency gains.

The influence of strategies on operational effectiveness also varies between the sectors. Strategies have a stronger impact on operational effectiveness in the aerospace sector, reflecting the industry’s emphasis on structured planning, risk management, and long-term investment in innovation. Aerospace organizations often operate within highly regulated environments and depend on strategic frameworks to ensure compliance, optimize resource allocation, and maintain competitiveness. In contrast, strategies in the manufacturing sector have a moderate impact on operational effectiveness, potentially due to less stringent regulatory requirements and a broader diversity of strategic priorities that dilute their direct influence on operations.

These differences also reflect sector-specific external factors. The aerospace sector’s dependence on global supply chains, government contracts, and collaborations with international organizations creates unique constraints and opportunities for innovation. In contrast, the manufacturing sector often operates with more localized supply chains and faces fewer regulatory hurdles, enabling greater flexibility in adopting process innovations and technologies. Furthermore, the cost of implementing additive technologies is a significant barrier for many manufacturing organizations, particularly small and medium-sized enterprises, whereas the aerospace sector’s higher budgets and critical need for innovation justify these investments.

6. Conclusions

This study reveals distinct outcomes for the manufacturing and aerospace industries regarding the relationship between additive technologies, strategies, process innovation, and operational effectiveness. Organizations across sectors should prioritize implementing additive technologies to enhance productivity and gain a competitive edge. These technologies can be integrated through in-house capabilities or outsourcing. However, adopting such innovations necessitates strategic adjustments, as they reshape competencies and operational processes.

For the aerospace sector, innovation models and process routines must be revisited since their current configurations fail to enhance operational effectiveness. A thorough review of process scope, frequency, complexity, and implementation methods is essential to yield positive impacts. Aerospace organizations must also recognize that Industry 4.0 concepts, including additive technologies, induce cross-cutting organizational changes. Adapting to these transformations is critical for survival in competitive markets.

Differences between sectors emerge in their perception and application of innovation. The general manufacturing industry acknowledges the importance of process innovation for operational effectiveness but underutilizes the potential of additive technologies. This indicates an opportunity for manufacturers to capitalize on the benefits of 3D printing, such as reduced waste and improved production flexibility. In contrast, the aerospace sector exhibits resistance to process innovations despite recognizing the value of additive technologies for advanced product development.

Barriers in Colombia, including limited access to technology, skill gaps, and high implementation costs, hinder the full potential of additive manufacturing. Smaller businesses face challenges in acquiring equipment and expertise, while infrastructural deficiencies further exacerbate these issues. Addressing these constraints requires a collaborative effort to improve workforce training, infrastructure, and access to financial support.

The findings emphasize the importance of aligning strategies with operational changes to maximize the benefits of additive technologies. Strategies must foster adaptability and integration of innovations into processes, ensuring that operational effectiveness is consistently enhanced. For the aerospace sector, strategic focus on reliability and quality is crucial due to safety-critical requirements, while manufacturing industries must overcome traditional production biases to embrace additive technologies fully.