THEORETICAL FOUNDATIONS OF
COMPETITIVENESS IN SMES OF THE STEEL-
AUTOMOTIVE SECTOR IN NORTHEASTERN
MEXICO
FUNDAMENTOS TEÓRICOS DE LA COMPETITIVIDAD EN
PYMES DEL SECTOR SIDERÚRGICO-AUTOMOTRIZ EN EL
NORESTE DE MÉXICO.
Arlethe Yarí Aguilar Villarreal
Universidad Autónoma de Nuevo León, Facultad de Ciencias Químicas
Jesús Fabián López Pérez
Universidad Autónoma de Nuevo León, Facultad de Contaduría Pública y
Administración
pág. 7203
DOI: https://doi.org/10.37811/cl_rcm.v9i4.19313
Theoretical Foundations of Competitiveness in SMEs of the Steel-
Automotive Sector in Northeastern Mexico
Arlethe Yarí Aguilar Villarreal1
arlethe.aguilarvll@uanl.edu.mx
https://orcid.org/0000-0002-1438-2180
Universidad Autónoma de Nuevo León,
Facultad de Ciencias Químicas
San Nicolás de los Garza, Nuevo León, México
Jesús Fabián López Pérez
jesus.lopezpz@uanl.edu.mx
https://orcid.org/0000-0002-8283-6359
Universidad Autónoma de Nuevo León,
Facultad de Contaduría Pública y
Administración
San Nicolás de los Garza, Nuevo León, México
ABSTRACT
This article presents a theoretical review of the factors that influence the competitiveness of small and
medium-sized enterprises (SMEs) in the steel-automotive sector in Northeastern Mexico. Based on a
rigorous analysis of academic literature and national and international empirical studies, twelve key
variables affecting the level of SME competitiveness are identified. These factors include: degree of
technological innovation, productivity, energy efficiency, business profitability, level of Industry 4.0
adoption, strategic alliances, supply chain, employee training, globalization, innovation capacity, market
orientation, and quality. The main objective is to establish a robust theoretical framework that explains
how these variables interact and shape competitiveness in a global, dynamic, and highly demanding
environment such as the steel industry linked to the automotive sector. Findings from previous research
are integrated to support the relevance of each construct, enabling the design of a measurement
instrument to assess the level of business competitiveness. This work aims to contribute to the
development of a theoretical foundation for understanding the impact of competitiveness on industrial
SMEs, and to offer a basis for the design of strategies that enhance their performance in both national
and international markets.
Keywords: Competitiveness, SMEs, Steel Industry-Automotive Sector, Theoretical Framework,
Northeastern México
1 Autor principal.
Correspondencia: arlethe.aguilarvll@uanl.edu.mx
DOI: https://doi.org/10.37811/cl_rcm.v9i4.19313
Theoretical Foundations of Competitiveness in SMEs of the Steel-
Automotive Sector in Northeastern Mexico
Arlethe Yarí Aguilar Villarreal1
arlethe.aguilarvll@uanl.edu.mx
https://orcid.org/0000-0002-1438-2180
Universidad Autónoma de Nuevo León,
Facultad de Ciencias Químicas
San Nicolás de los Garza, Nuevo León, México
Jesús Fabián López Pérez
jesus.lopezpz@uanl.edu.mx
https://orcid.org/0000-0002-8283-6359
Universidad Autónoma de Nuevo León,
Facultad de Contaduría Pública y
Administración
San Nicolás de los Garza, Nuevo León, México
ABSTRACT
This article presents a theoretical review of the factors that influence the competitiveness of small and
medium-sized enterprises (SMEs) in the steel-automotive sector in Northeastern Mexico. Based on a
rigorous analysis of academic literature and national and international empirical studies, twelve key
variables affecting the level of SME competitiveness are identified. These factors include: degree of
technological innovation, productivity, energy efficiency, business profitability, level of Industry 4.0
adoption, strategic alliances, supply chain, employee training, globalization, innovation capacity, market
orientation, and quality. The main objective is to establish a robust theoretical framework that explains
how these variables interact and shape competitiveness in a global, dynamic, and highly demanding
environment such as the steel industry linked to the automotive sector. Findings from previous research
are integrated to support the relevance of each construct, enabling the design of a measurement
instrument to assess the level of business competitiveness. This work aims to contribute to the
development of a theoretical foundation for understanding the impact of competitiveness on industrial
SMEs, and to offer a basis for the design of strategies that enhance their performance in both national
and international markets.
Keywords: Competitiveness, SMEs, Steel Industry-Automotive Sector, Theoretical Framework,
Northeastern México
1 Autor principal.
Correspondencia: arlethe.aguilarvll@uanl.edu.mx
pág. 7204
Fundamentos teóricos de la competitividad en PyMEs del sector
siderúrgico-automotriz en el noreste de México.
RESUMEN
Este artículo desarrolla una revisión teórica sobre los factores que inciden en la competitividad de las
pequeñas y medianas empresas (PyMES) del sector siderúrgico-automotriz en el Noreste de México.
Con base en un análisis riguroso de literatura académica y estudios empíricos nacionales e
internacionales, se identifican 12 variables clave que influyen en el nivel de competitividad de las
PyMES, los factores relacionados son: grado de innovación tecnológica, productividad, eficiencia
energética, rentabilidad empresarial, nivel de adopción de tecnologías 4.0, alianzas estrategias, cadena
de suministros, nivel de capacitación para el personal, globalización, capacidad innovadora, mercado y
calidad. El objetivo principal es establecer un marco teórico robusto que explique cómo estas variables
se relacionan y condicionan la competitividad en un entorno global, dinámico y altamente demandante
como el de la industria del acero vinculada al sector automotriz. Se integran hallazgos de investigaciones
previas que sustentan la pertinencia de cada constructo, lo que permite diseñar un instrumento de
medición para diagnosticar el nivel de competitividad empresarial. Este trabajo busca contribuir en el
desarrollo del marco teórico que permita comprender el impacto de la competitividad en PyMEs
industriales, así como ofrecer una base para el diseño de estrategias que impulsen su desempeño en
mercados nacionales e internacionales.
Palabras clave: Competitividad, PyMEs, Sector Siderúrgico-Automotriz, Marco Teórico, Noreste de
México.
Artículo recibido 10 julio 2025
Aceptado para publicación: 16 agosto 2025
Fundamentos teóricos de la competitividad en PyMEs del sector
siderúrgico-automotriz en el noreste de México.
RESUMEN
Este artículo desarrolla una revisión teórica sobre los factores que inciden en la competitividad de las
pequeñas y medianas empresas (PyMES) del sector siderúrgico-automotriz en el Noreste de México.
Con base en un análisis riguroso de literatura académica y estudios empíricos nacionales e
internacionales, se identifican 12 variables clave que influyen en el nivel de competitividad de las
PyMES, los factores relacionados son: grado de innovación tecnológica, productividad, eficiencia
energética, rentabilidad empresarial, nivel de adopción de tecnologías 4.0, alianzas estrategias, cadena
de suministros, nivel de capacitación para el personal, globalización, capacidad innovadora, mercado y
calidad. El objetivo principal es establecer un marco teórico robusto que explique cómo estas variables
se relacionan y condicionan la competitividad en un entorno global, dinámico y altamente demandante
como el de la industria del acero vinculada al sector automotriz. Se integran hallazgos de investigaciones
previas que sustentan la pertinencia de cada constructo, lo que permite diseñar un instrumento de
medición para diagnosticar el nivel de competitividad empresarial. Este trabajo busca contribuir en el
desarrollo del marco teórico que permita comprender el impacto de la competitividad en PyMEs
industriales, así como ofrecer una base para el diseño de estrategias que impulsen su desempeño en
mercados nacionales e internacionales.
Palabras clave: Competitividad, PyMEs, Sector Siderúrgico-Automotriz, Marco Teórico, Noreste de
México.
Artículo recibido 10 julio 2025
Aceptado para publicación: 16 agosto 2025
pág. 7205
INTRODUCTION
On a global scale, micro and small enterprises (MSEs) play a fundamental role in economies, not only
due to their capacity to generate employment and income, but also for their contribution to productive
dynamism, innovation, and economic growth (OECD, 2021). However, the advancement of
globalization has intensified competition, particularly with large multinational corporations, which has
weakened the competitive position of many local businesses (Porter, 2007). In this context, Wanjohi
(2008) highlights that the business environment is one of the determining factors for the sustained
growth of MSEs.
In Latin America, these enterprises are a vital pillar of the productive structure. According to the
Economic Commission for Latin America and the Caribbean (ECLAC, 2021), micro and small
businesses account for 99% of all businesses and generate approximately 67% of regional employment
(Europyme, 2021). Nevertheless, their impact on economic development still faces limitations due to
structural barriers that affect their competitiveness.
In Mexico, the steel industry holds significant weight in the national productive apparatus, largely
comprised of micro and small enterprises. These organizations face major competitive challenges, both
domestically and internationally, especially in their linkage to strategic sectors such as the automotive
industry, where the competition for market positioning is increasingly intense (Espinoza, Cavazos, &
Cruz Álvarez, 2019). Within this context, MSEs in the steel-automotive sector emerge as key players
for economic development, while requiring strengthening strategies to improve their participation in
global value chains (Nahuat Arreguín, Blanco Jiménez, Cruz, & Buenrostro, 2016).
The steel industry represents a strategic sector in northeastern Mexico, particularly in the states of Nuevo
León and Coahuila. In Nuevo León, the steel value chain encompasses various activities, including raw
material production, pipe manufacturing, casting and rolling processes, production using electric
furnaces, service centers, marketing, and other steel-related industries (CANACERO, 2023).
In Coahuila, pipe production and steelmaking using both blast and electric furnaces are also
concentrated. The state also benefits from significant mineral deposits and a strategic border location
that provides customs infrastructure for the import and export of steel products (CANACERO, 2023).
INTRODUCTION
On a global scale, micro and small enterprises (MSEs) play a fundamental role in economies, not only
due to their capacity to generate employment and income, but also for their contribution to productive
dynamism, innovation, and economic growth (OECD, 2021). However, the advancement of
globalization has intensified competition, particularly with large multinational corporations, which has
weakened the competitive position of many local businesses (Porter, 2007). In this context, Wanjohi
(2008) highlights that the business environment is one of the determining factors for the sustained
growth of MSEs.
In Latin America, these enterprises are a vital pillar of the productive structure. According to the
Economic Commission for Latin America and the Caribbean (ECLAC, 2021), micro and small
businesses account for 99% of all businesses and generate approximately 67% of regional employment
(Europyme, 2021). Nevertheless, their impact on economic development still faces limitations due to
structural barriers that affect their competitiveness.
In Mexico, the steel industry holds significant weight in the national productive apparatus, largely
comprised of micro and small enterprises. These organizations face major competitive challenges, both
domestically and internationally, especially in their linkage to strategic sectors such as the automotive
industry, where the competition for market positioning is increasingly intense (Espinoza, Cavazos, &
Cruz Álvarez, 2019). Within this context, MSEs in the steel-automotive sector emerge as key players
for economic development, while requiring strengthening strategies to improve their participation in
global value chains (Nahuat Arreguín, Blanco Jiménez, Cruz, & Buenrostro, 2016).
The steel industry represents a strategic sector in northeastern Mexico, particularly in the states of Nuevo
León and Coahuila. In Nuevo León, the steel value chain encompasses various activities, including raw
material production, pipe manufacturing, casting and rolling processes, production using electric
furnaces, service centers, marketing, and other steel-related industries (CANACERO, 2023).
In Coahuila, pipe production and steelmaking using both blast and electric furnaces are also
concentrated. The state also benefits from significant mineral deposits and a strategic border location
that provides customs infrastructure for the import and export of steel products (CANACERO, 2023).
pág. 7206
Within the national supply chain, the basic iron and steel industry, along with the manufacture of derived
products, are key sectors in supplying the automotive industry. According to INEGI (2021), inputs from
the steel sector account for 6.3% of the total demand from the automotive industry, making it the second
most important source, only surpassed by the manufacture of auto parts.
A significant portion of regional steel production is destined for the automotive industry, which is
divided into two main branches: final vehicle assembly and auto parts manufacturing. This study focuses
on companies dedicated to the production of vehicles and engines.
According to INEGI (2021), the Mexican automotive industry is primarily concentrated in ten federal
entities, which account for 97.5% of national production and generate 88.8% of sectoral employment.
Coahuila ranks second nationwide in automobile and truck manufacturing, with a 15.9% share, while
Nuevo León ranks sixth, with 8.6% of total production.
Globally, automotive production is divided into two major categories: light and heavy vehicles. In
Mexico, the official classification defines light vehicles as passenger cars with up to eight seats, as well
as light commercial vehicles such as pickups, SUVs, minivans, and panel trucks. Heavy vehicles include
trucks over seven tons and buses with a capacity for more than eight passengers and also exceeding that
weight.
The automotive value chain relies on both domestic and imported inputs from various economic sectors.
In this regard, 41.5% of the inputs used are of national origin, while 58.5% come from foreign sources.
Among the most relevant national inputs are those from the basic iron and steel industry, which account
for 72.7% domestic participation, as well as the manufacture of iron and steel products, with 85% of
components being domestically sourced.
The competitiveness of small and medium-sized enterprises (SMEs) in the steel-automotive sector in
Mexico faces challenges that limit their ability to integrate sustainably and efficiently into national and
international value chains. Despite the economic and strategic relevance of this industry, significant gaps
remain. This work presents empirical studies on the competitive performance of SMEs across various
sectors, particularly in this sector, which is highly relevant to the country's economic development.
This contribution provides a theoretical framework that encourages the development of analytical
instruments and effective strategies to strengthen the competitive position of these companies. The aim
Within the national supply chain, the basic iron and steel industry, along with the manufacture of derived
products, are key sectors in supplying the automotive industry. According to INEGI (2021), inputs from
the steel sector account for 6.3% of the total demand from the automotive industry, making it the second
most important source, only surpassed by the manufacture of auto parts.
A significant portion of regional steel production is destined for the automotive industry, which is
divided into two main branches: final vehicle assembly and auto parts manufacturing. This study focuses
on companies dedicated to the production of vehicles and engines.
According to INEGI (2021), the Mexican automotive industry is primarily concentrated in ten federal
entities, which account for 97.5% of national production and generate 88.8% of sectoral employment.
Coahuila ranks second nationwide in automobile and truck manufacturing, with a 15.9% share, while
Nuevo León ranks sixth, with 8.6% of total production.
Globally, automotive production is divided into two major categories: light and heavy vehicles. In
Mexico, the official classification defines light vehicles as passenger cars with up to eight seats, as well
as light commercial vehicles such as pickups, SUVs, minivans, and panel trucks. Heavy vehicles include
trucks over seven tons and buses with a capacity for more than eight passengers and also exceeding that
weight.
The automotive value chain relies on both domestic and imported inputs from various economic sectors.
In this regard, 41.5% of the inputs used are of national origin, while 58.5% come from foreign sources.
Among the most relevant national inputs are those from the basic iron and steel industry, which account
for 72.7% domestic participation, as well as the manufacture of iron and steel products, with 85% of
components being domestically sourced.
The competitiveness of small and medium-sized enterprises (SMEs) in the steel-automotive sector in
Mexico faces challenges that limit their ability to integrate sustainably and efficiently into national and
international value chains. Despite the economic and strategic relevance of this industry, significant gaps
remain. This work presents empirical studies on the competitive performance of SMEs across various
sectors, particularly in this sector, which is highly relevant to the country's economic development.
This contribution provides a theoretical framework that encourages the development of analytical
instruments and effective strategies to strengthen the competitive position of these companies. The aim
pág. 7207
is to create a solid conceptual base that allows for comparison between studies and contexts, reflecting
the generation of cumulative and transferable knowledge. This article outlines a comprehensive
theoretical model that identifies, classifies, and relates the most relevant variables influencing the
competitiveness of these types of organizations.
This study presents the consolidation of a robust theoretical framework that underpins the analysis of
competitiveness in SMEs within the steel-automotive sector—a strategic segment for industrial
development in northeastern Mexico. The theoretical approach helps systematize existing knowledge
and facilitates the identification of conceptual gaps and the integration of dispersed empirical findings.
This theoretical contribution is key for guiding future research focused on business strengthening and
performance evaluation mechanisms.
The conceptual framework presented offers a useful tool for developing diagnostic instruments to
measure business competitiveness levels. This work contributes theoretical knowledge about
competitiveness in key industrial sectors.
THEORETICAL FRAMEWORK
As part of this research, a theoretical review is presented for each of the proposed variables in relation
to the dependent variable of competitiveness, as the central focus of study in this context.
Technological Innovation Degree
Regarding the variable of technological innovation degree, Skuza et al. (2020) state that despite the
growing demand for steel in Poland, the restructuring process of recent decades has driven both
structural and technological change in the steel industry. The privatization of major steel producers and
the influx of foreign capital have placed Polish metallurgy in a challenging period due to rising energy
prices, CO₂ emission fees, and a market shift toward “green steel.”
Additionally, Sekiguchi (2021) argues that OECD countries experienced an increase in steel production,
which led to improved international competitiveness. At the micro level, the analysis evaluated the link
between technology and export performance of major non-OECD steel-producing countries. The
technology selection of Chinese steel companies has contributed to the development of the steel
industry.
is to create a solid conceptual base that allows for comparison between studies and contexts, reflecting
the generation of cumulative and transferable knowledge. This article outlines a comprehensive
theoretical model that identifies, classifies, and relates the most relevant variables influencing the
competitiveness of these types of organizations.
This study presents the consolidation of a robust theoretical framework that underpins the analysis of
competitiveness in SMEs within the steel-automotive sector—a strategic segment for industrial
development in northeastern Mexico. The theoretical approach helps systematize existing knowledge
and facilitates the identification of conceptual gaps and the integration of dispersed empirical findings.
This theoretical contribution is key for guiding future research focused on business strengthening and
performance evaluation mechanisms.
The conceptual framework presented offers a useful tool for developing diagnostic instruments to
measure business competitiveness levels. This work contributes theoretical knowledge about
competitiveness in key industrial sectors.
THEORETICAL FRAMEWORK
As part of this research, a theoretical review is presented for each of the proposed variables in relation
to the dependent variable of competitiveness, as the central focus of study in this context.
Technological Innovation Degree
Regarding the variable of technological innovation degree, Skuza et al. (2020) state that despite the
growing demand for steel in Poland, the restructuring process of recent decades has driven both
structural and technological change in the steel industry. The privatization of major steel producers and
the influx of foreign capital have placed Polish metallurgy in a challenging period due to rising energy
prices, CO₂ emission fees, and a market shift toward “green steel.”
Additionally, Sekiguchi (2021) argues that OECD countries experienced an increase in steel production,
which led to improved international competitiveness. At the micro level, the analysis evaluated the link
between technology and export performance of major non-OECD steel-producing countries. The
technology selection of Chinese steel companies has contributed to the development of the steel
industry.
pág. 7208
On the other hand, Yuguo et al. (2021) present a study in which the development and application of a
multidimensional model provide a method for assessing low-carbon emissions. This technique helps
determine a company’s carbon level and raise awareness among stakeholders about competitiveness
trends in low-carbon contexts. Low-carbon competitiveness will become an integral part of business
rivalry and a driving force for corporate survival and sustainability.
Tong et al. (2022) investigated the impact of core technological competence on the competitive
advantage of high-tech SMEs in China, using 379 survey responses and a Structural Equation Modeling
(SEM) approach. The results show that infrastructure and technology, advanced technologies, and R&D
capacity significantly affect competitive advantage and organizational flexibility, which mediates the
relationship between R&D and competitiveness. The study highlights the importance of strengthening
technological infrastructure and organizational adaptability to achieve competitive advantage.
Radicic et al. (2023) analyzed the impact of digitalization on technological product and process
innovations in German SMEs using data from the Mannheim Innovation Panel (MIP). They assessed
three types of digitalization: production and logistics, digital value chains, and big data analytics using
binary probit models across different company sizes. Results showed a heterogeneous impact depending
on the type of digitalization and innovation. Internal R&D mitigates the effect of digitalization, proving
to be beneficial for SMEs.
Finally, Merung A.Y. et al. (2024) examined social capital, technological innovation, and
entrepreneurial orientation and how they influence the competitiveness of MSMEs in Kintamani, Bali.
Using quantitative analysis with data from 276 firms and a SEM-PLS model, they found a positive
correlation between competitiveness, social capital, innovation, and entrepreneurial behavior. Social
capital acts as a moderator, strengthening the effects on competitiveness. The model showed a good fit,
suggesting strategies to improve competitiveness and sustainable growth in Kintamani through
enhanced social capital, technology adoption, and entrepreneurial orientation.
On the other hand, Yuguo et al. (2021) present a study in which the development and application of a
multidimensional model provide a method for assessing low-carbon emissions. This technique helps
determine a company’s carbon level and raise awareness among stakeholders about competitiveness
trends in low-carbon contexts. Low-carbon competitiveness will become an integral part of business
rivalry and a driving force for corporate survival and sustainability.
Tong et al. (2022) investigated the impact of core technological competence on the competitive
advantage of high-tech SMEs in China, using 379 survey responses and a Structural Equation Modeling
(SEM) approach. The results show that infrastructure and technology, advanced technologies, and R&D
capacity significantly affect competitive advantage and organizational flexibility, which mediates the
relationship between R&D and competitiveness. The study highlights the importance of strengthening
technological infrastructure and organizational adaptability to achieve competitive advantage.
Radicic et al. (2023) analyzed the impact of digitalization on technological product and process
innovations in German SMEs using data from the Mannheim Innovation Panel (MIP). They assessed
three types of digitalization: production and logistics, digital value chains, and big data analytics using
binary probit models across different company sizes. Results showed a heterogeneous impact depending
on the type of digitalization and innovation. Internal R&D mitigates the effect of digitalization, proving
to be beneficial for SMEs.
Finally, Merung A.Y. et al. (2024) examined social capital, technological innovation, and
entrepreneurial orientation and how they influence the competitiveness of MSMEs in Kintamani, Bali.
Using quantitative analysis with data from 276 firms and a SEM-PLS model, they found a positive
correlation between competitiveness, social capital, innovation, and entrepreneurial behavior. Social
capital acts as a moderator, strengthening the effects on competitiveness. The model showed a good fit,
suggesting strategies to improve competitiveness and sustainable growth in Kintamani through
enhanced social capital, technology adoption, and entrepreneurial orientation.
pág. 7209
Productivity
As an independent variable, productivity has been examined in several studies. Conceição et al. (2017)
presented a scenario where it was necessary to increase competitiveness without additional
investment—only by optimizing products and the production process. The objective was achieved by
updating equipment and reducing waste in certain areas. Ultimately, the project led to a 41% increase
in productivity through the implementation of Lean tools. It also met customer demand and avoided the
need to purchase a new production line, resulting in significant cost savings for the company while
minimizing losses from the original line through increased output.
Similarly, Kumar (2021) argues that in India, over the past 30 years, both steel production and
consumption have increased, leading to expanded production capacity. However, the competitiveness
of India’s steel industry does not show a significant break from the pre-reform decade. Real
productivity—both labor and capital—has improved during the period studied. Kumar concludes that
productivity is a critical factor in competitiveness. Using longitudinal time-series data, he offers a
measurement framework to evaluate productivity trends, attributable to technological progress, under
the identification of three key parameters for India’s steel industry: changes in ownership structure, trade
integration, and technological shifts in production routes.
Additionally, Owalla et al. (2022) conducted a systematic literature review to map global research on
SME productivity, analyzing 109 empirical studies. They identified six key themes influencing
productivity: organizational environment, capabilities, investment, types of innovation, external
knowledge base, and commercialization. The results reveal the fragmented nature of current research
and significant knowledge gaps. The authors propose a future research agenda and discuss policy
implications for enhancing SME productivity in the context of evolving global trends.
Mansur et al. (2023) assessed the impact of various capabilities and orientations on the competitiveness
of informal small businesses in Surabaya. Using surveys from 187 participants and SEM analysis,
findings showed that production capacity, innovation, and labor productivity positively influence
performance and competitiveness. Innovation and labor productivity contribute to competitiveness
through performance. These results underscore the importance of strengthening productive and
innovative capacities to enhance competitiveness.
Productivity
As an independent variable, productivity has been examined in several studies. Conceição et al. (2017)
presented a scenario where it was necessary to increase competitiveness without additional
investment—only by optimizing products and the production process. The objective was achieved by
updating equipment and reducing waste in certain areas. Ultimately, the project led to a 41% increase
in productivity through the implementation of Lean tools. It also met customer demand and avoided the
need to purchase a new production line, resulting in significant cost savings for the company while
minimizing losses from the original line through increased output.
Similarly, Kumar (2021) argues that in India, over the past 30 years, both steel production and
consumption have increased, leading to expanded production capacity. However, the competitiveness
of India’s steel industry does not show a significant break from the pre-reform decade. Real
productivity—both labor and capital—has improved during the period studied. Kumar concludes that
productivity is a critical factor in competitiveness. Using longitudinal time-series data, he offers a
measurement framework to evaluate productivity trends, attributable to technological progress, under
the identification of three key parameters for India’s steel industry: changes in ownership structure, trade
integration, and technological shifts in production routes.
Additionally, Owalla et al. (2022) conducted a systematic literature review to map global research on
SME productivity, analyzing 109 empirical studies. They identified six key themes influencing
productivity: organizational environment, capabilities, investment, types of innovation, external
knowledge base, and commercialization. The results reveal the fragmented nature of current research
and significant knowledge gaps. The authors propose a future research agenda and discuss policy
implications for enhancing SME productivity in the context of evolving global trends.
Mansur et al. (2023) assessed the impact of various capabilities and orientations on the competitiveness
of informal small businesses in Surabaya. Using surveys from 187 participants and SEM analysis,
findings showed that production capacity, innovation, and labor productivity positively influence
performance and competitiveness. Innovation and labor productivity contribute to competitiveness
through performance. These results underscore the importance of strengthening productive and
innovative capacities to enhance competitiveness.
pág. 7210
Energy Efficiency
Chowdhury et al. (2018) report that in the United Kingdom, the industrial and manufacturing sectors
face a major challenge in contributing to the national goal of reducing CO₂ emissions by 80%, while
also improving economic competitiveness in the face of low-cost imports. The study explores energy
efficiency improvements from three perspectives: steam network system efficiency, waste heat recovery
technologies, and bioenergy utilization, particularly in two sectors—the iron and steel industry and the
food and beverage sector. Currently, there are no standardized business models for energy efficiency in
industry, so adapting a known business model that integrates energy systems optimization is necessary.
Haider et al. (2019) conducted an analysis comparing energy use in India’s steel industry. The objective
was to estimate energy efficiency within the framework of total factor productivity and identify potential
energy savings across states at optimal scale. The study recommends implementing a standardized
energy efficiency program and promoting a market-based and regulatory mechanism to realize the
enormous energy-saving potential.
Vögele et al. (2020) provide a broad overview of the challenges facing the steel industry in the European
Union, such as volatile input prices, uncertainties regarding CO₂ regulations, emissions, and market
shocks caused by import tariffs.
Radoslaw (2020) also studied the steel sector—critical to both Poland’s national economy and the global
market. In response to global steel market challenges and the need to boost competitiveness, the study
outlines a series of actions to improve energy efficiency in steel production. It seeks to identify energy
efficiency trends within companies, particularly those aiming to improve production processes. It offers
investment policy recommendations for Poland’s steel sector in the Industry 4.0 era. The proposed
econometric model shows the relationship between electricity consumption per ton of steel and
investment levels, linking these expenditures to Industry 4.0 implementation strategies. The study
suggests that steel companies should engage in network-based cooperation with cyber-physical
intelligence to improve flexibility along the supply chain and reduce energy consumption.
Stroud et al. (2020) propose energy efficiency as a key area of innovation activity in the European steel
industry, with authorities aiming to “green” worker behavior. The focus is on combining digital
innovation and strategic management with gamification to drive behavioral change toward energy
Energy Efficiency
Chowdhury et al. (2018) report that in the United Kingdom, the industrial and manufacturing sectors
face a major challenge in contributing to the national goal of reducing CO₂ emissions by 80%, while
also improving economic competitiveness in the face of low-cost imports. The study explores energy
efficiency improvements from three perspectives: steam network system efficiency, waste heat recovery
technologies, and bioenergy utilization, particularly in two sectors—the iron and steel industry and the
food and beverage sector. Currently, there are no standardized business models for energy efficiency in
industry, so adapting a known business model that integrates energy systems optimization is necessary.
Haider et al. (2019) conducted an analysis comparing energy use in India’s steel industry. The objective
was to estimate energy efficiency within the framework of total factor productivity and identify potential
energy savings across states at optimal scale. The study recommends implementing a standardized
energy efficiency program and promoting a market-based and regulatory mechanism to realize the
enormous energy-saving potential.
Vögele et al. (2020) provide a broad overview of the challenges facing the steel industry in the European
Union, such as volatile input prices, uncertainties regarding CO₂ regulations, emissions, and market
shocks caused by import tariffs.
Radoslaw (2020) also studied the steel sector—critical to both Poland’s national economy and the global
market. In response to global steel market challenges and the need to boost competitiveness, the study
outlines a series of actions to improve energy efficiency in steel production. It seeks to identify energy
efficiency trends within companies, particularly those aiming to improve production processes. It offers
investment policy recommendations for Poland’s steel sector in the Industry 4.0 era. The proposed
econometric model shows the relationship between electricity consumption per ton of steel and
investment levels, linking these expenditures to Industry 4.0 implementation strategies. The study
suggests that steel companies should engage in network-based cooperation with cyber-physical
intelligence to improve flexibility along the supply chain and reduce energy consumption.
Stroud et al. (2020) propose energy efficiency as a key area of innovation activity in the European steel
industry, with authorities aiming to “green” worker behavior. The focus is on combining digital
innovation and strategic management with gamification to drive behavioral change toward energy
pág. 7211
efficiency. The study presents challenges for workers and unions in the sector, highlighting the dual
pressure of green transformation and digitalization. It outlines labor relations, digital innovation
management for green practices, and potential outcomes for workers within a heavily unionized
industry.
Talaei et al. (2020) developed a system-based model to assess the long-term potential of energy
efficiency alternatives in reducing household gas emissions. A case study was conducted on Canada’s
iron and steel sector. The results informed the development of energy demand projections, offering
detailed insights into unit operations, fuel types, and energy intensities. These data were used in a long-
term energy alternatives planning model.
Di Foggia (2021) analyzed how energy-efficient servitization capabilities impact business performance
in 293 manufacturers of electrical and machinery equipment. Using two structural equation models, the
mediating role of servitization was assessed in relation to competitive strategy analysis and regulatory
framework awareness. The findings show both factors positively influence business performance
through servitization. The growing demand for energy-efficient products and energy management
services highlights the importance of these approaches for decarbonization and enhanced industrial
competitiveness.
Gąsior et al. (2022) also studied the relationship between energy-efficient servitization and business
performance in 293 manufacturers of electrical and machinery equipment. Using structural equation
models, they tested how competitive structure analysis and regulatory knowledge affect performance
through servitization. Results show both factors significantly enhance business performance. With
expected growth in demand for energy-efficient products, the need for lower energy footprints and
energy management services becomes critical to support industrial decarbonization and
competitiveness.
Majid et al. (2023) examined the impact of eco-efficiency actions—such as resource savings and
renewable energy use—on SME performance across 28 EU countries. Using survey data and logistic
regression analysis in SPSS, they analyzed how these practices influence costs, investments, and
barriers. Findings reveal that SMEs often lack information about the financial and innovation benefits
efficiency. The study presents challenges for workers and unions in the sector, highlighting the dual
pressure of green transformation and digitalization. It outlines labor relations, digital innovation
management for green practices, and potential outcomes for workers within a heavily unionized
industry.
Talaei et al. (2020) developed a system-based model to assess the long-term potential of energy
efficiency alternatives in reducing household gas emissions. A case study was conducted on Canada’s
iron and steel sector. The results informed the development of energy demand projections, offering
detailed insights into unit operations, fuel types, and energy intensities. These data were used in a long-
term energy alternatives planning model.
Di Foggia (2021) analyzed how energy-efficient servitization capabilities impact business performance
in 293 manufacturers of electrical and machinery equipment. Using two structural equation models, the
mediating role of servitization was assessed in relation to competitive strategy analysis and regulatory
framework awareness. The findings show both factors positively influence business performance
through servitization. The growing demand for energy-efficient products and energy management
services highlights the importance of these approaches for decarbonization and enhanced industrial
competitiveness.
Gąsior et al. (2022) also studied the relationship between energy-efficient servitization and business
performance in 293 manufacturers of electrical and machinery equipment. Using structural equation
models, they tested how competitive structure analysis and regulatory knowledge affect performance
through servitization. Results show both factors significantly enhance business performance. With
expected growth in demand for energy-efficient products, the need for lower energy footprints and
energy management services becomes critical to support industrial decarbonization and
competitiveness.
Majid et al. (2023) examined the impact of eco-efficiency actions—such as resource savings and
renewable energy use—on SME performance across 28 EU countries. Using survey data and logistic
regression analysis in SPSS, they analyzed how these practices influence costs, investments, and
barriers. Findings reveal that SMEs often lack information about the financial and innovation benefits
pág. 7212
of these practices. The results provide guidance for SMEs and policymakers to promote sustainable
development and improved decision-making.
Tazhibekova et al. (2024) evaluated the environmental sustainability of SMEs in Kazakhstan by
analyzing their adoption of green strategies and energy-saving technologies through surveys with
entrepreneurs and managers. Results indicate high environmental awareness and willingness to
implement sustainable practices, reflecting SMEs’ potential for sustainable development. The growing
adoption of energy-efficient technologies enhances competitiveness and reduces ecological footprints.
These findings support the development of effective environmental policies and green investment
strategies to strengthen SMEs’ resilience and environmental responsibility.
Business Profitability
As part of the study, business profitability was also considered an independent variable. Nguyen et al.
(2016) developed a research model to examine the influence of organizational capabilities in Taiwan’s
steel industry, considering manufacturing strategy, business performance, and the effect of
manufacturing strategy on performance. The study concluded that organizational capabilities positively
affect both the manufacturing strategy and business performance. The results empirically verify that
improving organizational capabilities is the most critical factor for enhancing manufacturing strategy
and business outcomes. The authors suggest that Taiwanese steel companies should strengthen their
organizational capabilities to develop manufacturing strategies that improve profitability.
Vătămănescu et al. (2017) analyzed the relevance of strengthening relational capital in SMEs operating
in a globalized market. Their study demonstrated how competitiveness influences business networks
with the goal of facilitating the internationalization of European SMEs in the steel tube sector. The
results indicate that internationalization effectiveness is indirectly influenced by competitiveness, which
drives SME managers to leverage personal and organizational relationships through consistent work
networks and capitalized trust. At this level, business networking had a positive and significant impact.
Lesáková et al. (2019) analyzed SME profitability in Slovakia’s mechanical engineering industry by
evaluating influential internal and external factors. Using the DuPont pyramid analysis and survey data,
the study identified elements affecting profitability. Friedman and Wilcoxon tests were applied to assess
survey responses and test three defined hypotheses. The findings provide key guidelines for short- and
of these practices. The results provide guidance for SMEs and policymakers to promote sustainable
development and improved decision-making.
Tazhibekova et al. (2024) evaluated the environmental sustainability of SMEs in Kazakhstan by
analyzing their adoption of green strategies and energy-saving technologies through surveys with
entrepreneurs and managers. Results indicate high environmental awareness and willingness to
implement sustainable practices, reflecting SMEs’ potential for sustainable development. The growing
adoption of energy-efficient technologies enhances competitiveness and reduces ecological footprints.
These findings support the development of effective environmental policies and green investment
strategies to strengthen SMEs’ resilience and environmental responsibility.
Business Profitability
As part of the study, business profitability was also considered an independent variable. Nguyen et al.
(2016) developed a research model to examine the influence of organizational capabilities in Taiwan’s
steel industry, considering manufacturing strategy, business performance, and the effect of
manufacturing strategy on performance. The study concluded that organizational capabilities positively
affect both the manufacturing strategy and business performance. The results empirically verify that
improving organizational capabilities is the most critical factor for enhancing manufacturing strategy
and business outcomes. The authors suggest that Taiwanese steel companies should strengthen their
organizational capabilities to develop manufacturing strategies that improve profitability.
Vătămănescu et al. (2017) analyzed the relevance of strengthening relational capital in SMEs operating
in a globalized market. Their study demonstrated how competitiveness influences business networks
with the goal of facilitating the internationalization of European SMEs in the steel tube sector. The
results indicate that internationalization effectiveness is indirectly influenced by competitiveness, which
drives SME managers to leverage personal and organizational relationships through consistent work
networks and capitalized trust. At this level, business networking had a positive and significant impact.
Lesáková et al. (2019) analyzed SME profitability in Slovakia’s mechanical engineering industry by
evaluating influential internal and external factors. Using the DuPont pyramid analysis and survey data,
the study identified elements affecting profitability. Friedman and Wilcoxon tests were applied to assess
survey responses and test three defined hypotheses. The findings provide key guidelines for short- and
pág. 7213
long-term decision-making, highlighting the importance of strategically managing profitability in this
essential sector of Slovakia's economy.
Ramirez-Garzon et al. (2020) assessed the application of the Organizational Management
Modernization Model (MMOM) and its impact on Return on Assets (ROA) in 144 Colombian SMEs.
Using multiple regression analysis, they found that components such as strategic direction, production
management, human resource management, logistics, and innovation and knowledge accounted for 20%
to 23% of profitability. The findings underscore the importance of these organizational elements for
business competitiveness and their influence on SME profitability, providing a foundation to improve
management and performance in the sector.
Gajdzik et al. (2021) analyzed resource intensity in the Polish steel industry and its relationship with
investment, focusing on energy consumption during steel production. Using statistical data from 2004
to 2018, the authors developed econometric models to evaluate the impact of investment on reducing
electricity and coke consumption per facility. The results confirmed that higher investments contribute
to reducing resource intensity, thus improving competitiveness and environmental protection. These
findings are relevant for public policy and business leaders, suggesting a focus on technological
investments to optimize efficiency and sustainability.
Shashina et al. (2022) emphasized that profitability management is key to improving long-term
efficiency and business competitiveness. Their study analyzed how to optimize profitability through an
integrated model within the company’s general strategy. The importance of internal factors such as
productive efficiency, organizational structure, leadership quality, and asset composition is highlighted.
The proposed model includes an information base and indicator system to evaluate both internal and
external environments, aligning with strategic goals. Proper implementation of the model can identify
opportunities and ensure sustainable economic growth.
Mansur et al. (2023) studied various factors influencing performance and competitiveness in informal
small businesses in Surabaya, Indonesia. Based on primary data from 187 surveys and using Structural
Equation Modeling (SEM), results show that production capacity, innovation, and labor productivity
significantly affect performance and competitiveness. Market orientation, however, only affects
competitiveness. Furthermore, innovation and labor productivity enhance competitiveness through their
long-term decision-making, highlighting the importance of strategically managing profitability in this
essential sector of Slovakia's economy.
Ramirez-Garzon et al. (2020) assessed the application of the Organizational Management
Modernization Model (MMOM) and its impact on Return on Assets (ROA) in 144 Colombian SMEs.
Using multiple regression analysis, they found that components such as strategic direction, production
management, human resource management, logistics, and innovation and knowledge accounted for 20%
to 23% of profitability. The findings underscore the importance of these organizational elements for
business competitiveness and their influence on SME profitability, providing a foundation to improve
management and performance in the sector.
Gajdzik et al. (2021) analyzed resource intensity in the Polish steel industry and its relationship with
investment, focusing on energy consumption during steel production. Using statistical data from 2004
to 2018, the authors developed econometric models to evaluate the impact of investment on reducing
electricity and coke consumption per facility. The results confirmed that higher investments contribute
to reducing resource intensity, thus improving competitiveness and environmental protection. These
findings are relevant for public policy and business leaders, suggesting a focus on technological
investments to optimize efficiency and sustainability.
Shashina et al. (2022) emphasized that profitability management is key to improving long-term
efficiency and business competitiveness. Their study analyzed how to optimize profitability through an
integrated model within the company’s general strategy. The importance of internal factors such as
productive efficiency, organizational structure, leadership quality, and asset composition is highlighted.
The proposed model includes an information base and indicator system to evaluate both internal and
external environments, aligning with strategic goals. Proper implementation of the model can identify
opportunities and ensure sustainable economic growth.
Mansur et al. (2023) studied various factors influencing performance and competitiveness in informal
small businesses in Surabaya, Indonesia. Based on primary data from 187 surveys and using Structural
Equation Modeling (SEM), results show that production capacity, innovation, and labor productivity
significantly affect performance and competitiveness. Market orientation, however, only affects
competitiveness. Furthermore, innovation and labor productivity enhance competitiveness through their
pág. 7214
influence on business performance. This study offers key insights for improving business
competitiveness.
Henríquez-Calvo (2024) analyzed activities, limitations, and challenges related to process innovation in
56 Colombian exporting SMEs through a 19-question survey, artificial neural networks (ANN), and
Spearman correlation. The findings reveal that collaboration with research institutions and suppliers is
critical for process innovation, which is prioritized by SMEs to boost competitiveness. Innovation was
linked to growth, productivity, and internationalization, despite Colombia’s innovation gap. Companies
are investing in R&D and external collaboration with a focus on efficiency. The study recommends
exploring innovation connections using machine learning.
Strategic Alliances
Strategic alliances were also studied as an independent variable. Yeh et al. (2017) report that companies
seek to create synergy through research and development partnerships. This study examines the
performance of firms within such alliances, focusing on their dependence on resources, organizational
learning, and the impact on alliance performance. The results indicate that alliances have significant
implications for effectiveness, and practitioners aim to improve their outcomes. A company’s ability to
leverage both internal and external R&D activities influences its capacity to generate economic value
through innovation and sustain its competitive advantage.
Adoption Level of Industry 4.0 Technologies (First Part)
Götz et al. (2020) reported on the implications and effects of adopting Industry 4.0 in internationally-
oriented companies. Their study reveals that businesses are preparing to face challenges such as
acquiring the necessary knowledge and becoming familiar with implementing 4.0 technologies. The
study highlights that the path toward Industry 4.0 favors quality over low cost, arguing that a company's
competitiveness will depend on its maturity in adopting Industry 4.0. Furthermore, this impact is shaped
by cooperation among partners.
Sima et al. (2020) explored major opportunities and challenges, especially in education, related to
changes in the work environment brought by Industry 4.0, such as evolving occupations, job profiles,
and other human capital drivers. The study analyzes consumer behavior and workforce development
from the perspective of the Fourth Industrial Revolution. The findings reflect technological shifts—
influence on business performance. This study offers key insights for improving business
competitiveness.
Henríquez-Calvo (2024) analyzed activities, limitations, and challenges related to process innovation in
56 Colombian exporting SMEs through a 19-question survey, artificial neural networks (ANN), and
Spearman correlation. The findings reveal that collaboration with research institutions and suppliers is
critical for process innovation, which is prioritized by SMEs to boost competitiveness. Innovation was
linked to growth, productivity, and internationalization, despite Colombia’s innovation gap. Companies
are investing in R&D and external collaboration with a focus on efficiency. The study recommends
exploring innovation connections using machine learning.
Strategic Alliances
Strategic alliances were also studied as an independent variable. Yeh et al. (2017) report that companies
seek to create synergy through research and development partnerships. This study examines the
performance of firms within such alliances, focusing on their dependence on resources, organizational
learning, and the impact on alliance performance. The results indicate that alliances have significant
implications for effectiveness, and practitioners aim to improve their outcomes. A company’s ability to
leverage both internal and external R&D activities influences its capacity to generate economic value
through innovation and sustain its competitive advantage.
Adoption Level of Industry 4.0 Technologies (First Part)
Götz et al. (2020) reported on the implications and effects of adopting Industry 4.0 in internationally-
oriented companies. Their study reveals that businesses are preparing to face challenges such as
acquiring the necessary knowledge and becoming familiar with implementing 4.0 technologies. The
study highlights that the path toward Industry 4.0 favors quality over low cost, arguing that a company's
competitiveness will depend on its maturity in adopting Industry 4.0. Furthermore, this impact is shaped
by cooperation among partners.
Sima et al. (2020) explored major opportunities and challenges, especially in education, related to
changes in the work environment brought by Industry 4.0, such as evolving occupations, job profiles,
and other human capital drivers. The study analyzes consumer behavior and workforce development
from the perspective of the Fourth Industrial Revolution. The findings reflect technological shifts—
pág. 7215
especially digitalization, information technology, and communication technologies—as drivers of
transformation in labor dynamics and competitiveness.
Miśkiewicz et al. (2020) conducted a case study analyzing the implementation of digitalization in a
manufacturing company, which led to improved efficiency and changes in the organizational structure.
The study emphasizes that technological changes require the integration of information technologies.
The authors recommend that production companies adopt digital processes and cloud computing to
improve production efficiency and financial performance. Applied specifically to the steel industry—
where digital production processes are still rare, this study identifies the need to address multiple
dimensions: economic, political and legal, environmental, technical, technological, and
sociodemographic. Technological changes also imply the adoption of IT and communication systems
for production management.
As part of the analysis, the study highlights the importance of identifying all relevant domains necessary
for the transformation of the steel industry under Industry 4.0, including economic, legal, environmental,
technical, and demographic aspects. This holistic view reinforces the idea that digital transformation
must be systemic to improve competitiveness.
Technological changes also demand the implementation of information and communication systems for
production management. In particular, the integration of these technologies enables real-time
monitoring, enhanced traceability, and data-driven decision-making, which are critical to optimizing
steel production processes and reducing inefficiencies.
Moreover, companies must not only invest in technologies but also in the upskilling of their workforce
to handle new tools and adapt to a digitally connected production environment. The transition to Industry
4.0 goes beyond machinery, it implies cultural and organizational change.
In summary, the literature highlights that the level of Industry 4.0 adoption is a determining factor in the
competitiveness of firms in the steel sector. Organizations that are able to integrate advanced
technologies with flexible, data-driven management strategies are more likely to maintain a sustainable
competitive advantage in increasingly dynamic and globalized value chains.
especially digitalization, information technology, and communication technologies—as drivers of
transformation in labor dynamics and competitiveness.
Miśkiewicz et al. (2020) conducted a case study analyzing the implementation of digitalization in a
manufacturing company, which led to improved efficiency and changes in the organizational structure.
The study emphasizes that technological changes require the integration of information technologies.
The authors recommend that production companies adopt digital processes and cloud computing to
improve production efficiency and financial performance. Applied specifically to the steel industry—
where digital production processes are still rare, this study identifies the need to address multiple
dimensions: economic, political and legal, environmental, technical, technological, and
sociodemographic. Technological changes also imply the adoption of IT and communication systems
for production management.
As part of the analysis, the study highlights the importance of identifying all relevant domains necessary
for the transformation of the steel industry under Industry 4.0, including economic, legal, environmental,
technical, and demographic aspects. This holistic view reinforces the idea that digital transformation
must be systemic to improve competitiveness.
Technological changes also demand the implementation of information and communication systems for
production management. In particular, the integration of these technologies enables real-time
monitoring, enhanced traceability, and data-driven decision-making, which are critical to optimizing
steel production processes and reducing inefficiencies.
Moreover, companies must not only invest in technologies but also in the upskilling of their workforce
to handle new tools and adapt to a digitally connected production environment. The transition to Industry
4.0 goes beyond machinery, it implies cultural and organizational change.
In summary, the literature highlights that the level of Industry 4.0 adoption is a determining factor in the
competitiveness of firms in the steel sector. Organizations that are able to integrate advanced
technologies with flexible, data-driven management strategies are more likely to maintain a sustainable
competitive advantage in increasingly dynamic and globalized value chains.
pág. 7216
Supply Chain Management
As part of the study, the variable supply chain was analyzed. Popescu et al. (2016) conducted an analysis
and assessment of the growth in excess steel production capacity and its integration into the international
supply chain, as well as the effects of steel manufacturing on employment in the United States. This
study provides evidence on mechanisms that drive top-tier productivity growth in the U.S. steel industry,
the growth models within international steel supply chains, and the advantages of implementing
corrective trade measures for this sector.
Pradabwong (2017) examined the interrelationships between business process management and supply
chain collaboration, collaborative advantage, and organizational performance. The study highlights the
role of both intra- and inter-organizational practices, demonstrating the combined and joint impact of
business process management and supply chain collaboration. The author suggests that focusing solely
on internal improvements is insufficient and that enhancing supply chain collaboration is necessary to
raise overall organizational performance levels.
Pinto et al. (2020) conducted a study identifying various strategies for supply chain integration aimed at
self-sufficiency and resource ownership retention. In this case study of the European steel industry,
improvements were reported that increased the self-sufficiency of raw materials and retention of
resource ownership. The study also describes the adoption of vertical integration strategies on the supply
side, and horizontal strategies at end-of-life stages for recycling, restoration services, repairs, and
maintenance. These approaches strengthen the resilience and sustainability of the supply chain,
contributing to the long-term competitiveness of steel-producing companies.
Training and Workforce Development
As part of the study, workforce training was analyzed as a variable. Carreño et al. (2016) presented the
results of research conducted on a sample of companies from the steel and metal-mechanical sectors in
the department of Boyacá, Colombia. The study evaluated workers’ standing in relation to the labor
competency standards relevant to their daily activities. The objective was to highlight the importance of
human talent training as a key factor for business competitiveness.
Evans et al. (2016) presented a study that explores the actions needed to “green” existing occupations
and meet the skill demands of new environmental sectors and jobs. The authors argue that efforts to
Supply Chain Management
As part of the study, the variable supply chain was analyzed. Popescu et al. (2016) conducted an analysis
and assessment of the growth in excess steel production capacity and its integration into the international
supply chain, as well as the effects of steel manufacturing on employment in the United States. This
study provides evidence on mechanisms that drive top-tier productivity growth in the U.S. steel industry,
the growth models within international steel supply chains, and the advantages of implementing
corrective trade measures for this sector.
Pradabwong (2017) examined the interrelationships between business process management and supply
chain collaboration, collaborative advantage, and organizational performance. The study highlights the
role of both intra- and inter-organizational practices, demonstrating the combined and joint impact of
business process management and supply chain collaboration. The author suggests that focusing solely
on internal improvements is insufficient and that enhancing supply chain collaboration is necessary to
raise overall organizational performance levels.
Pinto et al. (2020) conducted a study identifying various strategies for supply chain integration aimed at
self-sufficiency and resource ownership retention. In this case study of the European steel industry,
improvements were reported that increased the self-sufficiency of raw materials and retention of
resource ownership. The study also describes the adoption of vertical integration strategies on the supply
side, and horizontal strategies at end-of-life stages for recycling, restoration services, repairs, and
maintenance. These approaches strengthen the resilience and sustainability of the supply chain,
contributing to the long-term competitiveness of steel-producing companies.
Training and Workforce Development
As part of the study, workforce training was analyzed as a variable. Carreño et al. (2016) presented the
results of research conducted on a sample of companies from the steel and metal-mechanical sectors in
the department of Boyacá, Colombia. The study evaluated workers’ standing in relation to the labor
competency standards relevant to their daily activities. The objective was to highlight the importance of
human talent training as a key factor for business competitiveness.
Evans et al. (2016) presented a study that explores the actions needed to “green” existing occupations
and meet the skill demands of new environmental sectors and jobs. The authors argue that efforts to
pág. 7217
green the workforce are developing at different levels of intensity, primarily due to variations in
institutional contexts. These efforts include adapting existing training systems and creating new skill
frameworks to respond to the environmental transformation of industries like steel.
Bismala et al. (2017) analyzed how to optimize human resource management (HRM) to improve the
competitiveness of 69 SMEs using observations, surveys, interviews, and literature review. The results
show that SME competitiveness increases when key HRM functions are strengthened—such as targeted
recruitment based on skills and knowledge, employee retention through fair compensation and a positive
work environment, talent development, and performance evaluation using objective and equitable
indicators. This comprehensive HRM approach is emphasized as an essential strategy to enhance
competitiveness in small and medium-sized enterprises.
Globalization
As part of the study, globalization was analyzed as an independent variable. Parc (2018), using the
generalized double diamond model, incorporated internationalization as a crucial element—especially
for Asian countries such as Japan. The study compared Japan’s competitiveness with neighboring
countries competing in the global market. It concluded that Japan’s current economic challenges and its
slow recovery are due more to a lack of globalization compared to its regional counterparts, rather than
specific macroeconomic issues.
Konak et al. (2019) presented a study aiming to test the effect of steel production on global output and
the Global Competitiveness Index. The analysis examined the extent to which iron and steel production
influence these variables. According to the results, a one-unit increase in total steel production boosts
long-term economic growth by 0.104 and short-term growth by 1.386 units. Additionally, a one-unit
increase in steel production reduces unemployment in the long term by 0.105 units, and global
competitiveness increases by 0.22 units.
Yuguo et al. (2021) assumed that low-carbon competitiveness is an effective way for companies to
remain relevant in the global green economy agenda. They selected three Chinese steel companies as
case studies and assessed their low-carbon performance using a set of mathematical methods. The
approach allowed them to quantitatively compare the low-carbon competitiveness of the three firms.
green the workforce are developing at different levels of intensity, primarily due to variations in
institutional contexts. These efforts include adapting existing training systems and creating new skill
frameworks to respond to the environmental transformation of industries like steel.
Bismala et al. (2017) analyzed how to optimize human resource management (HRM) to improve the
competitiveness of 69 SMEs using observations, surveys, interviews, and literature review. The results
show that SME competitiveness increases when key HRM functions are strengthened—such as targeted
recruitment based on skills and knowledge, employee retention through fair compensation and a positive
work environment, talent development, and performance evaluation using objective and equitable
indicators. This comprehensive HRM approach is emphasized as an essential strategy to enhance
competitiveness in small and medium-sized enterprises.
Globalization
As part of the study, globalization was analyzed as an independent variable. Parc (2018), using the
generalized double diamond model, incorporated internationalization as a crucial element—especially
for Asian countries such as Japan. The study compared Japan’s competitiveness with neighboring
countries competing in the global market. It concluded that Japan’s current economic challenges and its
slow recovery are due more to a lack of globalization compared to its regional counterparts, rather than
specific macroeconomic issues.
Konak et al. (2019) presented a study aiming to test the effect of steel production on global output and
the Global Competitiveness Index. The analysis examined the extent to which iron and steel production
influence these variables. According to the results, a one-unit increase in total steel production boosts
long-term economic growth by 0.104 and short-term growth by 1.386 units. Additionally, a one-unit
increase in steel production reduces unemployment in the long term by 0.105 units, and global
competitiveness increases by 0.22 units.
Yuguo et al. (2021) assumed that low-carbon competitiveness is an effective way for companies to
remain relevant in the global green economy agenda. They selected three Chinese steel companies as
case studies and assessed their low-carbon performance using a set of mathematical methods. The
approach allowed them to quantitatively compare the low-carbon competitiveness of the three firms.
pág. 7218
The proposed evaluation method demonstrates the capacity to measure and compare the abstract concept
of low-carbon competitiveness, emphasizing its growing importance in a globalized context.
Innovation Capacity
Innovation capacity was also considered an independent variable in this study. Álvarez et al. (2021)
provided empirical evidence on the complementarity between different sources of knowledge and
innovation performance in manufacturing companies in Argentina's automotive and iron & steel
industries. The authors tested the relationship between national and foreign knowledge sources and their
influence on innovation.
The findings reveal that while international markets and activities can enhance firms’ innovation
performance, they do not necessarily undermine local knowledge bases. This supports the argument in
favor of building national and local capacities—particularly relevant for Latin American countries.
These empirical results highlight the ongoing relevance of developing internal capabilities within firms
as a foundation for absorbing external knowledge, especially in emerging economies. Furthermore, they
emphasize the predominance of embedded knowledge acquisition as a key mechanism for innovation in
developmental contexts.
Market Orientation
Market orientation was also analyzed as an independent variable. Guzmán et al. (2019) conducted an
econometric analysis of steel production in Mexico to determine the price elasticity of domestic steel
production and quantify the impact of international prices on wholesale prices in Mexico. The study
covered annual data from 1980 to 2017 and included three regression equations.
The findings indicate that in both the short and long term, steel production in Mexico responds
inelastically (0.0425% in the short term and 0.2419% in the long term) to a 1% change in its own price.
Additionally, the international steel price influences Mexico’s wholesale price by a factor of 0.05 for
every 1% change. These results suggest that international market conditions are a significant determinant
of pricing and competitiveness in the domestic steel industry.
Quality
Finally, quality was analyzed as part of the theoretical framework. Whang (2017) conducted an analysis
of bilateral trade data from the 83 largest economies in the world to examine the relationship between
The proposed evaluation method demonstrates the capacity to measure and compare the abstract concept
of low-carbon competitiveness, emphasizing its growing importance in a globalized context.
Innovation Capacity
Innovation capacity was also considered an independent variable in this study. Álvarez et al. (2021)
provided empirical evidence on the complementarity between different sources of knowledge and
innovation performance in manufacturing companies in Argentina's automotive and iron & steel
industries. The authors tested the relationship between national and foreign knowledge sources and their
influence on innovation.
The findings reveal that while international markets and activities can enhance firms’ innovation
performance, they do not necessarily undermine local knowledge bases. This supports the argument in
favor of building national and local capacities—particularly relevant for Latin American countries.
These empirical results highlight the ongoing relevance of developing internal capabilities within firms
as a foundation for absorbing external knowledge, especially in emerging economies. Furthermore, they
emphasize the predominance of embedded knowledge acquisition as a key mechanism for innovation in
developmental contexts.
Market Orientation
Market orientation was also analyzed as an independent variable. Guzmán et al. (2019) conducted an
econometric analysis of steel production in Mexico to determine the price elasticity of domestic steel
production and quantify the impact of international prices on wholesale prices in Mexico. The study
covered annual data from 1980 to 2017 and included three regression equations.
The findings indicate that in both the short and long term, steel production in Mexico responds
inelastically (0.0425% in the short term and 0.2419% in the long term) to a 1% change in its own price.
Additionally, the international steel price influences Mexico’s wholesale price by a factor of 0.05 for
every 1% change. These results suggest that international market conditions are a significant determinant
of pricing and competitiveness in the domestic steel industry.
Quality
Finally, quality was analyzed as part of the theoretical framework. Whang (2017) conducted an analysis
of bilateral trade data from the 83 largest economies in the world to examine the relationship between
pág. 7219
empirical findings and theoretical models. The study found support for a “quality competition” model
rather than a “price competition” one. In this model, companies in countries with a comparative
advantage in a particular product tend to improve product quality rather than reduce production costs—
competing on price adjusted for quality. The results emphasize the strategic importance of product
quality in differentiated product markets.
Compañero et al. (2021) conducted a study based on interviews to identify the different quality
dimensions of steel scrap. The research revealed varying definitions among scrap traders and steel mills
regarding the desired condition, physical state, shape, size, and homogeneity of the material. The study
established that the relationship between quality and the level of information about material
characteristics increases opportunities for efficient resource use.
Valdez de la Rosa et al. (2021) identified the causal relationship between independent variables such as
process quality and product innovation, and the dependent variable of competitiveness in the
manufacturing sector of the automotive industry, which relies heavily on steel inputs. The study found
that both process quality and product innovation have independent and positive causal effects on
competitiveness in automobile manufacturing.
RESEARCH OBJECTIVE
To develop a comprehensive theoretical framework that identifies and analyzes the key factors
influencing the competitiveness level of micro, small, and medium-sized enterprises (MSMEs) in the
steel-automotive sector in northeastern Mexico, based on a review of specialized literature and empirical
evidence. The purpose is to support future research and inform the design of strategies aimed at
strengthening the competitive position of this sector.
METHODOLOGY
This study adopts a qualitative, exploratory approach based on a systematized theoretical and
documentary review. An extensive search of scientific literature was conducted, selecting documents
published between 2005 and 2023.
As a result, over 80 primary sources were analyzed, from which theoretical constructs and variables
related to business competitiveness were extracted. In addition, national and international empirical
studies were included to validate and contextualize the identified factors.
empirical findings and theoretical models. The study found support for a “quality competition” model
rather than a “price competition” one. In this model, companies in countries with a comparative
advantage in a particular product tend to improve product quality rather than reduce production costs—
competing on price adjusted for quality. The results emphasize the strategic importance of product
quality in differentiated product markets.
Compañero et al. (2021) conducted a study based on interviews to identify the different quality
dimensions of steel scrap. The research revealed varying definitions among scrap traders and steel mills
regarding the desired condition, physical state, shape, size, and homogeneity of the material. The study
established that the relationship between quality and the level of information about material
characteristics increases opportunities for efficient resource use.
Valdez de la Rosa et al. (2021) identified the causal relationship between independent variables such as
process quality and product innovation, and the dependent variable of competitiveness in the
manufacturing sector of the automotive industry, which relies heavily on steel inputs. The study found
that both process quality and product innovation have independent and positive causal effects on
competitiveness in automobile manufacturing.
RESEARCH OBJECTIVE
To develop a comprehensive theoretical framework that identifies and analyzes the key factors
influencing the competitiveness level of micro, small, and medium-sized enterprises (MSMEs) in the
steel-automotive sector in northeastern Mexico, based on a review of specialized literature and empirical
evidence. The purpose is to support future research and inform the design of strategies aimed at
strengthening the competitive position of this sector.
METHODOLOGY
This study adopts a qualitative, exploratory approach based on a systematized theoretical and
documentary review. An extensive search of scientific literature was conducted, selecting documents
published between 2005 and 2023.
As a result, over 80 primary sources were analyzed, from which theoretical constructs and variables
related to business competitiveness were extracted. In addition, national and international empirical
studies were included to validate and contextualize the identified factors.
pág. 7220
Through thematic and comparative analysis, the variables were organized into conceptual categories,
and an integrative theoretical framework was proposed. This framework comprises 12 key factors that
influence the competitive performance of SMEs in the steel-automotive sector in northeastern Mexico.
RESULTS
The analysis led to the identification of 12 critical variables consistently associated with competitiveness
levels in industrial SMEs, particularly those linked to the steel-automotive sector. These variables are:
1. Degree of Technological Innovation
2. Productivity
3. Energy Efficiency
4. Business Profitability
5. Adoption Level of Industry 4.0 Technologies
6. Strategic Alliances
7. Supply Chain
8. Employee Training Level
9. Globalization
10. Innovative Capacity
11. Market Orientation
12. Quality
These factors were categorized into internal dimensions (degree of technological innovation,
productivity, business profitability, innovative capacity) and external dimensions (strategic alliances,
globalization, market orientation). Additionally, the analysis confirmed the importance of interactions
between variables such as technological innovation, employee training, energy efficiency, and
profitability in enhancing competitiveness.
DISCUSSION
The theoretical framework presented shows that the competitiveness of SMEs in the steel-automotive
sector does not rely solely on internal factors such as productivity or quality, but rather on the dynamic
combination of technological capabilities, linkage strategies, and adaptability to the global environment.
Through thematic and comparative analysis, the variables were organized into conceptual categories,
and an integrative theoretical framework was proposed. This framework comprises 12 key factors that
influence the competitive performance of SMEs in the steel-automotive sector in northeastern Mexico.
RESULTS
The analysis led to the identification of 12 critical variables consistently associated with competitiveness
levels in industrial SMEs, particularly those linked to the steel-automotive sector. These variables are:
1. Degree of Technological Innovation
2. Productivity
3. Energy Efficiency
4. Business Profitability
5. Adoption Level of Industry 4.0 Technologies
6. Strategic Alliances
7. Supply Chain
8. Employee Training Level
9. Globalization
10. Innovative Capacity
11. Market Orientation
12. Quality
These factors were categorized into internal dimensions (degree of technological innovation,
productivity, business profitability, innovative capacity) and external dimensions (strategic alliances,
globalization, market orientation). Additionally, the analysis confirmed the importance of interactions
between variables such as technological innovation, employee training, energy efficiency, and
profitability in enhancing competitiveness.
DISCUSSION
The theoretical framework presented shows that the competitiveness of SMEs in the steel-automotive
sector does not rely solely on internal factors such as productivity or quality, but rather on the dynamic
combination of technological capabilities, linkage strategies, and adaptability to the global environment.
pág. 7221
The literature shows consensus that the incorporation of emerging technologies (such as Industry 4.0)
and continuous workforce training are key catalysts for enhancing competitive performance.
There are identified theoretical gaps regarding the integrated measurement of these factors and how they
interrelate under the specific conditions of the Mexican industrial context. The proposed theoretical
framework aims to fill this gap by serving as a foundation for future research that can empirically
validate the relationships between the variables, as well as for the development of diagnostic instruments
and strategic proposals aimed at improving business competitiveness. This theoretical approach can be
adapted and applied to industrial sectors across Latin America, contributing to the conceptual
understanding of competitiveness in emerging economies.
Based on a systematic analysis of literature and empirical studies, twelve variables were identified as
having a significant impact on the competitiveness of SMEs in the steel-automotive sector in
northeastern Mexico. These variables were organized into an integrative conceptual model based on four
key dimensions: technological, internal organizational, external environment, and human capital.
The results highlight relevant relationships between variables, such as the direct influence of
technological innovation on productivity and innovation capacity; the contribution of Industry 4.0
adoption to energy efficiency and profitability; and the strategic role of alliances and supply chain
management in integration into global markets. Furthermore, the cross-cutting effect of workforce
training on multiple dimensions of business performance is emphasized. This theoretical model provides
a structured view of the interrelated factors that shape the competitiveness of industrial SMEs, enabling
further empirical validation and the development of diagnostic tools to support strategic decision-
making within the sector.
CONCLUSIONS
This study proposes a comprehensive theoretical framework that synthesizes the main factors
determining the competitiveness of micro, small, and medium-sized enterprises (MSMEs) in the steel-
automotive sector. It is based on an exhaustive review of scientific literature and empirical evidence.
The conceptual model developed identifies 12 key variables and establishes connections among them,
allowing for an understanding of their interaction within a complex and highly competitive industrial
environment.
The literature shows consensus that the incorporation of emerging technologies (such as Industry 4.0)
and continuous workforce training are key catalysts for enhancing competitive performance.
There are identified theoretical gaps regarding the integrated measurement of these factors and how they
interrelate under the specific conditions of the Mexican industrial context. The proposed theoretical
framework aims to fill this gap by serving as a foundation for future research that can empirically
validate the relationships between the variables, as well as for the development of diagnostic instruments
and strategic proposals aimed at improving business competitiveness. This theoretical approach can be
adapted and applied to industrial sectors across Latin America, contributing to the conceptual
understanding of competitiveness in emerging economies.
Based on a systematic analysis of literature and empirical studies, twelve variables were identified as
having a significant impact on the competitiveness of SMEs in the steel-automotive sector in
northeastern Mexico. These variables were organized into an integrative conceptual model based on four
key dimensions: technological, internal organizational, external environment, and human capital.
The results highlight relevant relationships between variables, such as the direct influence of
technological innovation on productivity and innovation capacity; the contribution of Industry 4.0
adoption to energy efficiency and profitability; and the strategic role of alliances and supply chain
management in integration into global markets. Furthermore, the cross-cutting effect of workforce
training on multiple dimensions of business performance is emphasized. This theoretical model provides
a structured view of the interrelated factors that shape the competitiveness of industrial SMEs, enabling
further empirical validation and the development of diagnostic tools to support strategic decision-
making within the sector.
CONCLUSIONS
This study proposes a comprehensive theoretical framework that synthesizes the main factors
determining the competitiveness of micro, small, and medium-sized enterprises (MSMEs) in the steel-
automotive sector. It is based on an exhaustive review of scientific literature and empirical evidence.
The conceptual model developed identifies 12 key variables and establishes connections among them,
allowing for an understanding of their interaction within a complex and highly competitive industrial
environment.
pág. 7222
Among the main findings are the central role of technological innovation, the adoption of emerging
technologies, and workforce training as strategic pillars for strengthening competitiveness. Additionally,
the study underscores the need to improve connections with international markets, optimize production
processes, and consolidate strategic alliances to enhance business positioning.
The primary value of this research lies in its theoretical contribution: it offers a solid conceptual
foundation that can serve as a starting point for quantitative studies, the development of measurement
instruments, and the design of intervention strategies for industrial SMEs. Furthermore, the model has
the potential to be adapted to other manufacturing sectors in similar contexts, thereby broadening its
applicability and relevance in the study of business competitiveness in emerging economies.
REFERENCES
Al Rodhan, N. R. F., & Stoudmann, G. (2006). Definiciones de la globalización: una visión general
exhaustiva y una propuesta de definición. Centro de Ginebra para la Política de Seguridad.
Ansoff, H. (1976). La estrategia de la empresa. Pamplona: McGraw-Hill.
Aragón Sánchez, A. & Rubio Bañón, A. (2005). Factores explicativos del éxito competitivo: el caso de
las pymes en el estado de Veracruz. Revista de Contabilidad y Administración, 35–69.
Arvis, J.-F., Rastogi, C., Rodrigue, J.-P., & Ulybina, D. (2021). Un índice de disrupción global en la
cadena de suministro marítima: el índice de estrés de la cadena de suministro global
(Documento de trabajo n.° 10839). Banco Mundial.
Ballou, R. H. (2004). Logística empresarial / gestión de la cadena de suministro: planificación,
organización y control de la cadena de suministro (5.ª ed.). Pearson/Prentice Hall.
Baumert, T., & Heijs, J. (2002). Los determinantes de la capacidad innovadora regional: una
aproximación econométrica. Economía Industrial, (347), 67–84.
Cámara de Diputados del H. Congreso de la Unión, Secretaría General. (2021). Ley para el desarrollo
de la competitividad de la micro, pequeña y mediana empresa.
http://www.diputados.gob.mx/LeyesBiblio/pdf/247_130819.pdf
Cámara Nacional del Acero (CANACERO). (2022). Radiografía de la industria del acero en México.
https://www.canacero.org.mx/
Among the main findings are the central role of technological innovation, the adoption of emerging
technologies, and workforce training as strategic pillars for strengthening competitiveness. Additionally,
the study underscores the need to improve connections with international markets, optimize production
processes, and consolidate strategic alliances to enhance business positioning.
The primary value of this research lies in its theoretical contribution: it offers a solid conceptual
foundation that can serve as a starting point for quantitative studies, the development of measurement
instruments, and the design of intervention strategies for industrial SMEs. Furthermore, the model has
the potential to be adapted to other manufacturing sectors in similar contexts, thereby broadening its
applicability and relevance in the study of business competitiveness in emerging economies.
REFERENCES
Al Rodhan, N. R. F., & Stoudmann, G. (2006). Definiciones de la globalización: una visión general
exhaustiva y una propuesta de definición. Centro de Ginebra para la Política de Seguridad.
Ansoff, H. (1976). La estrategia de la empresa. Pamplona: McGraw-Hill.
Aragón Sánchez, A. & Rubio Bañón, A. (2005). Factores explicativos del éxito competitivo: el caso de
las pymes en el estado de Veracruz. Revista de Contabilidad y Administración, 35–69.
Arvis, J.-F., Rastogi, C., Rodrigue, J.-P., & Ulybina, D. (2021). Un índice de disrupción global en la
cadena de suministro marítima: el índice de estrés de la cadena de suministro global
(Documento de trabajo n.° 10839). Banco Mundial.
Ballou, R. H. (2004). Logística empresarial / gestión de la cadena de suministro: planificación,
organización y control de la cadena de suministro (5.ª ed.). Pearson/Prentice Hall.
Baumert, T., & Heijs, J. (2002). Los determinantes de la capacidad innovadora regional: una
aproximación econométrica. Economía Industrial, (347), 67–84.
Cámara de Diputados del H. Congreso de la Unión, Secretaría General. (2021). Ley para el desarrollo
de la competitividad de la micro, pequeña y mediana empresa.
http://www.diputados.gob.mx/LeyesBiblio/pdf/247_130819.pdf
Cámara Nacional del Acero (CANACERO). (2022). Radiografía de la industria del acero en México.
https://www.canacero.org.mx/
pág. 7223
Contreras Salluca, N. P., & Díaz Correa, E. D. (2015). Estructura financiera y rentabilidad: origen,
teorías y definiciones. Revista de Investigación Valor Contable, 2(1).
Dachs, B., Kinkel, S., & Jäger, A. (2019). Bringing it all back home? Backshoring of manufacturing
activities and the adoption of Industry 4.0 technologies. Journal of World Business, 54(6),
101017. https://doi.org/10.1016/j.jwb.2019.101017
Data México. (2021). Artículos de hierro o acero. https://datamexico.org/es/profile/product/articles-of-
iron-or-steel
De Castro, G. M., Verde, M. D., Sáez, P. L., & Navas López, J. E. (2010). Innovación tecnológica.
Technological Innovation. https://doi.org/10.1057/9780230281462_3
Del Prado, L. (2005). Alianzas estratégicas. Boletín de Lecturas Sociales y Económicas, 13(1), 68–87.
Garcia, R., & Calantone, R. (2002). A critical look at technological innovation typology and
innovativeness terminology: A literature review. Journal of Product Innovation Management,
19(2), 110–132. https://doi.org/10.1016/S0737-6782(01)00132-1
Guzmán-Soria, E., de la Garza-Carranza, M. T., Rebollar-Rebollar, S., Hernandez-Martinez, J., &
Callejas-Juárez, N. (2019). Producción de acero en México: Un análisis econométrico. Journal
of Globalization, Competitiveness and Governability, 13(2), 34–39.
International Energy Agency. (2022). World Energy Outlook 2022. https://www.iea.org/reports/world-
energy-outlook-2022
Kotler, P. (1992). Dirección de marketing (7.ª ed.). Madrid: Prentice Hall.
Krajewski, L. J., Ritzman, L. P., & Malhotra, M. K. (2010). Gestión de operaciones: Procesos y cadenas
de suministro (9.ª ed.). Pearson.
Kumar, S. (2021). Cambios estructurales y competitividad de la industria del acero en la India:
evaluación mediante el crecimiento de la productividad tras las reformas económicas.
International Journal of Global Business and Competitiveness, 16(1), 39–59.
https://doi.org/10.1007/s42943-021-00024-w
Larrondo Petrie, M. M., Álvarez, H., & Esparragoza, I. E. (Eds.). (2012). Megaproyectos: Construyendo
infraestructura mediante colaboración en ingeniería, integración eficaz y planificación
Contreras Salluca, N. P., & Díaz Correa, E. D. (2015). Estructura financiera y rentabilidad: origen,
teorías y definiciones. Revista de Investigación Valor Contable, 2(1).
Dachs, B., Kinkel, S., & Jäger, A. (2019). Bringing it all back home? Backshoring of manufacturing
activities and the adoption of Industry 4.0 technologies. Journal of World Business, 54(6),
101017. https://doi.org/10.1016/j.jwb.2019.101017
Data México. (2021). Artículos de hierro o acero. https://datamexico.org/es/profile/product/articles-of-
iron-or-steel
De Castro, G. M., Verde, M. D., Sáez, P. L., & Navas López, J. E. (2010). Innovación tecnológica.
Technological Innovation. https://doi.org/10.1057/9780230281462_3
Del Prado, L. (2005). Alianzas estratégicas. Boletín de Lecturas Sociales y Económicas, 13(1), 68–87.
Garcia, R., & Calantone, R. (2002). A critical look at technological innovation typology and
innovativeness terminology: A literature review. Journal of Product Innovation Management,
19(2), 110–132. https://doi.org/10.1016/S0737-6782(01)00132-1
Guzmán-Soria, E., de la Garza-Carranza, M. T., Rebollar-Rebollar, S., Hernandez-Martinez, J., &
Callejas-Juárez, N. (2019). Producción de acero en México: Un análisis econométrico. Journal
of Globalization, Competitiveness and Governability, 13(2), 34–39.
International Energy Agency. (2022). World Energy Outlook 2022. https://www.iea.org/reports/world-
energy-outlook-2022
Kotler, P. (1992). Dirección de marketing (7.ª ed.). Madrid: Prentice Hall.
Krajewski, L. J., Ritzman, L. P., & Malhotra, M. K. (2010). Gestión de operaciones: Procesos y cadenas
de suministro (9.ª ed.). Pearson.
Kumar, S. (2021). Cambios estructurales y competitividad de la industria del acero en la India:
evaluación mediante el crecimiento de la productividad tras las reformas económicas.
International Journal of Global Business and Competitiveness, 16(1), 39–59.
https://doi.org/10.1007/s42943-021-00024-w
Larrondo Petrie, M. M., Álvarez, H., & Esparragoza, I. E. (Eds.). (2012). Megaproyectos: Construyendo
infraestructura mediante colaboración en ingeniería, integración eficaz y planificación
pág. 7224
innovadora [Actas de la 10th Latin American and Caribbean Conference for Engineering and
Technology]. LACCEI Inc.
Marsillac, E., & Roh, J. J. (2014). Connecting product design, process and supply chain decisions to
strengthen global supply chain capabilities. International Journal of Production Economics,
147, 317–329.
McClelland, D. C. (1973). Testing for competence rather than for intelligence. American Psychologist,
28(1), 1–14. https://doi.org/10.1037/h0034092
Miao, J., & Wang, N. (2005). Optimal capital structure and industry dynamics. The Journal of Finance,
60(6), 2621–2659.
Mintzberg, H. (1987). The Strategy Concept I: Five Ps for Strategy. California Management Review,
Fall.
Moreira, D. A. (1991). Medición de la productividad en la empresa moderna (2.ª ed.). São Paulo:
Pioneira.
Neely, A. D. (1999). The performance measurement revolution: Why now and what next? International
Journal of Operations & Production Management, 19(2), 205–228.
https://doi.org/10.1108/01443579910249102
Ocloo, C. E., Akaba, S., & Worwui-Brown, D. K. (2014). Globalization and competitiveness: Challenges
of small and medium enterprises (SMEs) in Accra, Ghana. International Journal of Business
and Social Science, 5(4), 287–296.
Park, S. H., Chen, R. R., & Gallagher, S. (2002). Firm resources as moderators of the relationship
between market growth and strategic alliances in semiconductor start-ups. Academy of
Management Journal, 45(3), 527–545.
Porter, M. E. (1980). Competitive Strategy: Techniques for Analyzing Industries and Competitors. Free
Press.
Porter, M. E. (1990). The Competitive Advantage of Nations. Free Press.
Porter, M. E. (1999). Ser competitivos: nuevas aportaciones y conclusiones. Bilbao: Deusto.
Prokopenko, J. (1989). Manual de productividad. Organización Internacional del Trabajo.
innovadora [Actas de la 10th Latin American and Caribbean Conference for Engineering and
Technology]. LACCEI Inc.
Marsillac, E., & Roh, J. J. (2014). Connecting product design, process and supply chain decisions to
strengthen global supply chain capabilities. International Journal of Production Economics,
147, 317–329.
McClelland, D. C. (1973). Testing for competence rather than for intelligence. American Psychologist,
28(1), 1–14. https://doi.org/10.1037/h0034092
Miao, J., & Wang, N. (2005). Optimal capital structure and industry dynamics. The Journal of Finance,
60(6), 2621–2659.
Mintzberg, H. (1987). The Strategy Concept I: Five Ps for Strategy. California Management Review,
Fall.
Moreira, D. A. (1991). Medición de la productividad en la empresa moderna (2.ª ed.). São Paulo:
Pioneira.
Neely, A. D. (1999). The performance measurement revolution: Why now and what next? International
Journal of Operations & Production Management, 19(2), 205–228.
https://doi.org/10.1108/01443579910249102
Ocloo, C. E., Akaba, S., & Worwui-Brown, D. K. (2014). Globalization and competitiveness: Challenges
of small and medium enterprises (SMEs) in Accra, Ghana. International Journal of Business
and Social Science, 5(4), 287–296.
Park, S. H., Chen, R. R., & Gallagher, S. (2002). Firm resources as moderators of the relationship
between market growth and strategic alliances in semiconductor start-ups. Academy of
Management Journal, 45(3), 527–545.
Porter, M. E. (1980). Competitive Strategy: Techniques for Analyzing Industries and Competitors. Free
Press.
Porter, M. E. (1990). The Competitive Advantage of Nations. Free Press.
Porter, M. E. (1999). Ser competitivos: nuevas aportaciones y conclusiones. Bilbao: Deusto.
Prokopenko, J. (1989). Manual de productividad. Organización Internacional del Trabajo.
pág. 7225
Rubio, A., & Aragón, A. (2006). Competitividad y recursos estratégicos en la Pyme. Revista de Empresa,
(17), 32–47.
Saavedra García, M. L., Milla Toro, S. O., & Tapia Sánchez, B. (2013). Determinación de la
competitividad de la PYME en el nivel micro. FAEDPYME International Review, 2(4), 18–32.
Samuelson, P. A., & Nordhaus, W. D. (2001). Economía. McGraw-Hill Internacional.
Schwab, K. (2018). The Global Competitiveness Report 2018. World Economic Forum.
Shove, E., & Trentmann, F. (Eds.). (2018). Infrastructures in Practice: The Dynamics of Demand in
Networked Societies. Routledge.
Sima, V., Gheorghe, I. G., Subić, J., & Nancu, D. (2020). Influences of the Industry 4.0 Revolution on
the Human Capital Development and Consumer Behavior: A Systematic Review. Sustainability,
12(10), 4035.
Song Teng, H. S. (2014). Qualitative productivity analysis: does a non-financial measurement model
exist? International Journal of Productivity and Performance Management, 63(2), 250–256.
Stickney, C. P., & Weil, R. L. (2002). Contabilidad financiera: Una introducción a conceptos, métodos
y usos (10.ª ed.). South Western College Publishing.
Valdez de la Rosa, L. M., Villarreal Villarreal, L. A., & Alarcón Martínez, G. (2021). Calidad e
innovación como impulsores de la competitividad en la manufactura de autopartes. The TQM
Journal, 33(5), 966–986.
Vögele, S., Grajewski, M., Govorukha, K., & Rübbelke, D. (2020). Challenges for the European steel
industry: Analysis, possible consequences and impacts on sustainable development. Applied
Energy, 264.
World Economic Forum. (2021). World Economic Forum. https://es.weforum.org/
Rubio, A., & Aragón, A. (2006). Competitividad y recursos estratégicos en la Pyme. Revista de Empresa,
(17), 32–47.
Saavedra García, M. L., Milla Toro, S. O., & Tapia Sánchez, B. (2013). Determinación de la
competitividad de la PYME en el nivel micro. FAEDPYME International Review, 2(4), 18–32.
Samuelson, P. A., & Nordhaus, W. D. (2001). Economía. McGraw-Hill Internacional.
Schwab, K. (2018). The Global Competitiveness Report 2018. World Economic Forum.
Shove, E., & Trentmann, F. (Eds.). (2018). Infrastructures in Practice: The Dynamics of Demand in
Networked Societies. Routledge.
Sima, V., Gheorghe, I. G., Subić, J., & Nancu, D. (2020). Influences of the Industry 4.0 Revolution on
the Human Capital Development and Consumer Behavior: A Systematic Review. Sustainability,
12(10), 4035.
Song Teng, H. S. (2014). Qualitative productivity analysis: does a non-financial measurement model
exist? International Journal of Productivity and Performance Management, 63(2), 250–256.
Stickney, C. P., & Weil, R. L. (2002). Contabilidad financiera: Una introducción a conceptos, métodos
y usos (10.ª ed.). South Western College Publishing.
Valdez de la Rosa, L. M., Villarreal Villarreal, L. A., & Alarcón Martínez, G. (2021). Calidad e
innovación como impulsores de la competitividad en la manufactura de autopartes. The TQM
Journal, 33(5), 966–986.
Vögele, S., Grajewski, M., Govorukha, K., & Rübbelke, D. (2020). Challenges for the European steel
industry: Analysis, possible consequences and impacts on sustainable development. Applied
Energy, 264.
World Economic Forum. (2021). World Economic Forum. https://es.weforum.org/