Successful Management System by a Metalworking Mexican Company During Covid-19 Situation. Analysis Through a New Index (Case Study).

Sierra, Azael Carrasco; Flores, María Jesús Cobos; Duarte, Beatriz Fuentes; Comi, Boris Isauro Hernández

doi:10.37335/ijek.v8i2.116

Cited by 9 publications

(6 citation statements)

References 13 publications

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“…However, Moore, Kissinger [ 68 ]; Sierra, Flores [ 69 ]; Wackernagel and Rees [ 61 ] suggest that proper management in the physical infrastructure and transportation sector can benefit economic growth. They suggested that vehicle mileage taxes provide direct and indirect benefits at many scales, such as reducing pollution, improving air quality, promoting public safety and health, and reducing fossil fuel consumption and increasing employment in public transportation.…”

Section: Literature Reviewmentioning

confidence: 99%

Assessing the asymmetric impact of physical infrastructure and trade openness on ecological footprint: An empirical evidence from Pakistan

et al. 2022

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This study analyzed the asymmetric impact of the physical infrastructure and trade openness on Pakistan’s ecological footprint over the period 1970–2019 using the non-linear autoregressive distributed lag model. The study results posit that positive and negative shocks to physical infrastructure increase and decrease the ecological footprint asymmetrically in the short-run and symmetrically in the long-run. Likewise, the positive and negative shocks to trade openness increase and decrease the ecological footprint asymmetrically, both in the short and in the long run. Furthermore, urbanization also positively and significantly increases Pakistan’s ecological footprint in the short and long run. Moreover, a 1% increase in physical infrastructure increases the ecological footprint by 0.32%, while a 1% decrease in physical infrastructure decreases the ecological footprint by 0.33% in the long run. Similarly, a 1% increase in trade openness causes a 0.09% increase in the ecological footprint in the long term, while a 1% reduction in trade openness causes a 0.61% reduction in the ecological footprint. The results also conclude that urbanization is a major determinant of Pakistan’s long-term ecological footprint. Thus, a 1% increase in urbanization causes a 1.31% increase in the ecological footprint in the long run. Finally, this study recommends that policies regarding physical infrastructure be formulated keeping in view its environmental impact. In addition, strict environmental policies should be implemented to reduce the environmental degradation effect of trade openness.

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Section: Literature Reviewmentioning

confidence: 99%

Assessing the asymmetric impact of physical infrastructure and trade openness on ecological footprint: An empirical evidence from Pakistan

et al. 2022

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“…The activity of many corporations worldwide has been jeopardised due to Covid-19 implications. Sierra et al (2020) discuss successfully implemented strategies in a metal working Mexican company, by computing a new index of organisational prevalence. Sawangchai et al (2020) use an e-questionnaire on entrepreneurial Thai university students and prove that the quality of e-services and e-information positively influence e-learning education for entrepreneurs in the context of Covid-19 (Wach & Bilan, 2021;Nowiński et al, 2020).…”

Section: Literature Reviewmentioning

confidence: 99%

Dynamic indexing and clustering of government strategies to mitigate Covid-19

Kinnunen¹,

Georgescu²,

Hosseini³

et al. 2021

EBER

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The objective of the article is to identify the reference group of countries with similar Covid strategies and other groups with their performance success, and to construct a composite Covid Mitigation Index for comparative purposes, thus, implying how to redesign the strategic policies. Research Design & Methods: Gaussian Mixture Modelling and Factor Analysis: the main design is quantitative, using Gaussian Mixture Modelling to find the optimal number of country clusters, and Factor Analysis with Principal Axis Factoring (FA-PAF) to build a composite index of governmental policies. Data includes eight mitigation policy variables and three supporting economic policy variables. Data are aggregated to form three periods and the cluster changes are identified by Gaussian Mixture Modelling. Then, the Covid Mitigation Index (CMI) is constructed by FA-PAF to obtain a comparative measure over the periods and the country clusters. The results were obtained by means of R studio and SPSS. Findings: The dynamic clustering leads to a decreasing number of clusters from nine clusters in the first period (January-February 2020), four clusters in the second period (March-April 2020), and two clusters in the third period (May-June 2020). In the first period, China (with CMI=48) took serious actions forming its own cluster, while 11 other countries (with CMI>10), e.g., early affected European countries such as Italy and Spain and large Asian countries such India and Indonesia, took moderate actions. In the second period all cluster averages were greater than China's in the first period, i.e., most world countries were dedicated to fight Covid-19. In Europe, Italy, San Marino and France showed the highest CMI values, similarly to Iraq and Palestine in the Middle East, Peru and Honduras in the Latin America, and China, India and Indonesia in Asia. In the third period, cluster averages showed even tighter policies even though 42 countries had lower CMI values than previously. Implications & Recommendations:The approach provided a big picture for decision makers both in business and in governments. The key idea was to reveal reference groups of countries which help governmental actors to design and adapt their strategies over time by learning by their own experience and the results of the better performing clusters. It was suggested that a multi-criteria approach accounting for individual government's preferences over health and economy is used along with the presented approach. Contribution & Value Added: Clustering with Gaussian Mixture Models and factor analysis based on Principal Axis Factoring for composite-index building were used. The methods are well-established, but they were applied in a novel way dynamically over time and for the composite CMI. CMI was built on two factors which identified the structure of mitigation policies and economic policies. The development of governmental polices over the first cycle of Covid-19 pandemic was described. Article type:research article

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“…The family environment highly affects university students' interest in doing entrepreneurship. Self-concept allows recognizing the environment easier and faster and spot business opportunities better (Carrasco Sierra et al, 2020).…”

Section: Literature Beckgroundmentioning

confidence: 99%

Impact of social environment indicators on students´propensity to do business: Case study from central European countries

Dvorský¹,

Petráková²,

Mezuláník³

et al. 2021

Journal of International Studies

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The aim of the article is to identify and quantify the impact of selected social environment indicators on students' propensity to do business. A survey-based questionnaire was conducted with students in the last year of their economic studies at 25 universities. The database contains 1,352 filled-out questionnaires showing Slovak, Czech and Polish students' attitudes. A linear regression analysis was used to evaluate the formulated hypotheses. This approach was implemented separately for each country (Czech Republic -CR, Slovakia -SR, and Poland -PL). The results showed several findings. The comparison of social environment

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Successful Management System by a Metalworking Mexican Company During Covid-19 Situation. Analysis Through a New Index (Case Study).

Cited by 9 publications

References 13 publications

Assessing the asymmetric impact of physical infrastructure and trade openness on ecological footprint: An empirical evidence from Pakistan

Assessing the asymmetric impact of physical infrastructure and trade openness on ecological footprint: An empirical evidence from Pakistan

Dynamic indexing and clustering of government strategies to mitigate Covid-19

Impact of social environment indicators on students´propensity to do business: Case study from central European countries

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