DOI 10.47576/2712-7516_2022_11_1_49 УДК 331:004
UPSKILLING AND RESKILLING FOR A GREENER GLOBAL BUSINESS ECOSYSTEM: WEB 4.0 PERSPECTIVE
Ray Samrat,
assistant Professor, marketing management, ISMS Sankalp Business School Pune, India, e-mail: samrat.ray@ismspune.in
Elkady Ghada ElkadyGhada,
Arab Academy for Science, Technology & Maritime Transport, Alexandria, Egypt Nair Rashmi,
Research Scholar, Savitribai Phule Pune University, Pune, India, e-mail: mailrashmi08@gmail. com
Korchagina Elena,
Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia
In introduction, there has been given the definition and the importance of the up skilling and the re-skilling in any department of the industries nowadays. The implementation of the new technologies in the industries has the need of the updating of the skill of the employees in the companies. In Background there has been given the brief description of the re-skilling and the up skilling and the different steps that can be helpful for this work. The companies have been seen profit in updating of the skills of the employees in compare with the appointments of the new people in their workplace. In the modern business, greener upskilling as well as reskilling is an import aspect to maintain the rate of productivity of the industry. In this researcher work, greener skills help the employees to increase the performances. Through the skill gaps, the researcher understood the clear view of the important of greener skills in the automobile industry. To implement the greener skills in the employees' career, automobile industry produced the feedback looping system where all the accurate data took places. The results of the forecast have been found to be relevant to the past trends that have been derived from the historical data. The regression model and the forecast derived from its shows a positive trend in the future years. Moreover, the trend line has also been derived in an uptrend as has been derived from the analysis.
Keywords: professional development; personnel; organization; labor; web 4.0.
УДК 331:004
ПОВЫШЕНИЕ КВАЛИФИКАЦИИ И ПЕРЕПОДГОТОВКА КАДРОВ ДЛЯ БОЛЕЕ ЭКОЛОГИЧНОЙ ГЛОБАЛЬНОЙ БИЗНЕС-ЭКОСИСТЕМЫ: ПЕРСПЕКТИВА WEB 4.0
Рэй Самрат,
доцент кафедры управления маркетингом, Бизнес-школа ISMS Sankalp, г. Пуна, Индия, e-mail: samrat.ray@ismspune.in
Элькади Гада Элькадыгада,
Арабская академия науки, технологий и морского транспорта, г. Александрия, Египет
Наир Рашми,
научный сотрудник, Университет Савитрибай Пхуле Пуна, г. Пуна, Индия, e-mail: mailrashmi08@gmail.com
Корчагина Елена,
Санкт-Петербургский политехнический университет Петра Великого, г. Санкт-Петербург, Россия
В статье рассматриваются особенности повышения квалификации и переподготовки в промышленности. Отмечается, что внедрение новых технологий в отраслях промышленности требует повышения квалификации сотрудников компаний, повышение квалификации, а также переподготовка кадров являются важным аспектом поддержания уровня производительности отрасли. Более экологичные навыки помогают сотрудникам повысить производительность. Рассматриваются особенности повышения квалификации в автомобильной промышленности, где создана система обратной связи, в которой хранятся все точные данные. Было установлено, что результаты прогноза соответствуют тенденциям, которые были получены на основе исторических данных. Регрессионная модель и полученный на ее основе прогноз показывают положительную тенденцию в будущем.
Ключевые слова: повышение квалификации; кадры; организация; труд; web 4.0.
1. Introduction
In this era, the major growth of industry 4.0 is turning into the automation type of the working process from the huge investment of manual tasks. New technologies and the invention in different spaces like computers and the implementation of loT have given a new picture to the companies for their need for growth. According to Wahab et al. (2021) [30], the process of working in the industries is being changed and the dependency on manual work is decreasing day by day. However, this does not mean that the need for human work is decreasing; instead, it can be called for the new human skills of the people. In the supply chain system of the organization, there has been a huge change related to the information and the process of the supply and it is also seen that the total system is being transferred to the digital system that is being controlled by human beings. The companies can recruit new employees, but it has been seen that the companies can get more profit if they up skill and re-skill the workers that exist in the market (Maisiri et al. 2021) [15].
The need for technical skills and automated systems is being increased and it has been creating a great impact on the climate of industrial performance and the efforts of sustainability in the huge market of competition. The companies are giving the main priority to increase the skills of their workers can help them to increase the productivity of the companies in the market. Web 4.0 is the technologies related to the reasoning of the automation about the system, "self-learning", collaborative on the basis of process of "Artificial intelligence". The automationsystemcan present the use of the database of the management
with the help of the "intelligent agent". It helps to maintain organisational development based on enhancing application of new technologies. As per the views of Bailey, (2020), the "digital transformation" of the employees has been facing a great need to emphasize the growth and the production of the company, which can be helpful for sustainable growth. The "World Economic Forum" has said that the world industry needs 70% of the up skilling of the total workforce to enhance the skill by the end of the year 2025, which includes all sustainability components of the environment. It has been suggested that the new skills contain the sustainability of the workplace [4].
There are a great number of educational activities to enhance the quality of the skills related to the technologies available in the market (Asiator, 2022) [2]. Many workers do not want to use the resources to enhance their work process. However, the companies have a great need to enhance the productivity of the employees and to get the advantage of the new technologies in the market to enhance the quality of the services and the process of the work. The use of natural resources and wastage from the factories are affecting the earth in a great way and this is creating a great impact on the management of the industries. The industries are facing challenges to maintain the balance of the use of the resources and to maximize the use of the finance of the company and the resources that are available in the market (MAsiahuty et al. 2022) [18]. The leaders of the industry have to find new and advanced technologies, skills and sustainable solutions that can help to minimize the "carbon footprint" of the company to make life more sustainable. Industries have been affecting
the climate and the weather of the whole planet mainly and there are many activities are taking part in this.
2. Background
The word "Skill" is defined to know the abilities of the people that can help to apply the knowledge that has been gained before them in the time of solving problems if faced. According to Felsberger et al. (2022) [7], "Knowledge" can be said as per the learning outcome of the people from any subject from any theories or the principles or any sources of data. "Gap of skill" can be mentioned when the skill of the people does not match those that are needed to make successful work in the workplace. The gap of the skilling can reduce the production of the company andthe gap of skillcan reduces maximization of the workplace in the industry. There fore, the up skilling of the employees and the workers is needed in the industries to enhance the productivity and to enhance the quality of the servicesof the companies that are sustainable in the market.
There are 17 goals that should be fulfilled to make the world sustainable and the industries are taking the steps to maintain the sustainability of the planet. In the year of 2021, there were 21% of the people who have been up skilling in the different companies in ASIA in the last twelve months as up gradation of the systems related to automation in companies are taking place (Bailey and De Propris, 2020) [3]. The employees have to be technically skilled and should know the requirements of the technologies to help in the advancement and to run them. The employees have the main need of the requirements of the skills and in this place, there may be the conflicts and "ethical challenges" faced. There are many industries have been supporting the employees to up skill but it has been far from this (Conego et al. 2021) [6]. In the last few years, the words up skilling and re-skilling have been used in great numbers. Up skilling is defined as the learning of the new project and skills related to new or existing topics and re-skilling is the up gradation of the skills that are already known by the employees. There are many employees have skills related to machine learning, they keep the knowledge about up gradation of business techniquesand they are experts in some places but as the inventions and the technologies are being invented day by day, the employees
have the need to know the use of them and the process of using them.
There is another term that can be said as' 'green jobs' ' or "green skills' ' that are being popular nowadays. The jobs are more sustainable and require more growth in the market and they have the use of the natural resources in the maximized way (Milisavljevic-Syed et al. 2020) [16]. The companies have been adopting policies related to sustainable growth and the use of natural resources that can be effective for them and can be helpful for making life more sustainable.
Most of the companies find new talents or skills when they have the demand to introduce a new skill or update in their work process. The wish to hire the new experts has been the specialization in the new field of the employees. However, nowadays with the automation system and the implementation of the "Artificial Intelligence" system, the organizations have felt the need of the up skilling of the employees that already existed in the market. The management of the companies foundthat the up skilling has been the cost saving process for the workers who have been in the payrolls and they can be called to know new things and can be trained to update their skills to help the company in a more efficient way (Oko et al. 2021) [21]. As per the research report of "Wharton School of Business", it has been seen that the external hiring for the updating of the skills can be costed over 18% to 20% more than the re-skilling of the existed employees. It has been also seen that up skilling is better that the new appointment of the hire of talents and the new hired talents can match the level of the job skill of the people that have been re-skilled after two or more years. Thus, the instructors of companies found that up skilling has been the best option than the new appointment of talents for the improvement of the skills and the productivity of the companies with the help of the new and updated skills and technologies. The companies have a need of the management of the skills of the people to increase the productivity and to enhance the quality of the products of them in their market.
The existing worker or the employees are familiar with the work process of the companies and the objective of the companies that should be maintained by every employee. The employees can take the help of the training programmed it can help them to gain more knowledge about the
updating of the machines. The tools that can be more helpful for the companies and that can help the company in a more significant way (Bailey, 2020) [3]. The productivity of the company can be increased with the help of the increment in quality of the employees and the skills that have been implemented by them in new technologies. Interactive session and effective communication can be helpful for the development of Industry 4.0 that have been made to fulfil the demand of the customers in the market. Improvement of IoT has a great application on the technologies related to the industries and this is why there is a need for the application of the management of the skill of the employees for the updating of their knowledge.
3. Literature review and methodology
Green growth
The researcher focused on this research work that is related to upskilling as well as reskilling for a greener business ecosystem throughout the world. As per the view by Jetha et al. (2021) [12], the term green growth refers to the different forecasting that is related to the industries' economic growth as well as development. Green growth is explained by different researchers that are related to the development of economic growth where all the natural assets ensure that it provides resources as well as environmental services. In recent days, green skills are more needed for the green growth of industries for upskilling as well as reskilling. As per the opinion by GAGNIDZE, (2022) [9] stated that green growth helps the industry to cut its cost which helps the industry to develop its economical background. The researcher also stated that through greener upskilling as well as reskilling, industries improve the efficiencies of employees as well as create healthier work environments for employees. Through the help of greener upskilling and reskilling the rate of production of an industry is increased in an effective way. Through the growing skills gap, different kinds of opportunities that are related to the training in the market take place. Based on the study by Taylor et al. (2021) [25], through the greener economy growth, industries help in the growth of employees as well as the income of industries. The greener upskilling, as well as reskilling, will help the industry to increase the efficiency rate of the employees as well as increase productivity at a lower cost. Nowadays, greener skilling helps industries to attract different investors as a result
it creates different kinds of financial opportunities. On the other hand, Mysirli, (2021) [19] stated that greener skills are an important aspect of a green economy that helps the industries to boost their performance. Through upskilling, employees improve their skills and explore the various advanced pathway to learning new skills. The upskilling will help the employees to progress in their careers.
Importance of up skilling and re skilling
Upskilling, as well as reskilling, is important to the development of industries. As per the review by Wagner (2021) [28], greener upskilling, as well as reskilling of industries, provide different kinds of training as well as programs that are related to the development of industries. Up skilling helped to make more growth in income and stimulated the production of the company. It has also helped the overall growth of the business organisations. The development program of industries helps to promote the employees' learning as well as growth. On the other hand, Zahidi (2020) [32] stated that in the business ecosystem, upskilling help to encompass different hard as well as soft skills of employees. The upskilling helps the employees to learn different additional skills which help to enhance the current skill in an effective way. In this pandemic situation, greener upskilling as well as reskilling help the industry to maintain a healthier work environment as well as the development of the industry in an effective way.
In this research work, the researcher, all the data that is related to the companies' upskilling as well reskilling of employees through the different databases. The researcher gets information through Google scholar and Scopus as well as different journal websites. The researcher used those websites to get the data that is related to the industries' greener upskilling as well as reskilling. The researcher does this research work in an effective manner that and different steps such as defining the research work, searching, select of databases, analysing databases and presenting all the analysis data. The researcher used the search section in this research work that includes different papers that related to the skills of employees as well as the different jobs of employees. In this research, the researcher used different terms for searching the information about this research topic that is related to the industry's skill gap as well as reskilling and upskilling of industries.
The researcher did not use the first searches about the research work that related to the development of green skills. The researcher did not use data that is treated to the development of skills for the transformation of industries. The researcher used the statistic software to analyse the different data that is related to the greener upskilling as well as reskilling of the industry.
4. Results
In order to derive a forecast of the "Corporate Social Responsibility (CSR)" of the automobile industry in Asia, the dataset regarding the usage of renewable energy has been used. The output has been derived by applying the "Forecasting
time-series model" of the "SPSS statistical tool". In this aspect, the reskilling and upskilling of the ways of the companies falling in this industry of the region have been analyzed. The analysis includes the approach of deriving the target that has been set as a means of achieving a "greener global business ecosystem". In Table 1, the dataset has been shown for 22 financial years from 2000 to 2022 and the forecasted estimate has been derived from the annual reports of the companies to form an average till 2025. The forecasting model has been created according to the historical data on progress in the trend of renewable energy in the companies.
Year Renewable EnergyUsage
2000 17.10%
2001 17.70%
2002 18.00%
2003 18.30%
2004 18.75%
2005 19.14%
2006 19.53%
2007 19.92%
2008 20.31%
2009 20.70%
2010 21.09%
2011 21.48%
2012 21.87%
2013 22.26%
2014 22.65%
2015 23.04%
2016 23.43%
2017 23.82%
2018 24.21%
2019 24.60%
2020 24.99%
2021 25.38%
2022 25.77%
Table 1. Dataset of renewable energy usage in the automobile industry of Asia
In the above dataset, it can be observed that the usage of renewable energy as an approach to achieving a greener global business ecosystem has been facilitated. The primary companies with the largest market share in the industry have been found to be "Toyota, Lexus, Mazda, Tata, Hyundai and Kia". The management of
these companies has facilitated a priority toward forming a company with greater corporate social responsibility. In this aspect, the forecast has been done to determine the initiative of the companies to achieve their benchmarks of using more renewable energy to derive a sustainable business approach.
Year Renewable_ Energy_ Usage YEAR_ DATE_ Predicted_Renewable_ Energy_Usage_Model_1 LCL_Renewable_ Energy Usage Model 1 UCL_Renewable_ Energy Usage Model 1
2000 17.10% 2000 2000 17.10%) 16.00% 18.20%
2001 17.70% 2001 2001 17.10%o 16.00% 18.20%
2002 18.00% 2002 2002 17.70% 16.60% 18.80%
2003 18.30% 2003 2003 18.00% 16.90% 19.10%
2004 18.75% 2004 2004 18.30% 17.20% 19.40%
2005 19.14% 2005 2005 18.75% 17.65% 19.85%
2006 19.53% 2006 2006 19.14% 18.04% 20.24%
2007 19.92% 2007 2007 19.53% 18.43% 20.63%
2008 20.31% 2008 2008 19.92% 18.82% 21.02%
2009 20.70% 2009 2009 20.31% 19.21% 21.41%
2010 21.09% 2010 2010 20.70% 19.60% 21.80%
2011 21.48% 2011 2011 21.09% 19.99% 22.19%
2012 21.87% 2012 2012 21.48% 20.38% 22.58%
2013 22.26% 2013 2013 21.87% 20.77% 22.97%
2014 22.65% 2014 2014 22.26% 21.16% 23.36%
2015 23.04% 2015 2015 22.65% 21.55% 23.75%
2016 23.43% 2016 2016 23.04% 21.94% 24.14%
2017 23.82% 2017 2017 23.43% 22.33% 24.53%
2018 24.21% 2018 2018 23.82% 22.72 % 24.92%
2019 24.60% 2019 2019 24.21% 23.11% 25.31%
2020 24.99% 2020 2020 24.60% 23.50% 25.70%
2021 25.38% 2021 2021 24.99% 23.89% 26.09%
2022 25.77% 2022 2022 25.38% 24.28% 26.48%
2023 26.50% 2023 2023 25.77% 24.67% 26.87%
2024 27.32% 2024 2024 26.50% 25.40% 27.60%
2025 28.68% 2025 2025 27.32% 26.22% 28.42%
2026 29.51% 2026 2026 28.68% 27.58% 29.78%
2027 30.20% 2027 2027 29.51% 28.41% 30.61%
Table 2. Forecasted trend of renewable energy usage
In Table 2, the forecasted trend of the usage of renewable energy has been derived using the forecasting tool in SPSS, which shows that by 2027, the forecasted usage will be at 29.51% as the lower-class limit. On the other hand, the higher estimate in the form of the higher-class limit of the trend forecast has been found at 30.61%, with an average of 28.41%. This reflects the prevalence of reaching higher sustainability in the form of the usage of renewable energy in business activities. This also reflects that the carbon footprint of the automobile companies of Asia has been found to be decreasing with the rise in usage of renewable sources of energy. It includes companies like "Toyota Kirloskar Motor (TKM)", which has benchmarked its CO2 emission by using solar energy to a large extent. In this aspect, it has been a target for
the company to reach the target of "zero carbon emission" by 2035 (Toyota, 2021) [27]. In this aspect, the benchmarks of the other leading companies in the automobile industry such as "Tata, Mahindra, Kia and Lexus" have also led to better energy sources. This reflects that the companies involved in the automobile industry have introduced the necessity of reskilling and upskilling their business activities and products according to the trends of the global business.
Further, it can be analyzed in the forecast of the renewable energy usage that the companies have also reflected an uptrend in the usage of renewable energy sources since the beginning of the decade. The prediction done according to the rising trend of usage has been found to be relevant to the benchmarks of the companies. This shows that there will be a consistency in
the upskilling of renewable energy usage in approach for the companies involved in more these companies. Moreover, there will be more CO2 emission in the business activities and the prioritization of reaching a sustainable business products of the company (Forbes, 2020).
Model Fit
Fit Statistic Mean SE Minimum Maximum Percentile
5 10 25 50 75 90 95
Stationary R-squared 4.726 -4.726 -4.726 -4.726 -4.726 -4.726 -4.726 -4.726 -4.726 -4.726
R-squared .979 .979 .979 .979 .979 .979 .979 .979 .979 .979
RMSE .534 .534 .534 .534 .534 .534 .534 .534 .534 .534
MAPE 2.008 2.008 2.008 2.008 2.008 2.008 2.008 2.008 2.008 2.008
MaxAPE 4.742 4.742 4.742 4.742 4.742 4.742 4.742 4.742 4.742 4.742
MAE .468 .468 .468 .468 .468 .468 .468 .468 .468 .468
MaxAE 1.360 1.360 1.360 1.360 1.360 1.360 1.360 1.360 1.360 1.360
Normalized BIC - 1.135 -1.135 -1.135 -1.135 -1.135 -1.135 -1.135 -1.135 -1.135 -1.135
Table 3. Forecasting Model Fit
The forecasting done in the above model reflects that the "stationary R-squared" derived from the dataset is - 4.726. The negative value of the "stationary r-squared" shows that the trend of the data that has been derived from the dataset is not a linear line and has fluctuations in it. In this aspect, it can be analyzed that the value of "stationary R-squared" cannot be considered as a performance metric in the forecast of the sustainable business prediction of the industry. Further, the "R-squared" of the dataset has been found to be at 0.979, which is close to 1. This reflects that there is a strong positive correlation in the trend of renewable energy usage in the industry. Moreover, this also shows that there is more anticipation of a positive movement of the trend in the future financial years which will lead the industry to a better position of corporate social responsibility (Wang et al. 2019) [31]. The "root-mean-square deviation" of the industry has been derived at 0.534, which reflects that the value is above 0.5. This shows that there is high accuracy in the forecast of the trend of the dataset. This also reflects that there should be more energy usage from renewable sources.
It has also been found that the "mean absolute percentage error (MAPE)" has been found at the value of 2.008 (Bissing et al. 2019) [5]. In this context, it can be analyzed that the error in the mean derivation of the dataset has been derived
at a considerable level. Hence, the forecast of the reskilling and upskilling of the data has been derived from a positive aspect. It also shows that the percentage error of the forecast and the data that has been derived from the forecast have fewer errors and is accurate. The value of "MAPE" represents the average level of errors that have been caused in the predictions of the dataset. The value of "MaxAPE" can be observed in the above table at 4.742, which reflects that the maximum error in the forecast of the data is estimated to be around 4% to 5%. Moreover, the "Mean Absolute Error (MAE)" of the dataset has been derived from the forecast, which shows the error in the prediction of the errors in the forecasted data according to the paired values in subsequent years (Wang et al. 2019). It reflects whether there are any errors in the data modelling of the "time-series forecasting model". This value has been derived at a level of 0.468 which shows fewer errors in the "mean absolute value" of the data. In this aspect, it can be analyzed that the industry and the forecast of the data have fewer errors in the approach of forecasting. The ways of increasing the usage of renewable sources of energy and their implication in the initiatives of "corporate social responsibility" have been utilized by almost all the automobile companies in Asia according to the trends of international business standards (Forbes, 2020).
Model Statistics
Model Number of Predictors Model Fit statistics Ljung-Box Q(18) Number of Outliers
R-squared Statistics DF Sig.
Renewable Energy Usage-Model 1 0 .979 17.895 17 .396 0
Table 4. Model statistics of the usage of renewable energy
The outline of the forecasting trend that has been derived from the above table shows that there has been more anticipated usage of renewable energy in the Asian automobile industry. It has been found that the "R-squared value" of the industry is 0.979, which shows the accuracy of predictions of the usage of renewable sources of energy is appropriate. The section "Ljung-Box Q (18)" also shows that the statistics of the data have been derived at 17.895, which reflects that there will be a directional movement
in the positive aspect of the trend in the future and there will be increased corporate social responsibility performance of the industry in the coming years. In this aspect, the anticipation of the forecast has been found to be relevant to the benchmarks of the leading companies in the industry with a target of reaching zero carbon emissions. It has also been found that the "degree of freedom (DF)" has been considered to be 17 according to the periods that have been taken into account for the forecast.
Figure 1. Forecasting trendline
In the above graph, the forecast of the trend of usage of renewable energy as an initiative of upskilling the green global business ecosystem has been depicted. The trend line shows the prediction that has been done in the previous table in the form of a forecast model. This shows that there is a positive uptrend in the forecast that has been derived from the statistical tool using the model (Khashei, Bakhtiarvand and Etemadi, 2021) [13]. Moreover, it has also been found that there is a strong chance of achieving zero emission of carbon in the companies involved in the automobile industry of the continent very soon. It provides a differentiated trend line for the observed data and the fit forecast in the form of the forecast model. The anticipation shows that there will be more prioritization in the coming years for an increasingly competitive corporate social responsibility framework for the companies. This is relevant to the plans of the management of the companies in the industry and the interests
of the stakeholders of the businesses (Hong and Fan, 2019) [10]. It also shows that the forecast of the data on renewable energy will influence the business activities of the rest of the companies and the industries in the continent to align with the greener initiatives of energy. In this aspect, the forecast has been derived accordingly with the data derived from the historical data.
5. Discussion
In the result section, the researcher mentioned different purposes of this research work that related to the greener upskilling as well as reskilling of the automobile industry. Through the result, the researcher builds the skills gap in the automobile industry. The researcher used different kinds of approaches to deal with different kinds of matches that realist to the research work. The researcher also explains various literature review gaps in the previous research that are dealing with the skills of employees in the automobile industry. The greener upskilling, as well as reskilling of
employees, help the employees to get several job opportunities which help the employees to build their perfect career. Through this research work, the researcher elaborates on the industrial skills gaps that are happened in recent days. Through investigating the different databases of the automobile industry, the researcher gets help to get relevant data as well as information. Based on the overall findings of the research, it can be stated that with the help of innovative technological advancement, all industries could induce new components in the markets and thus, employees skills could be upgraded for gaining competitive advantages in the market.
From the graph, it has been observed that there is an uptrend in the use of renewable energy resources by the automobile industry of Asia to reduce carbon emission through business activities and products. In this research work, the researcher investigates the first step in a good manner about the greener upskilling as well reskilling of the automobile industry. The upskilling and reskilling of greener in the automobile industry is an important aspect to develop the necessary skills for its employees. The researcher used the literature reviews to lead the different matching that is related to the development of skills in the automobile industry. Through the literature gap, the researcher identifies different important skills as well as job opportunities that are related to the employees. This gap also helps the researcher to the learner about the different tasks as well as learning items that take place through the greener upskilling as well as reskilling in the automobile industry. The elaborated research study helps the researcher to understand the research work. The broader literature review helps the researcher to understand the different challenges related to the skill gaps [11; 14; 17; 20; 26; 29; 33].
The research explained that one of the major goals of this research work is to understand the skill gap. The different previous research works help to support the hypothesis that is matched with the skill gap theoretically. Through the previous research evidence, the match that is related to the skill gaps in the automobile industry take place and is worked in a proper way. Through the finding of this research work, different aspects of the automobile industry take place. Different aspects of the automobile industry such as policy makers of the industry as well as different guide processes and human
resources as well as the individual transformation of the automobile industry. All the transformation takes place through the greener upskilling as well as reskilling of the industry to the employees.
As per the opinion by Taylor et al. (2020), the greener upskilling as well as reskilling clear the views of the development of the automobile industry. The researcher also explained the different kind of spaces that is related to the automobile industry and those spaces are supply space as well as demand space of the company. Through demand matching, the automobile industry explained the newer skills that will be learned by employees. On the other hand, Zahidi (2020) stated that in the development of performances of the automobile industry, different kinds of adjectives in spaces are described in mathematical ways. Both of these opinions help the researcher to understand the matching that is related to the skill gap in the automobile industry in an effective way. Greener reskilling, as well as upskilling, is the process which helps the industry to increase its performance in an effective way through the cost-saving process. This skill helps the industry to maintain a healthier work environment for its employees.
Based on the study by Favero (2022), the researcher shows the perspective of the research work in an effective way. Through the investigation, the researcher takes decisions about the trends of the automobile industry to its business ecosystem. The research explained the whole matching process that is related to the skill gaps in the automobile industry in an effective way. Through this research context, research explained the different mathematical grounds as a result, the researcher gained knowledge about the different skills. The researcher learns different skills to understand the matches related to the learning programs of the automobile industry. As per the opinion by Favero (2022), the researcher elaborates the clear view related to the skill gap in the automobile industry and through that the gaining knowledge about the new skills.
As per the study by Relly et al. (2022) [22], learning of upskilling as well as reskilling of advanced technology help employees gets different job opportunities. Advanced technologies such as machine learning as well as artificial intelligence and big data fit in the recent days' job opportunities. On the other hand, Clarke and Lipsig-Mumme (2020) stated that in the automobile industry it is an exciting fact
that advanced technologies and humans work together to increase performance. Sometimes, for increasing the rate of implementation in the automobile industry, advanced technology is preferable compared to human beings. The different databases help the researcher to get information about the matching system which is built in the future. All the information from the different databases helps to maintain the matching system of the automobile industry through the different approaches. Through the get data from the different databases, the whole matching process takes place. These matches are done in an effective way. The researcher explained the procedure of matching through the help of getting information from the databases. Through the matching system, the development, as well as the learning of new skills, takes place over time.
As per the study by Florea and Brad (2022), the feedback system is important to greener upskilling as well as reskilling in the automobile industry. The implementation of a feedback loop system helps the industry to maintain its performance in the future. Through the feedback loop system, the industry gets accurate data which helps to improve the system from time to time. On the other hand, Snell (2018) [24] stated that through the feedback looping system, the real-world context can be understood easily. The feedback lopping system is important to get accurate data which helps the automobile industry to take advantages about the business strategy through accurate data.
In recent days, big data is one of the major techniques which help in the data pipeline. As per the opinion by Schlogl et al. (2021) [23], big data help the automobile industry to filter the data in the databases as a result; effective as well as filtered databases take place. Through the big data process, an effective matching system takes place in the automobile industry by using the data pipeline method. These big data technologies help the industry to match data automatically in a short period of time by a thorough investigation. Machine learning technology is an important technology in the automobile industry.
Through big data, technology helps the industry to match different kinds of objectives in an effective way. Through greener upskills as well as reskills, the automobile industry provides training to its employees to increase the rate of productivity. Through data analysis
skills, the perfect decision-making process takes place for a better decision about the business-related aspect of the automobile industry. On the other hand, Florea and Brad, (2022) [8] stated that a thorough investigation of the skill gaps creates a bad impact such as dressed the rate of productivity. The skill gaps in the automobile industry did not maintain the work culture in an effective way.
As per the opinion by Astrov et al. (2022), the automated matching system for databases is important to maintain accuracy in an effective way [1]. Advanced technology such as big data, data pipeline, artificial intelligence and machine learning skills help the employees to get different job opportunities. Through these advanced technologies, the employees can take actually decision about the business process in the automobile industry. On the other hand, Schlogl et al. (2021), through the matching system in the databases, plays different roles in the different business activities in the automobile industry. These upskilling, as well as reskilling, get the motivation to the employees which create an impact on the performances of the employees. This matching system helps the employees to get knowledge about the skill gaps and these advanced technologies help them to achieve the skill gaps in their work environment.
In this research work, the researcher has an aim that is related to the steps of learning different advanced skills through the matching as well as opportunities of research. The researcher gives the different outcomes through the matching system, the green upskilling, as well as reskilling development in the automobile industry, takes place. Advanced technology such as AI, ML, big data and data pipeline improved the skills of the employees which help to get success in an effective manner. Through the information from the different database, the implementation of the matching system in the automobile industry takes place. In recent days, greener upskilling, as well as reskilling, has been important to grow a business ecosystem in an effective way in the automobile industry. Introduction of the solar energy andthe renewable energy resources can help the automobile industry to reduce the carbon emission that can help to make life more sustainable. To maintain the rate of performance of employees, upskilling and reskilling are important for the employees. These skills help the employees to take proper decisions in
different kinds though situations. To learn the greener skills in the work places, help to maintain the good as well healthier work environment in the future.
6. Conclusion
The green growth of an industry that is related to the improvement of performance as well as the development of the industry helps in maintaining the different resources as well as the environment. The researcher used different kinds of journals to get the data, as well as information that are related to the greener, upskills as well as reskills of industries. This upskills and reskills program helps the employees to improve their skills in an effective way which helps to increase the rate of performance. Through the closing skill
gap, the researcher analyses different kinds of opportunities that are related to the employee's skills as well as job profiles, different training methods and different business trends. Through greener upskilling and reskilling help, employees learn different skills that are related to artificial intelligence as well as machine learning and the internet of things. Through advanced learning skills, employees take the proper decisions as per the situations. Thus, it can be said that automobile industry should implement the bio plant and solar plant to continue the supply of the energy resources they had the need. The industry should maintain the carbon emission for maintaining the ecological balance to make life more sustainable.
References _
1. Astrov V., Stehrer R. and Zavarská Z., 2022. Recovery and Resilience Facility funding in the Visegrád countries and its impact on Austria (No. 56). Policy Notes and Reports.
2. Asiator G.V., 2022. The opportunities and challenges of Industry 4.0 for industrial development: A case study of Morocco's automotive and garment sectors.
3. Bailey D. and De Propris L., 2020. 13 Industry 4.0 and transformative regional industrial policy. Industry 4.0 and regional transformations, p.238.
4. Bailey D., 2020. Industry 4.0 and regional transformations.
5. Bissing D., Klein M.T., Chinnathambi R.A., Selvaraj D.F. and Ranganathan P., 2019. A hybrid regression model for day-ahead energy price forecasting. Ieee Access, 7, pp.36833-36842.
6. Cónego L., Pinto, R. and Goncalves G., 2021, November. Education 4.0 and the Smart Manufacturing Paradigm: A Conceptual Gateway for Learning Factories. In Working Conference on Virtual Enterprises (pp. 721-728). Springer, Cham.
Favero F., 2022. Political economy of labor mark et policies for current labor mark et transformations in Europe (No. 180/2022). Working Paper.
7. Felsberger A., Qaiser F.H., Choudhary A. and Reiner G., 2022. The impact of Industry 4.0 on the reconciliation of dynamic capabilities: Evidence from the European manufacturing industries. Production Planning & Control, 33(2-3), pp.277-300.
8. Florea A. and Brad S., 2022. Digital Transformation-A Prerequisite for Sustainability in all Economic Sectors and for Society at Sibiu Innovation Days 2021. International Journal of Advanced Statistics and IT&C for Economics and Life Sciences, 12(1).
9. Forbes (2020). Renewable Energy Is Powering the Future of The Automobile Industry. Available at:https://www.forbes. com/sites/sap/2020/10/07/renewable-energy-is-powering-the-future-of-the-automobile-industry/?sh=21f305742ef4 [Accessed on 14 September 2022]. GAGNIDZE, I., 2022, May. The numerous challenges of the post-covid economy. In 6th FEB International Scientific Conference (p. 11).
10. Hong W.C. and Fan G.F., 2019. Hybrid empirical mode decomposition with support vector regression model for short term load forecasting. Energies, 12(6), p.1093.
11. Jayeola O., Sidek S., Abdul-Samad Z., Hasbullah N. N., Anwar S., An N. B. & Ray S. (2022). The Mediating and Moderating Effects of Top Management Support on the Cloud ERP Implementation-Financial Performance Relationshi p. Sustainability, 14(9), 5688.
12. Jetha A., Shamaee A., Bonaccio S., Gignac M.A., Tucker L.B., Tompa E., Bültmann U., Norman C.D., Banks C.G. and Smith P.M., 2021. Fragmentation in the future of work: A horizon scan examining the impact of the changing nature of work on workers experiencing vulnerability. American journal of industrial medicine, 64(8), pp.649-666.
13. Khashei M., Bakhtiarvand N. and Etemadi S., 2021. A novel reliability-based regression model for medical modeling and forecasting. Diab etes & M etabolic Syndrome: Clinical Research & Reviews, 15(6), p.102331.
14. Korchagina E., Desfonteines L., Ray S. & Strekalova N. (2022). Digitalization of Transport Communications as a Tool for Improving the Quality of Life. In International Scientific Conference on Innovations in Digital Economy (pp. 22-34). Springer, Cham.
15. Maisiri W. and Van Dyk L., 2021. Industry 4.0 skills: A perspective of the South African manufacturing industry. SA Journal of Human Resource Management, 19, p.1416.
16. Milisavljevic-Syed J., Thames J.L. and Schaefer D., 2020. The digitization of design and manufacturing: A state-of-the-art report on the transition from strategic vision to implementation in industry. Procedia CIRP, 93, pp.575-580.
17. Gangopadhyay P., Suwandaru A., Das N. & Alghamdi T. Commentary on "Climate Adaptation Interventions in Coastal Areas: A Rapid Review of Social and Gender Dimensions. Frontiers in Climate, 123.
18. MAsiahuty S., Upadhyay A. and Rothwell H., 2022. Strategic sustainable development of Industry 4.0 through the lens of social responsibility: The role of human resource practices. Business Strategy and the Environment.
19. Mysirli T., 2021. European Green Deal: Will the Transition Be Orderly for the Private Sector, or Will There Be Discrepancies?. HAPSc Policy Briefs Series, 2(2), pp.230-238.
20. Pradhan D., & Priyanka K. C. (2021). GREEN-Cloud Computing (G-CC) Data Center and Its Architecture toward Efficient Usage of Energy. In Future Trends in 5G and 6G (pp. 163-182). CRC Press.
21. Oko T., Guilcrits M.C. and Navarro E.M., 2021. Industry 4.0: Costa Rica's State-Of-The-Art in relation to Technology and Value Addition. Harvard Deusto Business Research, 10(1), pp.210-223.
22. Relly S.J., Killip G., Robson J., Emms K., Klassen M. and Laczik A., 2022. Greening Construction (Vol. 30).
23. Schlogl L., Weiss E. and Prainsack B., 2021. Constructing the 'Future of Work': An analysis of the policy discourse. New Technology, Work and Employment, 36(3), pp.307-326.
24. Snell D., 2018. 'Just transition'? Conceptual challenges meet stark reality in a 'transitioning'coal region in Australi a. Globalizations, 15(4), pp.550-564.
25. Taylor A., Nelson J., O'Donnell S., Davies E. and Hillary J., 2022. The Skills Imperative 2035: What Does the Literature Tell Us about Essential Skills Most Needed for Work? Working Paper 1. National Foundation for Educational Research.
26. Tongkachok K., Cavaliere L. P. L., Sudakshina C., Hosamani G., Kapila D. & Ray S. (2021, December). Towards a framework for Internet of Things and Its Impact on Performance Management in a Higher Education Institution. In 2021 International Conference on Computing Sciences (ICCS) (pp. 86-90). IEEE.
27. Toyota (2021). Toyota Kirloskar Motor Achieves 100% Carbon Neutrality in Renewable Energy. Available at: https:// www.toyotabharat.com/news/2021/tkm-achieves-100-percent-carbon-neutrality-in-renewable-energy.html [Accessed on 14 September 2022]
28. Wagner, M., 2021. Just Decarbonisation: A comparative case study on how to make the green transition work for all. The Public Sphere: Journal of Public Policy, 9(1).
29. Ray S. (2021). Can economics of olfactory branding be replicated through historical sensation: cases from college street booksellers? Вестник Бурятского государственного университета. Экономика и менеджмент, (3), 66-73.
30. Wahab S.N., Rajendran S.D. and Yeap S.P., 2021. Upskilling and reskilling requirement in logistics and supply chain industry for the fourth industrial revolution. LogForum, 17(3).
31. Wang X., Hua Y., Kodirov E. and Robertson N.M., 2019. Imae for noise-robust learning: Mean absolute error does not treat examples equally and gradient magnitude's variance matters. arXiv preprint arXiv:1903.12141.
32. Zahidi S., 2020, January. We need a global reskilling revolution-here's why. In World Economic Forum (Vol. 22).
33. Anwar A., Siddique M., Dogan E., & Sharif A. (2021a). The moderating role of renewable and non-renewable energy in environment-income nexus for ASEAN countries: Evidence from Method of Moments Quantile Regression. Renewable Energy, 164, 956-967.