Pub Date : 2021-12-09DOI: 10.5755/j01.ee.32.5.26032
Nela Milosevic, M. Dobrota, Veljko Dmitrović, Sladjana Barjaktarovic Rakocevic
This paper aims to examine the relationship between the managerial perception of human capital, innovations, and bank performance. We specifically sought to examine the influence of human capital on bank performance, by introducing the factors of innovation speed and quality. The study was taken in the Serbian banking industry, with the focus on the perception and the viewpoint of CEOs and general managers of different departments. We used a two-phase survey to design the questionnaire and the correlation and regression analyses to examine our hypotheses. Our findings propose that, from managers’ perspective, human capital is critical to the success of banks, and that innovation speed is more influential than its quality. The backward multiple regression model shows that human capital and innovation speed account for 67.5% of the variability of the bank performance. The findings of this research can contribute to bank management policies by revealing how to enhance bank performance by focusing on human capital and innovation agility and readiness. The proposed research model could potentially be implemented in other sectors and industries to hopefully endorse the significance of the detected relationships.
{"title":"Managerial Perception of Human Capital, Innovations, and Performance: Evidence from Banking Industry","authors":"Nela Milosevic, M. Dobrota, Veljko Dmitrović, Sladjana Barjaktarovic Rakocevic","doi":"10.5755/j01.ee.32.5.26032","DOIUrl":"https://doi.org/10.5755/j01.ee.32.5.26032","url":null,"abstract":"This paper aims to examine the relationship between the managerial perception of human capital, innovations, and bank performance. We specifically sought to examine the influence of human capital on bank performance, by introducing the factors of innovation speed and quality. The study was taken in the Serbian banking industry, with the focus on the perception and the viewpoint of CEOs and general managers of different departments. We used a two-phase survey to design the questionnaire and the correlation and regression analyses to examine our hypotheses. Our findings propose that, from managers’ perspective, human capital is critical to the success of banks, and that innovation speed is more influential than its quality. The backward multiple regression model shows that human capital and innovation speed account for 67.5% of the variability of the bank performance. The findings of this research can contribute to bank management policies by revealing how to enhance bank performance by focusing on human capital and innovation agility and readiness. The proposed research model could potentially be implemented in other sectors and industries to hopefully endorse the significance of the detected relationships.","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88187129","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-09DOI: 10.5755/j01.ee.32.5.27943
A. Guerrero González, Daniel Robles Quiñonero, Samuel Fraile Vega
This work analyzes how the so-called Industry 4.0 technologies are being implemented in companies in the Region of Murcia, in Southeastern Spain. The objective was to determine through questionnaires and face-to-face interviews the current state of 4.0 technologies in Murcia, including additional data of the companies, such as age, number of employees and turnover. Most types of companies in the Region were represented in terms of size, age, turnover, profits and profitability. This study analyzes the relationship between the degree of implementation of 4.0 technologies, investment and training of workers, with companies’ seniority, number of employees, turnover, profits and profitability. The results obtained are significantly higher in companies with higher turnover, profits and profitability, which in turn, have the best levels of investment and training of their workers in 4.0 technologies. The opinions of the companies determined the factors that drove the companies to implement these technologies, the factors perceived as barriers, the opportunities in the current context that encourage the adoption of technologies, as well as the threats that may jeopardize their progress in digital transformation. The conclusions obtained can be taken into account in regional policies that implement appropriate actions to help drive the fourth industrial revolution in the region.
{"title":"Assessment of the Degree of Implementation of Industry 4.0 Technologies: Case Study of Murcia Region in Southeast Spain","authors":"A. Guerrero González, Daniel Robles Quiñonero, Samuel Fraile Vega","doi":"10.5755/j01.ee.32.5.27943","DOIUrl":"https://doi.org/10.5755/j01.ee.32.5.27943","url":null,"abstract":"This work analyzes how the so-called Industry 4.0 technologies are being implemented in companies in the Region of Murcia, in Southeastern Spain. The objective was to determine through questionnaires and face-to-face interviews the current state of 4.0 technologies in Murcia, including additional data of the companies, such as age, number of employees and turnover. Most types of companies in the Region were represented in terms of size, age, turnover, profits and profitability. This study analyzes the relationship between the degree of implementation of 4.0 technologies, investment and training of workers, with companies’ seniority, number of employees, turnover, profits and profitability. The results obtained are significantly higher in companies with higher turnover, profits and profitability, which in turn, have the best levels of investment and training of their workers in 4.0 technologies. The opinions of the companies determined the factors that drove the companies to implement these technologies, the factors perceived as barriers, the opportunities in the current context that encourage the adoption of technologies, as well as the threats that may jeopardize their progress in digital transformation. The conclusions obtained can be taken into account in regional policies that implement appropriate actions to help drive the fourth industrial revolution in the region.","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79807029","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-09DOI: 10.5755/j01.ee.32.5.28619
Zahid Yousaf, M. Radulescu, A. Nassani, A. Aldakhil, E. Jianu
Environmental Management Initiatives (EMI), as part of the sustainability management movement, have become an integrated part of the organisational management practices and of the current research. Since the implementation of Environmental Management System (EMS), there have been many studies analysing this relationship with the environmental performance. Corporate Social Responsibility (CSR) also gained a great importance for the organisations’ performance, including their performance in the environmental area. However, previous studies analysed the direct link between those variables and environmental performance, while the mediating effect of those variables has not been tested yet because using a mediator in the relationship between two variables is a rather new approach in the research area used in the behavioural sciences area. This research analyses the role of EMI in defining the Environmental Performance (EP) of hotel industry, given the strong relationship between those two variables and the importance of the tourism sector for the economic development, both in the developed, but especially in the developing countries. It also investigates the CSR authenticity as mediator between EMI and EP link. Data was collected through a questionnaire of managers of the hotels in Pakistan. Correlation, Structural Equation Model and linear regressions were applied for testing the hypotheses and for checking the viability of the model. Findings revealed that EMI and CSR authenticity are important and significant determinants of EP in the hotel industry. Findings show that CSR authenticity acts as a mediator for the EMI and EP link. The stakeholder pressures and customers’ environmental awareness have forced the hotel industry to implement environmental standards and this shift of focus is more important in the hotel industry. The current research demonstrates that efforts of EMI is a prerequisite for enhancing CSR authenticity in the environmental area, and this, in its turn, contributes to the increase of the EP of hotel and tourism sector in a developing country. Given the lack of large financial resources of the developing countries, this model is an important outcome for the tourism industry that helps hotels to become green, to attract more clients and to gain competitive advantages.
{"title":"Environmental Management System towards Environmental Performance of Hotel Industry: Does Corporate Social Responsibility Authenticity Really Matter?","authors":"Zahid Yousaf, M. Radulescu, A. Nassani, A. Aldakhil, E. Jianu","doi":"10.5755/j01.ee.32.5.28619","DOIUrl":"https://doi.org/10.5755/j01.ee.32.5.28619","url":null,"abstract":"Environmental Management Initiatives (EMI), as part of the sustainability management movement, have become an integrated part of the organisational management practices and of the current research. Since the implementation of Environmental Management System (EMS), there have been many studies analysing this relationship with the environmental performance. Corporate Social Responsibility (CSR) also gained a great importance for the organisations’ performance, including their performance in the environmental area. However, previous studies analysed the direct link between those variables and environmental performance, while the mediating effect of those variables has not been tested yet because using a mediator in the relationship between two variables is a rather new approach in the research area used in the behavioural sciences area. This research analyses the role of EMI in defining the Environmental Performance (EP) of hotel industry, given the strong relationship between those two variables and the importance of the tourism sector for the economic development, both in the developed, but especially in the developing countries. It also investigates the CSR authenticity as mediator between EMI and EP link. Data was collected through a questionnaire of managers of the hotels in Pakistan. Correlation, Structural Equation Model and linear regressions were applied for testing the hypotheses and for checking the viability of the model. Findings revealed that EMI and CSR authenticity are important and significant determinants of EP in the hotel industry. Findings show that CSR authenticity acts as a mediator for the EMI and EP link. The stakeholder pressures and customers’ environmental awareness have forced the hotel industry to implement environmental standards and this shift of focus is more important in the hotel industry. The current research demonstrates that efforts of EMI is a prerequisite for enhancing CSR authenticity in the environmental area, and this, in its turn, contributes to the increase of the EP of hotel and tourism sector in a developing country. Given the lack of large financial resources of the developing countries, this model is an important outcome for the tourism industry that helps hotels to become green, to attract more clients and to gain competitive advantages.","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73005150","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-12-09DOI: 10.5755/j01.ee.32.5.28057
V. Pilinkienė, A. Stundžienė, E. Stankevičius, Andrius Grybauskas
The COVID-19 pandemic caused a number of challenges worldwide regarding not only the human health perspective, but also the economic situation. Quarantine, imposed in many countries, forced a substantial part of businesses to close or narrow down their activities, thus leaving corporations and employees without any or with lower income. If national governments had not undertaken any actions to save national economies, the consequences could have been even more devastating. The real estate market is an important part of economy. Instability in the real estate market can cause financial problems, vulnerability of population’s welfare and other negative effects. This research aims to assess the impact of the economic stimulus measures on the real estate market under the conditions of the COVID-19 pandemic in Lithuania. The research methods include comparative analysis, correlation analysis, stationarity test, regression analysis and the ARDL models. The results indicate that the economic stimulus measures only partially contribute to stabilization of the real estate market in Lithuania. The drop in housing prices was 2.9 percent lower because of the economic stimulus in the second quarter of 2020. Maintenance of household cash and deposits as well as lending to business enterprises are the measures that allow to stabilize the real estate market in the shortest time under the conditions of the economic shock. The other governmental support measures are also important, especially if they are aimed at preserving jobs.
{"title":"Impact of the Economic Stimulus Measures on Lithuanian Real Estate Market under the Conditions of the COVID-19 Pandemic","authors":"V. Pilinkienė, A. Stundžienė, E. Stankevičius, Andrius Grybauskas","doi":"10.5755/j01.ee.32.5.28057","DOIUrl":"https://doi.org/10.5755/j01.ee.32.5.28057","url":null,"abstract":"The COVID-19 pandemic caused a number of challenges worldwide regarding not only the human health perspective, but also the economic situation. Quarantine, imposed in many countries, forced a substantial part of businesses to close or narrow down their activities, thus leaving corporations and employees without any or with lower income. If national governments had not undertaken any actions to save national economies, the consequences could have been even more devastating. The real estate market is an important part of economy. Instability in the real estate market can cause financial problems, vulnerability of population’s welfare and other negative effects. This research aims to assess the impact of the economic stimulus measures on the real estate market under the conditions of the COVID-19 pandemic in Lithuania. The research methods include comparative analysis, correlation analysis, stationarity test, regression analysis and the ARDL models. The results indicate that the economic stimulus measures only partially contribute to stabilization of the real estate market in Lithuania. The drop in housing prices was 2.9 percent lower because of the economic stimulus in the second quarter of 2020. Maintenance of household cash and deposits as well as lending to business enterprises are the measures that allow to stabilize the real estate market in the shortest time under the conditions of the economic shock. The other governmental support measures are also important, especially if they are aimed at preserving jobs.","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2021-12-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91256402","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.5755/j01.ee.32.4.28459
Adrian-Nicolae Buturache, Stelian Stancu
Solar radiation is among the renewable resources on which modern society relies to partially replace the existing fossil fuel-based energy resources. Awareness of how the energy is produced must complement awareness of how it is consumed. In the economic context, the gains derive from predictability across the entire supply chain. This paper represents a compressive study on how standard recurrent neural networks, long short-term memory, and gated recurrent units can be used to forecast power production of photovoltaic (PV) systems. This approach can be used for other use cases in solar or even wind power prediction since it provides solid fundamentals for working with weather data and recurrent artificial neural networks, being the core of any smart grid management system. Few studies have explored how these models should be implemented, and even fewer have compared the outcomes of different model types. The data used consist of weather and power production data with a one-hour resolution. The data were further pre-processed to unveil the maximum information. The most effective model parameters were selected to make the forecast. Solar energy plays a key role among other renewable energy sources in the European Union’s climate action and the European Green Deal. Under these initiatives, important regulations are implemented and financial resources made available for those who possess the capabilities required to solve the open points. The much-needed predictability that gives the flexibility and robustness needed for deploying and adopting more renewable technologies can be ensured by utilizing a neural-based predictive approach.
{"title":"Solar Energy Production Forecast Using Standard Recurrent Neural Networks, Long Short-Term Memory, and Gated Recurrent Unit","authors":"Adrian-Nicolae Buturache, Stelian Stancu","doi":"10.5755/j01.ee.32.4.28459","DOIUrl":"https://doi.org/10.5755/j01.ee.32.4.28459","url":null,"abstract":"Solar radiation is among the renewable resources on which modern society relies to partially replace the existing fossil fuel-based energy resources. Awareness of how the energy is produced must complement awareness of how it is consumed. In the economic context, the gains derive from predictability across the entire supply chain. This paper represents a compressive study on how standard recurrent neural networks, long short-term memory, and gated recurrent units can be used to forecast power production of photovoltaic (PV) systems. This approach can be used for other use cases in solar or even wind power prediction since it provides solid fundamentals for working with weather data and recurrent artificial neural networks, being the core of any smart grid management system. Few studies have explored how these models should be implemented, and even fewer have compared the outcomes of different model types. The data used consist of weather and power production data with a one-hour resolution. The data were further pre-processed to unveil the maximum information. The most effective model parameters were selected to make the forecast. Solar energy plays a key role among other renewable energy sources in the European Union’s climate action and the European Green Deal. Under these initiatives, important regulations are implemented and financial resources made available for those who possess the capabilities required to solve the open points. The much-needed predictability that gives the flexibility and robustness needed for deploying and adopting more renewable technologies can be ensured by utilizing a neural-based predictive approach.","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72686619","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Inventory management is an important part of supply chain management: inventory shortages could result in reduced delivery speeds and response speeds while excess inventory could lead to increased inventory and operating costs. Therefore, finding ways to efficiently control inventory has become an issue companies are most concerned about. Choosing a proper inventory management method based on the lead-time demand distribution fitted from historical data has become the key criteria to solve this issue. However, it is difficult to determine the lead-time distribution based on the limited amount of historical data directly. Thus, the method this report introduces uses a multivariate higher-order Markov chain to reconstruct historical data in order to expand the amount of data used to fit the lead-time distribution of demand, which is significant for inventory management.
{"title":"The Research on Distribution of Lead-Time Demand on the Basis of Multivariate Higher-Order Markov Chain","authors":"Jiahui Xu, Pin-Yang Liu, Xuemin Xu, Zhenni Huang, Wenshuang Zhao, Kwok Leung Tam, Aiping Jiang","doi":"10.5755/j01.ee.32.4.27571","DOIUrl":"https://doi.org/10.5755/j01.ee.32.4.27571","url":null,"abstract":"Inventory management is an important part of supply chain management: inventory shortages could result in reduced delivery speeds and response speeds while excess inventory could lead to increased inventory and operating costs. Therefore, finding ways to efficiently control inventory has become an issue companies are most concerned about. Choosing a proper inventory management method based on the lead-time demand distribution fitted from historical data has become the key criteria to solve this issue. However, it is difficult to determine the lead-time distribution based on the limited amount of historical data directly. Thus, the method this report introduces uses a multivariate higher-order Markov chain to reconstruct historical data in order to expand the amount of data used to fit the lead-time distribution of demand, which is significant for inventory management.","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83719674","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.5755/j01.ee.32.4.28060
Zhijie Zhao, Yang Liu, Jiaying Wang, Biao Wang, Yiqi Guo
Brands are increasingly using social media to create and manage posts to initiate and maintain consumer engagement. Based on the theory of consumer engagement, a perspective of brand post content, form and posting time is introduced to construct a conceptual model of consumer engagement for Sina Weibo. Rough set method and reduction algorithm of Holte 1 R are used to automatically generate the optimal decision rules. Rough set method does not need any prior knowledge and assumptions, which could effectively overcome the disadvantages of traditional statistical methods. The results show that entertainment content is easy to trigger moderate level of consumer engagement, the effect of information content on shares is significantly stronger than that of comments and likes, and the promotion content has an impact on liking. As the most vivid and the most interactive characteristic respectively, videos and questions significantly affect the mid-level consumer engagement. Keeping post length in the range of 16–50 characters stimulates the medium degree of sharing. Posts created on weekend promote the medium level of sharing and the low level of liking, while published at the peak or low peak period trigger the same level of sharing, but do not affect comments or likes. The study detects the characteristics that affect consumer engagement and define the scope of its role. The relationship and intensity of different characteristics on different levels of consumer engagement are effectively evaluated and identified by refining the association rules of consumer engagement, which are available for providing reference for brand managers to formulate social media marketing strategies.
{"title":"Association Rules Analysis between Brand Post Characteristics and Consumer Engagement on Social Media","authors":"Zhijie Zhao, Yang Liu, Jiaying Wang, Biao Wang, Yiqi Guo","doi":"10.5755/j01.ee.32.4.28060","DOIUrl":"https://doi.org/10.5755/j01.ee.32.4.28060","url":null,"abstract":"Brands are increasingly using social media to create and manage posts to initiate and maintain consumer engagement. Based on the theory of consumer engagement, a perspective of brand post content, form and posting time is introduced to construct a conceptual model of consumer engagement for Sina Weibo. Rough set method and reduction algorithm of Holte 1 R are used to automatically generate the optimal decision rules. Rough set method does not need any prior knowledge and assumptions, which could effectively overcome the disadvantages of traditional statistical methods. The results show that entertainment content is easy to trigger moderate level of consumer engagement, the effect of information content on shares is significantly stronger than that of comments and likes, and the promotion content has an impact on liking. As the most vivid and the most interactive characteristic respectively, videos and questions significantly affect the mid-level consumer engagement. Keeping post length in the range of 16–50 characters stimulates the medium degree of sharing. Posts created on weekend promote the medium level of sharing and the low level of liking, while published at the peak or low peak period trigger the same level of sharing, but do not affect comments or likes. The study detects the characteristics that affect consumer engagement and define the scope of its role. The relationship and intensity of different characteristics on different levels of consumer engagement are effectively evaluated and identified by refining the association rules of consumer engagement, which are available for providing reference for brand managers to formulate social media marketing strategies.","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84616343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.5755/j01.ee.32.4.28536
A. Efimova, Petr Briš, Alexander Efimov
Contemporary world with constantly increasing speed of change and rapid development of technologies is challenging companies to accustom to existing complexity. This led to the fact that various methodologies change accordingly. Practitioners and researchers are seeking the ways to ameliorate processes using emerging technologies. One of the methodologies is Six Sigma that has always been connected with technologies necessary for data collection and analysis. The emergence of new technologies might benefit or challenge Six Sigma. In this paper an attempt has been performed to analyze the trends in research output of the conjunction of Industry 4.0 technologies and Six Sigma methodology. This paper is based on the bibliometric analysis. In the process of analysis, it was found that the combination of Six Sigma methodology and Industry 4.0 technology has positive potential, however, not all of the technologies have been analyzed.
{"title":"A Bibliometric Analysis of the Evolution of Six Sigma in the Context of Industry 4.0","authors":"A. Efimova, Petr Briš, Alexander Efimov","doi":"10.5755/j01.ee.32.4.28536","DOIUrl":"https://doi.org/10.5755/j01.ee.32.4.28536","url":null,"abstract":"Contemporary world with constantly increasing speed of change and rapid development of technologies is challenging companies to accustom to existing complexity. This led to the fact that various methodologies change accordingly. Practitioners and researchers are seeking the ways to ameliorate processes using emerging technologies. One of the methodologies is Six Sigma that has always been connected with technologies necessary for data collection and analysis. The emergence of new technologies might benefit or challenge Six Sigma. In this paper an attempt has been performed to analyze the trends in research output of the conjunction of Industry 4.0 technologies and Six Sigma methodology. This paper is based on the bibliometric analysis. In the process of analysis, it was found that the combination of Six Sigma methodology and Industry 4.0 technology has positive potential, however, not all of the technologies have been analyzed.","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86185097","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.5755/j01.ee.32.4.29192
V. Djakovic, J. Ivetic, Goran B. Andjelic
The subject of the research is to analyse and evaluate methods of investment risk modelling in dynamic, changing market circumstances, with a special focus on the assessment success of the expected effects of investment activities in ’extreme’ return points. In that sense, different Value at Risk models were used: the Historical Simulation (HS VaR), the Delta Normal VaR (D VaR) and the Extreme Value Theory model (EVT). The research objective is to test the performance of these models in specific, volatile, market circumstances, in terms of estimating the maximum possible losses from these activities. The basic hypothesis of the research is that it is possible to successfully anticipate the maximum possible losses from the investment activities in the extreme points of the return function by applying different methods of investment risk modelling in volatile market circumstances. The analysed financial data comprise daily stock returns of the BELEX15 (Serbia), BUX (Hungary), CROBEX (Croatia) and SBITOP (Slovenia) stock exchange indices in the period 2012-2019, which is relatively long time period suitable for the sound analyses. The main findings of the research point to the superior application adequacy of the Extreme Value Theory model (EVT) for successful risk modelling, i.e. for making optimal investment decisions. The research results represent innovated, concrete knowledge in the field of understanding the behaviour of the return function in its extremes, and consequently are of great importance to both the academic and professional public in the process of generating decisions on investment activities in volatile market conditions.
{"title":"Modelling Risk under Volatile Conditions: Tail Index Estimation and Validation","authors":"V. Djakovic, J. Ivetic, Goran B. Andjelic","doi":"10.5755/j01.ee.32.4.29192","DOIUrl":"https://doi.org/10.5755/j01.ee.32.4.29192","url":null,"abstract":"The subject of the research is to analyse and evaluate methods of investment risk modelling in dynamic, changing market circumstances, with a special focus on the assessment success of the expected effects of investment activities in ’extreme’ return points. In that sense, different Value at Risk models were used: the Historical Simulation (HS VaR), the Delta Normal VaR (D VaR) and the Extreme Value Theory model (EVT). The research objective is to test the performance of these models in specific, volatile, market circumstances, in terms of estimating the maximum possible losses from these activities. The basic hypothesis of the research is that it is possible to successfully anticipate the maximum possible losses from the investment activities in the extreme points of the return function by applying different methods of investment risk modelling in volatile market circumstances. The analysed financial data comprise daily stock returns of the BELEX15 (Serbia), BUX (Hungary), CROBEX (Croatia) and SBITOP (Slovenia) stock exchange indices in the period 2012-2019, which is relatively long time period suitable for the sound analyses. The main findings of the research point to the superior application adequacy of the Extreme Value Theory model (EVT) for successful risk modelling, i.e. for making optimal investment decisions. The research results represent innovated, concrete knowledge in the field of understanding the behaviour of the return function in its extremes, and consequently are of great importance to both the academic and professional public in the process of generating decisions on investment activities in volatile market conditions.","PeriodicalId":46830,"journal":{"name":"Inzinerine Ekonomika-Engineering Economics","volume":null,"pages":null},"PeriodicalIF":2.8,"publicationDate":"2021-10-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72776552","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":3,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2021-10-28DOI: 10.5755/j01.ee.32.4.28431
Agnė Gadeikienė, Asta Svarcaite
The intensive spread and the growth of the sharing economy challenge the sharing platforms to attract and retain consumers. Thus, a comprehensive understanding of consumers’ perceived value and marketing strategy oriented to value growth is becoming essential both from the scientific and practical point of view. However, in the scientific literature, the construct structure of consumer perceived value from sharing economy and the factors that determine it are not sufficiently explored. To fill this gap, this study aims to investigate consumer perceived value from sharing economy and explore how it is influenced by consumer environmental consciousness and consumer attitude towards sharing platforms. Based on the quantitative research findings, it was found that consumer environmental consciousness has a significant direct effect on attitude towards sharing economy platforms and directly influences consumer perceived social value. The results of this study confirm the mediating effect of the consumer attitude toward sharing platforms in the relationship between consumer environmental consciousness and consumer perceived economic, functional, emotional value from sharing economy.
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