Abstract In this paper we analyse the situation of the Portuguese Economy referring to the Covid-19. We start by contextualizing in the problematic “Bubble – Miracle” as described by Tomé, 2018. We then analyse the current situation in a Macroeconomic way, according to eight specific questions, and then we specify regarding four sectors, namely tourism, education, the public sector, and the industrial sector. We conclude that the Covid-19 is the ultimate and unexpected test to the Portuguese economy, and that it will contribute to solving the “Bubble vs. Miracle” question. Rather curiously, we believe that the Covid-19 will accelerate the change to the “Miracle” society, because solving the crisis will require changes that will direct the society towards the “Miracle” paradigm and will distance Portugal from the old and “Bubble” one.
{"title":"Did the Bubble Burst? The Portuguese Economy During COVID-19","authors":"E. Tomé, E. Gromova, A. Hatch","doi":"10.2478/mmcks-2020-0028","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0028","url":null,"abstract":"Abstract In this paper we analyse the situation of the Portuguese Economy referring to the Covid-19. We start by contextualizing in the problematic “Bubble – Miracle” as described by Tomé, 2018. We then analyse the current situation in a Macroeconomic way, according to eight specific questions, and then we specify regarding four sectors, namely tourism, education, the public sector, and the industrial sector. We conclude that the Covid-19 is the ultimate and unexpected test to the Portuguese economy, and that it will contribute to solving the “Bubble vs. Miracle” question. Rather curiously, we believe that the Covid-19 will accelerate the change to the “Miracle” society, because solving the crisis will require changes that will direct the society towards the “Miracle” paradigm and will distance Portugal from the old and “Bubble” one.","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"14 1","pages":"477 - 495"},"PeriodicalIF":3.7,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72700235","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The purpose of this paper is to investigate the complexity of the COVID-19 crisis by using the grounded theory approach. It is a new approach based on a data set constituted from published papers, reports delivered by official organizations or research institutes, working papers, and public information in media. Each of these documents presents data, information, knowledge, and ideas, usually from a single perspective. The present research uses the method of grounded theory and constructs an integrated model of analysis that explores the complexity of the global crisis induced by COVID-19. For the present research, the data were extracted from published papers focused on different aspects of the COVID-19 pandemic induced economic crisis. That means a meta-analysis of the initial quantitative data but performed from a semantic perspective. The findings show that COVID-19 induced economic crisis is a complex phenomenon that is influenced directly and indirectly by the health system crisis, governmental policies, and behavior of people. The integrated model we got can be used as a tool in a further investigation for a deeper understanding of the complexity of COVID-19. The originality of this paper comes from creating a meta-analysis with the grounded theory of different aspects investigated in a series of papers and constructing a dynamic model capable of approaching the complexity of this Black Swan phenomenon.
{"title":"Toward understanding the complexity of the COVID-19 crisis: a grounded theory approach","authors":"C. Bratianu","doi":"10.2478/mmcks-2020-0024","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0024","url":null,"abstract":"Abstract The purpose of this paper is to investigate the complexity of the COVID-19 crisis by using the grounded theory approach. It is a new approach based on a data set constituted from published papers, reports delivered by official organizations or research institutes, working papers, and public information in media. Each of these documents presents data, information, knowledge, and ideas, usually from a single perspective. The present research uses the method of grounded theory and constructs an integrated model of analysis that explores the complexity of the global crisis induced by COVID-19. For the present research, the data were extracted from published papers focused on different aspects of the COVID-19 pandemic induced economic crisis. That means a meta-analysis of the initial quantitative data but performed from a semantic perspective. The findings show that COVID-19 induced economic crisis is a complex phenomenon that is influenced directly and indirectly by the health system crisis, governmental policies, and behavior of people. The integrated model we got can be used as a tool in a further investigation for a deeper understanding of the complexity of COVID-19. The originality of this paper comes from creating a meta-analysis with the grounded theory of different aspects investigated in a series of papers and constructing a dynamic model capable of approaching the complexity of this Black Swan phenomenon.","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"244 1","pages":"410 - 423"},"PeriodicalIF":3.7,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"75048885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
E. Bolisani, E. Scarso, Christine Ipsen, Kathrin Kirchner, J. P. Hansen
Abstract During the COVID pandemic, many companies, schools, and public organizations all around the world asked their employees to work from home i.e. to adopt what are called “smart working” modalities. This has and will presumably have a serious impact on both employees and employers, which still needs to be clarified and investigated: indeed, if smart working becomes a common working modality, this may have a significant impact on both organizations and employees. This paper reports the results of an online survey of “smart workers” in Italy during the COVID pandemic, when a great number of employees suddenly moved to working from home with no or little preparation. The study offers interesting indications about the involvement and usefulness perception of smart working by the sampled people and makes it possible to single out different categories of employees based on their attitude towards this modality. Also, it points out the potential impact on socialization among colleagues, and the consequent implications for knowledge sharing and knowledge management. From the collected responses, a fully positive or negative conclusion about working from home was not possible, nor a clear indication about the efficiency and effectiveness of this working modality. The analysis, instead, highlighted the presence of different but numerically similar groups of people, i.e. those who were not satisfied at all with the experience, those who were very satisfied, and those who were “undecided”. Furthermore, respondents underlined the importance and the difficulty to maintain working contacts and the intense use of communication systems made for this purpose. Lastly, collected opinions on positive and negative aspects of working from home provided some practical suggestions about how to successfully implement this solution.
{"title":"Working from home during COVID-19 pandemic: lessons learned and issues","authors":"E. Bolisani, E. Scarso, Christine Ipsen, Kathrin Kirchner, J. P. Hansen","doi":"10.2478/mmcks-2020-0027","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0027","url":null,"abstract":"Abstract During the COVID pandemic, many companies, schools, and public organizations all around the world asked their employees to work from home i.e. to adopt what are called “smart working” modalities. This has and will presumably have a serious impact on both employees and employers, which still needs to be clarified and investigated: indeed, if smart working becomes a common working modality, this may have a significant impact on both organizations and employees. This paper reports the results of an online survey of “smart workers” in Italy during the COVID pandemic, when a great number of employees suddenly moved to working from home with no or little preparation. The study offers interesting indications about the involvement and usefulness perception of smart working by the sampled people and makes it possible to single out different categories of employees based on their attitude towards this modality. Also, it points out the potential impact on socialization among colleagues, and the consequent implications for knowledge sharing and knowledge management. From the collected responses, a fully positive or negative conclusion about working from home was not possible, nor a clear indication about the efficiency and effectiveness of this working modality. The analysis, instead, highlighted the presence of different but numerically similar groups of people, i.e. those who were not satisfied at all with the experience, those who were very satisfied, and those who were “undecided”. Furthermore, respondents underlined the importance and the difficulty to maintain working contacts and the intense use of communication systems made for this purpose. Lastly, collected opinions on positive and negative aspects of working from home provided some practical suggestions about how to successfully implement this solution.","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"24 1","pages":"458 - 476"},"PeriodicalIF":3.7,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"82265238","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract COVID-19 has created an un-precedent crisis for SMEs and challenged each single enterprise to reconsider its business operations and to adapt to the new unexpected circumstances. The present paper aims to explore the resilience measures that the micro and small enterprises in Romania can consider to dealing with the disruptions caused by the pandemic. A questionnaire-based survey was used to collect data from a sample of micro and small enterprises operating in the central part of the country. An exploratory factor analysis was employed to identify underlying variables that explain the pattern of correlations between the resilience measures for enterprises, which help them cope with the pandemic effects. There are seventeen resilience measures to the pandemic included in the analysis and further tested in the paper. In addition, a multiple linear regression was conducted to determine which of the resilience measures has the most impact on the enterprises’ overcoming illness. The results show that in order for the micro and small enterprises to better cope with the disruption caused by the COVID-19 pandemic they should demonstrate, on the first place, openness to production innovation and adaptation and ensure a strong support for customers and communities. On the second place, efforts should be directed toward ensuring efficiency of their internal operational management and worker protection. While there exist external circumstances that lead enterprises to adopt several resilience measures to better respond to the pandemic, the motivations that are most relevant in this decision are generally internal in nature.
{"title":"Resilience measures to dealing with the COVID-19 pandemic Evidence from Romanian micro and small enterprises","authors":"Carmen Păunescu, E. Mátyus","doi":"10.2478/mmcks-2020-0026","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0026","url":null,"abstract":"Abstract COVID-19 has created an un-precedent crisis for SMEs and challenged each single enterprise to reconsider its business operations and to adapt to the new unexpected circumstances. The present paper aims to explore the resilience measures that the micro and small enterprises in Romania can consider to dealing with the disruptions caused by the pandemic. A questionnaire-based survey was used to collect data from a sample of micro and small enterprises operating in the central part of the country. An exploratory factor analysis was employed to identify underlying variables that explain the pattern of correlations between the resilience measures for enterprises, which help them cope with the pandemic effects. There are seventeen resilience measures to the pandemic included in the analysis and further tested in the paper. In addition, a multiple linear regression was conducted to determine which of the resilience measures has the most impact on the enterprises’ overcoming illness. The results show that in order for the micro and small enterprises to better cope with the disruption caused by the COVID-19 pandemic they should demonstrate, on the first place, openness to production innovation and adaptation and ensure a strong support for customers and communities. On the second place, efforts should be directed toward ensuring efficiency of their internal operational management and worker protection. While there exist external circumstances that lead enterprises to adopt several resilience measures to better respond to the pandemic, the motivations that are most relevant in this decision are generally internal in nature.","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"54 19","pages":"439 - 457"},"PeriodicalIF":3.7,"publicationDate":"2020-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"72445865","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract This study aims to explore the role of social networks in the internationalisation of startups. For this purpose, the social network LinkedIn is used, and two case studies of Portuguese technological startups are employed. The findings indicate that social networks can contribute to the acceleration of the internationalisation process and decrease their costs. Their relevance is greater in the initial phase of the internationalisation process. However, its relevance is limited in more advanced phases of this process. LinkedIn can be used by startups to obtain several benefits such as brand awareness, identification of new opportunities, customer feedback, among others. The results of this study are essentially useful in a practical dimension for companies that plan to start or improve their internationalisation process sustained on social networks.
{"title":"The Role of Social Networks in the Internationalisation of Startups: LinkedIn in Portuguese Context","authors":"F. Almeida, J. D. Santos","doi":"10.2478/mmcks-2020-0020","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0020","url":null,"abstract":"Abstract This study aims to explore the role of social networks in the internationalisation of startups. For this purpose, the social network LinkedIn is used, and two case studies of Portuguese technological startups are employed. The findings indicate that social networks can contribute to the acceleration of the internationalisation process and decrease their costs. Their relevance is greater in the initial phase of the internationalisation process. However, its relevance is limited in more advanced phases of this process. LinkedIn can be used by startups to obtain several benefits such as brand awareness, identification of new opportunities, customer feedback, among others. The results of this study are essentially useful in a practical dimension for companies that plan to start or improve their internationalisation process sustained on social networks.","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"90 1","pages":"345 - 363"},"PeriodicalIF":3.7,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83774699","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The article explores the impact of some specific barriers to the integration of non-EU immigrants on the European Union labour market, measuring the influence of age, level of education and investments on the employment rate of non-EU immigrants. The study is based on a mixed approach, combining a statistically descriptive analysis of the 2008-2018 European labour market trends (in terms of the non-EU immigrants’ employment rate) with an econometric evaluation, aiming to measure the influence of investments (in terms of % of Gross fixed capital formation in Gross Domestic Product), age of asylum seekers (in terms of % of total asylum seekers) and level of education of non – EU immigrants (in terms of % of total non – EU immigrants). The analysis highlights the fact that the highest impact of non-EU immigrants on the employment rate is found in the case of non-EU immigrants with age between 18-34 and 35-64 years and with a tertiary level of education. For the other categories of non-EU immigrants, with ages outside the aforementioned range and with a lower level of education, the challenges are even much greater, which indicates the importance of specific educational integration policies, focusing mainly on continuous education and training.
{"title":"Integrating the non-EU immigrants into the EU labour market. An econometric analysis of some of the specific factors","authors":"A. Nicolescu, G. Drăgan","doi":"10.2478/mmcks-2020-0021","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0021","url":null,"abstract":"Abstract The article explores the impact of some specific barriers to the integration of non-EU immigrants on the European Union labour market, measuring the influence of age, level of education and investments on the employment rate of non-EU immigrants. The study is based on a mixed approach, combining a statistically descriptive analysis of the 2008-2018 European labour market trends (in terms of the non-EU immigrants’ employment rate) with an econometric evaluation, aiming to measure the influence of investments (in terms of % of Gross fixed capital formation in Gross Domestic Product), age of asylum seekers (in terms of % of total asylum seekers) and level of education of non – EU immigrants (in terms of % of total non – EU immigrants). The analysis highlights the fact that the highest impact of non-EU immigrants on the employment rate is found in the case of non-EU immigrants with age between 18-34 and 35-64 years and with a tertiary level of education. For the other categories of non-EU immigrants, with ages outside the aforementioned range and with a lower level of education, the challenges are even much greater, which indicates the importance of specific educational integration policies, focusing mainly on continuous education and training.","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"61 1","pages":"364 - 380"},"PeriodicalIF":3.7,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"90714229","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract The purpose of this paper is to analyze the impact of the Information and communication technology (ICT) on the competitiveness of the republics of former Yugoslavia (Serbia, North Macedonia, Montenegro, Bosnia and Herzegovina, Croatia and Slovenia) as tourism destinations. This paper relies on the correlation analysis and panel regression method. Regression analysis has examined the impact of the ICT on the competitiveness of the republics of Former Yugoslavia (Serbia, North Macedonia, Montenegro, Bosnia and Herzegovina, Croatia and Slovenia) as tourism destinations. The destination competitiveness is measured by international tourist arrivals and international tourism receipts, while the ICT is measured by the ICT Development Index (IDI). The results indicate that the IDI use has a significant impact on the number of international tourist arrivals and an indirect positive impact on the international tourism receipts. The originality of the research lies in the fact there are no previous studies about the impact of ICT on the competitiveness of the republics of former Yugoslavia as tourism destinations. This study contributes to a better understanding of the impact of ICT on the competitiveness of a tourism destination by linking the IDI with tourist arrivals and tourism revenues.
{"title":"ICT as a factor of destination competitiveness: The case of the republics of former Yugoslavia","authors":"S. Milićević, J. Petrović, Nataša Đorđević","doi":"10.2478/mmcks-2020-0022","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0022","url":null,"abstract":"Abstract The purpose of this paper is to analyze the impact of the Information and communication technology (ICT) on the competitiveness of the republics of former Yugoslavia (Serbia, North Macedonia, Montenegro, Bosnia and Herzegovina, Croatia and Slovenia) as tourism destinations. This paper relies on the correlation analysis and panel regression method. Regression analysis has examined the impact of the ICT on the competitiveness of the republics of Former Yugoslavia (Serbia, North Macedonia, Montenegro, Bosnia and Herzegovina, Croatia and Slovenia) as tourism destinations. The destination competitiveness is measured by international tourist arrivals and international tourism receipts, while the ICT is measured by the ICT Development Index (IDI). The results indicate that the IDI use has a significant impact on the number of international tourist arrivals and an indirect positive impact on the international tourism receipts. The originality of the research lies in the fact there are no previous studies about the impact of ICT on the competitiveness of the republics of former Yugoslavia as tourism destinations. This study contributes to a better understanding of the impact of ICT on the competitiveness of a tourism destination by linking the IDI with tourist arrivals and tourism revenues.","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"26 1","pages":"381 - 392"},"PeriodicalIF":3.7,"publicationDate":"2020-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91234511","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Recent increase in peer-to-peer lending prompted for development of models to separate good and bad clients to mitigate risks both for lenders and for the platforms. The rapidly increasing body of literature provides several comparisons between various models. Among the most frequently employed ones are logistic regression, Support Vector Machines, neural networks and decision tree-based models. Among them, logistic regression has proved to be a strong candidate both because its good performance and due to its high explainability. The present paper aims to compare four pairs of models (for imbalanced and under-sampled data) meant to predict charged off clients by optimizing F1 score. We found that, if the data is balanced, Logistic Regression, both simple and with Stochastic Gradient Descent, outperforms LightGBM and K-Nearest Neighbors in optimizing F1 score. We chose this metric as it provides balance between the interests of the lenders and those of the platform. Loan term, debt-to-income ratio and number of accounts were found to be important positively related predictors of risk of charge off. At the other end of the spectrum, by far the strongest impact on charge off probability is that of the FICO score. The final number of features retained by the two models differs very much, because, although both models use Lasso for feature selection, Stochastic Gradient Descent Logistic Regression uses a stronger regularization. The analysis was performed using Python (numpy, pandas, sklearn and imblearn).
{"title":"Will they repay their debt? Identification of borrowers likely to be charged off","authors":"R. Caplescu, A. Panaite, D. Pele, V. Strat","doi":"10.2478/mmcks-2020-0023","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0023","url":null,"abstract":"Abstract Recent increase in peer-to-peer lending prompted for development of models to separate good and bad clients to mitigate risks both for lenders and for the platforms. The rapidly increasing body of literature provides several comparisons between various models. Among the most frequently employed ones are logistic regression, Support Vector Machines, neural networks and decision tree-based models. Among them, logistic regression has proved to be a strong candidate both because its good performance and due to its high explainability. The present paper aims to compare four pairs of models (for imbalanced and under-sampled data) meant to predict charged off clients by optimizing F1 score. We found that, if the data is balanced, Logistic Regression, both simple and with Stochastic Gradient Descent, outperforms LightGBM and K-Nearest Neighbors in optimizing F1 score. We chose this metric as it provides balance between the interests of the lenders and those of the platform. Loan term, debt-to-income ratio and number of accounts were found to be important positively related predictors of risk of charge off. At the other end of the spectrum, by far the strongest impact on charge off probability is that of the FICO score. The final number of features retained by the two models differs very much, because, although both models use Lasso for feature selection, Stochastic Gradient Descent Logistic Regression uses a stronger regularization. The analysis was performed using Python (numpy, pandas, sklearn and imblearn).","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"131 1","pages":"393 - 409"},"PeriodicalIF":3.7,"publicationDate":"2020-07-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74862746","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Abstract Forecasting the demand of network of retail sales is a rather challenging task, especially nowadays where integration of online and physical store orders creates an abundance of data that has to be efficiently stored, analyzed, understood and finally, become ready to be acted upon in a very short time frame. The challenge becomes even bigger for added-value third party logistics (3PL) operators, since in most cases and demand forecasting aside, they are also responsible for receiving, storing and breaking inbound quantities from suppliers, consolidating and picking retail orders and finally plan and organize shipments on a daily basis. This paper argues that data analytics can play a critical role in contemporary logistics and especially in demand data management and forecasting of retail distribution networks. The main objective of the research presented in this paper is to showcase how data analytics can support the 3PL decision making process on replenishing the network stores, thus improving inventory management in both Distribution Centre (DC) and retail outlet levels and the workload planning of human resources and DC automations. To do so, this paper presents the case of a Greek 3PL provider fulfilling physical store and online orders on behalf of a large sporting goods importer operating a network of 129 stores in five different countries. The authors utilize the power of ‘R’, a statistical programming language, which is well-equipped with a multitude of libraries for this purpose, to compare demand forecasting methods and identify the one producing the smallest forecast error.
{"title":"Demand Forecasting of Retail Sales Using Data Analytics and Statistical Programming","authors":"P. Lalou, S. Ponis, O. Efthymiou","doi":"10.2478/mmcks-2020-0012","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0012","url":null,"abstract":"Abstract Forecasting the demand of network of retail sales is a rather challenging task, especially nowadays where integration of online and physical store orders creates an abundance of data that has to be efficiently stored, analyzed, understood and finally, become ready to be acted upon in a very short time frame. The challenge becomes even bigger for added-value third party logistics (3PL) operators, since in most cases and demand forecasting aside, they are also responsible for receiving, storing and breaking inbound quantities from suppliers, consolidating and picking retail orders and finally plan and organize shipments on a daily basis. This paper argues that data analytics can play a critical role in contemporary logistics and especially in demand data management and forecasting of retail distribution networks. The main objective of the research presented in this paper is to showcase how data analytics can support the 3PL decision making process on replenishing the network stores, thus improving inventory management in both Distribution Centre (DC) and retail outlet levels and the workload planning of human resources and DC automations. To do so, this paper presents the case of a Greek 3PL provider fulfilling physical store and online orders on behalf of a large sporting goods importer operating a network of 129 stores in five different countries. The authors utilize the power of ‘R’, a statistical programming language, which is well-equipped with a multitude of libraries for this purpose, to compare demand forecasting methods and identify the one producing the smallest forecast error.","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"16 1","pages":"186 - 202"},"PeriodicalIF":3.7,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85997084","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Anna Kotásková, J. Bélas, Y. Bilan, Khurram Ajaz Khan
Abstract Personnel risk significantly affects the operation of small and medium-sized enterprises. The aim of the paper is to define and present significant factors affecting the perception of personnel risk in the SME segment, and compare the current status and development in the Czech Republic and Slovakia. The empirical research was conducted in 2020 in the SME segment in the Czech Republic and Slovakia via an online questionnaire, using a sample of 822 respondents. The obtained data were evaluated using the Chí square and Z score. Personnel risk significantly affects the SME segment and its business activities. This risk is perceived as the most significant business risk in both countries, even though its intensity is moderate and does not have a heavy negative impact on SMEs’ activities. The overall evaluation of personnel risk’s impact on SMEs’ activities is similar in both countries. The evaluation of employee turnover was relatively positive, as a considerable part of entrepreneurs stated that turnover is low and does not have a negative impact on their business. The evaluation of turnover was similar in both countries. Based on entrepreneurs’ statements, there are certain gaps in employee error rate, which affects their business. Slovak entrepreneurs provided a worse evaluation of the quality of their employees than the Czech entrepreneurs. Entrepreneurs in both countries are dissatisfied with the way their employees strive to improve their performance or how they compete among each other. The comparison based on business size and age did not yield significant differences, nor did it provide a clear trend despite the general belief presented in literature that larger enterprises have a better access to important fields of business management.
{"title":"Significant Aspects of Managing Personnel Risk in the SME Sector","authors":"Anna Kotásková, J. Bélas, Y. Bilan, Khurram Ajaz Khan","doi":"10.2478/mmcks-2020-0013","DOIUrl":"https://doi.org/10.2478/mmcks-2020-0013","url":null,"abstract":"Abstract Personnel risk significantly affects the operation of small and medium-sized enterprises. The aim of the paper is to define and present significant factors affecting the perception of personnel risk in the SME segment, and compare the current status and development in the Czech Republic and Slovakia. The empirical research was conducted in 2020 in the SME segment in the Czech Republic and Slovakia via an online questionnaire, using a sample of 822 respondents. The obtained data were evaluated using the Chí square and Z score. Personnel risk significantly affects the SME segment and its business activities. This risk is perceived as the most significant business risk in both countries, even though its intensity is moderate and does not have a heavy negative impact on SMEs’ activities. The overall evaluation of personnel risk’s impact on SMEs’ activities is similar in both countries. The evaluation of employee turnover was relatively positive, as a considerable part of entrepreneurs stated that turnover is low and does not have a negative impact on their business. The evaluation of turnover was similar in both countries. Based on entrepreneurs’ statements, there are certain gaps in employee error rate, which affects their business. Slovak entrepreneurs provided a worse evaluation of the quality of their employees than the Czech entrepreneurs. Entrepreneurs in both countries are dissatisfied with the way their employees strive to improve their performance or how they compete among each other. The comparison based on business size and age did not yield significant differences, nor did it provide a clear trend despite the general belief presented in literature that larger enterprises have a better access to important fields of business management.","PeriodicalId":44909,"journal":{"name":"Management & Marketing-Challenges for the Knowledge Society","volume":"34 1","pages":"203 - 218"},"PeriodicalIF":3.7,"publicationDate":"2020-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"73822194","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
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