The Application of Forecasting Sales of Services to Increase Business Competitiveness

Kolková, Andrea

doi:10.7441/joc.2020.02.06

Cited by 23 publications

(26 citation statements)

References 13 publications

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“…7 million adults (over 18 years of age) unemployed in Mexico due to the COVID-19 pandemic and although the last INEGI report issued at the end of September 2020, the Mexican unemployment rate fell in August to 5.2% by incorporating 608,000 people into the PEA (Economically Active Population), with which there are 2.8 million unemployed. According to Kolkova (2020), one of the keys of competitiveness companies is an accurate forecast of its business variables that it' s necessary in this globalized and digitalized world.…”

Section: Discussionmentioning

confidence: 99%

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

Sierra

Flores

Duarte

et al. 2020

IJEK

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The implications of the COVID-19 pandemic have jeopardized many corporations around the globe, especially those that were centered around what is considered to be a non-essential activity. The objective of this research is to discover what strategies the company in question applied successfully within its diverse areas, leading its system management to an overall positive outcome, despite having to adapt to 7 months of COVID-19. In order to achieve this, the company's data will be examined before the pandemic began to identify the processes within the main areas, where they could find their strengths and weaknesses. For the purpose of this investigation, the PDCA methodology was implemented to identify the different successful strategies related to the main activities at the company, followed by a validated questionnaire applied to main directors where the principal strategies previously identified have been evaluated. Considering all of this, a new index rate is proposed in this paper. By applying the organizational prevalence index, the sales result has a total prevalence of around 100.4%, so that sales remain the same. The prevalence for the stock has been observed to increase significantly, and in the case of personnel, there has been a minimal increase. Despite there being a noticeable decrease in the national context, there has been a decrease in the employment rate. This study was carried out with the goal of being a reference for resilience for companies where strategies are related to the results when applying the index. Because the study was conducted in only one company, the recommendation for the future is to replicate the study in a large number of companies to correlate data and verify that the index shows a more reliable relationship with company performance. Also, it is considered to apply this index in different company categories, but that will depend on confidentiality and data transparency in every organization.

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Section: Discussionmentioning

confidence: 99%

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

Sierra

Flores

Duarte

et al. 2020

IJEK

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“…Many governments have expropriated hotels to be used as temporary quarantine accommodation, referred to as the "quarantine hotel (QH)." Following the view of Kolkova (7), companies are responding to this need by intensifying accuracy requirements for forecasting market demand. The QH is the hotel industry's resilience strategy in response to a major global crisis.…”

Section: Introductionmentioning

confidence: 99%

The Association Between Fear of Coronavirus Disease 2019, Mental Health, and Turnover Intention Among Quarantine Hotel Employees in China

Teng

2021

Front. Public Health

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During the coronavirus disease 2019 (COVID-19) pandemic, quarantine hotel employees face a higher risk of infection while they host quarantine guests from overseas. This is the first research to empirically investigate the psychological effects of operating a quarantine hotel on its employees. The empirical results indicate that heightened fear of COVID-19 leads to adverse mental health issues for quarantine hotel employees and confirm that depression, anxiety, and stress have a significant influence on turnover intention. These findings contribute to the extant knowledge base by uncovering the role of mental health in employee turnover intention. Based on the results, implications are presented for practitioners.

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“…However, the model with the lowest margin of error among all tested models is the ANN model. ANNs can learn and generalize the nonlinear patterns in the data and thus create solutions with a reasonable margin of error for the problems that they have not encountered before (Kolkova, 2020;Vrbka, 2020). These findings reveal the ability of ANNs, a machine learning technique, to learn complex and nonlinear models effectively, which is a clear advantage over linear models.…”

Section: Empirical Findingsmentioning

confidence: 79%

Modelling and Forecasting Inbound Tourism Demand to Croatia using Artificial Neural Networks: A Comparative Study

Çuhadar

2020

JoTS

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Tourism demand is the basis on which all commercial decisions concerning tourism ultimately depend. Accurate estimation of tourism demand is essential for the tourism industry because it can help reduce risk and uncertainty as well as effectively provide basic information for better tourism planning. The purpose of this study is to develop the optimal forecasting model that yields the highest accuracy when compared to the forecast performances of three different methods, namely Artificial Neural Network (ANN), Exponential Smoothing, and Box-Jenkins methods for forecasting monthly inbound tourist flows to Croatia. Prior studies have been applied to forecast tourism demand to Croatia based on time series models and casual methods. However, the monthly and comparative tourism demand forecasting studies using ANNs are still limited, and this paper aims to fill this gap. The number of monthly foreign tourist arrivals to Croatia covers the period between January 2005-December 2019 data were used to build optimal forecasting models. Forecasting performances of the models were measured by Mean Absolute Percentage Error (MAPE) statistics. As a result of the experiments carried out, when compared to the forecasting performances of various models, 12 lagged ANN models, which have [4-3-1] architecture, were seen to perform best among all models applied in this study. Considering both the empirical findings obtained from this study and previous studies on tourism forecasting, it can be seen that ANN models that do not have any negativities (such as over-training, faulty architecture, etc.) produce successful forecasting results when compared with results generated by conventional statistical methods.

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The Application of Forecasting Sales of Services to Increase Business Competitiveness

Cited by 23 publications

References 13 publications

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

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

The Association Between Fear of Coronavirus Disease 2019, Mental Health, and Turnover Intention Among Quarantine Hotel Employees in China

Modelling and Forecasting Inbound Tourism Demand to Croatia using Artificial Neural Networks: A Comparative Study

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