Wyniki wyszukiwania - BazTech

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The study of the interdependencies of areas and aspects of smart city in Polish cities

Owczarek Tomasz, Sojda Adam, Wolny Maciej

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2022

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z. 161

203--214

EN

Purpose: To determine the interdependencies between Smart City areas as well as the aspects and areas between resident-oriented IT areas of the city. Design / methodology / approach: The data for the study was collected during a survey of 287 cities for Smart City. The study of interdependence was based on a correlation analysis using: Pearson's correlation coefficient, Cramér's V coefficient, and Kendall's tau. In addition, a PCA analysis was used to reduce variable dimensions. Findings: The results of the research indicate that the scope of using services within e-office services is more strongly related to functionality than to IT equipment. In turn, the economic area plays a fundamental role in the perception of the city as a Smart City. There was also a clear difference in self-evaluation regarding Smart City areas and IT aspects of the city depending on the size of the city. However, this difference does not translate into declarations regarding the readiness for evaluation in Smart City categories. Originality/value: presentation of the relationship between the areas defining the concept of Smart City dependence on the basis of an original study addressed to city representatives. The results of the study allow us to look at the Smart City concept from the perspective of the city. The results of the analysis, in addition to scientists dealing with Smart City, may be of interest to city managers in Poland. They show the way of understanding and dependencies between individual areas. They also show those dependencies that need to be strengthened in the context of sustainable development.

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Forecasting needs of the operational activity of a logistics operator

Kmiecik Mariusz, Wolny Maciej

LogForum

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2022

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Vol. 18, no. 2

197--212

EN

Background: The paper considers the issue of operational needs of logistics operator connected with the implementation of demand forecasting tool in his activity. The aim of this article is to present research results on the ability to meet the expectations of distribution centre managers at the operational level. To achieve the main goal, three research questions concerning general requirements and possibilities of meeting the requirements set by managers working for a logistics operator were also defined and related to operational needs. Methods: The research analysed the operational requirements of a logistics operator using a survey conducted among managers dealing with the operational work that is performed in the operator's warehouses. Then, the possibility of implementing and operating a forecasting tool based on the ARIMA algorithm in the logistics service of a confectionery manufacturer was analysed, providing the verification of usefulness of such a tool and the level of its adjustment to operational requirements. Results: The forecasting tool is especially useful in the operator's activity in order to support the resource planning process of warehouse operation. However, managers set high requirements regarding the verifiability of the operation of such a tool, which is not completely available in the current situation. The article also shows the future development paths of this tool. Conclusions: The article shows possibilities related to the use of a forecasting tool in activities related to the provision of services in contract logistics. This allows for verification of the needs and capabilities of the logistics operator who would forecast the demand to support the operations it carries out.

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The impact of standardisation method on smart city ranking

Sojda Adam, Wolny Maciej

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2020

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z. 142

83--94

EN

Purpose: The main purpose of the work is to present the impact of standardisation methods on the ranking results. The second purpose of the article was to present Warsaw’s position in comparison with the capitals of countries from the Eurozone. Design/methodology/approach: Major European cities were assessed using Eurostat data. The proprietary Smart City Index (SCI) indicator is proposed for the study, referring to six areas of Smart City assessment. Two measures are indicated in each of them. The first is an objective measure, while the second is a subjective measure, based on the opinion of the city’s residents about the situation in the city, or their own situation. Building rankings of the cities, following normalisation methods were used and compared: unitisation, unitisation with zero minimum, normalisation in range [-1, 1], classical standardisation, Weber standardisation and two quotient methods. Findings: The best results were obtained for the classical standardisation. For this method we obtained the smallest number of consistent positions in rankings and the minimal maximum of distance between the positions in rankings. The position of Warsaw as a city in 16th position (20 of all) was confirmed regardless of the standardization method used. Originality/value: There is proposed an original method to assess cities based on Eurostat data. This method allows construction of Smart City ranking. The main value of the work is that the classical standardisation is recommended to transform the original values of individual indicators.

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Forecasting demand for products in distribution networks using R software

Wolny Maciej, Kmiecik Mariusz

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2020

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z. 142

107--116

EN

Purpose: This article addresses the issue of forecasting demand for products flowing in a distribution network conducted from the perspective of a 3PL logistics operator. Its purpose is to present a tool based on the R software, which is to be used for automatic forecasting of time series. Design/methodology/approach: The work uses the algorithm of automatic forecasting of time series implemented in the "forecast" package. The algorithm was used in a loop for different lengths of the time series to determine the best length of the series. The minimal RMSE value in the training set and in the test set were considered as optimality criteria. Findings: It is shown that the best time series length is 60 weeks in the considered case. Originality/value: The procedure for selecting the best time window length for forecasting demand for products in distribution network.