Information system for city logistics. The case of Poland

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Transportation Research Procedia 39 (2019) 160–169 www.elsevier.com/locate/procedia

Green Cities 2018 Green Cities 2018

Information system for city logistics. The case of Poland Information system for city logistics. The case of Poland a

Maja Kiba-Janiakaa*, Katarzyna Chebabb Maja Kiba-Janiak *, Katarzyna Cheba

Wroclaw University of Economics, Nowowiejska 3, Jelenia Góra 58-500, Poland a West Pomeranian UniversityofofEconomics, TechnologyNowowiejska in Szczecin, Janickiego 31, 71-210 Szczecin, Wroclaw University 3, Jelenia Góra 58-500, Poland Poland b West Pomeranian University of Technology in Szczecin, Janickiego 31, 71-210 Szczecin, Poland b

Abstract Abstract According to the European Commission (2007), in the cities particular emphasis should be placed on the implementation of actions that could reduce greenhouse gas emissions, noise andcities otherparticular pollutions.emphasis The implementation of these objectives requires of access to According to the European Commission (2007), in the should be placed on the implementation actions muchcould up-to-date including the type of pollutions. the flow ofThe goods, passenger car trafficobjectives in the city, the number that reduce information greenhouse gas emissions, noiseand andsize other implementation of these requires access of to accidents caused by drivers ofincluding trucks andthe cars, Access to the current can greatly supportcarlocal authorities in making the right much up-to-date information typeetc.and size of flowdata of goods, passenger traffic in the city, the number of decisions in the field of urbanoflogistics (Małecki et al., 2014).toUnfortunately, in most Polish citieslocal suchauthorities information not collected or accidents caused by drivers trucks and cars, etc. Access current data can greatly support inismaking the right is collected Consequently, in many cities concerning the coordination of the flow of cargo and in the decisions in irregularly. the field of urban logistics (Małecki et al., decisions 2014). Unfortunately, in most Polish cities such information is notpeople collected or city are made intuitively rather than based on cities actualdecisions data. In concerning this paper the coordination authors haveofsetthetwo - theoretical andpeople empirical is collected irregularly. Consequently, in many flow of cargo and in theobjectives. Theintuitively theoreticalrather purpose concerns the actual authorial concept a simplified city logistics system.and Theempirical empiricalcity are made than based on data. In thisofpaper the authors have set information two - theoretical objective an analysis of the current the stateauthorial of logistics information systemscity in logistics the selected cities and identification of the objectives.includes The theoretical purpose concerns concept of a simplified information system. The empirical activities of Polish an local governments collecting analysinginformation data in the systems field of people goodscities movement within the city. In objective includes analysis of the in current state and of logistics in the and selected and identification of the order to identify thelocal relationships between the extent ofanalysing information theofsize of the city; and the organisation activities of Polish governments in collecting and datacollection; in the field people andresearch goods movement within the city. of In the task therelationships passenger and freight the transport, correspondence analysisthe was used. order to related identifytothe between extent the of information collection; size of the research city; and the organisation of the task related to the passenger and freight transport, the correspondence analysis was used. © 2018 The Authors. Published by Elsevier B.V. © 2019 The Authors. Published by Elsevier B.V. This is an open accessPublished article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) © 2018 The Authors. by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of Green Green Logistics Logistics for for Greener Greener Cities Cities 2018. 2018. This is an open access article under the CC BY-NC-ND licensecommittee (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific of Selection and peer-review under responsibility of the scientific committee of Green Logistics for Greener Cities 2018. Keywords: local government, city logistics information system, correspondence analysis. Keywords: local government, city logistics information system, correspondence analysis.

1. Introduction 1. Introduction One of the main tasks of city logistics is to coordinate the flows of human and material resources in the city in Onetoofimprove the main of city logistics to coordinate the flows of European human andCommission material resources in order thetasks quality of life of its isresidents. According to the (2011),ininthe thecity cities order to improve theshould quality life of According to the that European Commission (2011), the cities particular emphasis be of placed onits theresidents. implementation of actions could reduce greenhouse gasinemissions, particular emphasis should be placed on the implementation of actions that could reduce greenhouse gas emissions, * Corresponding author: Maja Kiba-Janiak. Tel.: +48757538223. E-mail address:author: [email protected] * Corresponding Maja Kiba-Janiak. Tel.: +48757538223. E-mail address: [email protected] 2352-1465 © 2018 The Authors. Published by Elsevier B.V. This is an open access under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) 2352-1465 © 2018 Thearticle Authors. Published by Elsevier B.V. Selection under responsibility of the scientific of Green Logistics for Greener Cities 2018. This is an and openpeer-review access article under the CC BY-NC-ND licensecommittee (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of Green Logistics for Greener Cities 2018. 2352-1465  2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the scientific committee of Green Logistics for Greener Cities 2018. 10.1016/j.trpro.2019.06.018

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noise and other pollutions. The implementation of these objectives requires access to much up-to-date information including the type and size of the flow of goods, passenger car traffic in the city, the number of accidents caused by drivers of trucks and cars, etc. Access to current data can greatly support local authorities in making the right decisions in the field of urban logistics. However, in Europe there is a lack of standards for the collection and analysis of data in this field. As a result, in many cities there is limited access to the data and sometimes even an inability to obtain those data (Ibeas, et al., 2012). An efficient information flow should be the foundation of city logistics. In most Polish cities information on passenger and freight transport is not collected or is collected irregularly. Consequently, in many cities decisions concerning the coordination of the flow of cargo and people in the city are made intuitively rather than based on actual data. In this paper the authors have set two - theoretical and empirical - objectives. The theoretical purpose concerns the authorial concept of a simplified city logistics information system. The empirical objective includes an analysis of the current state of logistics information systems in Polish cities and identification of the relation between scope of information collection and other factors related to the people and goods movement within the city . In order to identify the relationships between the extent of information collection; the size of the research city; and the organisation of the task related to the passenger and freight transport, the correspondence analysis was used. In this paper the calculation of the multiple correspondence analysis was based on Burt matrix. As a result of the correspondence analysis the relationship between concerned areas of the study has been confirmed. The paper is organised as follows. Section 2 presents the theoretical framework on an information system and a city logistics information system. Section 3 provides the research methodology including an overview on the research object and study stages. In section 4 the authors presented the survey results. In this part of the paper a Multivariate Statistical Analysis was conducted. In the last section the authors have presented conclusions and remarks. 2. City logistics information system According to Taniguchi and Thompson (2001) city logistics, through the introduction of innovative solutions, improves the quality of life of residents. The main objective of city logistics is mobility, sustainability, liveability (Taniguchi, et al., 2003) through the coordination of flows of people and goods in an efficient, effective and environmentally friendly way. To achieve this objective information on the needs of different stakeholders, such as: local government, transport companies, receivers, collective transport companies and shippers (Taniguchi and Tamagawa, 2005; Horacio and Carim, 2013) and passenger and freight transport flows should be collected (Iwan and Kijewska, 2014). For this purpose the efficient flow of information is required. Porter had already emphasised in the 1980's the benefits of the access to prompt and adequate information (Porter and Millar, 1985). Information system allows costs reduction, errors elimination and improvement of the flow of information between all stakeholders (Straka et al., 2017; Bae, 2016; Marcucci et al., 2017). It strengthen the competitive position of the organisation (Bergeron et al., 1991). „Information system can be defined as a set of interrelated components that collect (or retrieve), processes, store, and distribute information to support decision making and control in an organization” (Laudon and Laudon, 1999). Information system can be informal (office gossip) and formal (computer-based and manual), (Laudon and Laudon, 1999). The authors in this paper will refer to formal information system based on PC technology. Since the early 90s, many governments have introduced electronic flow of information (electronic government - e-government) between government administration / local government and the business community and residents (Wang and Liao, 2006). Local authorities notice many advantages of using this kind of technology (Wang and Liao, 2006; Ballantyne et al., 2013; Ni et al., 2016; Verkijika and De Wet, 2018). There are also examples of information systems which support decision making process of local authorities (Amirgholy et al., 2017). However, there is still lack of information system which could enable to collect data on city logistics and support decision making process in a coherent way. Moreover, there is a poor integration among local authority’s departments (Hatzopoulou and Miller, 2009). The access to current and relevant information is the base for an efficient planning and coordinating the flow of people and goods in the city. On the basis of these plans the traffic flow plans in cities should be developed. Despite the fact that some countries, such as the United Kingdom, Germany, France, the Netherlands or Italy have developed the legislation enabling Including goods in urban traffic flow plans, still in most European cities transport plans only

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cover passenger transport omitting freight. Therefore, there is a need to develop a logistics information system, which would include information about both passenger and goods flows. Logistics information system (LIS), through modern information technology and telecommunication, could provide decision support in logistics at levels: strategic, tactical and operational. One of the definitions says that LIS is "a production and distribution activity network of an organization to work collaboratively to meet consumers’ demand” (Perdana, 2012). More extended definition of LIS has been developed by Bendkowski and Kramarz (2006). According to them it is "the whole process of information from the analysis of the market, the distribution of marketing, through the transfer of this information in the form of projections and expectations to the production departments, where they are processed on the decisions in the area of supply”. LIS is seen as a strategic approach to support all logistics activities using information technology and telecommunications. In the literature, a considerable number of items can be found describing the use of LIS in business, but relatively few in relation to the city (Kang and Kwon, 1997; Ngai et al., 2010; ZHaokang et al., 2011). For example London has developed its freight transport information system, presented annually in the London Freight Data Report, which allows the gathering of information such as: number of people employed in London, especially in freight transport and logistics companies, number of warehouses in London, the weight of freight lifted by road, air, water and rail, number of vehicle kilometres travelled by different type of vehicle, number of casualties resulting from collisions involving Light Goods Vehicles and Heavy Goods Vehicles, etc. This information enables London’s local authorities to undertake the appropriate activities in the field of city logistics, (Allen et al., 2014). According to the authors a city logistics information system (CLIS) can be defined as the information processes with a use of information technology, teleinformation and telematics, along with the procedures and standards, in order to enable the efficient and effective planning, organising, coordinating and controlling the flow of people and goods within the city. A city logistics information system could be a system to support decision making. The authors of this study, based on own research, good practices, observations and personal experience, have made attempts to develop authoring a simplified model of a city logistics information system (Figure 1). The main organiser and operator of CLIS could be the local government, which is a key stakeholder of city logistics. However, different expectations of other stakeholders of city logistics could also be taken into consideration during the development and implementation of this type of system. For example the main objective in the field of freight transport is to reduce the uncertainty of activities in the area of logistics customer service related to: reliability, timeliness and consistency of supply. Another objective consists in reducing CO2 emissions and noise in the city centre. From the citizens’ point of view the purpose of CLIS is to improve city traffic and to reduce CO2 emissions and noise in the city centre. CLIS could take into account the functional areas such as: organisations and technology. An organisation area could include: standard operating procedures (way of communication among stakeholders, information flow procedures, type of data, which could be collected, etc.) and law regulations (restriction for freight transport, individual transport etc.). The technology area could include tools systems, such as: EDI, GPS, RFID, artificial intelligence, Internet, telematics and information technology. The use of modern information technologies in the relationship between the stakeholders of city logistics could enable faster acquisition of information about the expectations of stakeholders and the actions they have taken in favour of city logistics. CLIS data could be collected from internal and external sources, that might be primary or secondary data. Internal sources include reports, statements, analyses provided by departments and agencies of the municipal authority. External data comes from city logistics stakeholders and other institutions and organisations that will indirectly have an impact on the movement of people and goods in the city. The London Freight Data Report is the example where many different stakeholders were involved in collecting data in the field of freight transport. Among them can be distinguished: Department for Transport Road Freight Statistics Team, Department for Transport Road Vehicle Licensing Statistic Team, Greater London Authority, London Councils, MDS Transmodal, Network Rail, Port of London Authority, Skills for Logistics, Transport for London, Vehicle and Operator Services Agency, Westminster University. Such diverse information can be obtained through the use of various research methods based on both information technology and conventional methods of communication. Among the methods that use information technologies can be distinguished: electronic focus groups as well as tools to inform during the discussion and dialogues. The conventional methods include: conferences, repertory grid technique (creation of the personal constructs and mapping to analyse the phenomenon), interactive instruments for risk analysis (forecasting backwards), focus

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groups, the Delphi method, focused interviews and the residents’ jury (OECD, 2010).

City Logistics Information System Local authority Management (coordination of people and goods flows, cooperation with other stakeholders)

Organisations (Standard operating procedures, law regulatory)

Technology

(EDI, GPS, RFID, artificial intelligence,

Internet,

City logistics subsystem

input

Transport companies

output

Collective transport companies/city communication departments

Receivers (enterprises, residents and visitors)

Shippers

Legend: Information flow People flow Cargo flow

Logistics Information System City logistics stakeholders Fig. 1. City logistics information system reference model Source: own elaboration.

These methods allow the collection of information and opinions of stakeholders about the different areas of city logistics. Moreover, by using modern information technologies one would measure and monitor the consistency of the city logistics system. With such solutions stakeholders could quickly make appropriate decisions related to the improvement of urban logistics in the conditions of natural contradictions to the pursued objectives. However, to implement effectively CLIS, local government should provide guidance to the stakeholders and create favourable conditions for the integration of resources within the CLIS (Wu and Shangguan, 2012). 3. Research methodology and study results 3.1. Overview of the research subject Poland since 2004 has been a member country of the European Union, with a population of 38,433,000. More than 60% of the Polish population lives in cities, (Central Statistical Office, 2017). In Poland there has been a threetier structure of local government from 1 January 1999. The country is divided into 16 provinces, 379 counties, including 66 township districts (until December 31, 2012, there were 65), performing either tasks of municipalities

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and cities with county rights and 314 country district concentrating few or several neighboring municipalities (Statistical Yearbook of Poland, 2016). The basic unit of local government in Poland is the municipality with a legal entity. Municipalities have the right of ownership and other property rights. Local government revenue can be divided into: their own, including property tax, general subsidies and grants from the state budget. Responsibilities of the municipalities can be divided into equity (to satisfy local authorities’ needs and to improve the quality of life in the city) and commissioned by the government. Among the municipality tasks, in addition to the above, are also: building and maintaining municipal roads, streets, bridges and squares, environmental and nature protection, planning corporate spatial, traffic organisation, supervision of local public transport, maintaining cleanliness and orderliness, disposal of municipal waste (Government Act, 2001). The tasks in the area of urban logistics carried out by the Polish cities include: the protection of the environment and nature, construction and maintenance of municipal roads, streets and bridges, traffic organisation and supervision of local public transport. Local authorities do not have a statutory duty to carry out the tasks related to urban freight transport. 3.2. Research stages In order to verify the hypothesis the authors have conducted the study, which comprised seven stages. The first phase consisted of a literature review of Polish and foreign sources in the field of city logistics, IT and logistics information system. On the basis of the literature review (Lindholm, 2012) a questionnaire was developed, which experts subsequently tested. The developed survey was conducted in all cities with county rights in Poland. The sample was a target screening. The questionnaire was sent to all 65 cities with county administration rights via email address. Since in the survey were included various aspects, such as: passenger transport, freight transport, information system, the questionnaires were sent directly to the presidents of all cities with the county administration rights. Finally questionnaires were filled out by directors of various departments (responsible for freight transport, passenger transport, IT and environmental protection). In order to obtain all detailed information about some solutions interviews with representatives of seven city councils were also conducted. During the interviews the authors received information about the selected solutions and also explained some questions to respondents. The survey response rate was at 55% (36 out of 65 towns with county rights filled the questionnaires). Among the cities that have sent the completed questionnaire were: nine cities with the population up to 100 thousand, 14 cities with a population between 100 000 and 199 999, 5 cities with a population between 200 000 and 299 999 and 8 cities with the population 300 000 and more. The survey was focused on the role of local government in developing solutions in the field of people, goods and information flows. However, for the purpose of this paper, the authors have concentrated mainly on questions, which related to information system in the questionnaire. In the survey, the authors have asked, among others, following questions to the respondents:  What kind of data does the analysed cities collect in relation to city logistics, such as: passenger car traffic volumes in the city, heavy goods vehicles traffic volumes in the city, noise measurement in the city, measurement of CO2 emissions in the city, places of loading and unloading hindering traffic on the roads, the estimated number of residents travelling by public transport, the quality of public transport services, the amount of cargo being moved within the city?  What kind of sources and how the data are collected in the field of city logistics (from external sources: e.g. from Central Statistical Office, other stakeholders and from internal sources from: departments)? In order to identify the relationships between the extent of collecting information, size of the research city, organisation of the task related to the passenger and freight transport the correspondence analysis was used. Correspondence analysis as a factor method allows the identification of relationships between variables and objects mainly in a graphical form (Panek, 2009). The starting point is the choice of the notation of the observed number of category features. In this paper the calculation of the multiple correspondence analysis was based on Burt matrix (Bąk, 2009). It is a symmetric block matrix where the main diagonals are diagonal matrices containing the number of each category. Off- diagonal blocks are contingency tables between pairs of variables. Burt matrix (B) is the product of an internal matrix markers (Z):

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B=ZTZ

165

(1)

However, the matrix markers (system code) is constructed in such a way that each row corresponds to another observation, and the column - variants of all variables. Dimension of real space co (K) is determined by the formula: 𝑄𝑄

𝐾𝐾 = ∑𝑞𝑞=1(𝐽𝐽𝑞𝑞 − 1)

(2)

where: Jq – the number of categories of variable q (q = 1,2, …, Q), Q – number of variables. Greenacre criterion is used in selecting the eigenvalues (λk) which are significant, on the basis of the following formula:

𝜆𝜆𝑘𝑘 >

1 𝑄𝑄

(3)

where: λq – eigenvalues (k = 1,2, …, K), Q – number of variables. In order to improve the quality of the image modification of own values is carried out, as proposed by Greenecre (1984) based on the formula:

̃ 𝐅𝐅̃ = 𝐅𝐅 ∗ ∙ 𝚪𝚪 −𝟏𝟏 ∙ 𝚲𝚲

(4)

where: 𝐅𝐅̃ – the modified matrix of coordinate values for the category of the tested variables of the dimension Kxk, 𝐅𝐅 ∗ the matrix of primary coordinate values for the category of the tested variables of the dimension Kxk, 𝚪𝚪 −𝟏𝟏 - the ̃ –kxk, K – the number of dimension. inverse of diagonal matrix of singular value of dimension kxk, 𝚲𝚲

4. Study results

In Poland, there are no generally recognised standards for the collection of information related to people and goods flows in the city. Although the city must present an annual report to the Central Statistical Office and to the overarching competent authorities, the data do not relate to the movement of persons and goods in the city. Cities with the county rights are also required to perform periodic measurements of traffic in the city (Government Act, 1985). However, the results show that among the 36 analysed cities, 33 make measurements of traffic in the city in relation to individual transport. According to the respondents, irregular collection of information concerning city logistics was mainly due to a lack of funds. Moreover, the regulatory acts do not specify the frequency of this type of measurement. Consequently, the results show that there is a great variation among local governments in terms of frequency of performed measurements. In fact, each city collects data according to its own plans. For example, in the four examined cities traffic measurement for passenger cars takes place every day. In the subsequent four cities every year and in two research cities this measurement takes place every two to three years. Other cities perform this kind of measures every five years. A similar situation takes place in the case of road traffic measurement in relation to freight transport. This kind of measurement is carried out by three studied cities every day, four cities - every year, three cities - every two to three years and the other cities - every five years. Due to the fact that cities with county administration rights supervise urban public transport, the majority of them also implement various measurements in this area. Of the 35 analysed cities 30 collect information on the estimated number of residents travelling by public transport. Among them 28 analyse the quality of public transport services. Six cities, which are in the Silesian agglomeration, have commissioned public transport organisation to an external entity, so the cities do not execute research in this area. Poland, due to EU and national legislation is required to make regular noise level measurements in the city and to collect data on air pollution and CO2 emissions. The body responsible for the implementation of these measures is the Inspection of Environmental Protection (Government Act, 2001). However, research has shown that not all cities and towns carry out these measurements on their own. The noise measures are provided by 26 studied cities, while only six cities explore the level of air pollution and CO2. Studies show that Polish local governments commit to improvements in the flow of cargo only to a very small extent. Among the 36

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studied cities only two collect information about the places of loading and unloading hindering traffic on the roads and only one of them takes measurements of the amount of cargo being moved within the city. In the survey, respondents were asked to provide information about the source of collected information concerning the movement of persons and goods in the city All subjects showed the city administration services as a major source of information for the city department of communication (or collective transport company). A further 25 cities pointed to other city council departments, and ten to the Central Statistical Office. Only three surveyed cities pointed out shippers and transportation companies as a source of information related to the people and cargo flows. In the studied cities methods of collecting information were different. Most frequently indicated were reports, statements, and research based on a questionnaire. The diversity of methods also confirms the previously referred-to hypothesis, that the Polish local governments have no standards for collecting and analysing data and information on the flows of people and goods in the city. In order to analyze problem more thoroughly the authors decided to apply correspondence analysis and Ward’s method. The main purpose of this analysis was to find out if the scope of information collection correspond to other factors such as: size of the research city, organizational structure of the city hall, etc. All these factors were divided into five groups:  Group 1 describes the scope of information collection: D1 – narrow scope of logistics data collection, including the collection of only basic information about car and truck traffic in the city, D2 – the average scope of data collection in the range of the urban logistics, including apart from the basic information also some other data collected by established institutions for this purpose e.g. environmental inspectorates concerning noise and CO2 emissions in the city, D3 – a wide range of data collection in the range of the urban logistics, in addition to the basic information and data concerning the factors influencing the quality of the urban environment as well as additional information related with e.g.: loading transport vehicles or the quality of communication services within the city;  Group 2 describes the location of the department dealing with issues related to passenger and freight transport in an organization structure of city council: DL1 - the separation in the structures of city council the department dealing with issues related to passenger and freight transport, DL2 - no such department, DL3 - performing tasks related to the logistics of transportation in other departments,  Group 3 describes the organization of working time: P1 – limited working time spent on issues related to passenger and freight transport, due to the way the tasks are organised in cities associated with the fact that these tasks are concerned to be additional ones, temporary, performed occasionally, P2 – is the average working time spent on issues related to passenger and freight transport, which is typical for cities where implementation of tasks related to the city logistics is a part of the tasks carried out by certain employees, P3 – significant working time spent on issues related to passenger and freight transport, which characterises cities, in which urban logistics related tasks are separate activities carried out by specialised departments for this purpose,  Group 4 describes the number of employees performing tasks related to passenger and freight transport: O1 - a small number of employees performing tasks related to passenger and freight transport (fewer than 10 employed in different departments), O2 - the average number of employees performing tasks related to passenger and freight transport (from 10 to 30 people working in different departments) O3 - a significant number of employees performing tasks related to passenger and freight transport (over 30 people working in different departments),  Group 5 describes the size of the cities: M1 - town with a population of less than 100 thousand, M2 - city with a population in the range of 100-200 thousand residents, M3 - the city with a population of over 200 thousand. In the case of variables describing the number of employees performing tasks related to passenger and freight transport and time for the implementation of this task, the initial information gathered during the survey was used to designate particular categories of responses. This means that, for example, the range of the average working time is the average working time for 36 cities analysed in the study. For this purpose Burt table was created of size 15x15. By using the Greenacre criterion, it was examined to which extent the eigenvalues of a lower dimension explain the total inertia (λ = 2.0000). The information provided in the presented table shows that relevant research is the main host of eigenvalues, at most 4. The criterion for selection of the cast also used the below criterion according to which the correct projection space is the space indicated by the number of eigenvalues, for which there was a fault in the

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graph of eigenvalues (Panek, 2009). According to this criterion for the proper dimension of space projection the three-dimensional space was assumed for which a degree of explaining the inertia (the accuracy of the description of the simultaneous co-occurrence 5 analysed variables) was 50.95%. In order to improve the obtained solution a modification was implemented in accordance with the criterion of Greenacre whose first three eigenvalues represent 84,77% of the modified total inertia, which means that the result of the first three dimensions could explain a larger percentage of the total inertia than before modification. The results of this phase of the study are presented in Table 1. Table 1. The results of the correspondence analysis after the modification according to the Greenacre’a criteria Number of dimension K 𝜆𝜆̃𝑘𝑘 𝜆𝜆̃𝑘𝑘 /𝜆𝜆̃ 𝜏𝜏̃𝑘𝑘 1

0,3106

38,1190

38,1190

2

0,2074

25,4598

63,5788

3

0,1727

21,1955

84,7742

0,1241

15,2258

100,0000

4

𝜆𝜆̃𝑘𝑘 = 0,8147

Source: own calculations

As proposed in the work of Stanimir (2005) and Bąk (2009) to show the links between the variables of considered variants Ward's method was used. The results of this phase of the study are presented in Figure 5, the horizontal line marked the phase of interrupting the combination of classes. On the basis of the results of the analysis of solution obtained using the multiple correspondence analysis in combination with the results obtained using Ward method it can be indicated that there is a link between the categories of analysed variables describing the practices of analysed offices in the organisation of activities related to city logistics. The results allowed us to define the following classes: Class I (M1, O1, D1): includes the city less than 100 thousand inhabitants, in which the range of data collection related to passenger and freight transport is inconsiderable and a small number of employees who perform issues related to passenger and freight transport is observed (fewer than 10 people employed in different departments). Class II (M2, O2, P1, D2, DL2): includes cities with a population between 100-200 thousand, in which the range of collecting data in the field of passenger and freight transport is extended, in addition to the basic information also other data is collected. These cities do not have a selected city logistics department and the number of employees performing tasks related to passenger and freight transport is average (ranges from 10 to 30 people working in different departments). The time spent on carrying out tasks related to the city logistics is average. Class III (M3, O3, P3, D3, DL3, P2, DL1), covers the biggest surveyed cities with a population of over 200 thousand, in which the range of the data collection in the field of passenger and freight transport is significant, apart from basic information also significant amounts of additional data is collected. These cities have a separate department dedicated to city logistics or perform its tasks within any other department, e.g. the Department of Highways, Municipal Roads and Bridges Management or any similar, in which the number of employees performing the task related to passenger and freight transport is high (more than 30 people employed directly or in various departments). The time spent on carrying out tasks related to the city logistics is also significant. The identified information on the basis of analysis allow to make a few simple basic conclusions. The extension of collecting information and the number of employees performing tasks related to passenger and freight transport are directly related to the size of the city. This conclusion shows that the need of collecting data in big cities, where the problems related to passenger and freight transport are more significant than in small ones. 5. Conclusion There were two main purposes of the work: development of the authorial concept of a simplified city logistics information system and the analysis of the current state of logistics information systems in Polish cities. In the empirical work correspondence analysis and Ward’s method, have been used. The results show that there is a lack of comprehensive approach in the literature to the flow of information in the city. City logistics requires the involvement of many stakeholders pursuing different goals. Nevertheless, the city

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logistics information system could greatly improve the flow of information between stakeholders and allow local governments to efficiently manage the flow of passenger and cargo within the city. The proposed original and simplified model for city logistics information system shows the most important tasks and functions including stakeholders, who should be involved in its utilisation (to a lesser or greater extent). The authors are aware that the structure of the city cannot be compared to a single company, but local governments should take the role of coordinator in activities related to the flow of people and goods in the city. Therefore, the main user of the CLIS should be the local government, in cooperation with other stakeholders. The aim of the CLIS is not only to implement information, teleinformation and telematics tools but also to improve the procedures and standards for the collection and analysis of data concerning the movement of persons and goods in the city. The results of the research show that the Polish local governments lack standards for collecting and analysing data on the flow of people and goods. Diversity occurring quantity and frequency of collected data makes it impossible to compare them at the national level as well as creating difficulties in taking decisions by local governments in the area of urban logistics. Among the studied cities only a small number of them gather data on the flow of goods and loading and unloading areas in the city. As a result of the correspondence analysis the authors have identified the relationships between categories of features expressed on a nominal scale describing the practices examined in the offices within the activities related to the organisation of tasks related to the people and goods flows. The study selected three segments of the cities, varying mainly due to the organisation of the tasks related to the city logistics and size of the city. The correspondence analysis confirmed the authors’ observation, that the range of collected data on persons and cargo flows depends on the size of the city. The bigger the city the greater the range of collected data. References Allen, J., Browne M., Woodburn A., 2014. London Freight Data Report: 2014 Update – final version. University of Westminster. Transport for London, London. Amirgholy M., Shahabi M., Gao H. O., 2017. Optimal design of sustainable transit systems in congested urban networks: A macroscopic approach. Transportation Research Part E: Logistics and Transportation Review, 103, 261-285. Bae, H. S., 2016. The Moderating Effect of Logistics Information Systems on Interorganizational Collaboration and Performance of Korean Shipping and Logistics Firms. International Journal of e-Navigation and Maritime Economy, 5, 85 – 96. Bąk, I., 2009. The Use of the Correspondence Analysis in the Research of the Tourist Activity of University Students. Folia Oeconomica Stetinensia, 8(1), 7–18. Ballantyne, E. E. F., Lindholm, M., Whiteing, A., 2013. A comparative study of urban freight transport planning: addressing stakeholder needs. Journal of Transport Geography, 32, 93–101. Bendkowski, J., Kramarz, M., 2006. Logistyka stosowana, metody, techniki, analizy, Volume 1. Wydawnictwo Politechniki Śląskiej, Gliwice. Bergeron, F., Buteau, Ch., Source, L.R., 1991. Identification of Strategic Information Systems Opportunities: Applying and Comparing Two Methodologies. MIS Quarterly, 15 (1), 89-103. Statistical Yearbook of Poland, 2016. www.stat.gov.pl. Central Statistical Office, 2017. www.stat.gov.pl. European Commission, 2011. Commission Staff Working Document Accompanying the White Paper - Roadmap to a Single European Transport Area – Towards a competitive and resource efficient transport system. Brussels, 28.3.2011, SEC, 391 final. Government Act, 1985. OJ 1985 No. 14, item 60, The Act of 21 March 1985 on Public Roads, art. 20 p. 15. Government Act, 2001. OJ 2001 No. 62 item 627, Act of 27 April 2001. Environmental protection law. Greenacre, M., 1984. Theory and applications of correspondence analysis. Academic Press, London. European Commission, 2007. Green Paper: Towards a New Culture for Urban Mobility. Office for Official Publications of the European Communities, Luxemburg. Hatzopoulou, M, Miller, E.J., 2009. Transport policy evaluation in metropolitan areas: The role of modelling in decision-making. Transportation Research Part A: Policy and Practice, 43 (4), 323-338. Horacio C. F., Carim V., 2013. The effects of globalization and economic growth on income inequality: evidence for 24 OECD countries. Argumenta Oeconomica, 1 (30), 13-31. Ibeas, A., Moura, J.L., Nuzzolo, A., Comi, A., 2012. Urban freight transport demand: transferability of survey results analysis and models. Procedia - Social and Behavioral Sciences, 54, 1068 – 1079.

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