Logistical Processes Interaction Model Design in Agglomeration Development

Purpose of this study is to develop a logistics processes interaction model within the development of urban agglomeration, taking into account basic functional areas of logistics. Objectives of the study were to define the concept of "agglomeration logistics", to identify the main logistics processes of agglomeration, to calculate the logistics stability index (LSI) for the Almaty urban agglomeration 
In this paper such research methods as text analysis, logic modeling, survey method of analysis of hierarchies were used. 
The significance of the study lies in the development of a model explaining the nature of logistics processes interactions in Almaty urban agglomeration. The novelty of the research lies in adaptation and practical application of the methodology for assessing sustainability of urban agglomeration logistics and identifying most influencing factors in order to improve it. 
The main results of the research are: formulating the concept of "agglomeration logistics", identifying interaction algorithms of the main agglomeration logistics processes and calculating the logistics stability index for Almaty agglomeration. 
The following conclusions were made: there are problems of inefficient functioning of logistics processes within the agglomeration. Increasing number of road cargo and passengers has revealed the need to increase road transport network efficiency and carrying capacity; as a result of territorial structure, insufficient development of transport communications between the agglomerations ‘districts, loads on the road transport network increased, which led to violations of fundamental logistics` rules such as "just in time", "optimal route", "high delivery speed", which increases the load on logistics processes and hinders its integration; main constraints to the sustainability of logistics in Almaty agglomeration are air pollution and poor road safety.

The total share of the GRP in the Almaty region was 4.52, which is the 7th place according to Figure 2.
Agriculture, forestry and fisheries well developed in the Almaty region. Almaty region ranks 5th in terms of manufacturing industry 20%, 7th place in terms of transport and storage volumes 12%, 4th place in terms of construction volume 9%. The region also shows results in the field of trade growth 45%. The main production is concentrated in the Ili, Karasai and Talgar regions.
The agglomeration formation carries a number of problems such as the lack of methodological approach to the agglomeration leads to such problems as an excessive burden on the logistics infrastructure, which negatively affects the environmental situation and economic indicators. A comparative analysis by Net  questioning the respondents of Almaty agglomeration shows that there is a problem of inefficiency in logistics processes functioning, which leads to an increasing cost of transporting goods and passengers, an increase in losses of working time, a deterioration of environmental situation. The work forms the dependence of the GRP growth as the main indicator of the Almaty agglomeration development due to the contribution of agglomeration logistics as the basic regional economy service component.     The formaldehyde distribution, as shown in Figure 6, is quite different from the above pollutants' distribution.   It can be concluded, that consequence of the territorial structure, insufficient development of transport communications between the Almaty agglomeration regions, increased loads on the road transport network have become, which leads to logistics rules violation "just in the lines", "optimal route", "high delivery speed".
This factor increases the burden on logistics processes and prevents its integration (Anikina, 2020). Note. Compiled by the authors based on their research.
The analysis of the population mobility types and their Almaty agglomeration share according to the data in Table 1 indicates the linear movement of 33% of the population "Home ↔Work", 28% "Home ↔ Cultural and household facilities" and 16.2% "Home ↔ Study" (Appendix 1 Figure 2).
The analysis of the total mobility distribution by purpose of travel in the Almaty agglomeration and the numerical values of Figure 9 indicate that 75% are citywide travel, and 65% are travel from home. Note. Compiled by the authors based on their research.
Analysis of the main travel purposes and mobility per inhabitant of the Almaty agglomeration per day in Table 2 show the labor travel purposes with a transport utilization rate of 0.76. Note. Compiled by the authors based on Statistical collection Transport (2020).
According to Figure 9, the total number of employees in Almaty was 464,664 people. This number of residents move in the direction of "Home-Work".  According to the data of the motor transport movement time study, it is necessary to conclude that the main flow is concentrated from 6 am to 10 am, which indicates the movement of the population in the direction of "Home -Work" and "Home -Study" in relation to schoolchildren and students.
The next peak occurs in the time frame from 5 pm to 9 pm, which indicates the direction "Work -home", "Study -home" According to the data of the road transport movement chronometric study in Figure   11 during the year, it is necessary to conclude that the main flow is concentrated in the months of March, April, May, June, September, October, November, December. The decline in traffic intensity in January, July, August testifies to the vacation period of the working population and the vacation period for students.
Based on the above data, a "Model of the logistics processes interaction in the agglomeration development " was compiled (Appendix 2, Figures 1,2,3) considering the types of logistics development, such as production, warehouse, information, environmental, lean, customs according to the domestic regional product development in Almaty agglomeration. Highlighted logistics processes such as  (Burakov, 2009).
The authors have developed a "Model for making a decision on the logistics development in a specific agglomeration" based on the Almaty agglomeration development analysis (Appendix 2, Figures 1, 2, 3). To make a decision on the logistics services and processes quality, characterizing parameters in the Almaty agglomeration conditions, taking into account the road transport development intensity and the increase in the roads throughput and the transport infrastructure inconsistency, are criteria as "the right place", "the right time" and "emission reduction". This indicates the deterioration of the ecological situation in Almaty agglomeration. In conditions of the maximum intensity of automobile and urban transport movement organization, it is difficult to withstand the conditions for making the decision "the right place", "the right time" and "emission reduction". In this regard, the main evaluation criteria are set to parameters such as "speed of traffic", "quality of services in transport", "digitalization", "quality of roads", "delivery time", "optimal price of the service", "level of pollution", " traffic safety " (Burakov, 2008;Gadzhinsky, 1999).
The implementation of the tasks proposed in the framework of the Model for deciding on the logistics development in a particular agglomeration (Appendix 2, Figures 1, 2, 3) will allow to form an integrated agglomeration logistics, creating a basis for the further Almaty agglomeration development.
Methodology. Sustainable development in modern realities is one of the most urgent problems from natural and applied Sciences to fundamental ones. In logistics, there are several approaches to determining sustainability of logistics system, supply chain, company and its business processes that considered in the territorial aspect.  Step 1. The choice of the impact area. The first stage is the selection of the impact zone. There are seven areas of impact, and the user chooses for which the assessment will be performed. According to the LSI calculation method, the main areas affecting the sustainability of logistics development in a certain territory are: economy and energy; environment; transport; mobility and society; policy maturity; social recognition; user perception (Dzhunusova and Zhameshova, 2019).
The focus area for this study is the city of Almaty as the largest economic activity center in the Republic of Kazakhstan. The Almaty agglomeration, along with the agglomerations of Nur-Sultan and Shymkent, has a key strategic role in the formation of the Kazakh economy on the so-called hub principle according to a number of strategic program documents, such as the "national plan -100 concrete steps to implement five institutional reforms" and The state program "Kazakhstan 2050".
Step 2. Criteria selection. The indicators are selected taking into account the areas of impact, from the point of view of stakeholders -business, the population and the state.
Step 3. Selection and calculation of indicators. Within the criteria given above, the following indicators were selected to assess the sustainability of logistics in Almaty: Step 1: Selecting the impact area Step 2: Selecting criteria Step 3: Selecting and calculating metrics Step 4: Process of weighing Step 5: Value normalozatio n Step 6: Logistics sustainability Index Economy: the level of development of industrial production (in terms of production volume), the level of development of the small and medium -sized business -since these two sectors are the main consumers of transport and logistics services.
Environment: emissions volume of solid pollutants into the air, since this indicator is the main influencing factor of transport and logistics activities on the environment. In Kazakhstan, emissions of pollutants are recorded from stationary sources, i.e. from enterprises, while separate statistics on the impact of transport on the environment are not kept.
Transport. This group of criteria is reflected in two main indicators -transport productivity (cargo turnover) and road safety (number of road accidents per year).
The maturity of the policy. This criterion is cut off in the indicator "investment in fixed assets" (direct investment).
Step 4. Weighing prosses. Weighting, according to the LSI calculation method, is the process of comparing two or more elements according to the preferences of the decision maker. There are several weighing methods, but they all follow the same According to this method by Saati (2016), a subjective comparative assessment of the priority of the criteria for sustainable logistics development relative to each other is made, followed by measuring the specific impact weight on the final index of each of the criteria.
The process of determining the specific weight of each criterion for calculating the final rating is carried out by collecting public (expert) opinions of respondents from various groups: legal entities engaged in logistics activities in the study arearepresentatives of the logistics business; public administration entities in this territory; the population of the study area.
The focus group consisted of 224 respondents from the category of logistics business sector and local population of Almaty. The age structure of respondents is shown in the graph below ( Figure 12).   The figure illustrates respondents' structure by urban districts. The respondents were asked to subjectively determine the priority in each pair of criteria on a scale from 1 to 10, where the closer to the left or right criteria in each pair the Respondent makes a mark, the more important this criterion is for the development of the city.
The average response "5" is intermediate, indicating that both criteria are equally important ( Figure 14). Figure 15. Scale for assessing the priority of the criteria "industrial production volume" and "air cleanliness».
The figure 15 demonstrates survey question sample. All intermediate integer estimates are possible. If element 1 is less important than element 2, the corresponding inverse value is assigned (for example, 1/5).
The user fills in A matrix A (n x n), called a "comparison" or "inverse matrix", where n is the number of elements to compare. The cells below the unitary diagonal cells are filled with the input values of the user's rating, while the rest below are equal to the inverse value of the input value (Dzhunusova and Zhameshova, 2019).
An example is the following matrix A (3x3) (Formula 1).

Results
A matrix of the specific weight of criteria was formed according to the respondents' assessment (Table 3). The comparison is made in pairs with determining the priority of one criterion over another. It is noteworthy that the "air pollution" criterion has a clear advantage, which reflects the respondents ' concern about the impact of the environmental situation in the city on its sustainable development, including from the point of view of logistics. Fluctuations in the priority of other criteria are not so pronounced. Most respondents gave a neutral assessment of the priority between such criteria as the development of industrial production, investment volumes, the level of SMEs development, and the frequency of road accidents when they are trampled on.  Direct investment 0,20 1,00 5,00 5,00 5,00 The development of SMEs 0,20 0,20 1,00 5,00 5,00 The frequency of road accidents 0,20 0,20 0,20 1,00 5,00 Air pollution 0,10 0,20 0,20 0,20 1,00 Sum 1,70 6,60 11,40 16,20 26,00 Step 5   Step 6. Sustainability index of logistics.
The criteria used to assess the sustainability of logistics in Almaty can be divided into 2 categories: indicators whose growth is a positive dynamic for sustainable development, such as development of industrial production, volume of direct investment and the development of small and medium-sized businesses; indicators whose growth has a negative value for sustainable development: the road accidents frequency per year, the level of air pollution. Table 7 shows the values of these indicators in 2015 and 2019 and their impact on the final logistics sustainability index.  As can be seen from tables 5 and 6, the LSI indicator in 2015 is 77, in 2019 this index is 83. Therefore, the logistics sustainability index in Almaty has a positive trend with an increase of 6%. Therefore, it is a decision support tool that can be used to assess impact of a particular decision (project) on the city's` sustainable development. If the forecast results of management decision making show an increase of logistics sustainability index, the project should be adopted; if this index decreases according to the project's forecast, the project negatively affects the territory`s sustainable development and is subject to rejection.

Conclusion
Designing an integrated model of logistics processes integration in scope of urban agglomeration logistics systems is a source of increasing urban agglomeration logistics sustainability and efficiency.
The interaction of logistics processes, such as delivery, distribution, loading, unloading and delivery to consumers, in urban agglomeration is directly dependent on the development of production.
Sustainable development in modern realities is one of the most urgent problems of a number of branches of scientific knowledge: from natural and applied Sciences to fundamental ones. In logistics, there are several approaches to determining sustainability. The most common approaches are to determine the sustainability of logistics in terms of the logistics system, supply chain, company and its business processes. In this paper, the sustainability of logistics is considered in the territorial aspect.
Development of urban agglomeration and main socio-economic processes in it is linked with development of such areas as production, business, transport and transport infrastructure, investment, and road safety. These factors have different effects on the sustainability of agglomeration logistics. Based on the results of applying the LSI calculation method, it was determined that the factors of increasing logistics stability for Almaty agglomeration are increasing volumes of direct investment and the development of SMEs. Air quality and the frequency of road accidents are limiting factors.
Further research based on the results obtained can be aimed at improving the stability of agglomeration logistics by influencing negative factors. Also, this technique can be applied to other agglomerations to assess their logistics sustainability, taking into account specific factors.