The article aims at studying the theoretical basis and developing a methodological approach for assessing the development of urban infrastructure from the point of view of the use of venture capital. The article explores the tendencies of the development of venture capital investments in the world. Particular attention is paid to comparing volumes of the formal market of venture capital investment in the EU and Ukraine. The emphasis is placed on the fact that venture capital is a way of targeted investment in innovative development and can become a catalyst for the introduction of innovative technologies. It is substantiated that science and education are reliable segments for the diffusion of innovations. The focus is on the functioning of technology parks and it is revealed that they have become the most effective organizational and economic form of integration of science and production among all other innovative structures in the world. The best practices of Ukrainian universities on the commercialization of innovative developments and technology transfer in the domestic and foreign markets are presented. The creation of an innovative educational-production cluster based on the principles of publicprivate partnership in the form of a multilateral treaty union of state authorities and economic entities without unification of deposits is proposed. The results of calculating the accumulative influence of the multiplicative effect from the development of urban infrastructure have been presented and the effectiveness of its influence on the development of the regions of Ukraine economy has been proved.

This paper investigates the factors influencing on customers’ purchase decision of residential properties in Selangor, Malaysia. The study measures the effects of quality, price, location, promotion and corporate image on purchase decision by distributing some questionnaire among 312 randomly selected residents from some selected destinations at Selangor, Malaysia. Descriptive analysis and multiple regression analysis are used for analyzing the data. The findings reveal that quality, price, location, promotion, and corporate image positively and significantly influence on customers’ purchase decision. The results also indicate that location is the most important factor followed by price, quality, corporate image and promotion plays the smallest role on customers’ purchase intention. The study discusses the results and give constructive suggestions for promoting sales figures.

The present article exposes a model of Mixed Integer Linear Programming (MILP) as a support for strategic decision making, guided to the location of facilities in ethanol supply chains under a configuration of collection centers of raw material and production plants, directly impacting costs related to logistics and operations. The model is applied to the supply chain for the production of ethanol from two by-products and a coffee residue (pulp, mucilage, and stems, respectively) in Colombia. The results obtained by the model allow identifying locations for the corresponding links to the three types of biomass considered, and the flows of raw material between coffee producing departments and collection centers, from the latter to production plants, and from this, where the transformation of ethanol to mixing centers is generated.

Tower cranes, on today’s typical building construction sites, are the centerpiece of production, hoisting and transporting of a variety of loads. Due to a simple crane limited capacity; there is an urgent need to use high capacity cranes such as tower cranes. However, we have to select an appropriate type of cranes to be utilized to reduce the associated coste as much as possible. In this research, we propose a method to select the suitable type of crane and locate the best place for crane erection based on a minimum radius for requested crane and minimum cost. To fulfill the target, a computer program is designed to numerate these problems, demonstrating an example explaining how to apply the program and the results are discussed.

Location Allocation is one of the most important decision making problems, which attracted many operational researchers during recent decades and many solution procedures are developed so far to cope with this problem. This paper proposes a new graph theory based method to cope with small size capacitated location allocation problems. Additionally, a genetic algorithm is utilized to solve medium and large scale problems. Finally, through some computational experiments, the quality and capability of these algorithms are shown.