Determination of Biomass Power Plant Location Using GIS-Based Heuristic Methods: A Case Study in Turkey

Biomass conversion to bioenergy has always been necessary to ensure the most efficient use of the limited biomass resource and enable economic viability. Evaluating biomass transportation cost, electricity transmission cost and heat transferring cost between power plant location/s and supply/demand points and selection of an optimum power plant capacity is an important issue for a robust supply chain design. In this study, we employed designing optimum biomass to the bioenergy supply chain for agricultural activities using Geographic Information System and Simulated Annealing algorithm to overcome a real-world problem in Bismil District of Diyarbakır/Turkey. Our goal is to define a potential investment location/s on the trigeneration system by comparing the trade-offs between the raw material/end-product transportation costs and facility/s and pipeline installation costs. To determine possible locations for power plants, distance matrices were retrieved from suitable candidate power plant locations and agricultural parcel, settlement and the nearest high voltage electricity line from the Geographic Information System. The results showed that establishing one power plant is feasible. The net present value of a potential investment is almost 260 million Euros and the re-payment period is 1.33 years.

The Response of Creative Class Members to Regions Vying to Attract Them With Subsidies

There are no theoretical studies in regional science that examine which region to locate in from the standpoint of a creative class member, given that the pertinent regional authorities (RAs) are competing among themselves to attract the creative class using subsidies. This gap provides the motivation for our paper. This paper’s contribution is that it is the first to theoretically study the regional location choice of creative class members when the RAs of the locations in which they might locate are using subsidies to attract them. Specifically, a knowledge good producing creative class member must decide which of two regions ( A or B) to locate his plant in. This good is produced using a Cobb–Douglas function with creative and physical capital. We analyze plant location in four cases. In the benchmark case, we show that the representative creative class member ought to locate his plant in the less expensive region B. Next, we show that a small subsidy to creative capital by region A switches the plant location decision from region B to A. Finally, when both regions grant identical subsidies to creative capital, the representative creative class member is indifferent between locating in regions A and B. So, for identical subsidies to affect the plant location decision, they are better targeted to physical and not to creative capital. JEL Codes: R11, R58

Samsun İlinde Kurulabilecek Kompost Tesislerinin COCOSO ve WASPAS Yöntemiyle Optimallik Sıralaması

The compost product, which offers many benefits such as the evaluation of organic wastes, improvement of soil structure, neutralization of toxins and pH balance of the soil, has significant potential for the improvement of our country's lands. Considering the development of animal existence in our country, the production of compost product to be obtained from feces, which is the product of these animal beings, is an issue that needs to be emphasized. The choice of plant location, which must be determined for an investment to be made for the acquisition of this product emerges as a separate problem. For this reason, in this study, the order of optimality among the alternatives for compost plant installation is considered as a multi-criteria decision making problem. For this purpose, the criteria determined for 10 clusters with the potential of 35,829 animals that can produce compost in Samsun were weighted by the SWARA method. The optimal ranking of these 10 compost clusters was carried out using the COCOSO and WASPAS methods, by means of the criteria weights taken into consideration. According to the ranking results obtained from both methods, it was determined that the cluster number 27 was in the first rank, the cluster no 13 was in the second rank, and the cluster no 14 was in the third rank.

Application of Brown–Gibson model in workers’ productivity; an impact study of weighted parameters using experimental research design

Purpose The urban-rural divide in developing countries such as India often finds focus in every economic analysis. This paper aims to find the existing gap and to suggest an action plan to reduce the gap identified therein. With an aim to find a good leader in furtherance the group performance operating in rural areas, a multi-plant location model is tested taking its weighted assessment method on assumptions that the unorganized sector is devoid of accessing any scientific model for its growth and sustenance. Design/methodology/approach In this research, two different business groups in the same city location were taken as samples and the multi-plant location (Brown–Gibson) model was used to test the impact of any changes in leadership on the group. Findings The result in the first sample group indicated incremental profitability which was under observation for three years. The second group witnessed a varied trend of profitability under two different leaders which was studied for a four-year period. Research limitations/implications Purposive behavioural alignment under a controlled research environment often dampens the real objective of the study. A meticulous effort was meted out to remove it from research. Practical implications The research aims at providing a long-standing solution to leadership issues in the unorganized sector that contributes to the national economy but usually kept neglected. Originality/value Scientific model experimentation on human resources is unique and innovative.