Stylized Turkish cityscape with data network overlay, symbolizing investment analysis.

Location, Location, Location: Unlocking Investment Potential in Turkey's Metropolitan Cities

"A data-driven approach using APLOCO and MLP reveals the best cities for investment based on key economic factors."


Choosing where to invest is a multifaceted challenge, especially when considering diverse locations and economic factors. Investors and policymakers alike need a clear, data-driven approach to identify the most promising opportunities. Multi-criteria decision analysis (MCDA) offers a powerful framework, but selecting the right method is crucial.

This article explores a novel MCDA approach called APLOCO (Approach of Logarithmic Concept), designed to solve complex, multi-criteria decision-making problems. We'll delve into how APLOCO can be used to evaluate the investment potential of different cities, particularly in the context of Turkey's metropolitan landscape. APLOCO goes beyond simple ranking, offering a way to classify and select investment opportunities based on a range of weighted criteria.

Furthermore, we'll examine how the Multilayer Perceptron (MLP) method, a type of artificial neural network, can be integrated with APLOCO to determine the weight levels of independent variables relevant to factories in the operating phase. By combining these techniques, this study provides a comprehensive and insightful evaluation of investment potential.

APLOCO and MLP: A Two-Step Powerhouse for Investment Evaluation

Stylized Turkish cityscape with data network overlay, symbolizing investment analysis.

The APLOCO method itself involves a series of steps to analyze and rank alternatives based on multiple criteria. It begins with building a decision matrix, where each row represents a criterion (e.g., education index, safety index) and each column represents an alternative (e.g., a city). The values within the matrix reflect the performance of each city against each criterion.

However, not all criteria are created equal. This is where the Multilayer Perceptron (MLP) method comes in. MLP, a type of artificial neural network, is used to determine the weighting levels of the decision criteria. Imagine it as a way to quantify the importance of each factor in driving investment potential. In this study, MLP was used to analyze the factors affecting firms in production stage within Organized Industrial Zones (OIZs).

  • Data Collection: Gather data on relevant variables for each city, such as OIZ types, number of parcels in production, education index, safety index, and income levels.
  • MLP Analysis: Use MLP to determine the impact levels (weights) of each variable on the number of factories in the production stage.
  • APLOCO Implementation: Incorporate the MLP-derived weights into the APLOCO method to rank the cities based on their investment potential.
The combination of APLOCO and MLP creates a powerful, data-driven approach to investment evaluation. APLOCO provides a structured framework for considering multiple criteria, while MLP adds a layer of sophistication by objectively weighting those criteria based on their real-world impact.

Istanbul and Beyond: Key Takeaways for Investors

The results of the APLOCO and MLP analysis reveal a clear hierarchy of investment potential among Turkey's metropolitan cities. Istanbul emerged as the top choice, demonstrating its strength across a range of criteria, particularly the total number of parcels in production. This suggests that Istanbul offers a robust industrial base and a favorable environment for business growth.

However, the study also highlighted the potential of other cities, including Manisa, Denizli, Izmir, and Kocaeli. These cities represent attractive investment destinations, each with its own unique strengths and opportunities. Investors can use these insights to diversify their portfolios and capitalize on the economic dynamism of Turkey's regions.

The APLOCO and MLP method offers a valuable tool for policymakers seeking to promote regional development and attract investment. By understanding the key factors that drive investment potential, governments can tailor their policies to create more favorable business environments and unlock economic growth in metropolitan areas.

About this Article -

This article was crafted using a human-AI hybrid and collaborative approach. AI assisted our team with initial drafting, research insights, identifying key questions, and image generation. Our human editors guided topic selection, defined the angle, structured the content, ensured factual accuracy and relevance, refined the tone, and conducted thorough editing to deliver helpful, high-quality information.See our About page for more information.

This article is based on research published under:

DOI-LINK: 10.5121/ijaia.2018.9102, Alternate LINK

Title: A New Multi Criteria Decision Making Method : Approach Of Logarithmic Concept (Aploco)

Subject: General Medicine

Journal: International Journal of Artificial Intelligence & Applications

Publisher: Academy and Industry Research Collaboration Center (AIRCC)

Authors: Tevfik Bulut

Published: 2018-01-30

Everything You Need To Know

1

What is APLOCO and what is its role in evaluating investment potential?

APLOCO (Approach of Logarithmic Concept) is a Multi-criteria decision analysis (MCDA) method used to evaluate the investment potential of cities. It is designed to solve complex, multi-criteria decision-making problems by ranking and classifying investment opportunities based on various weighted criteria. This method is beneficial because it allows for a systematic approach to evaluating investment potential, going beyond simple ranking to provide a comprehensive assessment.

2

What is the Multilayer Perceptron (MLP) method, and how is it used in this analysis?

The Multilayer Perceptron (MLP) method is a type of artificial neural network. In the context of this evaluation, the MLP is used to determine the weight levels of independent variables relevant to factories in the operating phase. This weighting helps quantify the importance of each factor in driving investment potential, providing an objective assessment of the criteria used by APLOCO. The use of MLP adds sophistication to the analysis by ensuring that the criteria are weighted based on their real-world impact on investment potential, particularly in the context of firms within Organized Industrial Zones (OIZs).

3

Why is it important to use both APLOCO and MLP together in this analysis?

The importance of using APLOCO and MLP together is that they create a powerful, data-driven approach to investment evaluation. APLOCO provides a structured framework for considering multiple criteria, such as the education index and safety index, while MLP adds a layer of sophistication by objectively weighting those criteria based on their real-world impact. This combination allows for a more comprehensive and insightful evaluation of investment potential in cities, offering a way to classify and select investment opportunities based on a range of weighted criteria.

4

What are the key steps involved in the evaluation process using APLOCO and MLP?

The process involves several steps: Data Collection, MLP Analysis, and APLOCO Implementation. First, data on relevant variables for each city, such as OIZ types, number of parcels in production, education index, safety index, and income levels is gathered. Then, the MLP is used to determine the impact levels (weights) of each variable. Finally, these weights are incorporated into the APLOCO method to rank cities based on investment potential. This structured approach ensures a data-driven and objective assessment of investment opportunities.

5

Which city was identified as the top choice for investment, and what factors contributed to this ranking?

Istanbul was identified as the top choice for investment. This was determined by the analysis of data using APLOCO and MLP methods. The results demonstrated Istanbul's strength across a range of criteria, particularly the total number of parcels in production. This suggests that Istanbul offers a robust industrial base and a favorable environment for business growth, making it a prime location for investment within the context of the study.

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