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Developing a Macro-segmentation Model at Industry Level: Iranian Banking Industry

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Listed:
  • Hosseini Kashkouyieh , Seyyed Mahmoud

    (Shahid Beheshti University, Faculty of Management)

  • Asadi , Gholam Hossein

    (Shahid Beheshti University, Faculty of Management)

  • Hamidizadeh , Mohammad Reza

    (Shahid Beheshti University, Faculty of Management)

  • Moqaddasi , Mohammad

    (Shahid Beheshti University, Faculty of Management)

Abstract

Drastic changes and turbulence in macro-economic factors have the greatest impact on banks target market attractiveness in Iran. It is assumed that conventional segmentation models at the corporate level are not efficient for banking system. This study aims to develop a new segmentation model at the industry level for banks of Iran. For this purpose, structures and variables at the industry level were identified and defined by reviewing the literature and with the help of bank experts in focus group sessions. Then, data of ISIC 3-digit factories with 50 and more employees were extracted from Iran Statistic Center and Tehran Stock Exchange databases during 2005-2013. We used Hierarchical Cluster analysis in each year and identified 4 study groups across 9 years. We found that identified groups are significantly different regarding industry size, deposit and loan market size, industry growth, deposit and loan market growth, profitability, investment risk, and transaction with other industries.

Suggested Citation

  • Hosseini Kashkouyieh , Seyyed Mahmoud & Asadi , Gholam Hossein & Hamidizadeh , Mohammad Reza & Moqaddasi , Mohammad, 2015. "Developing a Macro-segmentation Model at Industry Level: Iranian Banking Industry," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 10(4), pages 95-123, October.
    • Handle: RePEc:mbr:jmonec:v:10:y:2015:i:4:p:95-123
    as

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    References listed on IDEAS

    as
    1. Namolosu Simona Mihaela, 2013. "Segmentation Of Sme Portfolio In Banking System," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(1), pages 1786-1796, July.
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    3. Kevin W. Chauvin & Mark Hirschey, 1993. "Advertising, R&D Expenditures and the Market Value of the Firm," Financial Management, Financial Management Association, vol. 22(4), Winter.
    4. Beck, Thorsten & Demirguc-Kunt, Asli, 2006. "Small and medium-size enterprises: Access to finance as a growth constraint," Journal of Banking & Finance, Elsevier, vol. 30(11), pages 2931-2943, November.
    5. Green, Paul E & Carmone, Frank J, 1977. "Segment Congruence Analysis: A Method for Analyzing Association among Alternative Bases for Market Segmentation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 3(4), pages 217-222, March.
    Full references (including those not matched with items on IDEAS)

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    More about this item

    Keywords

    Macro-segmentation; Manufacturing Industries; Segmentation based on industries; Hierarchical Clustering; Banking;
    All these keywords.

    JEL classification:

    • E44 - Macroeconomics and Monetary Economics - - Money and Interest Rates - - - Financial Markets and the Macroeconomy
    • G21 - Financial Economics - - Financial Institutions and Services - - - Banks; Other Depository Institutions; Micro Finance Institutions; Mortgages
    • L60 - Industrial Organization - - Industry Studies: Manufacturing - - - General
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing
    • C67 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Input-Output Models
    • C82 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Macroeconomic Data; Data Access

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